HAKONE’s personalization system has been developed using a proprietary research archive accumulated since 2014, comprising more than 2,000 human-drawn illustrations together with participant-reported emotional states and contemporaneous video-viewing categories.
a rare, human-origin longitudinal archive
The HAKONE Human Record
A Proprietary Archive Built Continuously Since 2014
A Twelve-Year Data Advantage
Built From Real Human Action—not Synthetic Content
More Than 2,000 Human-Made Records
Twelve Years of Expression Collected Since 2014
An Archive That Time Had to Build
Twelve Years of Human Expression Behind HAKONE
Since 2014, our research institute has accumulated more than 2,000 illustrations created by human hands through years of direct practice and observation.
This archive was not generated by AI, purchased as stock content, or collected from the internet. It was built one participant, one drawing, and one real human moment at a time.
Competitors may reproduce software features. They cannot instantly recreate twelve years of trust, provenance, lived context, and human expression.
The Data Moat No Competitor Can Recreate Overnight
They Can Copy the Interface. They Cannot Copy the Human History Behind It.
More than 2,000 works in the HAKONE archive were not generated by artificial intelligence, scraped from the internet, or created as decorative stock content.
They were drawn by real adult participants, by hand, after a deliberate interruption of an automatic smartphone action.
Where participant permission and data-governance rules allow, each work can be connected to the context in which it was created:
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the moment of behavioral interruption;
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the user’s self-reported emotional state;
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the alternative action performed;
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the reflection that followed; and
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the next action consciously selected.
These are therefore not merely illustrations.
They are human-origin primary records created at the boundary between impulse and choice.
Software Can Be Copied. History Cannot.
A competitor can reproduce a timer.
It can play flowing-water sound.
It can add an emotion selector or ask users to draw.
What it cannot do overnight is recreate the accumulated history that produced HAKONE’s archive:
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authentic human-created works;
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adult participant permissions;
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real intervention contexts;
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documented behavioral sequences;
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emotional and situational labels;
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timestamps and provenance;
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and the trust required for people to express something immediately after stopping.
Capital can purchase computing power.
It can hire engineers.
It can imitate a screen.
It cannot retroactively manufacture authentic human experience.
This accumulated history is HAKONE’s proprietary data advantage.
HAKONE Captures What Happens After the Stop
Most digital-wellbeing systems concentrate on defense:
block the application;
set a limit;
remove access;
reduce screen time.
HAKONE also examines what happens after the automatic movement has been interrupted.
The finger stops.
↓
The hand moves to paper.
↓
A human image is created.
↓
The emotional state becomes observable.
↓
The urge is translated into language.
↓
The next action is selected.
This creates a closed behavioral feedback loop:
Interruption → Human Expression → Self-Observation → Choice → Personalization
The strategic value lies not only in preventing one swipe.
It lies in learning what each person does, feels, and chooses after the swipe has been interrupted.
Human-Generated Data—not Synthetic Substitutes
Artificial intelligence can generate millions of attractive images in seconds.
That abundance does not make those images equivalent to the HAKONE archive.
An AI-generated image has no lived impulse behind it.
It did not emerge from a person who had just stopped an automatic smartphone action.
It was not created by a human hand during a defined behavioral intervention.
It does not carry the same relationship between:
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bodily movement;
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emotional context;
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behavioral timing;
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self-observation;
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and subsequent choice.
The value of the HAKONE archive is not simply what the images look like. It is why, when, and through which human action they were created.
That provenance cannot be replaced by synthetic content.
A Proprietary Feedback Loop for LÄRDA 2.0
With appropriate permission, de-identification, security, and data governance, the HAKONE archive may support the evaluation and personalization of LÄRDA 2.0.
The system is not intended to diagnose illness from a drawing.
It is not designed to identify hidden pathology, read a person’s mind, or assign a medical meaning to an illustration.
Its purpose is narrower and more practical:
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to learn which intervention timing is most useful;
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which prompts help the user pause;
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which sensory environment supports completion;
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which alternative actions are acceptable;
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which emotional patterns precede automatic use;
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and which form of reflection helps that individual make a deliberate choice.
Over time, this may allow LÄRDA 2.0 to become not a generic chatbot, but a highly personalized digital self-regulation companion.
The more the user practices, the more precisely the system may learn how to support that user’s own process of stopping, observing, and choosing.
A Data Advantage Built From Trust
HAKONE’s data advantage is not created by hidden surveillance.
It is created through voluntary human participation.
Its value depends on maintaining:
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clear permission;
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defined data-use purposes;
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participant control;
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privacy protection;
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accurate provenance;
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secure storage;
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and a documented distinction between publication, personalization, research, and AI development.
This is not merely a database.
It is a trust-based archive of human behavioral transitions.
And trust cannot be copied with code.
Evidence That Exists Beyond the Marketing Claim
The underlying illustrations physically exist.
They are not synthetic demonstrations created to make a webpage appear more convincing.
HAKONE can maintain an auditable record of:
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the existence of the original work;
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confirmation that it was human-created;
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adult participant permission;
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the circumstances under which it was collected;
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the purpose for which it may be used;
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anonymization or pseudonymization procedures;
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and its relationship to the intervention process.
Where lawfully requested, HAKONE can substantiate the existence and provenance of this archive to regulators or authorized independent reviewers under appropriate confidentiality and privacy safeguards.
The claim can be traced back to real human artifacts—not merely to promotional language.
The HAKONE Barrier
Big technology companies can buy servers.
They can copy features.
They can reproduce a visual interface.
They can generate unlimited synthetic images.
But they cannot purchase the past.
They cannot instantly reproduce more than 2,000 authentic human moments created at the precise boundary between automatic impulse and deliberate choice.
That boundary is HAKONE’s proprietary data moat.
They may imitate the mechanism.
They cannot inherit the history.
The World-Class Academic Journals Supporting HAKONE’s Scientific Foundation
The theoretical framework for each of HAKONE’s core features—including the 60-second pause, drawing, and affect labeling—is grounded in top-tier neuroscientific literature that has passed rigorous global peer review. The primary academic journals featuring the foundational research for this system include the following:
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PNAS (Proceedings of the National Academy of Sciences) Published by the National Academy of Sciences, this is one of the world’s most prestigious multidisciplinary scientific journals. Holding an authority rivaled only by Nature and Science, having a paper published in PNAS is considered a profound honor for any researcher (e.g., the study by Kober et al. on the cognitive regulation of craving).
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Journal of Neuroscience Published by the Society for Neuroscience, this is one of the largest and most trusted top-tier journals in the field of neuroscience globally. It exclusively publishes high-quality brain research that has survived an exceptionally rigorous peer-review process (e.g., studies on frontal-lobe networks by Aron, Jahfari, and colleagues).
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Nature Neuroscience / Neuron / JAMA These are elite, peer-reviewed journals with extraordinarily high impact factors, widely recognized as ranking among the top three globally in their respective fields of neuroscience and medicine.
The Basal Ganglia Are Not Broken
Automatic Smartphone Use as Learned Behaviour—not Proof of a Broken Brain
Open the smartphone.
Check a notification.
Swipe downward.
Move on to the next video.
Most people do not consciously plan every step of this sequence. After the same actions have been repeated many times, they become linked to particular places, times of day, emotions, notification sounds, screen layouts, and visual cues.
Eventually, the first cue can trigger the next movement with very little conscious deliberation.
In neuroscience, this is known as habitual behaviour.
Automatic smartphone use is not, by itself, evidence that the brain is damaged or that a person has a clinical disorder.
In many cases, it can be understood as a learned action sequence being efficiently reproduced by neural systems that evolved to make repeated behaviour easier.
The brain is not necessarily failing. It may be accurately repeating what it has learned.
Habit Is a Feature of the Brain—not a Defect
Human beings could not consciously supervise every movement involved in everyday life.
Walking, typing, preparing food, driving a familiar route, and carrying out routine work all depend partly on the brain’s ability to organise repeated actions into efficient sequences.
Habit allows familiar behaviour to run with less continuous conscious effort [1–5].
This is an adaptive function.
It reduces the need for the prefrontal cortex to reconsider every small movement and allows attention to be used elsewhere.
The basal ganglia are deeply involved in this process. They include interconnected structures such as the striatum, globus pallidus, subthalamic nucleus, and substantia nigra.
These structures contribute to:
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learning repeated cue–response relationships;
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selecting among competing actions;
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initiating and suppressing movement;
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reinforcing actions through reward learning;
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organising separate movements into familiar sequences; and
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shifting between goal-directed and habitual control [1–5].
The striatum—and particularly the dorsolateral striatum and the human posterior putamen—has repeatedly been associated with the development and expression of habitual behaviour [3–5].
There is therefore no single “addiction button” or “autopilot centre” in the brain.
What we call autopilot emerges from communication among cortical, striatal, pallidal, thalamic, motor, attentional, and reward-related systems.
The Problem Is Not That the Basal Ganglia Are Malfunctioning
The basal ganglia may be doing exactly what a learning system is supposed to do.
The problem begins when a sequence learned in the past continues to run automatically, even when it no longer matches the person’s present intention.
Someone may intend to check only one work-related message.
But if the following sequence has been repeated hundreds or thousands of times:
See the smartphone
↓
Reach for it
↓
Open a notification
↓
View a related post
↓
Scroll downward
↓
Search for the next stimulus
then the first movement may retrieve the entire sequence.
At that point, the user may no longer be making a fresh decision at every step.
The behaviour has become increasingly cue-driven.
In a human fMRI study, Tricomi and colleagues compared shorter and more extensive periods of repeated instrumental training. Following several days of training, behaviour became less sensitive to the current value of the outcome, while cue-related activity increased in the posterior putamen and globus pallidus [4].
The study did not involve smartphones, and it did not show that every repeated action becomes a permanent habit within three days.
It did demonstrate something important:
Repeated training can begin shifting control from deliberate, outcome-sensitive action toward cue-driven behaviour, accompanied by measurable changes in habit-related striatal activity.
The problem is therefore not that the brain has learned.
The problem is that the learned sequence may continue after it has stopped serving the user’s current goal.
Intentional Use and Automatic Use Are Not the Same
HAKONE does not begin with the assumption that all smartphone use is harmful.
A smartphone can be used deliberately for communication, work, navigation, education, safety, creativity, and access to essential services.
The scientifically and behaviourally important distinction is not simply:
phone use versus no phone use.
It is:
intentional use versus automatic continuation.
Intentional use usually begins with a recognisable purpose:
“I am opening the phone to answer this message.”
It can also end when that purpose has been completed:
“The message has been answered. I can now put the phone down.”
Automatic use may begin with a cue rather than a clearly chosen purpose:
“I saw the phone, felt uncomfortable, and my hand moved.”
It may then continue beyond the original intention:
“I opened one message, but twenty minutes later I was still scrolling.”
A randomised smartphone intervention study found that goal-directed planning and self-efficacy may contribute to changes in problematic use and total use time [41].
This supports an important principle:
The objective is not necessarily to remove the smartphone. It is to restore a clearer relationship between purpose, action, and stopping.
Smartphone Cues Can Become Behavioural Triggers
A notification is not merely a sound.
A familiar app icon is not merely an image.
Through repetition, these cues can acquire behavioural significance.
They can predict information, social feedback, novelty, reassurance, distraction, or the possibility of reward.
Research on problematic smartphone use suggests that smartphone-related cues can engage neural systems involved in attention, salience, reward processing, action preparation, and cognitive control.
In an fMRI study, Schmitgen and colleagues reported differences in neural responses to smartphone-related cues in individuals with problematic smartphone use. The implicated regions included the medial prefrontal cortex, anterior cingulate cortex, insula, and premotor areas [44].
An event-related potential study using a Go/No-Go task found that people with problematic mobile-phone use made more inhibitory errors when mobile-phone-related images appeared in the background. Differences were also observed in electrophysiological measures associated with inhibitory processing [45].
A later neuroimaging study reported abnormalities in frontoparietal control-network strength across tasks involving cue reactivity, response inhibition, and working memory in excessive smartphone users [46].
These studies do not prove that every person who checks a phone has an addiction.
They do support the idea that, in some individuals, smartphone cues become closely connected to attention, motivation, motor preparation, and control processes.
The cue is no longer passive.
It has become part of a learned behavioural sequence.
Smartphone research included in the source material similarly distinguishes reward- and cue-related responses from direct proof that HAKONE itself has produced a neural effect.
The Prefrontal Cortex and Basal Ganglia Are Not Opposing Brains
It is tempting to describe the prefrontal cortex as the centre of reason and the basal ganglia as the centre of instinct.
That image is easy to understand—but scientifically incomplete.
The prefrontal cortex and basal ganglia are not two independent systems fighting for control.
They are deeply interconnected through several cortical–striatal–pallidal–thalamic loops [3][5][8–12].
In simplified terms, basal-ganglia action control is often described through three interacting pathways:
The direct pathway
This pathway helps facilitate the execution of selected actions.
The indirect pathway
This pathway contributes to the suppression of competing or unwanted actions.
The hyperdirect pathway
This pathway provides a relatively rapid route from frontal regions to the subthalamic nucleus, allowing a broader interruption of motor output when an action needs to be stopped or reconsidered [7–12].
These pathways should not be understood as a simple accelerator and brake operating independently.
Action control depends on timing, context, competing goals, learned value, sensory information, and communication across distributed networks.
The basal ganglia help select and organise behaviour.
Frontal and prefrontal regions contribute to monitoring, evaluation, goal representation, conflict detection, inhibition, and the adjustment of behaviour.
The two systems work together.
The uploaded basal-ganglia review likewise describes the direct, indirect, and hyperdirect pathways as interacting components of a frontal–basal-ganglia control network rather than isolated “go” and “stop” centres.
What Happens in the Brain When an Action Is Stopped?
Neuroscientists often study action stopping with the stop-signal task.
A participant is asked to respond quickly to a “go” cue. On some trials, a stop signal appears after the response has already been prepared, requiring the participant to cancel the action.
This task has helped identify a distributed response-inhibition network.
Aron and colleagues found that damage to the right inferior frontal gyrus impaired the ability to stop an initiated response [6].
Aron and Poldrack subsequently reported that successful stopping involved the right inferior frontal cortex and subthalamic nucleus, while action initiation involved regions including the striatum, globus pallidus, and motor cortex [7].
A broader review by Aron and colleagues brought together evidence for a fronto-basal-ganglia network involved in the inhibitory control of action and cognition [8].
Jahfari and colleagues found that both:
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the hyperdirect frontal–subthalamic pathway; and
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the indirect frontal–striatal–pallidal pathway
may contribute to successful response inhibition [9].
Nambu and colleagues described the functional significance of the cortico-subthalamo-pallidal hyperdirect pathway as a rapid mechanism capable of broadly suppressing competing motor programmes [10].
Rae and colleagues reported that the prefrontal cortex may achieve inhibitory control partly by modifying connectivity among the pre-supplementary motor area, subthalamic nucleus, and downstream motor pathways [11].
Wessel and Aron further argued that motor suppression can extend beyond one isolated movement, influencing broader cognitive and behavioural processing when unexpected events require interruption [12].
Finally, temporary disruption of frontal-lobe function using brain stimulation has been shown to impair the capacity to stop an initiated response [13].
Together, these studies establish that stopping is not a single command sent from a single “rational” brain region.
Stopping is a coordinated network process involving frontal regions, the basal ganglia, the subthalamic nucleus, and motor systems.
The Brain’s Autopilot Is Not Irreversible
A learned response can feel immediate and compulsory.
But immediate does not always mean irreversible.
Behavioural control can remain sensitive to changes in goals, context, attention, outcome value, and competing actions.
The existence of habitual control does not mean that goal-directed control has disappeared.
Rather, the balance between them may shift.
Research on cognitive control shows that initiated actions can be interrupted through frontal–basal-ganglia networks [6–13].
Research on goal-directed smartphone interventions suggests that planning and self-efficacy can support behavioural change [41].
Research on smartphone restriction further suggests that responses to smartphone-related cues are not completely fixed.
In a 2025 fMRI study, 72 hours of smartphone restriction was followed by changes in cue-related activity involving the nucleus accumbens and anterior cingulate cortex [47].
A 2026 resting-state fMRI study reported changes after 72 hours in frontal, posterior cingulate, sensorimotor, and visual regions, with different patterns in problematic and non-problematic smartphone users [48].
These studies do not show that three days erase a smartphone habit.
They do show that measurable neural responses associated with smartphone cues and craving can change over a relatively short period.
A separate three-day experiment found that people with higher problematic-use scores reported stronger withdrawal-related symptoms and negative affect when access to their smartphones was restricted [43].
This is another reason why HAKONE does not define its 72-hour period as forced abstinence.
Removing a device may interrupt behaviour, but interruption alone does not automatically teach a new response.
HAKONE Does Not Treat the Basal Ganglia as the Enemy
HAKONE is not designed to overpower, disable, or “reset” the basal ganglia.
It does not assume that automatic behaviour is proof of a defective brain.
Its design begins from a different principle:
A normal learning system can acquire an unhelpful sequence. A new point of choice must therefore be inserted before that sequence is completed.
HAKONE intervenes at the entrance to the sequence.
Not after an hour of scrolling.
Not after the user has already lost track of time.
But at the moment the hand is preparing to continue the learned action.
The usual sequence may be:
Smartphone cue
↓
Reach
↓
Open
↓
Scroll
↓
Continue
HAKONE introduces another possibility:
Smartphone cue
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Pause
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Notice
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Redirect attention and action
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Choose what happens next
The aim is not to guarantee that the urge disappears.
The aim is to prevent the urge from automatically completing the decision.
From “I Must Stop Using It” to “I Can Choose How I Use It”
Many digital-wellbeing approaches begin after the user has already entered the application.
Others depend primarily on time limits, blocking, confiscation, or willpower.
These methods may be useful for some people.
HAKONE begins at an earlier point:
the moment before the habitual action sequence becomes fully engaged.
Its philosophy is not:
“The basal ganglia are dangerous and must be defeated.”
It is:
“The basal ganglia have learned a sequence. We must create enough time for another sequence to become available.”
This changes the goal.
The goal is not permanent avoidance of digital technology.
The goal is to make automatic continuation less inevitable.
To allow the user to distinguish:
I am opening this because I have chosen a purpose
from:
I am opening this because the cue has already moved my hand.
The Core Scientific Position
HAKONE’s first scientific principle can therefore be stated as follows:
Automatic smartphone behaviour can be understood, in part, as an efficient learned action sequence involving the basal ganglia and connected cortical systems. HAKONE does not attempt to destroy this learning system. It creates a structured interruption before the learned sequence is completed, with the aim of restoring an opportunity for monitoring, inhibition, and deliberate behavioural choice.
This position is grounded in established research on:
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habit formation and the striatum [1–5];
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goal-directed and habitual action control [3–5];
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frontal–basal-ganglia response inhibition [6–13];
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smartphone cue reactivity [44];
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inhibitory-control differences associated with problematic smartphone use [45][46];
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goal-directed smartphone interventions [41]; and
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short-term changes in smartphone-related neural and emotional responses [43][47][48].
It does not establish that the complete HAKONE system has already been proven to activate a specific brain region or suppress a specific habit circuit.
That product-specific question requires direct testing.
The second layer of this scientific page therefore examines the six component mechanisms on which HAKONE is built:
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temporal interruption of habitual action;
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fingertip sensation as an attention anchor;
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water-flow sound as a supportive sensory environment;
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stopping, noticing, and returning attention;
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competing motor, emotional, and verbal actions; and
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repeated practice across a 72-hour window.
Scope and Boundary of This First Principle
This page does not claim that:
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every automatic smartphone action is an addiction;
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problematic smartphone use is never a medical or psychological concern;
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the basal ganglia are the sole cause of smartphone overuse;
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a 60-second pause shuts down a basal-ganglia circuit;
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the prefrontal cortex acts as a single master controller;
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three days permanently rewire the brain; or
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every HAKONE user will experience the same result.
Automatic reaching for a smartphone is not, by itself, a diagnosis.
Where smartphone use causes serious impairment in sleep, work, education, relationships, safety, or mental health, professional assessment and support may be appropriate.
HAKONE is designed as a digital self-regulation and behavioural-choice system. It is not a medical diagnostic service and does not replace professional care.
References Cited in Layer 1
[1] Graybiel, A. M. (2008). Habits, rituals, and the evaluative brain. Annual Review of Neuroscience, 31, 359–387. https://doi.org/10.1146/annurev.neuro.29.051605.112851
[2] Wood, W., & Rünger, D. (2016). Psychology of habit. Annual Review of Psychology, 67, 289–314. https://doi.org/10.1146/annurev-psych-122414-033417
[3] Balleine, B. W., & O’Doherty, J. P. (2010). Human and rodent homologies in action control: Corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology, 35(1), 48–69. https://doi.org/10.1038/npp.2009.131
[4] Tricomi, E., Balleine, B. W., & O’Doherty, J. P. (2009). A specific role for posterior dorsolateral striatum in human habit learning. European Journal of Neuroscience, 29(11), 2225–2232. https://doi.org/10.1111/j.1460-9568.2009.06796.x
[5] Smith, K. S., & Graybiel, A. M. (2016). The striatum: Where skills and habits meet. Cold Spring Harbor Perspectives in Biology, 8(8), a021691. https://doi.org/10.1101/cshperspect.a021691
[6] Aron, A. R., Fletcher, P. C., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2003). Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nature Neuroscience, 6(2), 115–116. https://doi.org/10.1038/nn1003
[7] Aron, A. R., & Poldrack, R. A. (2006). Cortical and subcortical contributions to stop-signal response inhibition: Role of the subthalamic nucleus. Journal of Neuroscience, 26(9), 2424–2433. https://doi.org/10.1523/JNEUROSCI.4682-05.2006
[8] Aron, A. R., Durston, S., Eagle, D. M., Logan, G. D., Stinear, C. M., & Stuphorn, V. (2007). Converging evidence for a fronto-basal-ganglia network for inhibitory control of action and cognition. Journal of Neuroscience, 27(44), 11860–11864. https://doi.org/10.1523/JNEUROSCI.3644-07.2007
[9] Jahfari, S., Waldorp, L., van den Wildenberg, W. P. M., Scholte, H. S., Ridderinkhof, K. R., & Forstmann, B. U. (2011). Effective connectivity reveals important roles for both the hyperdirect and indirect fronto-basal ganglia pathways during response inhibition. Journal of Neuroscience, 31(18), 6891–6899. https://doi.org/10.1523/JNEUROSCI.5253-10.2011
[10] Nambu, A., Tokuno, H., & Takada, M. (2002). Functional significance of the cortico-subthalamo-pallidal hyperdirect pathway. Neuroscience Research, 43(2), 111–117. https://doi.org/10.1016/S0168-0102(02)00027-5
[11] Rae, C. L., Hughes, L. E., Anderson, M. C., & Rowe, J. B. (2015). The prefrontal cortex achieves inhibitory control by facilitating subcortical motor pathway connectivity. Journal of Neuroscience, 35(2), 786–794. https://doi.org/10.1523/JNEUROSCI.3093-13.2015
[12] Wessel, J. R., & Aron, A. R. (2017). On the globality of motor suppression: Unexpected events and their influence on behavior and cognition. Neuron, 93(2), 259–280. https://doi.org/10.1016/j.neuron.2016.12.013
[13] Chambers, C. D., Bellgrove, M. A., Stokes, M. G., et al. (2006). Executive brake failure following deactivation of human frontal lobe. Journal of Cognitive Neuroscience, 18(3), 444–455. https://doi.org/10.1162/089892906775990606
[41] Keller, J., Roitzheim, C., Radtke, T., Schenkel, K., & Schwarzer, R. (2021). A mobile intervention for self-efficacious and goal-directed smartphone use in the general population: Randomized controlled trial. JMIR mHealth and uHealth, 9(11), e26397. https://doi.org/10.2196/26397
[43] Aarestad, S. H., Flaa, T. A., Griffiths, M. D., & Pallesen, S. (2023). Smartphone addiction and subjective withdrawal effects: A three-day experimental study. SAGE Open, 13(4), 21582440231219538. https://doi.org/10.1177/21582440231219538
[44] Schmitgen, M. M., Horvath, J., Mundinger, C., et al. (2020). Neural correlates of cue reactivity in individuals with smartphone addiction. Addictive Behaviors, 108, 106422. https://doi.org/10.1016/j.addbeh.2020.106422
[45] Gao, L., Zhang, J., Xie, H., Nie, Y., Zhao, Q., & Zhou, Z. (2020). Effect of the mobile phone-related background on inhibitory control of problematic mobile phone use: An event-related potentials study. Addictive Behaviors, 108, 106363. https://doi.org/10.1016/j.addbeh.2020.106363
[46] Schmitgen, M. M., et al. (2023). Cognitive domain-independent aberrant frontoparietal network strength in individuals with excessive smartphone use. Psychiatry Research: Neuroimaging, 329, 111593. https://doi.org/10.1016/j.pscychresns.2023.111593
[47] Schmitgen, M. M., Henemann, G. M., Koenig, J., et al. (2025). Effects of smartphone restriction on cue-related neural activity. Computers in Human Behavior, 167, 108610. https://doi.org/10.1016/j.chb.2025.108610
[48] Haage, S. H., Schmitgen, M. M., Henemann, G. M., et al. (2026). Smartphone restriction modulates intrinsic neural activity in problematic smartphone users: Evidence from resting-state fMRI. Addictive Behaviors, 174, 108575. https://doi.org/10.1016/j.addbeh.2025.108575
HAKONE YUBIZEN
Six Science-Informed Mechanisms for Interrupting Automatic Smartphone Behavior
HAKONE is designed to intervene at a specific moment:
The point at which a smartphone cue is about to trigger a familiar action sequence.
Instead of waiting until prolonged scrolling is already underway, HAKONE introduces a short, structured alternative before the learned sequence is completed.
The sequence begins with YUBIZEN: a 60-second period in which the fingertip remains still on the smartphone while a continuous flowing-water sound is played.
The user then moves through a series of alternative actions:
Smartphone cue
↓
60-second fingertip stillness with flowing-water sound
↓
Attention returns to tactile and auditory experience
↓
Illustration Reading on paper
↓
Emotion identification
↓
Verbal reflection or AI-guided dialogue
↓
Deliberate selection of the next action
The scientific rationale for this sequence does not come from one study.
It comes from converging research on:
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habit formation;
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the basal ganglia and corticostriatal learning;
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response inhibition;
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Zen and focused-attention meditation;
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tactile-assisted meditation;
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natural sound;
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competing responses;
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drawing and visuomotor control;
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affect labeling;
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cognitive regulation of craving;
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goal-directed smartphone use; and
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short-term neural and behavioral change.
Each of the following six sections separates three different levels of evidence.
Established Evidence
What published research has demonstrated in related fields.
HAKONE Application
How HAKONE translates that research into a practical digital behavior intervention.
Boundary of Claim
What has not yet been directly established through HAKONE-specific controlled studies.
SCIENTIFIC BASIS 1
Temporal Interruption of Habitual Action
Why Fingertip Stillness May Create a Boundary Within an Automatic Smartphone Sequence
The Scientific Proposition
Repeated smartphone actions can become increasingly cue-driven and require progressively less conscious deliberation.
Habit learning involves corticostriatal systems, including the dorsolateral striatum and, in humans, the posterior putamen [1–5].
These systems are not defective when they automate a repeated action. They are efficiently reproducing a learned association between a cue and a response.
A typical sequence may begin with:
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a notification;
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the sight of the smartphone;
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an application icon;
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a moment of boredom;
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anxiety or discomfort;
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fatigue;
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or a habitual time of day.
Once the first movement begins, the remainder of the sequence may unfold rapidly:
See or think about the smartphone
↓
Reach for the device
↓
Open the screen
↓
Begin scrolling
↓
Seek the next cue, item, or reward
The person may have originally intended to check only one message. However, the first movement can retrieve a larger action sequence that has been repeated many times.
Tricomi and colleagues showed that repeated human training across several days could make behavior less sensitive to the current value of its outcome while increasing cue-related activity in the posterior putamen and globus pallidus [4].
This does not mean that three days automatically creates a permanent habit.
It demonstrates that cue–response control and activity in habit-related striatal regions can begin shifting during a relatively short period of repeated training.
Stopping Is a Network Function
When an initiated action must be canceled, the brain does not depend on one isolated “brake center.”
Stop-signal research implicates a coordinated fronto-basal-ganglia network that includes:
-
the right inferior frontal cortex;
-
the pre-supplementary motor area;
-
the subthalamic nucleus;
-
the striatum;
-
the globus pallidus; and
-
motor regions [6–13].
The hyperdirect pathway provides a relatively rapid route from frontal regions to the subthalamic nucleus.
The indirect pathway involves frontal, striatal, and pallidal connections that contribute to the suppression and selection of motor output [7–11].
Studies involving lesions and temporary brain stimulation have also shown that damage to, or disruption of, right frontal regions can impair the ability to stop an initiated response [6][13].
These findings establish the biological plausibility of placing an intentional interruption into an action sequence that is already beginning.
They do not establish that every voluntary pause uses precisely the same neural mechanism as a laboratory stop-signal task.
Why 60 Seconds?
HAKONE does not claim that every urge expires within exactly 60 seconds.
Urges differ in duration and intensity, and some may continue well beyond one minute.
The 60-second period is better understood as a defined behavioral interval, not as the neurological expiration time of an urge.
Relevant behavioral evidence comes from competing-response research.
Twohig and Woods compared competing responses lasting:
-
five seconds;
-
one minute; and
-
three minutes
in people who engaged in nail biting [14].
The one-minute and three-minute conditions produced improvements that were maintained more successfully than the five-second condition.
This was a small study of nail biting, not smartphone use.
It does not prove that holding a finger still for 60 seconds will stop scrolling.
It supports a narrower behavioral principle:
A competing or incompatible response may need to be sustained long enough to interrupt the original sequence, rather than functioning as a momentary gesture.
Habit-reversal interventions have also used competing responses that are introduced when an unwanted behavior or urge begins to emerge [14][15].
Again, smartphone scrolling should not be equated with tic disorders or body-focused repetitive behaviors. The relevance lies in the behavioral structure: detecting the beginning of an action and inserting another response before it is completed.
How HAKONE Applies the Evidence
HAKONE places a 60-second fingertip pause at the entrance to the automatic smartphone sequence.
The user does not continue swiping during this interval.
The habitual finger movement is temporarily replaced by stillness, converting an automatic movement into a deliberate task with:
-
a clear beginning;
-
a defined duration; and
-
a clear end.
The purpose of the pause is not to erase the learned habit.
The purpose is to prevent the sequence from reaching completion without a moment of evaluation.
The pause also prepares the user for the next step: an alternative motor, emotional, and cognitive sequence.
Established Evidence
Habitual cue–response sequences involve corticostriatal systems, including the posterior putamen and other regions of the basal ganglia [1–5].
Initiated responses can be inhibited through coordinated frontal–basal-ganglia pathways [6–13].
Sustained competing responses have behavioral support in habit-reversal research [14][15].
HAKONE Application
HAKONE inserts a 60-second period of fingertip stillness before scrolling continues.
The pause creates a physical and temporal boundary within the learned sequence and prepares the user to move toward a different action.
Boundary of Claim
No published study has yet established that HAKONE’s 60-second fingertip stillness:
-
recruits precisely the same pathways identified in stop-signal experiments;
-
reliably reduces smartphone use in all users;
-
changes basal-ganglia activity;
-
strengthens the hyperdirect pathway; or
-
eliminates an urge within one minute.
Direct testing with behavioral measures, active-control conditions, EEG, fNIRS, or fMRI is still required.
Website Statement
A deliberate 60-second pause creates a time boundary inside a learned smartphone sequence. Research on habit learning and response inhibition shows that cue-driven actions involve the striatum and that stopping an initiated response involves coordinated frontal–basal-ganglia networks. HAKONE applies these findings by interrupting the hand movement before scrolling continues. This is a literature-grounded application, not yet a direct demonstration of HAKONE-specific neural activity.
SCIENTIFIC BASIS 2
Tactile Anchoring and Present-Moment Attention
Why Fingertip Sensation May Help Return Attention From the Screen to the Body
The Scientific Proposition
Focused-attention meditation trains a repeated cognitive operation:
Select an object of attention
↓
Notice when attention has wandered
↓
Disengage from the distraction
↓
Return to the selected object
The object may be:
-
the breath;
-
posture;
-
bodily sensation;
-
a sound;
-
or another stable sensory experience.
Focused-attention practice is not based on the permanent absence of thought.
Its central operation is the repeated act of noticing distraction and returning attention.
Neuroimaging reviews indicate that focused-attention and mindfulness practices involve interactions among multiple systems, including:
-
executive-control networks;
-
salience networks;
-
default-mode networks;
-
anterior cingulate regions;
-
prefrontal regions;
-
insular regions; and
-
sensorimotor areas [16–18][27][28].
There is no single “meditation center” that becomes activated in every technique or every person.
The Fingertip as a Tactile Anchor
HAKONE uses the sensation of a fingertip resting on the smartphone screen as a tactile object of attention.
The user is not instructed to empty the mind.
Instead, the task is to notice:
-
the urge to move;
-
the physical contact with the screen;
-
pressure at the fingertip;
-
temperature;
-
stillness;
-
and the return of attention when it wanders.
The fingertip provides an immediately available, concrete bodily sensation.
For a beginner, this may be easier to follow than an abstract instruction such as:
“Clear your mind.”
A tactile signal gives the user something observable.
The user can tell whether:
-
the finger is still touching the screen;
-
the finger has begun to move;
-
attention has drifted toward another thought;
-
or attention has returned to the fingertip.
Directly Relevant Haptics-Assisted Meditation Research
Zheng and colleagues developed a haptics-assisted meditation procedure in which beginners synchronized fingertip pressure with respiration [26].
In an initial study, participants reported less mind-wandering during haptics-assisted meditation than during breath-counting meditation.
Following five days of practice, the experimental group improved on several attention measures. fNIRS measurements also indicated changes in prefrontal and sensorimotor activation and connectivity [26].
This is one of the closest published analogues to YUBIZEN because it combines:
-
meditation;
-
bodily attention;
-
fingertip sensation; and
-
physiological measurement.
However, the study differs from HAKONE in several important respects.
It involved:
-
both hands rather than one finger;
-
active adjustment of pressure;
-
synchronization with respiration;
-
a longer practice protocol;
-
no smartphone cue; and
-
a small preliminary sample.
The study therefore does not directly establish the effectiveness of placing one stationary finger on a smartphone for 60 seconds.
It does support the proposition that fingertip sensation can be incorporated into an attention practice and may help some beginners maintain attentional engagement.
Why a Tactile Anchor May Be Useful for Beginners
Meditation instructions can be difficult when they rely entirely on internal observation.
A tactile anchor may reduce some of this ambiguity.
It is:
-
physically present;
-
immediately measurable by the user;
-
available without special equipment;
-
possible without a formal seated posture;
-
and directly connected to the movement that is being interrupted.
The same screen that normally invites swiping is temporarily reassigned a different function.
For 60 seconds, it becomes the location of:
-
non-movement;
-
tactile observation; and
-
present-moment attention.
This is an important reversal of behavioral meaning.
The smartphone surface remains the same, but the action performed on that surface changes.
How HAKONE Applies the Evidence
The YUBIZEN attentional sequence is:
Notice the urge or beginning hand movement
↓
Keep the fingertip still
↓
Attend to contact, pressure, and temperature
↓
Notice distraction
↓
Return to the fingertip sensation
The user is not required to maintain perfect concentration.
Wandering is not treated as failure.
The relevant practice is:
Notice. Return. Continue.
Established Evidence
Focused-attention meditation repeatedly trains the process of detecting distraction and returning attention [16–18][27][28].
A pilot fNIRS study provides preliminary evidence that respiration-synchronized fingertip pressure can reduce mind-wandering and support attention-related processes in beginners [26].
HAKONE Application
YUBIZEN uses a stationary fingertip as a simple somatosensory anchor during the moment when a smartphone habit is about to begin.
Boundary of Claim
No published study has directly tested:
-
one stationary finger on a smartphone screen;
-
a 60-second tactile pause;
-
fingertip stillness triggered by a smartphone urge;
-
or the complete YUBIZEN procedure.
There is also no evidence that YUBIZEN necessarily produces the same effects as breath meditation, traditional Zen, or haptics-assisted respiration training.
A tactile anchor should therefore be described as an attentional support—not as a guaranteed method for producing a specific brain state.
Website Statement
Focused-attention practice is built around noticing distraction and returning to a chosen object. Preliminary haptics-assisted meditation research suggests that fingertip sensation can help beginners reduce mind-wandering and engage attention-related prefrontal and sensorimotor processes. HAKONE translates this principle into a 60-second tactile anchor on the smartphone itself.
SCIENTIFIC BASIS 3
Natural Flowing-Water Sound as Auditory Support
Why Continuous Nature Sound May Make Stillness Easier to Maintain
The Scientific Proposition
Smartphone audio often encourages rapid shifts in attention.
Notifications, speech, changing music, short videos, alerts, and sound effects repeatedly signal that another piece of information is available.
YUBIZEN replaces this variable and information-dense sound environment with a continuous flowing-water sound while the finger remains still.
The scientific claim is not that water sound automatically creates Zen or activates a specific inhibitory circuit.
The narrower proposition is:
Natural sound may provide a less demanding sensory context and may support physiological settling, stress recovery, or subjective comfort for some listeners.
Findings From Systematic Reviews and Meta-Analyses
Recent systematic reviews and meta-analyses have examined the relationship between exposure to natural sounds and physiological or psychological outcomes [29–31].
Reported outcomes include possible changes in:
-
heart rate;
-
blood pressure;
-
respiratory rate;
-
stress;
-
anxiety;
-
annoyance;
-
positive affect; and
-
subjective comfort.
Fan and Baharum reported statistically significant advantages of natural sounds over quiet conditions for heart rate, blood pressure, and respiratory rate, while not all subjective or physiological measures showed significant differences [29].
Zhu and colleagues reported pooled reductions in anxiety, heart rate, blood pressure, and respiratory rate, but also emphasized substantial heterogeneity and limited evidence for some cognitive-restoration outcomes [30].
Buxton and colleagues synthesized evidence associating natural sounds with lower stress and annoyance and with improvements in health-related outcomes and positive affect [31].
These reviews do not show that every natural sound has the same effect.
Results vary according to:
-
the type of sound;
-
volume;
-
duration;
-
study population;
-
control condition;
-
individual preference;
-
and outcome measured.
Experimental Evidence on Stress Recovery
Alvarsson and colleagues compared recovery following psychological stress during exposure to natural sound and environmental noise [32].
Natural sound was associated with faster recovery in measures of sympathetic activation than some noise conditions.
This suggests that the auditory environment can influence how physiological arousal changes after stress.
However, the study does not show that a nature sound will stop a habitual action or produce meditation.
Evidence From a 60-Second Forest-Sound Experiment
Jo and colleagues exposed 29 female university students to high-resolution forest and city sounds for 60 seconds [33].
Compared with the city-sound condition, forest sound was associated with:
-
lower heart rate;
-
lower indicators of sympathetic activity;
-
lower right-prefrontal oxygenated-hemoglobin concentration;
-
higher ratings of comfort;
-
higher ratings of relaxation; and
-
stronger ratings of naturalness.
The lower prefrontal oxygenation observed in this context should not be interpreted as reduced intelligence or weaker executive control.
It may reflect lower task demand or a more relaxed state.
This study is particularly relevant to YUBIZEN because its sound exposure also lasted 60 seconds.
Nevertheless, it tested forest sound rather than HAKONE’s specific flowing-water recording, and it did not involve fingertip stillness, smartphone cues, or meditation.
Water-Specific Evidence
Evidence specifically involving water sounds is more conditional.
Thoma and colleagues found that the stress-related effects of listening to water sounds varied according to participants’ somatic complaints [35].
Annerstedt and colleagues reported that natural sounds presented within a virtual forest environment could support physiological recovery after stress [34].
These studies indicate that water and nature sound may support a restorative sensory environment.
They also show that the response is not universal.
Individual differences, context, expectations, and sound preference may influence the outcome.
How HAKONE Applies the Evidence
The flowing-water sound in YUBIZEN is not presented as entertainment.
It does not provide:
-
semantic information;
-
a new story;
-
a changing social cue;
-
a notification;
-
or an invitation to search for the next item.
It functions as a continuous auditory background during a fixed 60-second interval.
Its proposed functions are to:
-
mark the beginning and duration of the pause;
-
reduce the perceived emptiness of waiting;
-
replace rapidly changing smartphone audio;
-
provide a stable auditory object;
-
and support the return of attention when it moves away from the fingertip.
The flowing-water sound is best described as auditory support for stillness—not as proof of a deeper or medically defined Zen state.
Established Evidence
Natural-sound research supports possible benefits for:
-
stress recovery;
-
heart rate;
-
blood pressure;
-
respiration;
-
anxiety;
-
comfort;
-
reduced annoyance; and
-
positive affect [29–35].
A 60-second forest-sound experiment found measurable physiological and subjective differences compared with city sound [33].
HAKONE Application
YUBIZEN uses continuous flowing-water sound to mark and support the 60-second non-scrolling interval.
Boundary of Claim
Existing research does not establish that flowing-water sound:
-
deepens Zen;
-
improves response inhibition;
-
activates a particular prefrontal or basal-ganglia pathway;
-
guarantees relaxation;
-
or causes every user to complete the pause.
Effects may differ according to the sound, listener, context, and outcome.
Website Statement
Natural sounds are associated with measurable changes in some autonomic, cardiovascular, respiratory, and emotional outcomes. In one study, only 60 seconds of forest sound produced different physiological and subjective responses from city sound. HAKONE uses flowing-water sound as a stable auditory environment for stillness, while avoiding the claim that sound alone creates Zen or guarantees behavioral control.
SCIENTIFIC BASIS 4
Stop, Notice, and Return
Repeated Recruitment of Attention and Control Processes
Zen Is a Practice of Returning—not a Guarantee of an Empty Mind
A central operation in focused-attention meditation is not the permanent absence of distraction.
It is the repeated sequence of:
Noticing that attention has wandered
↓
Disengaging from the distraction
↓
Returning to the selected object
Hasenkamp and colleagues used fMRI to examine fluctuating cognitive states during focused meditation [27].
They identified distinguishable phases associated with:
-
mind-wandering;
-
awareness of mind-wandering;
-
shifting attention; and
-
sustained attention.
This suggests that meditation is not one continuous, uniform brain state.
It is a dynamic sequence in which attention repeatedly moves away and returns.
Distributed Neural Networks in Meditation
Reviews and meta-analyses indicate that meditation practices involve distributed systems rather than one isolated center [16–18].
Reported regions include:
-
the anterior cingulate cortex;
-
prefrontal regions;
-
the insula;
-
supplementary motor regions;
-
the posterior cingulate cortex;
-
parietal regions;
-
and nodes within executive-control, salience, and default-mode networks.
Different meditation practices produce different activation patterns.
Findings also vary according to:
-
experience level;
-
technique;
-
task;
-
control group;
-
analysis method;
-
and duration of practice [16–18].
It is therefore scientifically inaccurate to state that all meditation simply “activates the prefrontal cortex.”
Evidence From Zen-Specific Studies
Kozasa and colleagues examined experienced meditators and non-meditators before and after a seven-day Zen retreat while participants completed a Stroop attention task [19].
Behavioral performance did not differ significantly between the groups.
However, experienced meditators showed lower task-related activity in regions including:
-
the anterior cingulate cortex;
-
ventromedial prefrontal cortex;
-
caudate;
-
putamen;
-
pallidum;
-
insula; and
-
posterior cingulate cortex.
The authors discussed this pattern as possible neural efficiency rather than simply stronger activation or deactivation.
The study does not prove that seven days of Zen created these differences, because experienced meditators already differed from non-meditators before the retreat.
Yu and colleagues studied beginners during a 20-minute Zen meditation session [20].
They reported changes involving:
-
anterior prefrontal activity;
-
EEG measures;
-
mood;
-
and measures associated with the serotonergic system.
Cross-sectional Zen research has also reported differences involving gray-matter volume, attentional performance, cortical thickness, and pain sensitivity [21][22].
Because some of these studies compare experienced practitioners with non-practitioners at one time point, they cannot establish that meditation alone caused the observed differences.
Pre-existing differences, lifestyle, personality, and self-selection may contribute.
Meditation and the Striatum
Kjaer and colleagues used PET to examine Yoga Nidra meditation, which is not the same as Zen [23].
They reported altered dopamine-related ligand binding in the ventral striatum during meditation.
This is evidence that a meditative state can be associated with striatal neurochemistry.
It should not be used to claim that:
-
YUBIZEN normalizes dopamine;
-
Zen always increases dopamine;
-
dopamine change is automatically beneficial;
-
or YUBIZEN reproduces Yoga Nidra.
Does Meditation Strengthen the Brain’s “Brake”?
A meta-analysis of 111 randomized controlled trials found small-to-moderate effects of mindfulness-based interventions on outcomes including:
-
global cognition;
-
executive attention;
-
working-memory accuracy;
-
inhibition accuracy;
-
shifting accuracy; and
-
sustained attention [24].
Another meta-analysis found small effects involving inhibition and working memory but concluded that evidence for executive-function improvement was not consistently robust across methods and samples [25].
The appropriate conclusion is therefore modest:
Sustained meditation or mindfulness training may support the accuracy of some attention and inhibition processes, but it does not uniformly improve every aspect of executive function and cannot be reduced to a single prefrontal brake.
YUBIZEN is also far shorter than most meditation programs examined in these studies.
How YUBIZEN Applies the Evidence
The YUBIZEN sequence is:
Notice the urge to touch or scroll
↓
Stop the finger
↓
Attend to fingertip sensation and flowing-water sound
↓
Recognize mind-wandering
↓
Return attention
↓
Choose the next action
Each YUBIZEN episode presents a brief task requiring:
-
awareness of the emerging action;
-
temporary non-completion of the movement;
-
attention to present sensory information;
-
recognition of distraction;
-
attentional return;
-
and behavioral choice.
These operations are consistent with functions attributed to frontal, cingulate, salience, sensorimotor, and basal-ganglia networks.
HAKONE has not yet measured those networks directly during YUBIZEN.
YUBIZEN and Traditional Zen Are Not Identical
Traditional Zen practice may include:
-
posture;
-
breathing;
-
sustained sitting;
-
long-term training;
-
teacher–student relationships;
-
philosophical or religious frameworks;
-
and a structured practice environment.
YUBIZEN does not reproduce all of these elements.
It is a 60-second digital behavior intervention performed at the point when a smartphone action is beginning.
The shared structural principle is narrower:
Stop. Notice. Return.
YUBIZEN translates that attentional structure into a brief tactile and auditory practice.
It should not be presented as medically reproducing traditional Zazen.
Established Evidence
Zen, focused-attention, and mindfulness research implicates distributed systems involved in:
-
attention;
-
monitoring;
-
salience;
-
executive control;
-
motor preparation;
-
self-reference;
-
and striatal processing [16–25][27][28].
Randomized-trial meta-analyses suggest small-to-moderate improvements in some cognitive and inhibitory outcomes [24][25].
HAKONE Application
YUBIZEN repeatedly presents a short stop–notice–return–choose task at the moment a habitual smartphone action is beginning.
Boundary of Claim
It has not been shown that each 60-second use of YUBIZEN:
-
activates the prefrontal cortex;
-
strengthens the hyperdirect pathway;
-
changes dopamine;
-
reproduces traditional Zen;
-
produces the same meditative state in every user;
-
or creates long-term executive-function improvement.
Website Statement
Zen and focused-attention practices train a recurring operation: notice distraction, disengage from it, and return. Neuroimaging links this operation to distributed attention, salience, monitoring, and control networks. YUBIZEN applies the same structural principle at the entrance to a smartphone habit, while remaining distinct from traditional Zen and from clinically validated meditation programs.
SCIENTIFIC BASIS 5
Post-Pause Action Replacement
Why HAKONE Designs What Happens After Stopping—not Only the Stop Itself
Stopping Alone Leaves an Empty Space
A pause may interrupt an action without changing what happens next.
When the 60 seconds end, the user may immediately return to scrolling unless another response is available.
HAKONE therefore follows YUBIZEN with a sequence that moves:
-
the hand;
-
attention;
-
emotion;
-
and language
away from the original action.
Fingertip pause
↓
Illustration Reading on paper
↓
Emotion selection
↓
Verbal reflection or AI-guided dialogue
↓
Deliberate next action
The system is not built only around the command:
“Do not scroll.”
It provides an alternative answer to the question:
“What do I do instead?”
Competing Responses and Habit-Reversal Evidence
Habit-reversal training teaches a person to:
-
notice an emerging urge or behavior; and
-
perform a competing response that is physically incompatible with the unwanted action.
Competing responses have been studied in body-focused repetitive behaviors and tic disorders [14][15].
Piacentini and colleagues reported that a comprehensive behavioral intervention containing habit-reversal elements improved tic severity in a randomized trial involving 126 children [15].
These studies do not concern smartphones.
Tic disorders and smartphone habits should not be treated as equivalent conditions.
The relevant behavioral principle is narrower:
An alternative action can be introduced at the point when a learned action is about to occur.
In HAKONE, drawing on paper cannot be performed at the same time as scrolling on the smartphone.
It therefore functions as a physically competing motor action.
Illustration Reading as a Different Motor–Cognitive Task
After YUBIZEN, HAKONE asks the user to pick up:
-
a pencil;
-
pen;
-
crayon;
-
or another drawing tool
and make lines, marks, shapes, or images on paper.
HAKONE calls this practice Illustration Reading.
The image does not need to be artistic, accurate, or recognizable.
The purpose is not artistic performance.
The purpose is to give the hand a different task.
Ino and colleagues used fMRI during a structured clock-drawing task and reported activity in regions including:
-
the posterior parietal cortex;
-
premotor regions;
-
the pre-supplementary motor area;
-
ventral prefrontal regions;
-
motor cortex;
-
and the cerebellum [36].
Purposeful drawing therefore combines:
-
visual processing;
-
spatial organization;
-
motor planning;
-
attention;
-
and hand movement.
That study used clock drawing, not free drawing.
It does not prove that free drawing rewrites or erases a scrolling circuit.
The scientifically defensible position is:
Drawing is a physically different and cognitively richer action that cannot be performed simultaneously with scrolling.
The HAKONE phrase—
“The drawing tool receives the impulse, and the paper absorbs what cannot yet be put into words”
—is an experiential metaphor.
It is not a literal neuroscientific claim.
Affect Labeling and Emotional Observation
Automatic smartphone use may occur in connection with:
-
boredom;
-
anxiety;
-
loneliness;
-
anger;
-
fatigue;
-
frustration;
-
uncertainty;
-
or discomfort.
If the screen is opened before the emotional state is recognized, the connection between emotion and behavior may remain hidden.
HAKONE therefore asks the user to identify the current emotional state.
Putting an emotional experience into words is known as affect labeling.
Lieberman and colleagues found that labeling negative emotional stimuli was associated with:
-
greater activity in the right ventrolateral prefrontal cortex; and
-
lower responses in the amygdala and other limbic regions [37].
Burklund and colleagues found that both affect labeling and cognitive reappraisal engaged regulatory prefrontal regions and were associated with lower amygdala activity and reduced subjective distress [38].
These findings support the process of turning an unexamined internal state into an object of observation and language.
They do not establish that:
-
selecting one label immediately removes an urge;
-
the same response occurs in every person;
-
or exactly 16 emotion categories are neurologically optimal.
The 16-category interface is a HAKONE design decision intended to balance detail with usability.
Verbal Reappraisal and Craving Regulation
An urge may initially appear without a clear verbal explanation:
“I just need to look.”
“I will not feel settled until I check.”
“I do not know why, but my hand is already moving.”
HAKONE uses verbal reflection to make the urge more observable.
Kober and colleagues studied cognitive regulation of craving [39].
When participants reconsidered the meaning and longer-term consequences of desired substances and foods, researchers observed:
-
increased prefrontal activity;
-
reduced activity in the ventral striatum;
-
reduced activity in the amygdala;
-
reduced activity in the ventral tegmental area; and
-
lower reported craving.
This does not show that every verbal question produces the same result.
It supports the broader principle that changing how an urge is mentally represented can alter subjective craving and activity in prefrontal–striatal systems.
The Urge Does Not Need to Disappear
Bowen and Marlatt examined a brief mindfulness-based “urge surfing” instruction among smokers [40].
The immediate intensity of the urge did not decline significantly.
Nevertheless, participants who received the instruction smoked fewer cigarettes during the following period.
This distinction is central to the HAKONE model:
An urge does not have to disappear before behavior changes.
The objective is not necessarily to eliminate the internal experience.
It is to change the relationship between the urge and the action that follows.
Goal-Directed Smartphone Use
Keller and colleagues examined a smartphone intervention designed to support self-efficacious and goal-directed use [41].
Participants in both the theory-based intervention and active digital-detox comparison showed reductions in problematic use and total smartphone time.
The theory-based intervention was not clearly superior to the active comparison.
However, planning and self-efficacy appeared relevant to behavioral change.
This supports a balanced principle:
Changing smartphone behavior may require more than restriction. It may also require planning, confidence, and a clear alternative response.
AI-Guided Reflection
HAKONE may use brief AI-guided dialogue to help the user consider:
-
What am I feeling?
-
What am I attempting to check?
-
Is this action necessary for my current purpose?
-
What may happen if I wait?
-
What do I want to choose next?
Conversational chatbot research in smoking cessation provides emerging evidence that structured dialogue can deliver coping and behavior-change content [42].
However, this field is still developing.
HAKONE uses AI as a reflective prompt—not as a diagnostic, therapeutic, or medical authority.
No evidence shows that a particular GPT exchange reproduces the neural effects observed in laboratory cognitive-reappraisal tasks.
The AI component should therefore be described as supporting:
-
verbalization;
-
self-observation;
-
planning;
-
and reflection.
It should not be described as directly activating or repairing the prefrontal cortex.
Established Evidence
The individual components of HAKONE’s post-pause sequence are supported by related evidence from:
-
competing-response interventions [14][15];
-
drawing neuroimaging [36];
-
affect-labeling fMRI [37][38];
-
cognitive regulation of craving [39];
-
urge surfing [40];
-
goal-directed smartphone interventions [41]; and
-
conversational behavior-support research [42].
HAKONE Application
HAKONE places drawing, emotional identification, and verbal reflection immediately after YUBIZEN.
Stopping is therefore followed by a concrete alternative motor–cognitive sequence.
Boundary of Claim
The complete ordered HAKONE sequence has not yet been directly compared with:
-
ordinary scrolling;
-
restriction alone;
-
digital detox;
-
meditation alone;
-
drawing alone;
-
emotional labeling alone;
-
or another active intervention.
Evidence for individual components does not equal proof of the integrated product.
Website Statement
HAKONE does not end with “do not scroll.” It replaces the original movement with drawing, turns emotion into an observable label, and converts an urge into language and choice. Each component has a related evidence base, although the complete HAKONE sequence remains an integrated mechanism that must be tested directly.
SCIENTIFIC BASIS 6
The 72-Hour Practice Window
Why Three Days Are Presented as an Initial Learning and Observation Period—not a Cure
Seventy-Two Hours Is Not a Magical Habit Deadline
HAKONE does not claim that a long-standing smartphone habit is:
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cured;
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erased;
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reset;
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or permanently rewired
within three days.
Habit formation and behavior change depend on many factors, including:
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the behavior;
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context;
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reinforcement;
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frequency;
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motivation;
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emotional state;
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environmental cues;
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and individual differences.
HAKONE uses 72 hours as an intensive initial period of observation and repeated practice.
During three days, a person is likely to encounter smartphone cues across different contexts:
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morning routines;
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work or study periods;
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boredom;
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waiting;
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fatigue;
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evening use;
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social situations;
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and emotional discomfort.
Each cue creates another opportunity to practice the alternative sequence.
The 72-hour period is long enough to observe behavior repeatedly, while remaining short enough to enter as a defined experiment rather than an indefinite prohibition.
Direct Evidence From 72-Hour Smartphone Research
Cue-Related fMRI Changes
Schmitgen and colleagues studied 25 young adults before and after 72 hours of smartphone restriction using cue-reactivity fMRI [47].
They reported modulation of neural responses in regions associated with:
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salience;
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motor inhibition;
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attention;
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and reward processing,
including the anterior cingulate cortex and nucleus accumbens.
This was a small study.
It did not demonstrate:
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structural brain change;
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recovery from addiction;
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permanent change;
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or the effectiveness of HAKONE.
It demonstrated that measurable neural responses to smartphone-related cues can differ after 72 hours of changed smartphone use.
Resting-State fMRI Changes
Haage and colleagues examined 36 adults with resting-state fMRI before and after 72 hours of smartphone restriction [48].
Participants with and without problematic smartphone use showed different patterns of change in:
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prefrontal regions;
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posterior cingulate regions;
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sensorimotor areas;
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visual areas;
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and other regions.
In the problematic-use group, greater craving was associated with lower intrinsic activity in the posterior cingulate cortex.
These findings indicate state-dependent differences.
They do not demonstrate that restriction produces a universal or beneficial effect in every user.
Subjective Withdrawal-Related Effects
Aarestad and colleagues randomly assigned 127 participants either to relinquish their smartphones for three days or continue normal use [43].
Participants with higher problematic-use scores reported stronger withdrawal-related effects and more negative affect under restriction.
The study measured subjective reports rather than neural activity.
It shows that the first three days can be psychologically meaningful and may be uncomfortable, particularly for individuals with stronger problematic-use tendencies.
This is one reason HAKONE does not define its 72-hour period as forced abstinence.
The system seeks to practice an alternative response while the smartphone remains part of everyday life.
Short-Term Learning Evidence
Tricomi and colleagues demonstrated that several days of repeated instrumental training could alter behavior and increase habit-related posterior-putamen responses [4].
This supports the broader principle that cue–response relationships and related striatal activity can begin changing during a period of several days.
It does not show that an existing smartphone habit can be reversed within the same period.
Dopamine-Related Plasticity Within 72 Hours
Lim and colleagues reported changes in striatal dopamine-receptor binding after 72 hours of sleep deprivation in a small mouse study [49].
They observed:
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lower D1-receptor binding;
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higher D3-receptor binding; and
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no significant change in D2-receptor binding.
This was an extreme animal sleep-deprivation procedure.
It was not a smartphone study.
The observed changes should not be presented as healthy or beneficial.
The study demonstrates only that measurable features of the dopamine system can respond within a 72-hour period under certain experimental conditions.
It does not establish that HAKONE changes human dopamine receptors.
How HAKONE Applies the Evidence
The repeated HAKONE sequence is:
A cue occurs in daily life
↓
YUBIZEN pause
↓
Alternative tactile and motor response
↓
Emotion and urge become observable
↓
The next action is chosen
↓
The sequence is repeated across 72 hours
The HAKONE proposition is deliberately limited.
It is not:
“A new habit is permanently installed in three days.”
It is:
Repeated practice may make “pause first” available as a new behavioral option alongside “open immediately.”
Seventy-two hours is therefore an initial opportunity to:
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observe automatic behavior;
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identify recurring cues;
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repeat the interruption;
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practice an alternative action;
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and collect early behavioral data.
Seventy-two hours is an initial window in which measurable responses may begin to change and a different action sequence can be practiced repeatedly. It is not a cure, reset, or completion point.
Established Evidence
Direct smartphone studies have reported measurable cue-related, resting-state, and subjective changes following 72 hours of restriction [43][47][48].
Short-term learning research shows that cue–response control and habit-related neural activity can begin changing within several days [4].
Animal evidence demonstrates that dopamine-related biological measures can respond within 72 hours under some conditions [49].
HAKONE Application
HAKONE uses 72 hours as a concentrated observation and practice period for repeating the pause-and-choose sequence across real-life contexts.
Boundary of Claim
No study has established that 72 hours of HAKONE:
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forms a new neural habit;
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cures problematic smartphone use;
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permanently changes reward circuitry;
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normalizes dopamine;
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produces the same response in every user;
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or creates effects that persist after the practice period.
Website Statement
Three days are long enough for smartphone-related neural and emotional responses to show measurable change in emerging research, and short-term learning studies show that cue–response patterns can begin shifting within days. HAKONE therefore treats 72 hours as an initial observation and training window—not as a cure, reset, or claim that a new habit is complete.
References for Scientific Basis 1–6
[1] Graybiel, A. M. (2008). Habits, rituals, and the evaluative brain. Annual Review of Neuroscience, 31, 359–387. https://doi.org/10.1146/annurev.neuro.29.051605.112851
[2] Wood, W., & Rünger, D. (2016). Psychology of habit. Annual Review of Psychology, 67, 289–314. https://doi.org/10.1146/annurev-psych-122414-033417
[3] Balleine, B. W., & O’Doherty, J. P. (2010). Human and rodent homologies in action control: Corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology, 35(1), 48–69. https://doi.org/10.1038/npp.2009.131
[4] Tricomi, E., Balleine, B. W., & O’Doherty, J. P. (2009). A specific role for posterior dorsolateral striatum in human habit learning. European Journal of Neuroscience, 29(11), 2225–2232. https://doi.org/10.1111/j.1460-9568.2009.06796.x
[5] Smith, K. S., & Graybiel, A. M. (2016). The striatum: Where skills and habits meet. Cold Spring Harbor Perspectives in Biology, 8(8), a021691. https://doi.org/10.1101/cshperspect.a021691
[6] Aron, A. R., Fletcher, P. C., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2003). Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nature Neuroscience, 6(2), 115–116. https://doi.org/10.1038/nn1003
[7] Aron, A. R., & Poldrack, R. A. (2006). Cortical and subcortical contributions to stop-signal response inhibition: Role of the subthalamic nucleus. Journal of Neuroscience, 26(9), 2424–2433. https://doi.org/10.1523/JNEUROSCI.4682-05.2006
[8] Aron, A. R., Durston, S., Eagle, D. M., Logan, G. D., Stinear, C. M., & Stuphorn, V. (2007). Converging evidence for a fronto-basal-ganglia network for inhibitory control of action and cognition. Journal of Neuroscience, 27(44), 11860–11864. https://doi.org/10.1523/JNEUROSCI.3644-07.2007
[9] Jahfari, S., Waldorp, L., van den Wildenberg, W. P. M., Scholte, H. S., Ridderinkhof, K. R., & Forstmann, B. U. (2011). Effective connectivity reveals important roles for both the hyperdirect and indirect fronto-basal-ganglia pathways during response inhibition. Journal of Neuroscience, 31(18), 6891–6899. https://doi.org/10.1523/JNEUROSCI.5253-10.2011
[10] Nambu, A., Tokuno, H., & Takada, M. (2002). Functional significance of the cortico-subthalamo-pallidal hyperdirect pathway. Neuroscience Research, 43(2), 111–117. https://doi.org/10.1016/S0168-0102(02)00027-5
[11] Rae, C. L., Hughes, L. E., Anderson, M. C., & Rowe, J. B. (2015). The prefrontal cortex achieves inhibitory control by facilitating subcortical motor pathway connectivity. Journal of Neuroscience, 35(2), 786–794. https://doi.org/10.1523/JNEUROSCI.3093-13.2015
[12] Wessel, J. R., & Aron, A. R. (2017). On the globality of motor suppression: Unexpected events and their influence on behavior and cognition. Neuron, 93(2), 259–280. https://doi.org/10.1016/j.neuron.2016.12.013
[13] Chambers, C. D., Bellgrove, M. A., Stokes, M. G., et al. (2006). Executive brake failure following deactivation of human frontal lobe. Journal of Cognitive Neuroscience, 18(3), 444–455. https://doi.org/10.1162/089892906775990606
[14] Twohig, M. P., & Woods, D. W. (2001). Evaluating the duration of the competing response in habit reversal: A parametric analysis. Journal of Applied Behavior Analysis, 34(4), 517–520. https://doi.org/10.1901/jaba.2001.34-517
[15] Piacentini, J., Woods, D. W., Scahill, L., et al. (2010). Behavior therapy for children with Tourette disorder: A randomized controlled trial. JAMA, 303(19), 1929–1937. https://doi.org/10.1001/jama.2010.607
[16] Tang, Y. Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16(4), 213–225. https://doi.org/10.1038/nrn3916
[17] Fox, K. C. R., Dixon, M. L., Nijeboer, S., et al. (2016). Functional neuroanatomy of meditation: A review and meta-analysis of 78 functional neuroimaging investigations. Neuroscience & Biobehavioral Reviews, 65, 208–228. https://doi.org/10.1016/j.neubiorev.2016.03.021
[18] Ganesan, S., Beyer, E., Moffat, B., Van Dam, N. T., Lorenzetti, V., & Zalesky, A. (2022). Focused attention meditation in healthy adults: A systematic review and meta-analysis of cross-sectional functional MRI studies. Neuroscience & Biobehavioral Reviews, 141, 104846. https://doi.org/10.1016/j.neubiorev.2022.104846
[19] Kozasa, E. H., Balardin, J. B., Sato, J. R., et al. (2018). Effects of a 7-day meditation retreat on the brain function of meditators and non-meditators during an attention task. Frontiers in Human Neuroscience, 12, 222. https://doi.org/10.3389/fnhum.2018.00222
[20] Yu, X., Fumoto, M., Nakatani, Y., et al. (2011). Activation of the anterior prefrontal cortex and serotonergic system is associated with improvements in mood and EEG changes induced by Zen meditation practice in novices. International Journal of Psychophysiology, 80(2), 103–111. https://doi.org/10.1016/j.ijpsycho.2011.02.004
[21] Pagnoni, G., & Cekic, M. (2007). Age effects on gray matter volume and attentional performance in Zen meditation. Neurobiology of Aging, 28(10), 1623–1627. https://doi.org/10.1016/j.neurobiolaging.2007.06.008
[22] Grant, J. A., Courtemanche, J., Duerden, E. G., Duncan, G. H., & Rainville, P. (2010). Cortical thickness and pain sensitivity in Zen meditators. Emotion, 10(1), 43–53. https://doi.org/10.1037/a0018334
[23] Kjaer, T. W., Bertelsen, C., Piccini, P., Brooks, D., Alving, J., & Lou, H. C. (2002). Increased dopamine tone during meditation-induced change of consciousness. Cognitive Brain Research, 13(2), 255–259. https://doi.org/10.1016/S0926-6410(01)00106-9
[24] Zainal, N. H., & Newman, M. G. (2024). Mindfulness enhances cognitive functioning: A meta-analysis of 111 randomized controlled trials. Health Psychology Review, 18(2), 369–395. https://doi.org/10.1080/17437199.2023.2248222
[25] Millett, G., D’Amico, D., Amestoy, M. E., Gryspeerdt, C., & Fiocco, A. J. (2021). Do group-based mindfulness meditation programs enhance executive functioning? A systematic review and meta-analysis of the evidence. Consciousness and Cognition, 95, 103195. https://doi.org/10.1016/j.concog.2021.103195
[26] Zheng, Y. L., Wang, D. X., Zhang, Y. R., & Tang, Y. Y. (2019). Enhancing attention by synchronizing respiration and fingertip pressure: A pilot study using functional near-infrared spectroscopy. Frontiers in Neuroscience, 13, 1209. https://doi.org/10.3389/fnins.2019.01209
[27] Hasenkamp, W., Wilson-Mendenhall, C. D., Duncan, E., & Barsalou, L. W. (2012). Mind wandering and attention during focused meditation: A fine-grained temporal analysis of fluctuating cognitive states. NeuroImage, 59(1), 750–760. https://doi.org/10.1016/j.neuroimage.2011.07.008
[28] Farb, N. A. S., Segal, Z. V., Mayberg, H., et al. (2007). Attending to the present: Mindfulness meditation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313–322. https://doi.org/10.1093/scan/nsm030
[29] Fan, L., & Baharum, M. R. (2024). The effect of exposure to natural sounds on stress reduction: A systematic review and meta-analysis. Stress, 27(1), 2402519. https://doi.org/10.1080/10253890.2024.2402519
[30] Zhu, R., Yuan, L., Pan, Y., Wang, Y., Xiu, D., & Liu, W. (2024). Effects of natural sound exposure on health recovery: A systematic review and meta-analysis. Science of the Total Environment, 921, 171052. https://doi.org/10.1016/j.scitotenv.2024.171052
[31] Buxton, R. T., Pearson, A. L., Allou, C., Fristrup, K., & Wittemyer, G. (2021). A synthesis of health benefits of natural sounds and their distribution in national parks. Proceedings of the National Academy of Sciences of the United States of America, 118(14), e2013097118. https://doi.org/10.1073/pnas.2013097118
[32] Alvarsson, J. J., Wiens, S., & Nilsson, M. E. (2010). Stress recovery during exposure to nature sound and environmental noise. International Journal of Environmental Research and Public Health, 7(3), 1036–1046. https://doi.org/10.3390/ijerph7031036
[33] Jo, H., Song, C., Ikei, H., et al. (2019). Physiological and psychological effects of forest and urban sounds using high-resolution sound sources. International Journal of Environmental Research and Public Health, 16(15), 2649. https://doi.org/10.3390/ijerph16152649
[34] Annerstedt, M., Jönsson, P., Wallergård, M., et al. (2013). Inducing physiological stress recovery with sounds of nature in a virtual reality forest—results from a pilot study. Physiology & Behavior, 118, 240–250. https://doi.org/10.1016/j.physbeh.2013.05.023
[35] Thoma, M. V., Mewes, R., & Nater, U. M. (2018). Preliminary evidence: The stress-reducing effect of listening to water sounds depends on somatic complaints: A randomized trial. Medicine, 97(8), e9851. https://doi.org/10.1097/MD.0000000000009851
[36] Ino, T., Asada, T., Ito, J., Kimura, T., & Fukuyama, H. (2003). Parieto-frontal networks for clock drawing revealed with fMRI. Neuroscience Research, 45(1), 71–77. https://doi.org/10.1016/S0168-0102(02)00194-3
[37] Lieberman, M. D., Eisenberger, N. I., Crockett, M. J., et al. (2007). Putting feelings into words: Affect labeling disrupts amygdala activity in response to affective stimuli. Psychological Science, 18(5), 421–428. https://doi.org/10.1111/j.1467-9280.2007.01916.x
[38] Burklund, L. J., Creswell, J. D., Irwin, M. R., & Lieberman, M. D. (2014). The common and distinct neural bases of affect labeling and reappraisal in healthy adults. Frontiers in Psychology, 5, 221. https://doi.org/10.3389/fpsyg.2014.00221
[39] Kober, H., Mende-Siedlecki, P., Kross, E. F., et al. (2010). Prefrontal-striatal pathway underlies cognitive regulation of craving. Proceedings of the National Academy of Sciences of the United States of America, 107(33), 14811–14816. https://doi.org/10.1073/pnas.1007779107
[40] Bowen, S., & Marlatt, A. (2009). Surfing the urge: Brief mindfulness-based intervention for college student smokers. Psychology of Addictive Behaviors, 23(4), 666–671. https://doi.org/10.1037/a0017127
[41] Keller, J., Roitzheim, C., Radtke, T., Schenkel, K., & Schwarzer, R. (2021). A mobile intervention for self-efficacious and goal-directed smartphone use in the general population: Randomized controlled trial. JMIR mHealth and uHealth, 9(11), e26397. https://doi.org/10.2196/26397
[42] Bricker, J. B., Sullivan, B., Mull, K., Santiago-Torres, M., & Lavista Ferres, J. M. (2024). Conversational chatbot for cigarette smoking cessation: Results from the 11-step user-centered design development process and randomized controlled trial. JMIR mHealth and uHealth, 12, e57318. https://doi.org/10.2196/57318
[43] Aarestad, S. H., Flaa, T. A., Griffiths, M. D., & Pallesen, S. (2023). Smartphone addiction and subjective withdrawal effects: A three-day experimental study. SAGE Open, 13(4), 21582440231219538. https://doi.org/10.1177/21582440231219538
[44] Schmitgen, M. M., Horvath, J., Mundinger, C., et al. (2020). Neural correlates of cue reactivity in individuals with smartphone addiction. Addictive Behaviors, 108, 106422. https://doi.org/10.1016/j.addbeh.2020.106422
[45] Gao, L., Zhang, J., Xie, H., Nie, Y., Zhao, Q., & Zhou, Z. (2020). Effect of the mobile phone-related background on inhibitory control of problematic mobile phone use: An event-related potentials study. Addictive Behaviors, 108, 106363. https://doi.org/10.1016/j.addbeh.2020.106363
[46] Schmitgen, M. M., et al. (2023). Cognitive domain-independent aberrant frontoparietal network strength in individuals with excessive smartphone use. Psychiatry Research: Neuroimaging, 329, 111593. https://doi.org/10.1016/j.pscychresns.2023.111593
[47] Schmitgen, M. M., Henemann, G. M., Koenig, J., et al. (2025). Effects of smartphone restriction on cue-related neural activity. Computers in Human Behavior, 167, 108610. https://doi.org/10.1016/j.chb.2025.108610
[48] Haage, S. H., Schmitgen, M. M., Henemann, G. M., et al. (2026). Smartphone restriction modulates intrinsic neural activity in problematic smartphone users: Evidence from resting-state fMRI. Addictive Behaviors, 174, 108575. https://doi.org/10.1016/j.addbeh.2025.108575
[49] Lim, M. M., Xu, J., Holtzman, D. M., & Mach, R. H. (2011). Sleep deprivation differentially affects dopamine receptor subtypes in mouse striatum. NeuroReport, 22(10), 489–493. https://doi.org/10.1097/WNR.0b013e32834846a0
HAKONE Integrated Mechanism Model
How Six Science-Informed Components Work Together as One Behavioral Sequence
HAKONE is not based on the idea that one sound, one exercise, or one brain region can stop automatic smartphone use.
Its design combines six distinct mechanisms into one ordered behavioral sequence:
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a deliberate interruption of the habitual hand movement;
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tactile attention to the fingertip;
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a continuous flowing-water sound;
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the repeated operation of stopping, noticing, and returning;
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replacement of scrolling with motor, emotional, and verbal actions; and
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repetition of the complete sequence across a 72-hour practice window.
Each component has a related scientific foundation.
However, the complete sequence is more than the sum of its individual parts.
The purpose of this layer is to explain how the six components interact as one integrated model.
HAKONE does not attempt to switch off the basal ganglia. It inserts enough structure into the beginning of a learned action sequence for attention, inhibition, emotional awareness, and deliberate choice to become available before the sequence is completed.
The Ordinary Habitual Sequence
Repeated smartphone behavior can become linked to external and internal cues.
External cues may include:
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a notification;
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an application icon;
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the sight of the device;
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a familiar location;
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a particular time of day;
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or another person using a smartphone.
Internal cues may include:
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boredom;
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anxiety;
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loneliness;
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fatigue;
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frustration;
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uncertainty;
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or the desire for reassurance.
Once a cue has become strongly associated with smartphone use, the first movement may retrieve a larger learned sequence.
The Cue-Driven Pathway
Smartphone-related cue
↓
The learned action sequence becomes available
↓
The hand reaches for the device
↓
The screen is opened
↓
Scrolling begins
↓
The next cue, item, or reward is sought
↓
The sequence continues beyond the original intention
Habit research links cue-driven action with corticostriatal systems, including the striatum, posterior putamen, and other parts of the basal ganglia [1–5].
This does not mean that the basal ganglia force the user to continue.
It means that repeated behavior can become efficient enough to proceed with progressively less conscious deliberation.
The learned sequence may therefore begin before the person has clearly answered three important questions:
Why am I opening this?
What do I intend to do?
When will I stop?
The HAKONE Intervention Sequence
HAKONE intervenes before the ordinary sequence reaches completion.
The HAKONE Pathway
Smartphone-related cue
↓
60-second fingertip stillness
↓
Attention to fingertip contact
↓
Continuous flowing-water sound
↓
Awareness of urge, distraction, and internal state
↓
Illustration Reading on paper
↓
Emotion identification
↓
Verbal reflection or AI-guided dialogue
↓
Deliberate selection of the next action
↓
The complete sequence is repeated across 72 hours
The intervention does not guarantee that the user will decide to put the smartphone down.
The user may still decide that opening the device is necessary.
The intended change is not:
never use the smartphone.
It is:
do not allow the learned sequence to complete the decision automatically.
Stage 1
A Cue Activates the Learned Sequence
The intervention begins with a cue.
At this stage, the urge may not yet be verbal.
The user may simply notice:
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the hand moving;
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the desire to check;
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physical restlessness;
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an expectation of information;
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or discomfort at not knowing what is on the screen.
The cue does not need to be eliminated.
HAKONE treats it as the beginning of an observable sequence.
This distinction matters.
A cue is not the same as an action.
An urge is not the same as a command.
A prepared movement is not yet a completed behavior.
The intervention begins by identifying the point at which the cue is becoming an action.
Stage 2
Fingertip Stillness Interrupts Motor Completion
The fingertip remains still on the smartphone for 60 seconds.
The finger is physically prevented from performing its familiar scrolling movement during this interval.
The purpose is not to suppress the basal ganglia or erase the learned response.
It is to create a defined boundary between:
the impulse to move
and:
the completion of the movement.
Research on response inhibition indicates that stopping an initiated action involves coordinated networks including the right inferior frontal cortex, pre-supplementary motor area, subthalamic nucleus, striatum, globus pallidus, and motor regions [6–13].
HAKONE applies the general principle of action interruption.
It has not yet been shown that its 60-second fingertip procedure recruits precisely the same neural pathway as a laboratory stop-signal task.
Function Within the Integrated Model
The pause:
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interrupts the scrolling movement;
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makes the normally automatic action observable;
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introduces a measurable delay;
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marks the beginning of the intervention;
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and prevents the original sequence from continuing without evaluation.
The first function of YUBIZEN is not relaxation. It is non-completion of the habitual movement.
Relaxation may occur for some users, but it is not required for the pause to serve its behavioral function.
Stage 3
Fingertip Sensation Becomes an Attention Anchor
Once the finger has stopped, the user directs attention toward the physical sensation of contact.
The relevant sensations may include:
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pressure;
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temperature;
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contact with the glass;
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muscle tension;
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stillness;
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or the urge to move.
Focused-attention meditation repeatedly trains the process of:
noticing distraction
↓
disengaging from it
↓
returning to a selected object
[16–18][27][28].
Preliminary haptics-assisted meditation research suggests that fingertip sensation can be used as a concrete attentional aid for beginners [26].
Function Within the Integrated Model
Tactile attention converts the smartphone screen from an object that normally invites movement into a temporary location of non-movement and observation.
The same surface is assigned a different behavioral meaning.
Ordinary meaning of the screen
Touch in order to obtain more information.
Temporary YUBIZEN meaning
Touch without moving, and observe what is happening.
The user is not required to remove all thoughts.
The task is simply:
Notice when attention leaves the fingertip and return to the sensation of contact.
Stage 4
Flowing-Water Sound Provides a Stable Auditory Environment
During the 60-second pause, HAKONE plays a continuous flowing-water sound.
Ordinary smartphone audio often promotes attentional switching.
Notifications, speech, clips, changing music, and sound effects signal that another item is available.
The flowing-water sound does not provide a new message or narrative.
It does not ask the user to evaluate language or search for the next item.
It creates a relatively stable auditory background.
Research on natural sounds has reported changes in some measures of:
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stress recovery;
-
heart rate;
-
blood pressure;
-
respiratory rate;
-
sympathetic activity;
-
anxiety;
-
comfort;
-
annoyance;
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and positive affect [29–35].
A 60-second experiment comparing forest and urban sounds found measurable physiological and subjective differences [33].
Function Within the Integrated Model
The sound may:
-
mark the duration of the pause;
-
provide continuity while the finger remains still;
-
reduce the perceived emptiness of waiting;
-
replace rapidly changing smartphone audio;
-
and give attention a second stable object when it moves away from the fingertip.
The sound is not presented as a cure or as proof of a meditative brain state.
Its proposed role is to support the stillness interval—not to create Zen by itself.
The fingertip and water sound therefore form a two-part attentional environment:
tactile anchor
+
auditory anchor
If attention moves away from one, the other remains available.
Stage 5
Stop, Notice, and Return
YUBIZEN does not depend on perfect concentration.
The user may think about a message, become impatient, remember a task, or feel the urge to move.
This is not treated as failure.
The operational sequence is:
Notice the urge
↓
Do not complete the movement immediately
↓
Return attention to the fingertip or water sound
↓
Notice again when attention wanders
↓
Return again
Focused-attention and Zen research describes meditation as a dynamic process involving mind-wandering, awareness, attentional shifting, and sustained attention rather than one continuous state of mental emptiness [16–28].
Function Within the Integrated Model
Every return provides another opportunity to distinguish:
the appearance of an impulse
from:
the execution of an action.
The user is not attempting to destroy the urge.
The user is practicing remaining present while the urge exists without allowing it to complete the next action automatically.
HAKONE therefore treats awareness as an event that can occur between a cue and a response.
Stage 6
The Empty Space Is Filled With an Alternative Action
Stopping alone may leave the original sequence ready to restart.
When the 60 seconds end, the user may immediately resume scrolling unless another action is available.
HAKONE therefore does not end with stillness.
It redirects the user into a different motor–cognitive sequence.
The Post-Pause Sequence
Release the smartphone movement
↓
Pick up a drawing tool
↓
Make marks on paper
↓
Identify the current emotional state
↓
Put the urge into words
↓
Consider the next action
This sequence moves the user through several forms of processing.
Motor processing
The hand moves from swiping to drawing.
Visual and spatial processing
The user observes and organizes marks on paper.
Emotional processing
The user identifies the present internal state.
Language processing
The urge becomes something that can be described.
Behavioral evaluation
The user considers whether opening the smartphone still serves the present goal.
Illustration Reading
Replacing Swiping With Intentional Mark-Making
HAKONE calls the drawing stage Illustration Reading.
The user may draw:
-
a line;
-
a shape;
-
a pattern;
-
an unrecognizable mark;
-
or a more complete image.
The purpose is not artistic quality.
It is to give the hand a task that is physically incompatible with scrolling.
Habit-reversal research supports the general use of competing actions introduced when an unwanted behavior is about to occur [14][15].
Drawing research also indicates that purposeful drawing can engage distributed networks involved in vision, motor planning, spatial organization, and hand movement [36].
Function Within the Integrated Model
Illustration Reading prevents the intervention from ending as passive restraint.
It moves the user from:
not doing the old action
to:
actively performing another action.
The HAKONE metaphor that the drawing tool “receives the impulse” and the paper “absorbs what cannot yet be put into words” describes the user experience.
It is not intended as a literal neuroscientific claim.
Emotion Identification
Making the Internal Trigger Observable
Automatic smartphone use may occur in connection with an emotional state that has not yet been consciously recognized.
The user may feel:
-
bored;
-
lonely;
-
anxious;
-
angry;
-
fatigued;
-
restless;
-
frustrated;
-
or uncertain.
HAKONE asks the user to select the emotion that best describes the present state.
Affect-labeling studies indicate that putting emotional experience into words can involve prefrontal regulatory regions and may be associated with lower amygdala or limbic responses [37][38].
Function Within the Integrated Model
Emotion identification introduces a different question:
Instead of:
“What is on the screen?”
the user asks:
“What is happening inside me before I open the screen?”
This may make recurring behavioral triggers more visible over time.
The 16-category interface is a HAKONE design decision.
Research supports the general act of affect labeling, but it does not establish that exactly 16 categories are neurologically optimal.
Verbal Reflection
Turning an Urge Into Something That Can Be Examined
An urge often begins as a movement or sensation before it becomes a sentence.
HAKONE uses short reflective prompts such as:
What are you feeling?
What are you trying to check?
Does opening the smartphone serve your present goal?
What do you expect to happen if you wait?
What would you like to choose next?
Cognitive-reappraisal research shows that changing the way a craving is mentally represented can alter subjective craving and activity in prefrontal–striatal systems [39].
Urge-surfing research also suggests that behavior can change even when the immediate urge does not disappear [40].
Goal-directed smartphone research indicates that planning and self-efficacy can contribute to changes in use [41].
Conversational chatbot studies provide emerging evidence that structured dialogue can deliver coping and behavior-change content [42].
Function Within the Integrated Model
Verbal reflection transforms:
an automatic movement
into:
an object of thought.
The AI component is not used as a medical authority.
It does not diagnose addiction or determine what the user must do.
Its role is to support:
-
clarification;
-
self-observation;
-
planning;
-
and deliberate choice.
Stage 7
The User Selects the Next Action
At the end of the sequence, the user makes a choice.
Possible choices may include:
-
opening the smartphone for a defined purpose;
-
delaying use;
-
placing the smartphone down;
-
completing another task;
-
continuing the reflective exercise;
-
or contacting someone intentionally.
HAKONE does not predetermine that one choice is always correct.
Its central aim is to restore the point at which a choice can occur.
The Difference Between Avoidance and Choice
Avoidance model
The smartphone must never be opened.
HAKONE model
The smartphone should not be opened solely because the learned sequence has already begun.
Intentional smartphone use remains possible.
The targeted problem is automatic continuation without a current purpose.
Stage 8
Repetition Across 72 Hours
One use of YUBIZEN is not expected to erase a long-standing behavioral pattern.
HAKONE repeats the complete sequence during a 72-hour observation and practice window.
Each real-life cue becomes another practice opportunity.
The user may encounter cues:
-
after waking;
-
during work;
-
while waiting;
-
during emotional discomfort;
-
when fatigued;
-
before sleep;
-
or during social situations.
The Repeated Learning Sequence
Cue
↓
Pause
↓
Tactile and auditory attention
↓
Alternative action
↓
Emotion identification
↓
Verbal reflection
↓
Choice
Repeated training research indicates that cue–response relationships and habit-related striatal activity can begin shifting over several days [4].
Emerging smartphone research also shows that cue-related neural activity, resting-state activity, craving relationships, and subjective withdrawal-related responses can differ following 72 hours of restriction [43][47][48].
These studies do not directly test HAKONE.
They support the narrower proposition that smartphone-related responses are not necessarily fixed and may show measurable short-term change.
Function Within the Integrated Model
The 72-hour period is intended to make a new response available:
Existing response
Cue → open immediately.
Practiced alternative
Cue → pause first → observe → choose.
The goal is not to complete a new permanent habit within three days.
The goal is to begin making “pause first” an executable behavioral option.
How the Six Scientific Bases Interact
The six foundations are not separate modules operating independently.
Each prepares the conditions required for the next.
Basis 1: Temporal Interruption
Creates enough time for the original action sequence to remain incomplete.
Basis 2: Tactile Anchoring
Gives attention a concrete bodily target during the pause.
Basis 3: Flowing-Water Sound
Provides a stable auditory environment that may support the stillness interval.
Basis 4: Stop, Notice, and Return
Turns distraction and urge awareness into repeated attentional operations.
Basis 5: Post-Pause Action Replacement
Prevents the pause from ending in an immediate return to the original behavior.
Basis 6: Repetition Across 72 Hours
Allows the complete sequence to be practiced under different real-life cues and emotional conditions.
The integrated mechanism can therefore be expressed as:
Interruption creates time.
Tactile and auditory anchors organize attention.
Awareness makes the urge observable.
Alternative action redirects the hand.
Emotion and language make the internal trigger examinable.
Deliberate choice changes what happens next.
Repetition makes the alternative sequence increasingly available.
The Model Does Not Depend on One Single Brain Region
It would be misleading to claim that HAKONE simply “activates the prefrontal cortex.”
The processes involved are distributed.
Related research implicates systems involved in:
-
habit learning;
-
action selection;
-
response inhibition;
-
motor preparation;
-
attention monitoring;
-
salience detection;
-
somatosensory processing;
-
emotional regulation;
-
language;
-
craving;
-
and goal-directed planning [1–49].
These processes involve regions that may include:
-
prefrontal cortical areas;
-
anterior cingulate cortex;
-
supplementary and premotor areas;
-
insular cortex;
-
posterior cingulate cortex;
-
parietal cortex;
-
amygdala;
-
striatum;
-
globus pallidus;
-
subthalamic nucleus;
-
sensorimotor regions;
-
and cerebellum.
HAKONE does not claim that every region is activated during every use.
The model proposes that the intervention requires operations known to depend on distributed control, attention, motor, emotional, and learning systems.
What HAKONE Is Attempting to Change
The direct target is not a single molecule, receptor, or brain structure.
The primary target is the relationship between:
cue
and
action.
HAKONE aims to modify four relationships.
1. Cue–movement relationship
The cue no longer has to be followed immediately by swiping.
2. Urge–behavior relationship
The presence of an urge no longer has to determine the next action.
3. Emotion–screen relationship
An emotional state can be identified before it is automatically redirected into smartphone use.
4. Smartphone–purpose relationship
The device can be opened for a chosen purpose rather than through unexamined continuation.
The Integrated Scientific Proposition
The full HAKONE model can be stated as follows:
Repeated smartphone cues may retrieve learned action sequences involving corticostriatal habit systems. HAKONE inserts a 60-second period of fingertip stillness and flowing-water sound before the usual movement is completed. During this interval, the user practices tactile attention, awareness of distraction, and attentional return. The pause is followed by drawing, affect labeling, verbal reflection, and deliberate behavioral selection. Repeating this sequence across 72 hours may make “pause and choose” increasingly available as an alternative to immediate cue-driven smartphone use.
This is a literature-grounded integrated model.
It is not yet a directly demonstrated HAKONE-specific neural mechanism.
Evidence Classification of the Integrated Model
Directly Supported Principles
Existing studies support the following individual principles:
-
repeated behavior can become cue-driven [1–5];
-
initiated actions can be inhibited [6–13];
-
competing responses can interrupt habitual or repetitive actions [14][15];
-
focused-attention practice involves noticing and returning [16–28];
-
fingertip sensation can be incorporated into an attention practice [26];
-
natural sounds can influence some physiological and emotional outcomes [29–35];
-
drawing recruits distributed visual and motor networks [36];
-
affect labeling changes emotional processing [37][38];
-
craving can be cognitively reappraised [39];
-
behavior can change without complete disappearance of an urge [40];
-
planning and self-efficacy can support smartphone-behavior change [41];
-
structured conversational support can deliver behavior-change content [42];
-
and measurable smartphone-related responses can differ after 72 hours [43][47][48].
Literature-Grounded HAKONE Applications
The following are applications of existing knowledge:
-
placing the pause at the entrance to smartphone use;
-
using one stationary fingertip as a tactile anchor;
-
using flowing-water sound during the pause;
-
following stillness with Illustration Reading;
-
using 16 emotion categories;
-
using AI-guided reflection;
-
and combining all components in one 72-hour sequence.
HAKONE-Specific Questions Still Requiring Direct Testing
Research has not yet established whether the complete intervention:
-
reduces unplanned smartphone opening;
-
reduces continuous-session duration;
-
increases canceled opening attempts;
-
improves response inhibition;
-
changes autonomic regulation;
-
changes smartphone-cue reactivity;
-
changes frontal or basal-ganglia activity;
-
creates a new learned response;
-
or produces effects that remain after 72 hours.
The source document deliberately separates established findings, product application, and unverified product-specific claims rather than presenting component evidence as proof of the whole system.
A Testable Model
A scientifically useful mechanism model must generate measurable predictions and remain open to being challenged.
If the HAKONE model is correct, controlled studies may observe some of the following outcomes:
-
a longer delay between a smartphone cue and opening the screen;
-
more occasions on which an intended opening action is canceled;
-
fewer unplanned unlocks;
-
shorter continuous smartphone sessions;
-
improved identification of emotional or situational triggers;
-
weaker coupling between reported urge intensity and immediate action;
-
changes in heart rate, heart-rate variability, respiration, skin conductance, or subjective arousal during YUBIZEN;
-
changes in stop-signal or Go/No-Go task performance;
-
changes in EEG, fNIRS, or fMRI measures related to attention, monitoring, inhibition, or smartphone-cue processing;
-
and persistence—or disappearance—of effects after the 72-hour practice period.
Null findings would also be informative.
They could indicate that:
-
60 seconds is too short;
-
fingertip contact provides no advantage;
-
flowing-water sound adds no measurable benefit;
-
the post-pause sequence is too demanding;
-
effects occur only in particular users;
-
or the complete sequence requires redesign.
The attached scientific framework similarly defines the model through observable behavioral and physiological predictions and treats negative findings as useful evidence rather than failure.
Scientific Boundary of the Integrated Model
The integrated model does not establish that:
-
HAKONE directly activates the prefrontal cortex;
-
HAKONE suppresses basal-ganglia habit activity;
-
YUBIZEN strengthens the hyperdirect pathway;
-
flowing-water sound deepens Zen;
-
fingertip stillness normalizes dopamine;
-
Illustration Reading rewrites a neural circuit;
-
AI dialogue reproduces laboratory cognitive reappraisal;
-
a new habit is completed within 72 hours;
-
problematic smartphone use is cured;
-
or every user experiences the same outcome.
Direct evaluation requires:
-
appropriately controlled behavioral studies;
-
active comparison conditions;
-
objective smartphone-use data;
-
follow-up after the 72-hour period;
-
and, where appropriate, physiological or neuroimaging measurements.
The complete scientific framework explicitly states that the cited research provides a rationale for HAKONE’s components but does not yet prove activation of the prefrontal cortex, suppression of basal-ganglia habit activity, dopamine change, deepened Zen, or a permanent 72-hour effect.
Website Summary
The HAKONE Integrated Mechanism Model
Automatic smartphone use can begin as a learned cue–response sequence before a clear decision has been made.
HAKONE intervenes at the entrance to that sequence.
The user keeps a fingertip still for 60 seconds while listening to flowing-water sound. Attention is directed toward the fingertip and sound. When attention wanders, the user notices and returns.
The pause is then followed by Illustration Reading, emotion identification, verbal reflection, and deliberate selection of the next action.
This complete sequence is repeated across a 72-hour observation and practice window.
HAKONE does not attempt to destroy the brain’s autopilot. It creates a structured detour before the learned sequence is completed.
The scientific rationale comes from converging evidence on habit learning, response inhibition, Zen and focused attention, tactile-assisted meditation, natural sound, competing actions, drawing, affect labeling, craving regulation, and short-term smartphone change.
The individual mechanisms are supported by related research.
The complete integrated HAKONE system remains a testable model requiring direct controlled evaluation.
Reference Numbering
The citation numbers in this third layer follow the same [1]–[49] master bibliography used in Scientific Basis 1–6.
The complete reference list will therefore appear once in the fourth layer, allowing every claim in Layers 1–3 to be traced to the same unified academic record.
Research Foundations and Evidence Map
The Academic Literature Underlying the Design of HAKONE
HAKONE was not designed around one paper, one neurological theory, or one claim about a single brain region.
Its scientific framework draws on 49 academic publications across multiple fields:
-
habit formation;
-
basal-ganglia function;
-
goal-directed and habitual action;
-
response inhibition;
-
frontal–basal-ganglia pathways;
-
Zen and mindfulness;
-
attention monitoring;
-
tactile-assisted meditation;
-
natural and flowing-water sounds;
-
competing responses;
-
drawing and visuomotor processing;
-
affect labeling;
-
cognitive regulation of craving;
-
urge surfing;
-
goal-directed smartphone use;
-
conversational behavior support;
-
smartphone cue reactivity;
-
72-hour smartphone restriction; and
-
short-term dopamine-system plasticity.
The strength of the HAKONE framework does not come from claiming that all 49 studies tested HAKONE.
They did not.
Its strength comes from showing that the individual operations used by HAKONE are connected to identifiable bodies of scientific research.
Each component has a traceable academic foundation. The complete HAKONE sequence remains an integrated model requiring direct evaluation.
How to Read the Evidence Map
The evidence base contains several different types of research.
Evidence Synthesis
Systematic reviews and meta-analyses combine findings from multiple studies.
They are particularly useful for determining whether a result appears across different laboratories, populations, and methods.
Examples within the HAKONE evidence base include reviews of:
-
habit psychology;
-
basal-ganglia function;
-
meditation neuroimaging;
-
executive functioning;
-
and natural-sound exposure [1–3][5][8][10][12][16–18][24][25][29–31].
Controlled Behavioral Interventions
Randomized or controlled studies test whether an intervention produces different outcomes from another condition.
The HAKONE reference base includes controlled research involving:
-
habit-reversal methods;
-
mindfulness-based interventions;
-
smartphone-use interventions;
-
water-sound exposure;
-
chatbot-supported behavior change;
-
and three-day smartphone restriction [14][15][24][35][41–43].
Mechanistic Neuroscience Studies
fMRI, PET, EEG, ERP, fNIRS, lesion, and brain-stimulation studies examine the neural or physiological processes involved in a task.
These studies provide mechanistic plausibility for:
-
habit learning;
-
response inhibition;
-
meditation;
-
fingertip attention;
-
drawing;
-
affect labeling;
-
craving regulation;
-
and smartphone cue reactivity [4][6][7][9][11][13][19–23][26–28][33][36–40][44–49].
Emerging Direct Smartphone Evidence
A smaller group of studies directly examines smartphone-related cues, problematic use, cognitive control, restriction, or withdrawal-related responses [41][43–48].
These studies are especially relevant to HAKONE.
However, even these studies did not examine the complete YUBIZEN and post-pause sequence.
Evidence Map at a Glance
Research domainReferencesWhat the literature supportsRelationship to HAKONE
Habit formation and basal ganglia[1–5]Repeated actions can become cue-driven and involve corticostriatal systems, including the posterior putamenSupports the concept of smartphone “autopilot” as learned behavior
Response inhibition[6–13]Initiated actions can be interrupted through distributed frontal–basal-ganglia networksSupports inserting a deliberate pause before scrolling continues
Competing responses[14–15]An alternative action can be positioned when an unwanted or repetitive action is emergingSupports moving the hand from scrolling to Illustration Reading
Meditation and attention[16–25][27–28]Meditation trains noticing, monitoring, shifting, and returning attentionSupports the stop–notice–return structure of YUBIZEN
Fingertip-based attention[26]Fingertip pressure combined with breathing may support attention in beginnersProvides a close analogue for fingertip sensation as an attention anchor
Natural and water sound[29–35]Nature sounds may affect stress, cardiovascular, respiratory, autonomic, and emotional outcomesSupports using flowing-water sound as an auditory environment for stillness
Drawing and motor cognition[36]Purposeful drawing engages distributed visuospatial and motor-planning networksSupports drawing as a different motor–cognitive task from scrolling
Affect labeling[37–38]Naming emotions can alter prefrontal–limbic processing and subjective distressSupports identifying the emotional state before choosing the next action
Craving and urge regulation[39–40]Reappraisal and urge surfing can change behavior and craving-related processingSupports putting an urge into words without requiring it to disappear
Goal-directed digital behavior and dialogue[41–42]Planning, self-efficacy, and structured conversational support can contribute to behavior changeSupports goal clarification and AI-guided reflection
Smartphone cue reactivity and control[43–46]Smartphone-related cues are associated with emotional, attentional, reward, and inhibitory processesConnects the broader mechanism directly to smartphone behavior
Seventy-two-hour change[43][47–49]Neural, emotional, and dopamine-related measures can respond within a 72-hour period under specific conditionsSupports 72 hours as an initial observation window—not a cure or reset
The evidence-strength table in the attached scientific master similarly classifies the six foundations separately, ranging from strong mechanistic support for action interruption to emerging direct smartphone evidence for the 72-hour framework.
Foundation A
Habit Formation and the Basal Ganglia
References [1–5]
Habit research provides the starting point for the entire HAKONE model.
Graybiel described habits as learned behavioral patterns that can become organized into efficient action sequences [1].
Wood and Rünger reviewed the psychology of habit, emphasizing that repeated actions can become linked to recurring contexts and initiated with decreasing conscious deliberation [2].
Balleine and O’Doherty described the distinction between:
-
goal-directed action, which remains sensitive to current outcomes; and
-
habitual action, which becomes increasingly controlled by learned stimulus–response relationships [3].
Tricomi and colleagues provided human fMRI evidence that repeated instrumental training across several days can make behavior less sensitive to the current value of its outcome while increasing activity in the posterior putamen and globus pallidus [4].
Smith and Graybiel reviewed the role of the striatum in the meeting point between learned skills and habits [5].
Relevance to HAKONE
This literature supports the first philosophical principle of HAKONE:
Automatic smartphone use can be understood, in part, as a learned and efficiently reproduced action sequence—not necessarily as proof of a broken brain.
It also supports intervening at the cue–response boundary before the complete sequence unfolds.
What It Does Not Establish
This literature does not prove that:
-
every smartphone action is a habit;
-
the basal ganglia are the sole cause of problematic smartphone use;
-
or HAKONE has already altered habit-related striatal activity.
Foundation B
Response Inhibition and Frontal–Basal-Ganglia Control
References [6–13]
Aron and colleagues found that damage to the right inferior frontal gyrus impaired stop-signal inhibition [6].
Aron and Poldrack linked successful stopping with the right inferior frontal cortex and subthalamic nucleus [7].
A broader synthesis by Aron and colleagues described converging evidence for a fronto-basal-ganglia network involved in inhibitory control [8].
Jahfari and colleagues reported that both the hyperdirect and indirect fronto-basal-ganglia pathways contribute to response inhibition [9].
Nambu and colleagues described the cortico-subthalamo-pallidal hyperdirect pathway as a relatively rapid mechanism for broadly suppressing motor programs [10].
Rae and colleagues proposed that prefrontal control can influence subcortical motor pathways through connectivity involving the pre-supplementary motor area and subthalamic nucleus [11].
Wessel and Aron reviewed evidence that unexpected events can produce broad motor suppression affecting behavior and cognition [12].
Chambers and colleagues showed that temporary deactivation of frontal regions can impair the ability to stop an initiated response [13].
Relevance to HAKONE
This literature supports the biological plausibility of inserting an interruption after an action has begun to form but before it is completed.
It provides the scientific background for HAKONE’s 60-second period of fingertip stillness.
What It Does Not Establish
A stop-signal task is not identical to:
-
resisting smartphone scrolling;
-
holding one finger still;
-
or listening to flowing-water sound.
No study has yet demonstrated that YUBIZEN recruits precisely the same pathways.
Foundation C
Competing Responses and Habit-Reversal Principles
References [14–15]
Twohig and Woods compared competing responses lasting five seconds, one minute, and three minutes in people who engaged in nail biting [14].
The one-minute and three-minute responses produced more durable improvement than the five-second response.
Piacentini and colleagues conducted a randomized controlled trial of behavioral therapy for children with Tourette disorder [15].
The intervention included awareness training and competing-response elements and produced improvement in tic severity.
Relevance to HAKONE
These studies support the general behavioral principle that:
When an unwanted or repetitive action is beginning, another action can be introduced that is difficult or impossible to perform at the same time.
HAKONE applies this principle by moving the hand from smartphone scrolling to drawing on paper.
What It Does Not Establish
Smartphone habits are not equivalent to nail biting or tic disorders.
These studies do not prove that Illustration Reading will produce the same clinical or behavioral outcomes.
Foundation D
Zen, Mindfulness, and Attention Regulation
References [16–25][27–28]
Tang, Hölzel, and Posner reviewed the neuroscience of mindfulness meditation, including attention, emotional regulation, and self-awareness [16].
Fox and colleagues conducted a meta-analysis of 78 functional neuroimaging studies and found that meditation involves multiple distributed systems rather than one universal meditation center [17].
Ganesan and colleagues reviewed focused-attention meditation and identified recurring involvement of executive-control, salience, and default-mode networks [18].
Kozasa and colleagues studied experienced and inexperienced participants during a seven-day Zen retreat and reported differences in activity involving the anterior cingulate cortex, prefrontal regions, caudate, putamen, pallidum, insula, and posterior cingulate cortex [19].
Yu and colleagues examined beginners during Zen meditation and reported changes involving anterior prefrontal activity, EEG, mood, and serotonergic measures [20].
Pagnoni and Cekic reported associations involving Zen experience, attentional performance, and age-related gray-matter differences [21].
Grant and colleagues reported differences in cortical thickness and pain sensitivity among Zen practitioners [22].
Kjaer and colleagues used PET during Yoga Nidra and reported altered dopamine-related binding in the ventral striatum [23].
Zainal and Newman combined 111 randomized controlled trials and found small-to-moderate effects of mindfulness interventions on several cognitive outcomes, including some measures of attention and inhibition [24].
Millett and colleagues reported smaller and less consistent executive-function effects and emphasized limitations in robustness [25].
Hasenkamp and colleagues identified distinguishable phases of mind-wandering, awareness, attentional shifting, and sustained attention during focused meditation [27].
Farb and colleagues reported distinct neural modes of self-reference associated with present-moment attention [28].
Relevance to HAKONE
This literature supports the structure:
Notice distraction. Disengage. Return attention.
YUBIZEN translates this operation into a 60-second practice performed at the entrance to a smartphone action.
What It Does Not Establish
This literature does not prove that:
-
YUBIZEN is equivalent to traditional Zazen;
-
one minute produces the same outcomes as sustained meditation training;
-
every use activates the prefrontal cortex;
-
or YUBIZEN changes dopamine.
Foundation E
Fingertip Sensation as an Attention Anchor
Reference [26]
Zheng and colleagues studied a haptics-assisted meditation procedure in which beginners synchronized fingertip pressure with respiration [26].
Participants reported less mind-wandering than during breath counting.
Following several days of practice, changes were reported in attention measures and fNIRS indicators involving prefrontal and sensorimotor activation and connectivity.
Relevance to HAKONE
This study is one of the closest published analogues to YUBIZEN.
It supports the possibility that fingertip sensation can serve as a concrete bodily focus for beginners.
What It Does Not Establish
The intervention differed from HAKONE because it involved:
-
both hands;
-
active pressure adjustment;
-
synchronized breathing;
-
longer practice;
-
and no smartphone cue.
A single stationary fingertip on a smartphone for 60 seconds remains untested.
Foundation F
Natural and Flowing-Water Sound
References [29–35]
Fan and Baharum conducted a systematic review and meta-analysis of natural-sound exposure and stress-related outcomes [29].
Zhu and colleagues reviewed the effects of natural sounds on health recovery, including anxiety, cardiovascular, and respiratory outcomes [30].
Buxton and colleagues synthesized evidence linking natural sounds with lower stress and annoyance and with positive health-related outcomes [31].
Alvarsson and colleagues compared stress recovery during exposure to nature sound and environmental noise [32].
Jo and colleagues compared forest and urban sounds in a 60-second experiment and reported differences involving heart rate, sympathetic indicators, prefrontal oxygenation, comfort, and relaxation [33].
Annerstedt and colleagues examined nature sound in a virtual forest after stress exposure [34].
Thoma and colleagues reported that the stress-related response to water sounds varied according to individual somatic complaints [35].
Relevance to HAKONE
This literature supports using a continuous nature sound as:
-
a stable auditory object;
-
a marker of the pause;
-
and a potentially less demanding alternative to notification-driven smartphone audio.
What It Does Not Establish
The evidence does not show that flowing-water sound:
-
creates Zen;
-
improves response inhibition;
-
strengthens the prefrontal cortex;
-
or guarantees completion of the pause.
Foundation G
Drawing and Visuomotor Processing
Reference [36]
Ino and colleagues used fMRI during a clock-drawing task [36].
They reported activity involving:
-
posterior parietal regions;
-
premotor regions;
-
the pre-supplementary motor area;
-
ventral prefrontal regions;
-
motor cortex;
-
and the cerebellum.
Relevance to HAKONE
The study supports describing drawing as a task combining:
-
vision;
-
spatial organization;
-
motor planning;
-
attention;
-
and hand movement.
Illustration Reading therefore gives the hand a motor–cognitive task that differs substantially from scrolling.
What It Does Not Establish
The study examined structured clock drawing—not free drawing.
It does not show that Illustration Reading erases or rewrites a smartphone circuit.
Foundation H
Affect Labeling and Emotional Observation
References [37–38]
Lieberman and colleagues found that labeling negative emotional stimuli was associated with increased right ventrolateral prefrontal activity and reduced amygdala and limbic responses [37].
Burklund and colleagues compared affect labeling and cognitive reappraisal and reported involvement of regulatory prefrontal regions, lower amygdala activity, and reduced subjective distress [38].
Relevance to HAKONE
This literature supports asking the user to identify the emotional state before deciding what to do next.
The screen-related action is no longer examined only as a motor event.
It is connected to the emotional context in which it begins.
What It Does Not Establish
The evidence does not demonstrate that:
-
one selected label immediately removes an urge;
-
16 categories are neurologically optimal;
-
or every user experiences reduced emotional reactivity.
Foundation I
Craving, Urge Surfing, and Cognitive Reappraisal
References [39–40]
Kober and colleagues found that cognitive regulation of craving increased prefrontal activity and reduced activity in the ventral striatum, amygdala, and ventral tegmental area, together with lower reported craving [39].
Bowen and Marlatt studied a brief urge-surfing instruction among smokers [40].
The immediate urge did not significantly decline, but subsequent smoking behavior was reduced.
Relevance to HAKONE
These studies support two central HAKONE principles:
An urge can be turned into an object of reflection.
and:
The urge does not have to disappear before behavior changes.
What It Does Not Establish
Smoking-related craving is not identical to smartphone use.
AI-guided reflection has not been shown to reproduce the neural effects of laboratory cognitive reappraisal.
Foundation J
Goal-Directed Smartphone Use and Conversational Support
References [41–42]
Keller and colleagues tested a mobile intervention designed to support goal-directed and self-efficacious smartphone use [41].
Reductions were observed in problematic smartphone use and total use time across intervention conditions, while the theory-based intervention did not clearly outperform the active comparison.
Bricker and colleagues reported the development and randomized evaluation of a conversational chatbot for smoking cessation [42].
The study supports the emerging use of structured dialogue to deliver behavior-change and coping content.
Relevance to HAKONE
These studies support:
-
planning;
-
self-efficacy;
-
clarification of purpose;
-
and structured reflective dialogue.
HAKONE uses AI to ask questions, not to make medical decisions.
What It Does Not Establish
These studies do not prove that:
-
HAKONE’s AI component is effective;
-
GPT activates a particular brain region;
-
or chatbot findings in smoking cessation transfer directly to smartphone behavior.
Foundation K
Smartphone Cue Reactivity and Inhibitory Control
References [43–46]
Aarestad and colleagues conducted a three-day smartphone restriction experiment and found that participants with higher problematic-use scores reported stronger withdrawal-related effects and negative affect under restriction [43].
Schmitgen and colleagues reported neural differences in response to smartphone-related cues involving regions associated with reward, salience, attention, and motor preparation [44].
Gao and colleagues used a Go/No-Go task with smartphone-related backgrounds and found differences in inhibitory errors and electrophysiological markers among problematic mobile-phone users [45].
A later Schmitgen study reported altered frontoparietal network strength across cue-reactivity, response-inhibition, and working-memory tasks in excessive smartphone users [46].
Relevance to HAKONE
These studies directly connect smartphone-related cues with:
-
emotional response;
-
attention;
-
reward;
-
motor preparation;
-
and inhibitory control.
They help bridge general habit and inhibition science with smartphone behavior.
What They Do Not Establish
They do not test:
-
YUBIZEN;
-
Illustration Reading;
-
emotion sliders;
-
AI-guided reflection;
-
or the complete HAKONE sequence.
Foundation L
Seventy-Two-Hour Neural and Behavioral Change
References [43][47–49]
Schmitgen and colleagues reported changes in neural responses to smartphone-related cues following 72 hours of smartphone restriction [47].
The implicated regions included the nucleus accumbens and anterior cingulate cortex.
Haage and colleagues reported resting-state neural changes after 72 hours of restriction, with different patterns among problematic and non-problematic smartphone users [48].
Aarestad and colleagues showed that emotional and withdrawal-related responses during three-day restriction vary according to problematic-use tendencies [43].
Lim and colleagues reported changes in striatal dopamine-receptor binding following 72 hours of sleep deprivation in mice [49].
Relevance to HAKONE
Together, these studies support the limited proposition that:
Neural, emotional, and neurochemical measures can respond within a 72-hour period under particular experimental conditions.
This supports using 72 hours as an initial period of observation and repeated practice.
What They Do Not Establish
These studies do not prove that:
-
HAKONE forms a new habit in 72 hours;
-
the brain is reset;
-
dopamine is normalized;
-
problematic smartphone use is cured;
-
or the effect is permanent.
Why the Academic Journals Matter
The HAKONE evidence base includes publications from internationally recognized journals such as:
-
Nature Reviews Neuroscience;
-
Nature Neuroscience;
-
Neuron;
-
JAMA;
-
Proceedings of the National Academy of Sciences of the United States of America;
-
Journal of Neuroscience;
-
Annual Review of Neuroscience;
-
Annual Review of Psychology;
-
Neuropsychopharmacology;
-
NeuroImage;
-
Computers in Human Behavior;
-
Addictive Behaviors;
-
and Health Psychology Review.
These journals publish different forms of evidence:
-
major reviews;
-
meta-analyses;
-
randomized trials;
-
mechanistic experiments;
-
neuroimaging studies;
-
and behavioral research.
Their inclusion matters because the HAKONE framework is not relying solely on general commentary or commercial wellness claims.
However:
The reputation of a journal does not convert a related study into direct proof of HAKONE.
A paper published in a highly respected journal supports the specific claim that the paper examined.
It does not automatically validate a later product that applies the finding.
Scientific credibility comes from accurately preserving that boundary.
Convergence Is More Important Than One Dramatic Study
No single paper establishes the entire HAKONE model.
The academic case is based on convergence.
Different research fields independently support different stages of the sequence:
-
habit science explains how the automatic sequence develops;
-
inhibition science explains how an initiated action can be interrupted;
-
tactile meditation supports a bodily attention anchor;
-
natural-sound research supports the sensory environment;
-
Zen and mindfulness research supports noticing and returning;
-
habit-reversal research supports a competing action;
-
drawing research supports the motor–cognitive shift;
-
affect labeling supports emotional observation;
-
craving research supports verbal reframing;
-
smartphone intervention research supports goal-directed use;
-
and 72-hour research supports short-term responsiveness.
The scientific argument is not that one study proves everything. It is that multiple fields converge on the individual operations used by HAKONE.
Full Master Bibliography
Habit Formation and Basal-Ganglia Function
[1] Graybiel, A. M. (2008). Habits, rituals, and the evaluative brain. Annual Review of Neuroscience, 31, 359–387. https://doi.org/10.1146/annurev.neuro.29.051605.112851
[2] Wood, W., & Rünger, D. (2016). Psychology of habit. Annual Review of Psychology, 67, 289–314. https://doi.org/10.1146/annurev-psych-122414-033417
[3] Balleine, B. W., & O’Doherty, J. P. (2010). Human and rodent homologies in action control: Corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology, 35(1), 48–69. https://doi.org/10.1038/npp.2009.131
[4] Tricomi, E., Balleine, B. W., & O’Doherty, J. P. (2009). A specific role for posterior dorsolateral striatum in human habit learning. European Journal of Neuroscience, 29(11), 2225–2232. https://doi.org/10.1111/j.1460-9568.2009.06796.x
[5] Smith, K. S., & Graybiel, A. M. (2016). The striatum: Where skills and habits meet. Cold Spring Harbor Perspectives in Biology, 8(8), a021691. https://doi.org/10.1101/cshperspect.a021691
Response Inhibition and Action Control
[6] Aron, A. R., Fletcher, P. C., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2003). Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nature Neuroscience, 6(2), 115–116. https://doi.org/10.1038/nn1003
[7] Aron, A. R., & Poldrack, R. A. (2006). Cortical and subcortical contributions to stop-signal response inhibition: Role of the subthalamic nucleus. Journal of Neuroscience, 26(9), 2424–2433. https://doi.org/10.1523/JNEUROSCI.4682-05.2006
[8] Aron, A. R., Durston, S., Eagle, D. M., Logan, G. D., Stinear, C. M., & Stuphorn, V. (2007). Converging evidence for a fronto-basal-ganglia network for inhibitory control of action and cognition. Journal of Neuroscience, 27(44), 11860–11864. https://doi.org/10.1523/JNEUROSCI.3644-07.2007
[9] Jahfari, S., Waldorp, L., van den Wildenberg, W. P. M., Scholte, H. S., Ridderinkhof, K. R., & Forstmann, B. U. (2011). Effective connectivity reveals important roles for both the hyperdirect and indirect fronto-basal-ganglia pathways during response inhibition. Journal of Neuroscience, 31(18), 6891–6899. https://doi.org/10.1523/JNEUROSCI.5253-10.2011
[10] Nambu, A., Tokuno, H., & Takada, M. (2002). Functional significance of the cortico-subthalamo-pallidal hyperdirect pathway. Neuroscience Research, 43(2), 111–117. https://doi.org/10.1016/S0168-0102(02)00027-5
[11] Rae, C. L., Hughes, L. E., Anderson, M. C., & Rowe, J. B. (2015). The prefrontal cortex achieves inhibitory control by facilitating subcortical motor pathway connectivity. Journal of Neuroscience, 35(2), 786–794. https://doi.org/10.1523/JNEUROSCI.3093-13.2015
[12] Wessel, J. R., & Aron, A. R. (2017). On the globality of motor suppression: Unexpected events and their influence on behavior and cognition. Neuron, 93(2), 259–280. https://doi.org/10.1016/j.neuron.2016.12.013
[13] Chambers, C. D., Bellgrove, M. A., Stokes, M. G., et al. (2006). Executive brake failure following deactivation of human frontal lobe. Journal of Cognitive Neuroscience, 18(3), 444–455. https://doi.org/10.1162/089892906775990606
Competing Responses and Behavioral Intervention
[14] Twohig, M. P., & Woods, D. W. (2001). Evaluating the duration of the competing response in habit reversal: A parametric analysis. Journal of Applied Behavior Analysis, 34(4), 517–520. https://doi.org/10.1901/jaba.2001.34-517
[15] Piacentini, J., Woods, D. W., Scahill, L., et al. (2010). Behavior therapy for children with Tourette disorder: A randomized controlled trial. JAMA, 303(19), 1929–1937. https://doi.org/10.1001/jama.2010.607
Zen, Meditation, Attention, and Executive Control
[16] Tang, Y. Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16(4), 213–225. https://doi.org/10.1038/nrn3916
[17] Fox, K. C. R., Dixon, M. L., Nijeboer, S., et al. (2016). Functional neuroanatomy of meditation: A review and meta-analysis of 78 functional neuroimaging investigations. Neuroscience & Biobehavioral Reviews, 65, 208–228. https://doi.org/10.1016/j.neubiorev.2016.03.021
[18] Ganesan, S., Beyer, E., Moffat, B., Van Dam, N. T., Lorenzetti, V., & Zalesky, A. (2022). Focused attention meditation in healthy adults: A systematic review and meta-analysis of cross-sectional functional MRI studies. Neuroscience & Biobehavioral Reviews, 141, 104846. https://doi.org/10.1016/j.neubiorev.2022.104846
[19] Kozasa, E. H., Balardin, J. B., Sato, J. R., et al. (2018). Effects of a 7-day meditation retreat on the brain function of meditators and non-meditators during an attention task. Frontiers in Human Neuroscience, 12, 222. https://doi.org/10.3389/fnhum.2018.00222
[20] Yu, X., Fumoto, M., Nakatani, Y., et al. (2011). Activation of the anterior prefrontal cortex and serotonergic system is associated with improvements in mood and EEG changes induced by Zen meditation practice in novices. International Journal of Psychophysiology, 80(2), 103–111. https://doi.org/10.1016/j.ijpsycho.2011.02.004
[21] Pagnoni, G., & Cekic, M. (2007). Age effects on gray matter volume and attentional performance in Zen meditation. Neurobiology of Aging, 28(10), 1623–1627. https://doi.org/10.1016/j.neurobiolaging.2007.06.008
[22] Grant, J. A., Courtemanche, J., Duerden, E. G., Duncan, G. H., & Rainville, P. (2010). Cortical thickness and pain sensitivity in Zen meditators. Emotion, 10(1), 43–53. https://doi.org/10.1037/a0018334
[23] Kjaer, T. W., Bertelsen, C., Piccini, P., Brooks, D., Alving, J., & Lou, H. C. (2002). Increased dopamine tone during meditation-induced change of consciousness. Cognitive Brain Research, 13(2), 255–259. https://doi.org/10.1016/S0926-6410(01)00106-9
[24] Zainal, N. H., & Newman, M. G. (2024). Mindfulness enhances cognitive functioning: A meta-analysis of 111 randomized controlled trials. Health Psychology Review, 18(2), 369–395. https://doi.org/10.1080/17437199.2023.2248222
[25] Millett, G., D’Amico, D., Amestoy, M. E., Gryspeerdt, C., & Fiocco, A. J. (2021). Do group-based mindfulness meditation programs enhance executive functioning? A systematic review and meta-analysis of the evidence. Consciousness and Cognition, 95, 103195. https://doi.org/10.1016/j.concog.2021.103195
Fingertip-Based Attention and Present-Moment Awareness
[26] Zheng, Y. L., Wang, D. X., Zhang, Y. R., & Tang, Y. Y. (2019). Enhancing attention by synchronizing respiration and fingertip pressure: A pilot study using functional near-infrared spectroscopy. Frontiers in Neuroscience, 13, 1209. https://doi.org/10.3389/fnins.2019.01209
[27] Hasenkamp, W., Wilson-Mendenhall, C. D., Duncan, E., & Barsalou, L. W. (2012). Mind wandering and attention during focused meditation: A fine-grained temporal analysis of fluctuating cognitive states. NeuroImage, 59(1), 750–760. https://doi.org/10.1016/j.neuroimage.2011.07.008
[28] Farb, N. A. S., Segal, Z. V., Mayberg, H., et al. (2007). Attending to the present: Mindfulness meditation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313–322. https://doi.org/10.1093/scan/nsm030
Natural and Flowing-Water Sound
[29] Fan, L., & Baharum, M. R. (2024). The effect of exposure to natural sounds on stress reduction: A systematic review and meta-analysis. Stress, 27(1), 2402519. https://doi.org/10.1080/10253890.2024.2402519
[30] Zhu, R., Yuan, L., Pan, Y., Wang, Y., Xiu, D., & Liu, W. (2024). Effects of natural sound exposure on health recovery: A systematic review and meta-analysis. Science of the Total Environment, 921, 171052. https://doi.org/10.1016/j.scitotenv.2024.171052
[31] Buxton, R. T., Pearson, A. L., Allou, C., Fristrup, K., & Wittemyer, G. (2021). A synthesis of health benefits of natural sounds and their distribution in national parks. Proceedings of the National Academy of Sciences of the United States of America, 118(14), e2013097118. https://doi.org/10.1073/pnas.2013097118
[32] Alvarsson, J. J., Wiens, S., & Nilsson, M. E. (2010). Stress recovery during exposure to nature sound and environmental noise. International Journal of Environmental Research and Public Health, 7(3), 1036–1046. https://doi.org/10.3390/ijerph7031036
[33] Jo, H., Song, C., Ikei, H., et al. (2019). Physiological and psychological effects of forest and urban sounds using high-resolution sound sources. International Journal of Environmental Research and Public Health, 16(15), 2649. https://doi.org/10.3390/ijerph16152649
[34] Annerstedt, M., Jönsson, P., Wallergård, M., et al. (2013). Inducing physiological stress recovery with sounds of nature in a virtual reality forest—results from a pilot study. Physiology & Behavior, 118, 240–250. https://doi.org/10.1016/j.physbeh.2013.05.023
[35] Thoma, M. V., Mewes, R., & Nater, U. M. (2018). Preliminary evidence: The stress-reducing effect of listening to water sounds depends on somatic complaints: A randomized trial. Medicine, 97(8), e9851. https://doi.org/10.1097/MD.0000000000009851
Drawing, Emotion, Craving, and Reflective Dialogue
[36] Ino, T., Asada, T., Ito, J., Kimura, T., & Fukuyama, H. (2003). Parieto-frontal networks for clock drawing revealed with fMRI. Neuroscience Research, 45(1), 71–77. https://doi.org/10.1016/S0168-0102(02)00194-3
[37] Lieberman, M. D., Eisenberger, N. I., Crockett, M. J., et al. (2007). Putting feelings into words: Affect labeling disrupts amygdala activity in response to affective stimuli. Psychological Science, 18(5), 421–428. https://doi.org/10.1111/j.1467-9280.2007.01916.x
[38] Burklund, L. J., Creswell, J. D., Irwin, M. R., & Lieberman, M. D. (2014). The common and distinct neural bases of affect labeling and reappraisal in healthy adults. Frontiers in Psychology, 5, 221. https://doi.org/10.3389/fpsyg.2014.00221
[39] Kober, H., Mende-Siedlecki, P., Kross, E. F., et al. (2010). Prefrontal-striatal pathway underlies cognitive regulation of craving. Proceedings of the National Academy of Sciences of the United States of America, 107(33), 14811–14816. https://doi.org/10.1073/pnas.1007779107
[40] Bowen, S., & Marlatt, A. (2009). Surfing the urge: Brief mindfulness-based intervention for college student smokers. Psychology of Addictive Behaviors, 23(4), 666–671. https://doi.org/10.1037/a0017127
[41] Keller, J., Roitzheim, C., Radtke, T., Schenkel, K., & Schwarzer, R. (2021). A mobile intervention for self-efficacious and goal-directed smartphone use in the general population: Randomized controlled trial. JMIR mHealth and uHealth, 9(11), e26397. https://doi.org/10.2196/26397
[42] Bricker, J. B., Sullivan, B., Mull, K., Santiago-Torres, M., & Lavista Ferres, J. M. (2024). Conversational chatbot for cigarette smoking cessation: Results from the 11-step user-centered design development process and randomized controlled trial. JMIR mHealth and uHealth, 12, e57318. https://doi.org/10.2196/57318
Smartphone Research and the 72-Hour Window
[43] Aarestad, S. H., Flaa, T. A., Griffiths, M. D., & Pallesen, S. (2023). Smartphone addiction and subjective withdrawal effects: A three-day experimental study. SAGE Open, 13(4), 21582440231219538. https://doi.org/10.1177/21582440231219538
[44] Schmitgen, M. M., Horvath, J., Mundinger, C., et al. (2020). Neural correlates of cue reactivity in individuals with smartphone addiction. Addictive Behaviors, 108, 106422. https://doi.org/10.1016/j.addbeh.2020.106422
[45] Gao, L., Zhang, J., Xie, H., Nie, Y., Zhao, Q., & Zhou, Z. (2020). Effect of the mobile phone-related background on inhibitory control of problematic mobile phone use: An event-related potentials study. Addictive Behaviors, 108, 106363. https://doi.org/10.1016/j.addbeh.2020.106363
[46] Schmitgen, M. M., et al. (2023). Cognitive domain-independent aberrant frontoparietal network strength in individuals with excessive smartphone use. Psychiatry Research: Neuroimaging, 329, 111593. https://doi.org/10.1016/j.pscychresns.2023.111593
[47] Schmitgen, M. M., Henemann, G. M., Koenig, J., et al. (2025). Effects of smartphone restriction on cue-related neural activity. Computers in Human Behavior, 167, 108610. https://doi.org/10.1016/j.chb.2025.108610
[48] Haage, S. H., Schmitgen, M. M., Henemann, G. M., et al. (2026). Smartphone restriction modulates intrinsic neural activity in problematic smartphone users: Evidence from resting-state fMRI. Addictive Behaviors, 174, 108575. https://doi.org/10.1016/j.addbeh.2025.108575
[49] Lim, M. M., Xu, J., Holtzman, D. M., & Mach, R. H. (2011). Sleep deprivation differentially affects dopamine receptor subtypes in mouse striatum. NeuroReport, 22(10), 489–493. https://doi.org/10.1097/WNR.0b013e32834846a0
Closing Statement for the Evidence Layer
HAKONE is not presented as proven because related papers appeared in prestigious journals. Its scientific strength lies in the transparent relationship between each design component and the research field from which it was derived. Habit learning, response inhibition, attention, tactile anchoring, natural sound, competing action, emotional labeling, verbal reappraisal, and short-term smartphone change are separately supported by published research. Their integration into one HAKONE sequence is a testable application—not a conclusion that should be accepted without direct evidence.
Scientific Notice and Scope of Evidence
How the Scientific Claims on This Page Should Be Interpreted
This page presents the scientific rationale underlying the design of HAKONE and YUBIZEN.
The cited literature examines individual mechanisms related to:
-
habit formation;
-
basal-ganglia function;
-
response inhibition;
-
Zen and focused-attention meditation;
-
tactile attention;
-
natural sound;
-
competing behavioral responses;
-
drawing;
-
affect labeling;
-
cognitive reappraisal;
-
craving regulation;
-
goal-directed smartphone use;
-
conversational behavior support;
-
smartphone-cue reactivity; and
-
short-term neural and emotional change.
Together, these studies provide a literature-grounded rationale for the individual components of HAKONE.
They do not constitute direct proof of the effectiveness or neural mechanism of the complete HAKONE intervention.
The scientific evidence supports the components and the design logic. The integrated HAKONE system remains a testable application that requires direct evaluation.
Three Levels of Scientific Evidence
The scientific material on this page should be read at three distinct levels.
1. Established Evidence
These are findings reported in published studies.
Examples include:
-
repeated actions can become increasingly cue-driven;
-
habit learning involves corticostriatal systems;
-
initiated actions can be interrupted through frontal–basal-ganglia networks;
-
focused-attention practice involves noticing distraction and returning attention;
-
fingertip sensation can be incorporated into an attention exercise;
-
natural sounds may influence some physiological and emotional outcomes;
-
drawing engages distributed visuomotor networks;
-
affect labeling can alter emotional processing;
-
cognitive reappraisal can influence craving-related responses; and
-
smartphone-related neural and emotional measures can differ after short-term restriction.
These findings belong to the original studies and should not be expanded beyond what those studies measured.
2. HAKONE Application
HAKONE translates findings from several fields into one ordered behavioral sequence:
Smartphone cue
↓
60-second fingertip stillness
↓
Flowing-water sound
↓
Tactile and auditory attention
↓
Illustration Reading
↓
Emotion identification
↓
Verbal or AI-guided reflection
↓
Deliberate choice
This is a product-design application of existing science.
The use of published evidence to support an application does not mean that the application itself has already been proven.
3. HAKONE-Specific Claims Requiring Direct Testing
The complete HAKONE sequence has not yet been directly evaluated in a peer-reviewed controlled study using the full intervention exactly as presented on this website.
HAKONE-specific questions include whether the system:
-
reduces unplanned smartphone opening;
-
increases canceled opening attempts;
-
shortens continuous-use sessions;
-
changes the relationship between urges and immediate action;
-
improves behavioral response inhibition;
-
changes physiological arousal;
-
changes neural responses to smartphone cues;
-
produces effects that remain after 72 hours;
-
or performs better than an appropriate active comparison.
These questions remain open to direct investigation.
What This Evidence Supports
The literature cited on this page supports the scientific plausibility of the following statements.
Automatic Behavior Can Be Learned
Repeated smartphone actions may become associated with recurring cues and may begin with less conscious deliberation over time [1–5].
An Initiated Action Can Be Interrupted
Stopping an action involves coordinated neural systems that include frontal regions, the basal ganglia, the subthalamic nucleus, and motor areas [6–13].
Attention Can Be Redirected
Focused-attention practice repeatedly trains the process of noticing distraction and returning to a selected sensory object [16–28].
A Tactile Sensation Can Serve as an Attention Object
Preliminary research suggests that fingertip sensation can be incorporated into an attention or meditation exercise for beginners [26].
Natural Sound Can Affect Some Physiological and Emotional Measures
Natural-sound studies report possible changes in stress recovery, cardiovascular measures, respiratory measures, comfort, anxiety, and affect, although findings are not uniform [29–35].
An Alternative Action Can Be Inserted
Competing-response and habit-reversal research supports the broader behavioral principle of introducing an action that is incompatible with the unwanted response [14][15].
Emotion Can Be Observed Through Language
Affect-labeling research indicates that naming an emotional state can alter prefrontal–limbic processing and subjective emotional experience [37][38].
An Urge Does Not Need to Disappear Before Behavior Changes
Craving-regulation and urge-surfing research suggests that the relationship between an urge and subsequent action can change even when the immediate urge remains present [39][40].
Short-Term Change Is Possible
Emerging studies indicate that smartphone-related neural and emotional responses can differ after a 72-hour period of changed use [43][47][48].
These findings support the rationale for HAKONE.
They do not prove the complete intervention.
What This Evidence Does Not Prove
The cited literature does not establish that HAKONE:
-
cures smartphone addiction;
-
treats a mental-health condition;
-
permanently rewires the brain;
-
resets the reward system;
-
normalizes dopamine;
-
activates the prefrontal cortex in every user;
-
suppresses the basal ganglia;
-
strengthens the hyperdirect pathway;
-
eliminates an urge within 60 seconds;
-
creates a new habit within 72 hours;
-
reproduces traditional Zen meditation;
-
deepens Zen through water sound;
-
or produces the same result in every person.
The following statements should therefore not be used:
“HAKONE has been scientifically proven to activate the prefrontal cortex.”
“YUBIZEN shuts down the basal ganglia.”
“The smartphone habit circuit is erased in 60 seconds.”
“The reward system is reset in 72 hours.”
“Flowing-water sound produces a Zen brain state.”
“Drawing rewrites the scrolling circuit.”
“AI dialogue directly controls dopamine.”
These statements go beyond the available evidence.
Accurate Neuroscience Language
Neuroscience findings are often simplified when communicated to the public.
This page uses accessible language, but several distinctions must be preserved.
Brain Activity Is Not the Same as Brain Structure
An fMRI study may detect a change in blood-oxygen-level-dependent activity.
That does not necessarily mean that:
-
brain tissue has been physically rebuilt;
-
a neural circuit has permanently changed;
-
or the observed effect will remain over time.
Association Is Not the Same as Causation
If problematic smartphone use is associated with activity in a particular region, that does not prove that the region caused the behavior.
The behavior may influence the brain measure, the brain measure may influence behavior, or both may be affected by other variables.
Activation Is Not Always Improvement
Higher activity in a region is not automatically better.
Lower activity is not automatically worse.
A reduction in activity may reflect:
-
reduced task demand;
-
increased efficiency;
-
relaxation;
-
disengagement;
-
or another process.
Interpretation depends on the task and comparison condition.
One Region Does Not Control the Whole Behavior
The prefrontal cortex is not a single master switch.
The basal ganglia are not a single autopilot button.
Stopping, attention, emotional regulation, reward processing, and action selection emerge from distributed networks.
Dopamine Is Not Simply a Pleasure Chemical
Dopamine contributes to:
-
learning;
-
motivation;
-
salience;
-
prediction;
-
movement;
-
and action preparation.
A change in a dopamine-related measure should not automatically be described as improvement, recovery, or normalization.
The 60-Second Boundary
HAKONE uses a 60-second fingertip pause.
This duration is a product-design choice informed by several adjacent findings, including:
-
response-inhibition research;
-
competing-response research;
-
brief natural-sound studies;
-
and the practical need for a defined interruption.
The scientific claim is not that an urge has a universal 60-second lifespan.
Some urges may weaken rapidly.
Others may remain strong for several minutes or longer.
The purpose of the 60-second period is to create:
-
a visible beginning and end;
-
temporary non-completion of the scrolling movement;
-
an opportunity for attention to return;
-
and preparation for an alternative action.
The 60 seconds should be described as a structured behavioral interval—not as a proven neurological expiration time for craving or impulse.
The 72-Hour Boundary
HAKONE uses a 72-hour practice and observation period.
Emerging smartphone studies have reported measurable neural and emotional differences after 72 hours of restriction [43][47][48].
Short-term habit-learning research also indicates that cue–response control can begin changing over several days [4].
However, these findings do not establish that:
-
a new HAKONE response is fully learned within 72 hours;
-
the original behavior is permanently extinguished;
-
or the effect will persist after the observation period.
HAKONE therefore defines 72 hours as:
an initial period for repeated observation, interruption, alternative action, and behavioral measurement.
It is not presented as:
-
a cure;
-
a detoxification endpoint;
-
a brain reset;
-
or a universal habit-formation deadline.
YUBIZEN and Traditional Zen
YUBIZEN is inspired by the attentional structure found in Zen and focused-attention practices:
stop;
notice;
return.
Traditional Zen may also involve:
-
posture;
-
breathing;
-
sustained sitting;
-
ethical and philosophical teaching;
-
teacher–student relationships;
-
religious or cultural context;
-
and long-term practice.
YUBIZEN does not reproduce the whole of traditional Zen.
It is a short digital self-regulation practice performed at the point when a smartphone action is beginning.
The scientifically appropriate wording is:
YUBIZEN translates the attentional structure of stopping, noticing, and returning into a 60-second fingertip practice. It is not presented as medically or spiritually equivalent to traditional Zazen.
The term “Zen” in YUBIZEN describes the design inspiration and attentional structure.
It should not be interpreted as a claim that the intervention produces a particular religious, spiritual, or neurological state.
Flowing-Water Sound
HAKONE uses flowing-water sound as an auditory background during fingertip stillness.
Research supports the possibility that natural sounds can influence some physiological and psychological outcomes [29–35].
However, the effect of natural sound depends on:
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individual preference;
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sound quality;
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sound level;
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context;
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duration;
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previous experience;
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and the outcome being measured.
Some users may find flowing-water sound calming.
Others may experience no meaningful effect or may prefer another sensory environment.
The sound should therefore be described as:
a supportive auditory environment for stillness and attention.
It should not be described as:
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a treatment;
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a sedative;
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proof of autonomic regulation;
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or a guaranteed means of deepening meditation.
Illustration Reading
Illustration Reading asks the user to move the hand from the smartphone to a drawing tool and paper.
The procedure is supported at the component level by research on:
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competing responses;
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visuomotor processing;
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motor planning;
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and drawing-related neural networks [14][15][36].
The method has not been shown to:
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erase a smartphone habit;
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rewrite a specific neural circuit;
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or provide art therapy.
Illustration Reading is not presented as professional art therapy unless it is delivered by an appropriately qualified practitioner within a properly defined service.
The scientifically appropriate description is:
a physically competing and cognitively different action that redirects hand movement and attention away from immediate scrolling.
The phrase that paper “absorbs what cannot yet be expressed in words” is an experiential metaphor.
It is not a literal biological or physical claim.
Emotion Identification
HAKONE includes 16 emotion categories.
Research supports the broader process of affect labeling [37][38].
It does not establish that exactly 16 categories are optimal.
The number and arrangement of categories are HAKONE interface decisions intended to support:
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usability;
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repeated recording;
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self-observation;
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and differentiation of emotional states.
Selecting an emotional label may help the user observe an internal state.
It does not guarantee that:
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the emotion will disappear;
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distress will immediately decline;
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or smartphone use will stop.
AI-Guided Reflection
HAKONE may use AI-guided prompts to help the user:
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identify the current state;
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clarify the purpose of opening the smartphone;
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consider what may happen if they wait;
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observe the urge;
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and choose the next action.
The AI does not:
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diagnose addiction;
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diagnose a mental-health condition;
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provide psychotherapy;
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prescribe treatment;
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determine whether a person is medically safe;
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or replace professional judgment.
Conversational behavior-support research provides an emerging rationale for structured dialogue [42].
It does not prove that HAKONE’s AI dialogue:
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reproduces laboratory cognitive reappraisal;
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activates a specific brain region;
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or produces clinical improvement.
The AI component should be understood as a reflective interface—not as a medical or psychological authority.
Individual Variation
Human responses to behavioral interventions vary.
Possible differences may arise from:
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age;
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previous meditation experience;
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severity of problematic smartphone use;
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neurodevelopmental characteristics;
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mental-health status;
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medication;
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sleep;
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stress;
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sensory preference;
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motivation;
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and environmental context.
Some users may experience:
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greater calm;
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improved awareness;
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a clearer sense of choice;
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or reduced immediate continuation.
Others may experience:
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frustration;
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impatience;
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increased awareness of craving;
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discomfort with stillness;
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no noticeable effect;
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or difficulty completing the sequence.
A lack of benefit in one person does not prove personal failure.
It may indicate that the intervention, duration, sound, sequence, or context is not appropriate for that person.
Medical and Psychological Boundary
HAKONE is presented as a digital self-regulation and behavioral-choice system.
It is not presented on this scientific page as:
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a medical diagnosis;
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a treatment for addiction;
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psychotherapy;
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a substitute for medical care;
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or a guaranteed prevention program.
Automatically reaching for a smartphone is not, by itself, a diagnosis.
However, professional support may be appropriate where smartphone use is associated with serious or persistent impairment involving:
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sleep;
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work;
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education;
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relationships;
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safety;
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emotional functioning;
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or daily responsibilities.
Users should not delay seeking qualified medical or psychological support because of information presented on this page.
Scientific Transparency
Scientific credibility requires more than citing respected journals.
It requires accurate description of:
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what was studied;
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who was studied;
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how long the intervention lasted;
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what was measured;
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what was not measured;
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and whether the result applies directly to HAKONE.
HAKONE therefore distinguishes:
Direct Evidence
Research examining the same or a closely matching intervention, population, duration, and outcome.
Related Evidence
Research examining a relevant mechanism, but not the complete HAKONE procedure.
Product-Specific Proposition
A design decision or integrated mechanism that remains to be tested directly.
This distinction should be preserved whenever the scientific page is translated, shortened, redesigned, or used in promotional material.
Future Evaluation
The HAKONE model can be evaluated through measurable outcomes.
Possible research measures include:
Behavioral Measures
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delay between cue and screen opening;
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canceled opening attempts;
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unplanned unlocks;
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continuous-session duration;
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total smartphone-use time;
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return to scrolling after YUBIZEN;
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and frequency of completing the alternative sequence.
Self-Report Measures
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urge intensity;
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perceived control;
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emotional awareness;
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discomfort during the pause;
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calmness;
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attention;
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and perceived usefulness.
Physiological Measures
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heart rate;
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heart-rate variability;
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respiration;
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skin conductance;
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and other measures of arousal.
Cognitive Measures
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stop-signal performance;
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Go/No-Go performance;
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sustained attention;
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and error monitoring.
Neurophysiological Measures
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EEG;
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event-related potentials;
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fNIRS;
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and fMRI.
Follow-Up Measures
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persistence after 72 hours;
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return to baseline;
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individual differences;
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and possible adverse or burdensome effects.
Positive findings would support parts of the model.
Null or negative findings would also be scientifically valuable and could indicate that:
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the pause is too short;
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the sound adds no benefit;
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the tactile component is unnecessary;
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the sequence is too demanding;
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effects are limited to particular users;
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or the intervention requires redesign.
Full Scientific Notice
The studies cited on this page examine habit formation, basal-ganglia function, response inhibition, Zen and mindfulness practice, tactile-assisted meditation, natural sound, competing responses, drawing, affect labeling, cognitive reappraisal, craving regulation, conversational behavior support, smartphone-cue reactivity, and short-term smartphone restriction. Together, they provide a scientific rationale for the individual components and design logic of HAKONE and YUBIZEN. They do not directly prove that the complete HAKONE intervention activates the prefrontal cortex, suppresses basal-ganglia habit activity, strengthens the hyperdirect pathway, changes dopamine receptors, deepens Zen, cures problematic smartphone use, or produces a permanent effect within 72 hours. Direct evaluation of HAKONE requires appropriately controlled behavioral studies, objective smartphone-use data, follow-up measurement, and, where relevant, physiological or neuroimaging methods such as heart-rate variability, EEG, fNIRS, or fMRI.
Medical and Service Notice
HAKONE is intended to support digital self-observation, behavioral interruption, and deliberate smartphone-use choices. It is not a medical diagnostic or treatment service and is not a substitute for professional medical, psychiatric, or psychological care. People experiencing serious impairment, severe distress, or safety concerns should seek support from an appropriately qualified professional.
Compact Notice for the Top of the Page
This page explains the published research underlying individual elements of HAKONE. The cited studies provide scientific rationale for the design but do not constitute direct proof of the complete HAKONE intervention.
Compact Footer Notice
Scientific boundary: HAKONE integrates findings from habit science, response inhibition, meditation, tactile attention, natural sound, drawing, affect labeling, craving regulation, and smartphone research. The integrated system remains subject to direct controlled evaluation and is not presented as a medical treatment or cure.
Closing Statement
Scientific honesty does not weaken the HAKONE model.
It strengthens it.
HAKONE does not claim that borrowed scientific authority has already proven the product.
Instead, it shows:
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where each component came from;
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which findings have been established;
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how those findings were translated into the system;
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what remains unknown;
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and how the model can be tested.
The purpose of this page is not to prevent scientific criticism. It is to make every claim traceable, limited, and open to verification.
That is the foundation on which credible science must stand.















