1． Why Do We Feel Constantly Exhausted Even When We Do Nothing?
A recent video essay explored a simple yet haunting question:
Why do we feel bored even when surrounded by endless entertainment?
(Harris, 2025)
In the video, Johnny Harris describes a familiar modern condition —a quiet
Sunday afternoon when the children are playing outside,all chores and work are
done, and yet a sense of restlessness lingers.
You find yourself thinking about the past and the future, unable to act on
anything in the present.Eventually, you reach for your phone, scrolling through
it without purpose —but the feeling of boredom remains.
That, Harris suggests, is not ordinary boredom.
It is a neurological signal — a symptom of a brain overwhelmed by artificial
stimulation, no longer knowing what to do in silence.
And that observation struck me deeply, because until recently, I was living in
exactly that state.
Barely keeping up with daily tasks, feeling exhausted for no reason, constantly
drawn back to YouTube or social media as if by gravity. Hours would pass
without awareness, leaving only fatigue behind.
Then I began encountering a term that explained everything: the “Attention
Economy.”
The concept was first proposed in 1969 by economist Herbert A. Simon,
who noted that “in an information-rich world, the wealth of information
means a dearth of attention.”
Half a century later, this has become our reality: platforms such as YouTube,
TikTok, and Instagram have turned human attention itself into a tradable
resource (Steinhorst, 2024).
Even in Japan, the term “attention economy” has entered mainstream vocabulary
(Eleminist, 2023).
In a world overflowing with information, our attention has become a resource to
be mined, traded, and competed over (Manamina, 2023).
To understand this phenomenon, we need to look at it from two seemingly distant perspectives — economics and neuroscience.
It is no longer that we use our brains for the economy.
Rather, the economy has begun to decide how our brains are used.
2． The Evolution of the Attention Economy: From Television’s Control to Algorithmic Guidance
In the latter half of the twentieth century, television sat at the center of
society. People across the country watched the same programs every night,
gathering the next day to discuss them. Television succeeded in aligning
collective consciousness in a single direction.
For certain generations,
television remains the primary source of information. Even today, news coverage
and televised debates continue to shape public opinion. Yet that influence has
rapidly waned with the rise of the Internet.
We have shifted from an era in which old media “controlled” attention to one in
which digital platforms “guide” it. The media’s power has not disappeared—it
has simply changed form.
At first glance, this transformation might appear to be a healthy
democratization of information. A world where anyone can create and verify
content. I, too, once welcomed that change. But in recent years, it has become
increasingly clear that this new economic model—fueled by advertising
revenue—has begun to reshape human behavior itself.
Ø The Transformation of Advertising: From “Viewership” to “Neural Response”
Television’s advertising model was simple. Audiences watched programs according
to fixed schedules, and advertisers purchased commercial slots during the hours
when potential customers were most likely watching. Marketing effectiveness was
measured by a single number: the viewership rating.
That simplicity vanished in the late 1990s with the rise of the Internet.
Platforms like Google and YouTube abandoned the vague metric of viewership and
began quantifying behavior at the individual level.
Which ad you clicked. Where you stopped watching a video. What search terms you
entered. All of it became data—measured, analyzed, and monetized in real time.
Advertisers no longer needed to imagine “target demographics.” Platforms now
calculate, with astonishing precision, who is most likely to make a purchase
and display ads directly to that person.
The core of this system lies in predicting what captures human attention— and
converting that attention into a tradable commodity.
In the television era, value was defined by how many people you could reach. In
the algorithmic era, value is defined by how deeply you can penetrate a single
brain. Attention has shifted from the collective to the individual, and within
the individual, down to the level of neural response.
Ø The Algorithm's True Goal: To Prevent You from Leaving
This transformation has changed the very nature of information. It is no longer
something delivered—it is something optimized. The goal of every major platform
is simple: keep the user from leaving.
To achieve that, algorithms continually feed stimuli that sustain engagement—
endless scrolls, suggested videos, the red glow of notification badges.
Such designs are not mere technical conveniences. They are neural architectures
of reward.
Our brains are wired to respond most strongly to unexpected rewards. The
uncertainty of “What comes next?” triggers the highest bursts of dopamine.
YouTube’s recommendations and social media feeds exploit this mechanism with
surgical precision. An algorithm is no longer an information delivery system.
It is a device that transforms human attention and emotion into reproducible
economic resources.
3． Neuroscience: Overstimulation and Down-Regulation of the Reward System
The human brain is equipped with mechanisms that reinforce behaviors
advantageous for survival. Eating, gaining social approval, solving problems —
when these actions succeed, the brain releases dopamine, a neurotransmitter
that generates a sense of pleasure. This circuit, known as the reward system,
primarily involves the prefrontal cortex, nucleus accumbens, and ventral
tegmental area (Purves, Augustine, & Fitzpatrick, 2018, as referenced by
ChatGPT, unverified by the author; see also Schultz, 2015).
These regions form a neural network that governs motivation and pleasure. A
large body of neuroscientific research supports the connection between
dopaminergic activity, reward prediction, and behavioral reinforcement
(Japanese Society for Neuroscience, 2019).
The reward system does not merely respond to pleasure; it learns the temporal
structure of reward. Dopaminergic neurons react most strongly to unexpected
rewards or those that occur after a brief delay — using those experiences to
strengthen future behavior (Schultz, 2015, pp. 853–858).
Ø Digital Stimuli and the Collapse of Reward Timing
Modern digital environments have disrupted this evolutionary design at its
core. A “like” on social media, the automatic replay of a video, the sound of a
level-up in a game—each of these can activate the dopaminergic system with
minimal effort. In the short term, such stimuli may produce a false sense of
achievement, reinforcing both expectation and reactivity toward rewards, as
suggested by studies on the neural reward system (Bromberg-Martin, Matsumoto,
& Hikosaka, 2010; Stanford Medicine, 2021).
When exposure to such stimuli becomes repetitive, adaptive changes occur within
the dopaminergic pathway—such as receptor down-regulation or decreased
sensitivity. As a result, the same stimulus no longer produces the same level
of satisfaction, prompting individuals to seek stronger or more frequent
stimulation. This hypothesis, observed in contexts such as substance addiction,
has been widely discussed in contemporary neuroscience (Mustafa, 2024).
In neuroscience, this state is known as down-regulation of the reward system—a
physiological decline in the brain’s sensitivity caused by chronic
overstimulation.
Ø The Diminished Capacity for “Quiet Satisfaction”
As this process progresses, people begin to lose the ability to experience deep
focus or quiet fulfillment as a form of reward. The sense of satisfaction once
derived from activities such as reading, studying, or creating is now replaced
by the fleeting bursts of stimulation provided by social media.
Long-term goals become difficult to sustain, and the feeling of “I can’t keep
going” becomes chronic. Empirical studies have linked decreases in attention,
memory, and working-memory capacity to chronic overstimulation of dopaminergic
pathways (Zahrt, Taylor, Mathew, & Arnsten, 1997; Arnsten, 2011).
Furthermore, the prefrontal cortex, a region closely tied to the brain’s reward system, also deteriorates under these conditions. The prefrontal cortex is responsible for inhibiting impulses and making long-term decisions—the very foundation of human rationality (Miller & Cohen, 2001).
Research on addiction has shown that chronic exposure to reward stimuli can cause hyper-adaptation within this region, leading to impaired self-control and an intensified drive for immediate gratification (Goldstein & Volkow, 2011).
Ø The Inversion of the Reward System — When Pleasure Destroys Effort
This process can be summarized in a single, devastating equation:
The immediacy of reward erases the meaning of effort.
The loss of effort collapses the value of reward.
As a result, we begin to oscillate between fatigue and apathy. We feel drained
even when we have done nothing, and when we try to begin something, our focus
quickly disintegrates. This is not mere psychological exhaustion. It is a
physiological reaction of a brain whose reward system has lost its equilibrium.
4． The Structural Reality: Profit Design and the Seeds of Political Use
Up to this point, we have seen how advertising-driven models stimulate the
human brain and reshape patterns of behavior. But what drives this system is
not merely technology or algorithmic design. It is the economic structure
itself.
Platform corporations—Google, YouTube, Meta, TikTok—are all built upon
mechanisms that capitalize on human attention. Within these systems, user
retention time serves as the primary metric of profit. In other words, the core
of their business lies in how effectively they can capture and prolong human
focus.
The issue here is not that these companies are inherently malicious. Quite the
opposite: few platforms set out with the intention of making people addicted.
They simply followed the logic of efficiency and profit—and in doing so,
arrived at an “optimal solution” that continuously stimulates the human nervous
system.
Yet this is precisely where we must pause and reflect. Even if the system
emerged accidentally, it now functions as a structure capable of governing
collective cognition and behavior across society. And increasingly, that
structure is expanding beyond the boundaries of economics—into the realm of
politics.
Ø The Connection Between Power and Platforms
In September 2025, the U.S. House Judiciary Committee launched an investigation
into whether Google/YouTube had restricted certain political content under
pressure from government agencies. In the course of this inquiry, Google
acknowledged that it had once received a censorship request from the Biden
administration—describing it as “inappropriate” and “unacceptable” (Donovan,
2025).
The Committee’s findings revealed several key facts:
l Government agencies (including the Department of Health and the
White House) had requested the removal or limitation of content related to
COVID-19 and election topics.
l As part of a cooperation posture, Google considered reinstating
channels that had been deplatformed.
l Indirect restrictions via third-party fact-checking organizations
were also being used.
This is not merely a domestic U.S. political issue.
These facts suggest that the collaboration between state power and platforms
may have already been operating as a functional “information sieve.”
More importantly, this may be the first time in history that the infrastructure
for intentionally manipulating human behavior has been (1) constructed, and (2)
demonstrably deployed.
For years, we assumed algorithms steered us unconsciously. Now, that
architecture has matured into a tool that can be consciously wielded. Whether
for political ends or economic gains, this structure is beginning to function
as an infrastructure of control.
5． Synthesis: Regaining Agency in an Engineered World
As we have seen, our sense of inability—the feeling that we “can’t focus” or
“can’t begin”—is not a failure of willpower or discipline. It is the natural
consequence of a brain that has adapted to an optimized environment.
You are not lazy. Your brain has simply adjusted to a world that constantly refines itself around your behavioral data.
Social networks and video platforms learn your patterns, identify the stimuli that trigger the strongest responses, and present them in rhythm with your habits. Without realizing it, your mind is surrounded by a pleasure apparatus tailored uniquely to you—one that gradually rewires your reward system to comply with its logic.
Once, entertainment existed between the rhythms of daily life. Now, daily life itself is engineered around entertainment.
Notifications, autoplay, gaming events—these do not fill our spare moments; rather, our moments are shaped to accommodate them. Within this structure, resistance through sheer will alone becomes extraordinarily difficult.
There is another factor we must not overlook: the speed of this transformation.
In all of human history, no generation has ever faced environmental adaptation at the neurological level occurring over so short a span of time. And as long as this process remains tied to the acceleration mechanisms of capitalism, it is unlikely that any meaningful social restraint will emerge.
That is precisely why self-defense must begin at the individual level. The algorithm is not your enemy, but its design will always optimize you for consumption. And in that process, our capacity for free, human action is being quietly eroded.
6． Behavioral Recovery in Three Steps: Externalize, Attenuate, Replace
Ø Regaining Control Over Action
Many people begin to recognize this problem only when they confront a behavior
they themselves cannot fully explain. Watching videos for hours. Closing a
social-media app—only to open it again moments later. Most of us have
experienced this cycle at least once. And in many cases, even after deciding
“This time I’ll stop,” we find ourselves slipping back into the same pattern
when our energy or mood fluctuates.
Everyday behavior has its own form of homeostasis. Even when willpower allows
temporary withdrawal, the brain exerts a powerful force to return to its
previous state. That is why this problem cannot be solved through mindset or
discipline alone.
After repeated trial and error, I eventually discovered a method that worked
for me: streaming myself while I work. By creating a simulated social
environment—the subtle awareness that others might be watching—I naturally
began to reduce passive video consumption and found myself spending entire days
in focused work. A week later, I could feel a dramatic improvement in my
productivity and mental clarity.
Ø “Streaming” as Externalization — Turning Social Inhibition into an Ally
From a neuroscientific perspective, the act of streaming oneself is a form of
externalized self-regulation. The human brain—particularly the prefrontal
cortex—activates stronger inhibitory control the moment it senses the presence
of others. This phenomenon, known as social inhibition, leads individuals to
suppress impulsive behaviors and opt for more deliberate, goal-oriented actions
when they feel they are being observed (Beer & Ochsner, 2006; Izuma, Saito,
& Sadato, 2008).
My own experiment deliberately recreated this mechanism. Through streaming, the brain shifts its orientation—from being a viewer to becoming a creator. In doing so, it redirects the output of the reward system away from external stimuli and toward self-generated action. This subtle rewiring transformed passive consumption into active engagement, allowing concentration to emerge naturally rather than through force of will.
Ø Step 1: Externalization — Supporting Self-Control Through Environment
The first step is simple: do not overestimate your brain. Human willpower and
attention are finite resources; when fatigued, they function poorly.
Therefore, instead of relying on discipline, we must design the environment to
guide behavior.
In practice, this means implementing external systems of control, such as:
l Using time-lock apps to limit social-media access
l Streaming yourself while working
l Placing your smartphone in another room
Behavioral science consistently shows that it is easier to change the
environment than to change the person. The goal is not to “trick” the brain but
to support it through structural design.
l Practical Example — Redesigning Context
Neuroscience offers a useful concept known as context-dependent memory. The
brain tends to encode actions together with the physical environment in which
they occur. If your desk at home has been repeatedly associated with opening
YouTube, simply sitting there may automatically trigger “viewing mode.” This
phenomenon is well documented: when the environment during learning and recall
is the same, memory and behavioral responses are facilitated (Godden &
Baddeley, 1975; Smith & Vela, 2001).
To break this conditioning, physical context reconstruction is remarkably
effective. Take your laptop to a café or library and establish a new rule: this
is a place only for work. Such a simple environmental switch can become a
surprisingly powerful behavioral-modification tool.
Ø Step 2: Downscaling — Gradually Lowering the Intensity of Reward Stimuli
The brain's reward system is highly sensitive to abrupt change. When
stimulation is cut off suddenly, the brain reacts with a rebound of anxiety,
boredom, and lethargy. This occurs because the dopaminergic system enters a
transient state of hyporesponsiveness, leading to diminished pleasure and
motivation (Volkow et al., 2004; Koob & Le Moal, 2001).
Therefore, the goal is not abstinence, but attenuation.
Examples include:
l Instead of turning off all notifications, check them only twice a
day—morning and evening.
l Instead of background watching videos, schedule specific
viewing periods.
l Instead of deleting social media apps entirely, reinstall and use
them only once a week.
By managing
information intake as carefully as one manages meals, the reward system
gradually settles into a calmer, more stable state.
The key lies not in prohibition, but in choice. The brain resists deprivation,
but it can adapt to self-imposed boundaries. This principle aligns with
neuroscientific models of addiction recovery, which emphasize gradual
recalibration of reward stimuli to restore natural motivation and
self-regulatory capacity (Volkow et al., 2011).
l Practical Example — Using a Café as a “Low-Stimulation Window”
In the previous section, we discussed the effectiveness of changing
environments—working in a café or library. It is important to clarify that such
places need not become permanent workspaces. The purpose is simpler: to create
short windows of minimal stimulation.
1.
The initial goal is not “hours
of deep focus,” but merely 15-30 minutes of low-stimulation time.
2.
The café should not be fully
linked to “productivity” but used as a temporary refuge from social
media and video feeds.
3.
Even brief disconnection
reveals just how fatigued the brain has become—and that realization alone is
transformative.
When you return home, you may relapse into old
patterns—and that is perfectly fine. What matters is the gradual reduction of
stimulation, allowing the brain to adapt step by step to calmer environments.
Human beings do not change overnight. But small, repeated recoveries make the
next small choice possible.
Over time, you may find that you no longer need to leave home to create quiet
space. Perhaps you simply place your phone in another room for 15 minutes
before bed, or brew coffee with notifications turned off. Such small rituals
eventually train the brain to recreate silence without leaving it behind.
Ø Step 3: Replacement — Redirecting the Source of Reward Toward Creation
In the final stage, the goal is to shift the direction of reward from receiving
to creating. The human brain exhibits strong dopaminergic activity during
creative acts such as writing, designing, composing, or learning. Indeed,
studies have shown that musical creation and even aesthetic appreciation
trigger dopamine release within the striatum, the core of the reward circuitry
(Salimpoor, Benovoy, Larcher, Dagher, & Zatorre, 2011).
In other words, the same neural pathways that once delivered external pleasure can be repurposed into creative reward.
For me, that meant writing and streaming. Through these practices, my brain gradually relearned to find pleasure not in the result but in the process itself. The stimulation is gentler, deeper, and closer to what the human brain is naturally designed to seek.
l Practical Example — Creation as Replacement
When you start going to a café simply to step away from stimulation, a new
question soon emerges: “What should I do now?” Without the constant feed of
social media or video, the brain—long optimized to receive—suddenly faces a
gap.
That gap feels empty at first. Yet it is precisely within that emptiness that
creation begins.
Many people struggle at this moment. But the instant you choose to create—to
write in a notebook, sketch, fold paper, or simply think—the brain’s reward
pathways start to reorganize quietly. The essential point is not what you make,
but that the time is generated from within rather than filled from without.
What I recommend is reclaiming the sensation of building time with your own
hands, however small the act may be. Write something. Design something. Record
something. The purpose is to transform the habit of consuming time into the art
of creating time.
As you spend more moments in creative flow, you begin to remember the quiet
focus and satisfaction that once felt natural. Completing even a simple
piece—no matter how small—redefines pleasure itself, restoring the courage to
pursue what truly matters to you.
Small creations are the gateway to large transformations. They mark the first
step by which the brain shifts from being a receiver of experience to once
again becoming its creator.
Ø Small Successes Reshape the Brain
The key to behavioral recovery lies in accumulating small moments of success.
The brain encodes each successful experience as a signal to continue the
behavior.
“Today, I didn’t check my notifications.” “Today, I
managed to focus for thirty minutes.” Even such seemingly minor achievements
begin to restructure the reward system in a positive direction.
This is not a matter of willpower. It is an exercise in neuroplasticity—the
brain’s inherent capacity to learn and rewire itself.
Ø Digital Detox Is Not Withdrawal — It Is Redesign
To reclaim ourselves within a digital society is not to reject technology.
It is to reclaim the design of our own reward systems. “Digital Detox” is not
the act of cutting off information—it is the act of redesigning our
relationship with it.
It means taking back the architecture of attention that has been delegated to
algorithms, and rebuilding it through conscious choice. That is the essence of
this chapter—and the first true step toward restoring our capacity to act.
7． Epilogue — The Brain That Still Remembers
My niece has stopped going to school. When I asked why, I was told she can no
longer let go of her smartphone—staring at the screen until dawn before finally
falling asleep.
What I have written in these pages may describe precisely what is happening
among her generation. Even those of us who grew up in the age of television and
early video games—a kind of prelude to today’s attention economy—are now deeply
woven into its design. For those who were born with a smartphone already in
hand, their very sense of action may have been built upon the consumption of
attention itself.
There are two things I wish to leave here.
Ø First: Radical deprivation does not work.
Taking away a smartphone rarely solves the problem. The human brain is not that
simple.
When the machinery of pleasure is abruptly cut off, no one can predict where
the rebound will go. What social media stimulates is not mere entertainment—it
is the circuitry of approval, empathy, and identity.
To strip that away by force risks redirecting the brain’s search for reward into
destructive outlets—extremism, conspiracy, or despair. At the root of such
behavior lies not malice, but adaptation. To suppress it without understanding
its mechanism only strengthens the brain’s instinct to defend itself.
Ø Second: Yet the human brain still remembers how to adapt.
Despite the staggering shifts of the last twenty years, our brains carry the
inheritance of hundreds of thousands of years—an unbroken chain of adaptation
to nature.
Your current actions are not sustained by will alone; they are the sum of
countless ancestral experiments that refined how we endure, learn, and
reconnect with the world. That same capacity for adaptation still resides
within you.
No algorithm, however sophisticated, can erase the deeper intelligence that
evolution has left in the human mind. No design can outdesign the design of
survival itself.
As I write these final lines, I do not know who will read them. But if you have
come this far—and if these words help you understand your own brain and reclaim
even a few quiet moments of your time—then that alone is enough. That alone is
joy.
Author’s Note
This article—including its structure,
phrasing, and all accompanying visuals—was created with the assistance of
generative AI (ChatGPT).
All factual content was verified by the author through primary sources wherever
possible.
For readers interested in the original Japanese
edition,
you can find it here:
- Note (日本語版)
→
- Blogger (日本語版) →
References
Confirmed References
Harris, J. (2025, May 22). Why we
feel bored even when we have everything [Video]. YouTube. https://www.youtube.com/watch?v=8uoJNv9ufjM
Berkeley Economic Review. (2021). Paying
attention: The attention economy. Retrieved from https://econreview.studentorg.berkeley.edu/paying-attention-the-attention-economy/
Eleminist. (2023, August 2). The
Attention Economy: The quality of information and the dangers of manipulation（アテンションエコノミーとは
注意したい情報の質と過剰な誘導）. Retrieved from https://eleminist.com/article/2534
Manamina. (2023, May 15). The
Attention Economy: Current challenges and future outlook（アテンションエコノミー～課題と今後）. Retrieved from https://manamina.valuesccg.com/articles/4048
Simon, H. A. (1969). Designing
organizations for an information-rich world. In M. Greenberger (Ed.), Computers,
communications, and the public interest (pp. 37–72). Baltimore, MD: Johns
Hopkins Press.
Steinhorst, C. (2024, February 6). Lost
in the scroll: The hidden impact of the attention economy. Forbes.
Retrieved from https://www.forbes.com/sites/curtsteinhorst/2024/02/06/lost-in-the-scroll-the-hidden-impact-of-the-attention-economy/
Mustafa, A. (2024). The role of
dopamine in addiction: A neurobiological perspective. Journal of
Addiction and Dependence, 10(2), 1–8. Retrieved from https://www.omicsonline.org/open-access-pdfs/the-role-of-dopamine-in-addiction-a-neurobiological-perspective.pdf
AI-Assisted References
Purves, D., Augustine, G. J., &
Fitzpatrick, D. (Eds.). (2018). Neuroscience (6th ed.). Oxford
University Press.
※ Citations in this section were referenced via generative AI (ChatGPT). The
author was unable to access the primary sources directly; verification is
pending.
Japanese Society for Neuroscience.
(2019). Neuroscience: Exploring the brain’s reward mechanisms. Tokyo:
JSN Press.
Schultz, W. (2015). Neuronal reward
and decision signals: From theories to data. Physiological Reviews,
95(3), 853–951. https://doi.org/10.1152/physrev.00023.2014
Bromberg-Martin, E. S., Matsumoto, M.,
& Hikosaka, O. (2010). Dopamine in motivational control: Rewarding,
aversive, and alerting. Neuron, 68(5), 815–834. https://doi.org/10.1016/j.neuron.2010.11.022
Stanford Medicine. (2021, October 4). Addictive
potential of social media, explained. Retrieved from https://med.stanford.edu/news/insights/2021/10/addictive-potential-of-social-media-explained.html
Volkow, N. D., Fowler, J. S., &
Wang, G. J. (2004). The addicted human brain: Insights from imaging studies.
The Journal of Clinical Investigation, 111(10), 1444–1451. https://doi.org/10.1172/JCI18533
Arnsten, A. F. T. (2011). Catecholamine
influences on dorsolateral prefrontal cortical networks. Biological
Psychiatry, 69(12), e89–e99. https://doi.org/10.1016/j.biopsych.2011.01.027
Zahrt, J., Taylor, J. R., Mathew, R. G.,
& Arnsten, A. F. T. (1997). Supranormal stimulation of D1 dopamine
receptors in the rodent prefrontal cortex impairs spatial working memory
performance. Journal of Neuroscience, 17(21), 8528–8535. https://doi.org/10.1523/JNEUROSCI.17-21-08528.1997
Miller, E. K., & Cohen, J. D.
(2001). An integrative theory of prefrontal cortex function. Annual
Review of Neuroscience, 24(1), 167–202. https://doi.org/10.1146/annurev.neuro.24.1.167
Goldstein, R. Z., & Volkow, N. D.
(2011). Dysfunction of the prefrontal cortex in addiction: Neuroimaging
findings and clinical implications. Nature Reviews Neuroscience,
12(11), 652–669. https://doi.org/10.1038/nrn3119
Beer, J. S., & Ochsner, K. N.
(2006). Social cognition: A multi level analysis. Brain Research,
1079(1), 98–105. https://doi.org/10.1016/j.brainres.2006.01.002
Izuma, K., Saito, D. N., & Sadato,
N. (2008). Processing of social and monetary rewards in the human striatum.
Neuron, 58(2), 284–294. https://doi.org/10.1016/j.neuron.2008.03.020
Godden, D. R., & Baddeley, A. D.
(1975). Context-dependent memory in two natural environments: On land and
underwater. British Journal of Psychology, 66(3), 325–331. https://doi.org/10.1111/j.2044-8295.1975.tb01468.x
Smith, S. M., & Vela, E. (2001). Environmental
context-dependent memory: A review and meta-analysis. Psychonomic
Bulletin & Review, 8(2), 203–220. https://doi.org/10.3758/BF03196157
Koob, G. F., & Le Moal, M. (2001). Drug
addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology,
24(2), 97–129. https://doi.org/10.1016/S0893-133X(00)00195-0
Volkow, N. D., Wang, G. J., Fowler, J.
S., & Telang, F. (2004). Overlapping neuronal circuits in addiction and
obesity: Evidence of systems pathology. Philosophical Transactions of
the Royal Society B: Biological Sciences, 363(1507), 3191–3200. https://doi.org/10.1098/rstb.2008.0107
Salimpoor, V. N., Benovoy, M., Larcher,
K., Dagher, A., & Zatorre, R. J. (2011). Anatomically distinct dopamine
release during anticipation and experience of peak emotion to music. Nature
Neuroscience, 14(2), 257–262. https://doi.org/10.1038/nn.2726
