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Cyber Threats of Trade Secrets
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Cyber Threats of Trade Secrets
In recent years, the issue of cyber theft of trade secrets has become an increasingly important concern for businesses and governments around the world. The growing importance of this issue is due to the growing reliance of businesses on digital information and the increasing sophistication of cyber criminals (Ciuriak & Ptashkina, P. 253).
Purpose: The article seeks to quantify the economic impact of trade secret theft, and to offer policy recommendations for addressing the issue. The article notes that while the economic impact of trade secret theft is difficult to quantify, it is likely to be significant (Ciuriak & Ptashkina, P. 255). The authors suggest that policy measures to address the issue should focus on improving the protection of trade secrets, and on increasing the penalties for those who engage in trade secret theft.
1. What are trade secrets?
Trade secrets are any information that has commercial value and is not generally known to the public. Trade secrets can include anything from customer lists and marketing plans to product designs and manufacturing processes.
A. The problem of cyber theft of trade secrets:
The problem of cyber theft of trade secrets is a growing concern for businesses and governments around the world. The reason for this is that trade secrets are increasingly being stored in digital form, and cyber criminals are becoming more sophisticated in their ability to access and steal this information.
B. The impact of cyber theft of trade secrets:
The impact of cyber theft of trade secrets can be significant for businesses and governments (Basuchoudhary & Searle, P. 400).
a. The loss of trade secrets can lead to:
i. The loss of competitive advantage.
ii. The loss of revenue.
iii. The loss of jobs.
2. What can be done to prevent trade secret theft?
There are a number of steps that businesses and governments can take to prevent trade secret theft. For example, businesses can implement security measures to protect their digital information, and governments can enact laws that make trade secret theft a crime.
A. The policy implications of cyber theft of trade secrets:
The policy implications of cyber theft of trade secrets are significant. The issue of cyber theft of trade secrets raises a number of policy questions, including:
a. How to protect trade secrets.
b. How to investigate and prosecute cases of cyber theft.
c. How to prevent the theft of trade secrets in the first place (Abd Jalil, P. 215).
3. How are trade secrets stolen?
Trade secrets can be stolen in a number of ways. Cyber attacks are a particularly effective way of stealing trade secrets because they can be done remotely and often go undetected.
A. Some of the ways in which trade secrets can be stolen include:
a. The use of email phishing scams. In these scams, cyber criminals send out emails that appear to be from a legitimate source, such as a business or government agency (Basuchoudhary & Searle, P. 470).
b. The use of social engineering. In social engineering scams, cyber criminals will try to trick employees of a company into revealing sensitive information. For example, a cyber criminal may pose as a customer service representative and call an employee of a company.
4. What are the consequences of trade secret theft?
The consequences of trade secret theft can be significant. For example, a company that has its trade secrets stolen may lose its competitive advantage, which can lead to financial losses. In addition, the theft of trade secrets can damage a company’s reputation and make it more difficult to do business.
A. The impact of Cyber Theft of Trade Secrets include:
a. It can lead to the loss of competitive advantage for the victim company. If a company’s trade secrets are stolen and made public, its competitors will be able to benefit from this information and gain an advantage over the victim company (Ettredge et al., P. 581).
b. Cyber theft of trade secrets can also lead to the loss of customer trust and loyalty. If customers believe that their personal information has been stolen from a company, they may be reluctant to do business with that company in the future.
c. Cyber theft of trade secrets can also lead to financial losses for the victim company. If a company’s trade secrets are stolen and used by its competitors, the company may suffer financial losses as a result (Ettredge et al., P. 570).
5. Conclusion:
The issue of trade secret theft is a growing concern for businesses and governments around the world. Trade secrets are valuable because they can give a business a competitive advantage in the marketplace. However, trade secrets can be stolen in a number of ways, including through cyber-attacks, espionage, and theft. The consequences of trade secret theft can be significant, and businesses and governments must take steps to prevent it.
Introduction
Trade secrets are any information that has commercial value and is not generally known to the public. Trade secrets can include anything from customer lists and marketing plans to product designs and manufacturing processes. A trade secret is something that is protected from outside parties. Trade secrets provide the business the capacity to safeguard its creations and obtain a competitive advantage. Theft of trade secrets is the term used to describe the improper sharing of this sort of knowledge. The corporation and its economy can suffer significant harm as a result of trade secret theft. Trade secret theft is a severe offense with far-reaching repercussions. Trade secrets are fiercely guarded and are not open to just anybody. They include highly private trade secrets and other industrial secrets. Anyone has the potential to steal. The workers, multinational corporations, or even other nations.
Key Words: Trade secrets, Cyber Crime, Economy
Problems of Cyber Theft of Trade Secrets
The problem of cyber theft of trade secrets is a growing concern for businesses and governments around the world. The reason for this is that trade secrets are increasingly being stored in digital form, and cyber criminals are becoming more sophisticated in their ability to access and steal this information.
Examples of Trade Secrets
Every business has its own trade secrets, which it only discloses to the appropriate authorities. The examples of trade secrets from some well-known and prosperous corporate organizations provide some fascinating information. The Coca-Cola firm has a proprietary secret recipe that is fiercely guarded. It is securely stored in a vault that was specially constructed in the World of Coca-Cola. Similar to this, the renowned fast-food restaurant KFC uses a secret blend of 11 herbs and spices to create its world-famous Kentucky fried chicken. The manufacturing corporation also protects the privacy of its trade secrets.
Science and technology firms also keep their research and studies under wraps, in addition to their recipes and production processes. Until the research are validated, they are kept a secret. If they divulge their trade secrets, the company’s product will no longer be valuable commercially. In order to escape criticism if their study is unproven, scientists also conduct their studies in secret. The protection of trade secrets is a growing problem for businesses today. It is also a good idea for the businesses to keep quiet about their trade secrets in light of all the continuing operations linked to trade secret theft. Additionally, they have begun to conceal their list of clients and consumers. The business must cherish its clients and consumers. A short check of the case law revealed that there are more than 150 federal court cases where it is alleged that client and customer information is being utilized improperly as trade secrets.
Prevention of Trade Secrets theft
There are a number of steps that businesses and governments can take to prevent trade secret theft. For example, businesses can implement security measures to protect their digital information, and governments can enact laws that make trade secret theft a crime. The policy implications of cyber theft of trade secrets are significant. The issue of cyber theft of trade secrets raises a number of policy questions.
According to surveys, accessing personal information unlawfully frequently results in 50% of employees losing their jobs. The motivations for the workers’ international migration are several. There may be some good ones and some bad ones. The business should begin with its personnel in order to secure its trade secrets. Everyone should be made aware of the repercussions of theft when recruiting a new employee. The organization should compile all relevant information about an employee that it suspected of committing theft. the details of his job history, including the projects he worked on, the data he accessed, his relationships with persons outside the organization, etc. The appropriate course of action in such a circumstance is to question the accused employee. The business has access to his works, his actions, and the circumstances that motivated him to take these actions.
The Economic Espionage Act of 1996 was a better method developed by the US government to safeguard trade secrets. Two different types of trade secret theft are proposed by this statute. Theft committed for financial gain and theft committed to boost the foreign economy. The accused might get a fine of up to $250,000 or double the loss the firm suffered, along with a sentence of up to 10 to 15 years in jail. The most current trade secret legislation, passed in 2016, allows the federal government the authority to take action in situations involving the unauthorized licensing of trade secrets. The owner of the business is also empowered by this law to take strong measures to protect trade secrets and other private information from third parties.
Steps of Trade Secret Protection
The most effective line of protection against trade secret theft is having agreements and processes in place. Companies that have developed protection procedures are able to safeguard trade secrets as effectively as feasible. Managing the hazards is another option. When trade secrets are protected, there are some dangers involved. The information pertaining to the materials that the business considers to be trade secrets, as well as the contents themselves, need to be registered. The components might be made of pricy, hefty manufacturers with cutting-edge engineering.
Additionally, the company details must be registered. To keep a watch on the trade secrets, the protection team should be set up. When trade secrets are misappropriated within the organization, building a cross-functional team will aid the business in laying the groundwork for trade secret protection. Important business and economic information that can assist the nation’s economy grow may be included in the business information. Similarly, the business must ensure that all workers are aware of the repercussions of stealing trade secrets.
Role of Computers in Theft of Trade Secrets
Trade secret theft is significantly facilitated by computers. A computer protects almost all trade secrets. Anyone who believes they won’t be caught stealing from a secured computer is very incorrect. The use of computers has grown with all the new software and programs that have been developed along with new technological advancements. Companies now utilize modern, updated technologies to safeguard their trade secrets. When someone is unaware that his actions are visible, they misappropriate trade secrets. Every day, a computer monitors every movement made by the employee. As a result, computers may be used to quickly find the individual who stole trade secrets.
The first thing a business may do in the event of an employee theft is to look at the employee’s computer. His use of computers created a computerized data network, making it possible to simply retrieve the history of his operations. Additionally, if he denies stealing, the computer he used might be considered trustworthy evidence against him in court. It is a truth that computers are used to operate every business, the government, the educational system, and many other aspects of life. The world we live in today would not be conceivable without computers. Therefore, it is shameful to believe that stealing will go undetected when computers are involved.
Abstract
In recent years, the issue of cyber theft of trade secrets has become an increasingly important concern for businesses and governments around the world. The growing importance of this issue is due to the growing reliance of businesses on digital information and the increasing sophistication of cyber criminals. Unimaginable sums of money have been lost as a result of trade secret theft. As a result of theft, many good companies had to close their doors. Every firm uses its own trade secrets to conduct trust-worthy and successful operations. When such secrets are stolen, they are exploited against the firm and cause it to lose money
Reference
Abd Jalil, Juriah, and Halyani Hassan. “Protecting trade secret from theft and corporate espionage: Some legal and administrative measures.”
International Journal of Business and Society21.S1 (2020): 205-218.
http://www.ijbs.unimas.my/images/repository/pdf/Vol21-S1-paper15.pdf
Basuchoudhary, Atin, and Nicola Searle. “Snatched secrets: Cybercrime and trade secrets modelling a firm’s decision to report a theft of trade secrets.”
Computers & Security87 (2019): 101-591..
https://www.sciencedirect.com/science/article/pii/S0167404819300616
Ciuriak, Dan, and Maria Ptashkina. “Quantifying trade secret theft: policy implications.”
CIGI Paper253 (2021).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3706511
Ettredge, Michael, Feng Guo, and Yijun Li. “Trade secrets and cyber security breaches.”
Journal of Accounting and Public Policy37.6 (2018): 564-585.
https://www.sciencedirect.com/science/article/pii/S0278425418302400
Schmitz, Kassidy. “TRIPing on Trade Secrets: How China’s Cybertheft of US Trade Secrets Violated TRIPS.”
Am. U. Int’l L. Rev.36 (2020): 929.
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Wisemen, P., & Liedtke, M. (2020, September 10). “Here are 5 cases where the U.S. Retrieved September 27, 2020,
Doyle, Charles. “Stealing Trade Secrets and Economic Espionage: An Overview of the
Economic Espionage Act.”
Congressional Research Service, 19 Aug. 2016, fas.org/sgp/crs/secrecy/R42681.pdf. Accessed 9 Sept. 2020.
Hurley, K. (2019, November 21). Anatomy of Computer Forensics In Trade Secret
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Application paper
[removed] PS66CH04-Botvinick ARI 11 November 2014 14:31
Motivation and Cognitive
Control: From Behavior
to Neural Mechanism
Matthew Botvinick1 and Todd Braver2
1Princeton Neuroscience Institute and Department of Psychology, Princeton University,
Princeton, New Jersey 08540; email: [emailprotected]
2Department of Psychology, Washington University in St. Louis, St. Louis, Missouri 63130
Annu. Rev. Psychol. 2015. 66:83113
First published online as a Review in Advance on
September 12, 2014
The Annual Review of Psychology is online at
psych.annualreviews.org
This articles doi:
10.1146/annurev-psych-010814-015044
Copyright c 2015 by Annual Reviews.
All rights reserved
Keywords
motivation, cognitive control, reward, effort, prefrontal cortex
Abstract
Research on cognitive control and executive function has long recognized
the relevance of motivational factors. Recently, however, the topic has come
increasingly to center stage, with a surge of new studies examining the in-
terface of motivation and cognitive control. In the present article we survey
research situated at this interface, considering work from cognitive and social
psychology and behavioral economics, but with a particular focus on neuro-
science research. We organize existing findings into three core areas, consid-
ering them in the light of currently vying theoretical perspectives. Based on
the accumulated evidence, we advocate for a view of control function that
treats it as a domain of reward-based decision making. More broadly, we
argue that neuroscientific evidence plays a critical role in understanding the
mechanisms by which motivation and cognitive control interact. Opportu-
nities for further cross-fertilization between behavioral and neuroscientific
research are highlighted.
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Cognitive control:
the set of
superordinate
cognitive functions
that encode and
maintain a
representation of the
current task,
marshaling to the task
subordinate functions
including working,
semantic, and episodic
memory; perceptual
attention; and action
selection and
inhibition
Motivation:
the orienting and
invigorating impact,
on both behavior and
cognition, of
prospective reward
Contents
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Scope and Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
CORE BEHAVIORAL PHENOMENA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
The Relationship Between Incentives and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
The Dynamics of Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
The Cost of Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
THREE THEORETICAL PERSPECTIVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Force-Field Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Resource Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Reward-Based Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
From Metaphor to Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
NEUROSCIENTIFIC FINDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
A Tale of Two Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
The Relationship Between Incentives and Performance:
Neuroscientific Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Control Dynamics: Neuroscientific Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
The Cost of Control: Neuroscientific Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
INTRODUCTION
Concentration comes out of a combination of confidence and hunger.
Arnold Palmer
Picture an undergraduate student sitting in the library with the intention of studying for an exam.
Sometimes she finds its going well. She is able to attend closely to the material and to devise and
execute effective strategies for retaining it. At other junctures, she struggles to concentrate, feeling
drawn to her email or social network accounts. Sometimes she yields to these impulses, feeling she
really needs a rest. At others, she reapplies herself, compelled by the thought that if she doesnt,
the exam might not go well, undermining her hopes of gaining admission to a prestigious medical
school.
From a psychological point of view, this scenario centers on cognitive or executive control,
the set of functions that regulate more basic attention-, memory-, language-, and action-related
faculties and coordinate their activity in the service of specific tasks. In this regard, the cognitive
processes underlying the students experience are relatively well understood; executive or
cognitive control has been a core research topic in cognitive science essentially since the fields
inception (Miller et al. 1960, Posner & Snyder 1975). Several decades of research have established
key behavioral phenomena (Banich 2009), revealed some basic computational (Botvinick &
Cohen 2014, OReilly et al. 2010) and neural mechanisms (Mars et al. 2011, Miller & Cohen
2001), and elucidated the nature and origins of individual differences in control function (Miyake
& Friedman 2012).
However, there is also a side to the library vignette that we do not yet understand quite so
well. This involves the aspects of the scenario that relate to the interaction of cognitive control
and motivation. It is clear that the student in the story is mobilizing cognitive control for a reason,
84 Botvinick Braver
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Incentive: a value- or
reward-laden outcome
that is associated by a
decision maker with a
particular line of
behavior and that is
assumed to motivate
that behavior. The
value in question can
be positive or negative,
and the incentive itself
can be intrinsic to
behavior itself, as
when the decision
maker finds
performance of a task
inherently enjoyable
and that this reason has directly to do with desired outcomes that can be brought about by the
application of control, as well as with undesired outcomes that would follow from a failure to
apply control. Furthermore, when the student has difficulty concentrating on her coursework, this
seems likely to occur because at some level she does not actually want to concentrate. Although
it may be necessary to review for the exam, it is not inherently enjoyable. In short, the function
of control is driven, powerfully and fundamentally, by the students desires and goals. Control is
motivated.
Once it is acknowledged that motivation may play an important role in cognitive control,
a number of important questions arise, many of which go beyond those that have traditionally
guided control research. What exactly are the motivational factors that fuel executive function?
Via what mechanism (or mechanisms) do incentives trigger control to engage, to withdraw, to
shift focus? What role might motivation play in driving the temporal dynamics of control, its
tendency to vary in focus and intensity over time? Obviously, these are questions that, in addition
to their academic relevance, also have a direct bearing on practical matters, including education,
workplace performance, and a range of clinical disorders, ranging from chronic fatigue syndrome
to attention-deficit/hyperactivity disorder (ADHD) to addiction.
In recognition of these points, recent research on cognitive control has increasingly focused
on its interaction with motivation. This reorientation has triggered new developments across a
diverse set of fields, including cognitive psychology, computational reinforcement learning, social
cognition, and behavioral economics. One aim of the present review is to provide a selective
overview of the key empirical observations and theoretical assertions that have emerged from
these collected disciplines to date.
Our primary objective, however, is to consider the relations between those findings and
observations from yet another domain of research: neuroscience. Like behavioral research,
neuroscientific research on cognitive control has also recently become increasingly focused on
issues of motivation. It is tempting to see such neuroscientific work as constituting a special topic,
a source of information that can be safely ignored if one is exclusively interested in behavior. In
particular, the temptation is to view neuroscientific research in this (and other) areas as involving
a search for the neural correlates of processes that can be fully specified and understood without
reference to the brain. Although this attitude may conceivably be defensible in some domains,
we argue that it is misguided when it comes to the interface of motivation and control. Far from
being a special topic, neuroscience lies squarely on the critical path toward truly understanding
the motivation-control link, holding an indispensable key to settling core issues. With this in
mind, our overarching aim in the present work is to contribute toward the dismantlement of
the walls that currently tend to segregate neuroscientific work on motivation and control from
psychologically and behaviorally focused investigations.
Scope and Definitions
The terms cognitive control and motivation can take on different meanings in different re-
search contexts, and so it behooves us to provide an explicit definition for each of these terms.
By cognitive control, we refer to that set of superordinate functions that encode and maintain
a representation of the current taski.e., contextually relevant stimulus-response associations,
action-outcome contingencies, and target states or goalsmarshaling to that task subordinate
functions including working, semantic, and episodic memory; perceptual attention; and action
selection and inhibition. The state of control at any instant can be characterized in terms of
(a) its direction, the specific task objectives toward which control is directing subordinate systems;
www.annualreviews.org Motivation and Cognitive Control 85
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PS66CH04-Botvinick ARI 11 November 2014 14:31
INDIVIDUAL AND GROUP DIFFERENCES
The impact of motivation on control function has been shown to vary in systematic ways across individuals both
with (a) the baseline inclination to engage in controlled information processing (see Westbrook et al. 2013) and
(b) general sensitivities to reward and punishment (see Braem et al. 2012, 2013; Engelmann et al. 2009; Frober
& Dreisbach 2014; Jimura et al. 2010; Locke & Braver 2008; Padmala & Pessoa 2011; Savine et al. 2010). On
the neural level, behavioral reward sensitivity positively predicts responses to incentives during cognitive tasks in
reward and control networks (Engelmann et al. 2009, Jimura et al. 2010, Locke & Braver 2008, Padmala & Pessoa
2011) as well as in functional connectivity between these networks (Padmala & Pessoa 2011). Interestingly, elevated
sensitivity to incentives, at both behavioral and neural levels, appears to arise during adolescence (Geier et al. 2010,
Jazbec et al. 2006, Luciana & Collins 2012, Luna et al. 2013, Padmanabhan et al. 2011, Somerville & Casey 2010,
Somerville et al. 2011), one of numerous examples of the moderation of motivation and control interactions by
age (Ennis et al. 2013, Somerville & Casey 2010, Westbrook et al. 2013) and/or clinical profile (Barch et al. 2008,
Slusarek et al. 2001, Strand et al. 2012, Strauss et al. 2013, Treadway et al. 2012).
and (b) its intensity, the strength of its top-down input to those systems (Bonner & Sprinkle 2002,
Shenhav et al. 2013).
By motivation, in turn, we refer to the orienting and invigorating impact, on both behavior and
cognition, of prospective reward (both extrinsic reward such as money and intrinsic reward tied to
the satisfaction of self-relevant behavioral goals, and including negative rewards, i.e., punishments).
The study of motivation also often includes a focus on specific motivational content, that is, the
particular behavioral goals to which people tend to strive or the specific outcomes or activities
that they find rewarding or reinforcing.
These definitions put us in position to be more precise about the scope of the present review.
In particular, we aim to review empirical findings and theories relating to cases where motivational
context impacts the intensity or direction of control. A number of topics, though undoubtedly
related to the topic so stated, must fall outside the scope of our review, given limited space. These
include effects relating to mood or affect (Chiew & Braver 2011, Pessoa 2008, van Steenbergen
et al. 2012); effects of subliminal incentive cues (Bijleveld et al. 2009, Zedelius et al. 2014); the
impact of control on motivation itself, as seen in the setting of self-control (Hare & Rangel 2009,
Wagner et al. 2013); individual differences related to stable personality traits (Braem et al. 2013,
Jimura et al. 2010); and changes associated with development, aging (Ennis et al. 2013, Mather &
Carstensen 2005), and various clinical disorders, such as ADHD and schizophrenia (Marx et al.
2013, Strauss et al. 2013) (see sidebar Individual and Group Differences).
The remainder of the review is organized as follows. We begin, in the following section, by
briefly introducing a core set of behavioral observations relating to motivation and cognitive
control. We then compare and contrast the set of theoretical perspectives that have dominated in-
terpretations of these core observations, arguing here for the important role of neuroscience. Next,
we turn to a review of the neuroscience literature on motivation and control interactions, and we
close with a set of broader observations concerning the potential synergy between neuroscientific
and behavioral research.
CORE BEHAVIORAL PHENOMENA
Here we briefly highlight a set of key behavioral phenomena relating to the interface between
motivation and control. These can be organized under three headings, which we consider in turn:
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a b c
Cue$20
HouseHouse
2,000
42,000
0.75 s
26 s
1 s
0.2 s
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26 s
Target
No reward
Re
ac
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Reward
600
650
No reward
A
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90
Reward
95
100
Congruent
Neutral
Incongruent
Figure 1
The results of a selective attention task indicate that incentives enhance cognitive control. (a) Illustration of the conflict task used by
Padmala & Pessoa (2011). In a reward condition (shown here), an initial cue ($20) indicated that participants would be rewarded for fast
and correct performance. In another condition (not shown), the initial cue ($00) signaled that no reward was available. Following a
short delay, a stimulus containing a picture of a house or building was shown along with a task-irrelevant word. Subsequent to the
subjects response, the screen displayed the potential reward and total number of points accrued. (b) Mean reaction times from reward
and no-reward conditions in three stimulus conditions. (c) Mean response accuracy. Adapted with permission from Padmala & Pessoa
(2011).
(a) the impact of incentives on control function, (b) the role of motivational factors in the temporal
dynamics of control, and (c) the inherent cost of cognitive control.
The Relationship Between Incentives and Performance
Perhaps the most fundamental set of phenomena linking control with motivation involves effects
of incentives on the performance of cognitive tasks. The most common observation in this arena is
simple: The introduction or enlargement of performance-contingent rewards or punishments re-
sults in improvements in task performance, specifically attributable to enhanced executive control.
An illustrative example comes from Padmala & Pessoa (2011) (Figure 1). This study involved
a Stroop-like selective attention task, in which participants were to classify a presented image as
a building or house while ignoring an overlying incongruent, neutral, or congruent letter string
(HOUSE, BLDNG, or XXXXX). Critically, some trials began with a trial precue that indicated
an available monetary reward for fast, correct responses, whereas other trials offered no reward.
Enhanced performance was found on reward trials relative to nonreward trials, in terms of both
error rates and response times. More specifically, not only were interference effects (i.e., on in-
congruent distractor trials) smaller on reward trials, but so also were facilitation effects (i.e., on
congruent distractor trials). This latter finding indicates a relatively selective effect in attenuating
the influence of the irrelevant distractor on attention and responding. In other words, incentives
appeared to enhance cognitive control.
Similar incentive-induced performance improvements in control have been observed in a range
of other tasks, tapping other facets of executive function. Libby & Lipe (1992), for example,
reported improvements in a free recall task when participants were paid per correct item, reflecting
enhancements in the control of episodic memory encoding and retrieval (see also Adcock et al.
2006, Wittmann et al. 2005). Leotti & Wager (2010) observed improvements in a stop-signal
task, reflecting enhancements in response inhibition (see also Boehler et al. 2014, Padmala &
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Pessoa 2010). Comparable incentive-induced performance enhancements have been observed in
task switching (Aarts et al. 2010, Kleinsorge & Rinkenauer 2012, Nieuwenhuis & Monsell 2002),
working memory (Gilbert & Fiez 2004, Heitz et al. 2008, Jimura et al. 2010, Taylor et al. 2004),
context processing (Chiew & Braver 2013, Locke & Braver 2008), and visual search (Navalpakkam
et al. 2009).
Although all of these studies have observed enhancements in control with increasing incentives,
it is important to note that this relationship is not inviolable. The broader literature, and in
particular research in behavioral economics, has revealed a number of boundary conditions, beyond
which incentives may have little effect on cognitive performance and can even undermine it. First,
perhaps obviously, incentives are liable to trigger performance improvements primarily in task
settings where adjustments in the intensity or direction of control tend to be efficacious (Camerer
& Hogarth 1999). This excludes settings where task complexity outstrips the subjects skill set
(Bonner et al. 2000, Rydval 2011) or basic information-processing capacity (Awasthi & Pratt
1990, Rydval & Ortmann 2004). Second, paradoxical effects can arise when incentive magnitude
becomes either very small or very large. Small monetary rewards can undermine performance,
relative to no pay, if the payments are so small as to appear insulting (Gneezy & Rustichini
2000), and very large performance incentives can sometimes induce decrements in performance,
a phenomenon sometimes referred to as choking under pressure (Ariely et al. 2009, Baumeister
1984, Beilock 2011, Bonner et al. 2000, Camerer & Hogarth 1999, Mobbs et al. 2009, Samuels &
Whitecotton 2011, Worthy et al. 2009, Zedelius et al. 2011). Finally, although a wealth of research
shows that the investment of cognitive effort can be driven by internal sources of motivation (e.g.,
need for cognition or achievement motivation; Cacioppo et al. 1996, Deci & Ryan 2000, Nicholls
1984, Satterthwaite et al. 2012), some research has suggested the existence of an undermining
effect, according to which the introduction of extrinsic (e.g., monetary) rewards can reduce the
intrinsic motivation associated with a task (see Murayama et al. 2010).
Although such findings indicate that the relationship between incentives and control may not
be entirely straightforward, they nonetheless combine with the observations described previously
to show that the relationship is generally extremely strong.
The Dynamics of Control
Another set of key observations at the interface of motivation and cognitive control relates to the
temporal dynamics of control. In almost any task context, the intensity and direction of control
tend to vary over time, both in response to the details of the task and independent of them (Eichele
et al. 2008, Esterman et al. 2013, Weissman et al. 2006). Such fluctuations have been observed
to occur at both short and long timescales, and in both cases the relevant phenomena are tightly
connected with motivation.
On a short, trial-to-trial timescale, control is known to vary in response to ongoing performance
monitoring. One hallmark of such monitoring is an increase in reaction time on trials following
errors. Sturmer et al. (2011) observed an increase in such error adaptation in the context of
performance-contingent reward (see also Boksem et al. 2006). In the case of conflict monitoring,
a standard observation is that responses associated with high conflict tend to be followed by
performance reflecting an increased focus on task-relevant information or a shift toward a more
conservative response threshold. Conflict adjustment effects have also been observed to increase
in size following performance-contingent monetary rewards (Braem et al. 2012, Sturmer et al.
2011) as well as following performance-contingent punishments (losses) (Braem et al. 2013; for
review, see Dreisbach & Fischer 2012). One further connection between conflict and motivation
is the proposal that conflict may act as an aversive signal prompting task avoidance (Botvinick
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Ego depletion:
reduced performance
on a cognitive task
when that task is
performed after
another cognitively
demanding activity.
The term derives from
a theory attributing
the effect to depletion
of a metabolic resource
2007). Consistent with this, Lynn et al. (2012) found that experimental participants performing
Stroop and working-memory tasks reported an increase in the urge to quit immediately following
difficult, conflict-inducing trials.
Different effects linking control and motivation are seen at longer timescales. A key set of
findings arising from the social/personality literature, under the heading of the ego depletion
effect (for review, see Hagger et al. 2010), suggests that engagement in a control-demanding
activity is followed by reduced persistence and/or poorer performance on a second task, compared
to when that second task is preceded by a less demanding activity. Initial demonstrations focused on
a range of self-regulatory behaviors, such as following a diet, solving an anagram, and suppressing
emotional responses (Muraven & Baumeister 2000). More recent work has suggested that such
phenomena are present in standard experimental paradigms of cognitive control as well. For
example, in a study by Schmeichel (2007) two groups of participants first watched a video clip,
one under attention-distraction conditions (ignoring words shown at the bottom of the screen)
and the other not. Both groups then performed the same standard test of working memory span.
The attention-distraction group showed a subsequent reduction in measured working memory
capacity, relative to the control group. Similar findings were observed across a range of studies
using different cognitive control tasks (for both the first and second phase).
Traditionally, these types of depletion effects have been explained in terms of a structural
constraint on the capacity for sustained cognitive control, manifesting as a kind of refractory
period following the control exertion (Baumeister et al. 1998). However, recent work has adopted
an alternative perspective on the depletion effect, characterizing it as a motivational phenomenon.
Specifically, Inzlicht and colleagues (2014) have proposed that self-control exertion at Time 1
leads to the motivated switching of task priorities, wherein mental work becomes increasingly
aversive, making mental leisure increasingly attractive (p. 130; see also Inzlicht & Schmeichel
2012). This possibility is supported by a number of studies demonstrating that depletion can be
reduced or eliminated by performance incentives (e.g., Boksem et al. 2006, Inzlicht et al. 2014,
Muraven & Slessareva 2003).
The Cost of Control
The idea that cognitive control may be inherently costly or aversive has cropped up not only in the
depletion literature but also in connection with other topics in social cognition (Taylor 1981) and
behavioral economics (Bonner & Sprinkle 2002, Smith & Walker 1993, Wilcox 1993). In such
contexts, the cost of control has generally been introduced as an explanatory principle, serving to
account for other phenomena (e.g., problem-solving strategies or patterns of social judgment; for
review, see Kool et al. 2010). It has not been until recently that control costs have been postulated
as measurable phenomena in and of themselves and subjected to direct empirical test.
To this end, Kool and colleagues (2010) introduced a demand-selection paradigm, in which
participants chose repeatedly between two sources of task stimuli that demanded subtly different
levels of cognitive control. Across a number of task variations, Kool et al. (2010) observed a
consistent preference for the lower-demand source (see also Schouppe et al. 2014). Detailed
behavioral analyses confirmed that this preference was not wholly driven by error avoidance or
by minimization of time on task. Similarly, Westbrook et al. (2013) gained evidence for a cost of
control using an economic discounting paradigm. Here, participants were presented with a series
of choices between performing a low-demand task at a particular level of pay and performing a
more demanding task for a different wage. The payment offered for the high-demand task was
titrated until an indifference point was identified. Invariably, this indifference point occurred at
a point where the pay offered for the high-demand task was substantially higher than that for
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Cognitive energetics
theory (CET): a
model that draws
heavily on a force-field
metaphor to account
for the impact of
motivation on
cognitive control
the low-demand task, suggesting that participants had economically discounted the value of the
high-demand task (for related findings, see Dixon & Christoff 2012).
THREE THEORETICAL PERSPECTIVES
As is evident even from the brief overview we have just provided, the relationship between mo-
tivation and cognitive control has been considered in a strikingly diverse range of subfields of
behavioral research, including cognitive psychology, social and personality psychology, behav-
ioral economics, and research on both self-control and behavioral energetics.
Cutting across these fields, one finds three basic theoretical approaches to the relationship
between motivation and cognitive control. One utilizes a force-field metaphor. A second centers
on the notion of a limited-capacity resource. The third views the topic in terms of reward-based
decision making. Before entering into our review of the neuroscience literatureand to prepare
the ground for itwe consider these three theoretical approaches, weighing up their relative
strengths and weaknesses.
Force-Field Models
The use of force-field metaphors has been commonplace in motivational research since the time
of William James, with their influence strongly bolstered by the work of Kurt Lewin (see Atkinson
& Birch 1978) as well as by accounts inspired by physiology, such as drive theory (Berridge 2004,
Hull 1943, Miller 1951). The basic idea is to conceptualize action as the result of forces, akin to
physical forces, that attract an individual toward a goal or else impede progress toward that goal.
Action choice is then explained through an analysis of these driving forces and their interplay.
Carrying this tradition forward, some investigators have applied the force-field metaphor to
the problem of motivation in cognitive control. A recent and highly developed example of this
approach, arising from the social/personality perspective, is cognitive energetics theory (CET),
put forth by Kruglanski and colleagues (2012) (Figure 2a). Here, the energy invested in a cogni-
tive activity is determined by an effective driving force. This, in turn, is a function of two other
quantities: (a) a potential driving force that scales with both goal importance and a pool of available
mental resources, which sets an upper bound on the effective driving force; and (b) an opposing
restraining force, that is modulated both by task difficulty and by the individuals inclination to con-
serve resources. According to CET, the effective driving force rises to the level of the restraining
force, subject to a limit imposed by the potential driving force. Kruglanski and colleagues (2012)
apply this force-field model to a wide variety of phenomena ranging from biases in judgment to
incentive effects under fatigue.
Resource Models
The CET model reviewed above involves, as one of its ingredients, the idea that cognitive activity
consumes some form of resource and that the available quantity of this resource imposes a limit
on cognitive processing. This notion of a limited resource figures in a wide range of theories
addressing the relationship between motivation and cognitive control (see, e.g., Bijleveld et al.
2009, Persson et al. 2013, Pessoa 2009). However, it has been most strongly emphasized in an
influential set of models addressing the ego depletion phenomenon. According to the strength
model of self-control introduced by Baumeister and colleagues (e.g., Muraven & Baumeister 2000),
depletionthe decline in cognitive per