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Value-based choice model of self-control. The cumulative subjective value of each response option (middle column) is a weighted sum of value inputs based on the option's attributes (left column). Example attributes for a choice option include primary rewards, effort costs, social acceptance or rejection, and self-consistency and-verification. The subjective value integration is not strictly rational but instead is modulated by a number of choice " anomalies " such as the tendency to discount delayed gains. Value accumulates dynamically and stochastically across time until a threshold is reached, and attention can influence the accumulation process by altering the relevant attributes. The option with the greatest value when the threshold is reached or time runs out is enacted.
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Self-control is often conceived as a battle between “hot” impulsive processes and “cold” deliberative ones. Heeding the angel on one shoulder leads to success; following the demon on the other leads to failure. Self-control feels like a duality. What if that sensation is misleading, and, despite how they feel, self-control decisions are just like a...
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Self-control is often conceived as a battle between “hot” impulsive processes and “cold” deliberative ones. Heeding the angel on one shoulder leads to success; following the demon on the other leads to failure. Self-control feels like a duality. What if that sensation is misleading, and, despite how they feel, self-control decisions are just like a...
Citations
... 3). I then demonstrate that accounts that rely on dual-process models of self-control cannot account for the complex role of motivation and value-based decision making (Berkman et al., 2017) in self-control decisions (Sect. 4). ...
... As Berkman and colleagues remark: "Dual-process models collapse this universe of behaviors into a single process, inhibition, and, in so doing, ignore the diversity of pathways to self-control success" (Berkman et al., 2017, p. 423). Self-control, according to Berkman et al. (2017), is nothing more than a subset of valuebased decision-making. That is, in self-control decisions such as those involved with the attention economy-pitting scrolling through social media or hours of autoplay on YouTube versus cleaning the house or finally getting around to reading that book your friend lent you-the subject is selecting a course of action based on values, motivation, biases, the attentional field, etc. among several alternatives, like any other value-based decision that we make. ...
... Dual-systems theory oversimplifies the numerous considerations that are at play in these self-control, value-based decision-making processes. 8 As Berkman et al. (2017) note, the neuroscientific research on self-control may initially appear to support a dual-systems theory approach. The deliberative process of self-control choices are associated with increased activity in lateral prefrontal areas and less activity in areas that correspond to reward such as the ventral striatum and ventromedial prefrontal cortex (vmPFC) (Berkman et al., 2017). ...
In recent years, philosophers have identified a number of moral and psychological harms associated with the attention economy (Aylsworth and Castro, In Journal of Applied Philosophy 38:662–673, 2021; Castro and Pham, In Philosophers’ Imprint 20:1–13, 2020; Williams, In Stand out of our light: Freedom and resistance in the attention economy, Cambridge University Press, 2018). Missing from many of these accounts of the attention economy, however, is what exactly attention is. As a result of this neglect of the cognitive science of attention, many of these accounts are not empirically credible. They rely on oversimplified and unsophisticated accounts of not only attention, but selfcontrol, and addiction as well. Of note are accounts of the attention economy that rely on the ‘brain disease’ rhetoric of addiction and subsequent control failures (Aylsworth and Castro, In Journal of Applied Philosophy 38:662–673, 2021; Bhargava and Velasquez, In Business Ethics Quarterly 31:321–359, 2021), accounts that rely on a strict dichotomy of top-down vs. bottom-up attention (Williams, In Stand out of our light: Freedom and resistance in the attention economy, Cambridge University Press, 2018; Aylsworth and Castro, In Journal of Applied Philosophy 38:662–673, 2021), and accounts that construe attention as a limited resource (Williams, In Stand out of our light: Freedom and resistance in the attention economy, Cambridge University Press, 2018). Drawing on recent work from the neuroscience and psychology of attention, I demonstrate the shortcomings of these accounts and sketch a way forward for an empirically grounded account of the attention economy. These accounts tend to uphold strict dichotomies of voluntary control (e.g., compulsion versus choice, dual-process models of self-control, and top-down versus bottom-up) that cannot account for the complexities of attentional control, mental agency, and decision-making. As such, these empirically and conceptually impoverished accounts cannot adequately address the current so-called crisis of attention. To better understand the harms associated with the attention economy, we need an empirically responsible account of the nature and function of attention and mental agency.
... The researchers propose that the more identity-relevant a perception of behavior, the more likely functional these beliefs are, thus, the more successful self-regulation will occur. It is worth highlighting here that there is an overlap of brain regions involved in self-related and reward processing, which is in line with a suggestion that behavior or information that is self-or identity-relevant would have high subjective value (Berkman et al., 2017). ...
... The researchers propose that the more identity-relevant a perception of behavior, the more likely functional these beliefs are, thus, the more successful self-regulation will occur. It is worth highlighting here that there is an overlap of brain regions involved in self-related and reward processing, which is in line with a suggestion that behavior or information that is self-or identity-relevant would have high subjective value (Berkman et al., 2017). ...
... It does so through estimating the costs of different signal identities (i.e., targeted response) and the intensity of such signals in order to deploy the optimal control signal that maximizes reward. Thus, EVC is a particular instance of a value-based control system (Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017) but is distinguishable from other value-based controllers because it requires a unique computational and neural architecture to evaluate when the computational cost of deploying control is beneficial (Shenhav, 2017). Given its added specificity in formalizing relations between control and valuation computations in the brain, the EVC model offers a new suite of computationally precise, testable hypotheses. ...
Heightened risk taking in adolescence has long been attributed to valuation systems overwhelming the deployment of cognitive control. However, this explanation of why adolescents engage in risk taking is insufficient given increasing evidence that risk-taking behavior can be strategic and involve elevated cognitive control. We argue that applying the expected-value-of-control computational model to adolescent risk taking can clarify under what conditions control is elevated or diminished during risky decision-making. Through this lens, we review research examining when adolescent risk taking might be due to—rather than a failure of—effective cognitive control and suggest compelling ways to test such hypotheses. This effort can resolve when risk taking arises from an immaturity of the control system itself, as opposed to arising from differences in what adolescents value relative to adults. It can also identify promising avenues for channeling cognitive control toward adaptive outcomes in adolescence.
... In particular, OFC has demonstrated importance in both economic decisions and inhibition. Progress in this area promises to help shed light on important debates, such as how economic decisionmaking relates to self-control (Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2016;Shenhav, 2017). ...
Stopping, or inhibition, is a form of self-control that is a core element of flexible and adaptive behavior. Its neural origins remain unclear. Some views hold that inhibition decisions reflect the aggregation of widespread and diverse pieces of information, including information arising in ostensible core reward regions (i.e. outside the canonical executive system). We recorded activity of single neurons in the orbitofrontal cortex (OFC) of macaques, a region associated with economic decisions, and whose role in inhibition is debated. Subjects performed a classic inhibition task known as the stop signal task. Ensemble decoding analyses reveal a clear firing rate pattern that distinguishes successful from failed inhibition and that begins after the stop signal and before the stop signal reaction time (SSRT). We also found a different and orthogonal ensemble pattern that distinguishes successful from failed stopping before the beginning of the trial. These signals were distinct from, and orthogonal to, value encoding, which was also observed in these neurons. The timing of the early and late signals was, respectively, consistent with the idea that neuronal activity in OFC encodes inhibition both proactively and reactively.
... We believe that research on ego depletion and mental fatigue would greatly benefit from tackling this phenomenon from such a more motivational, value-based standpoint. Theoretical frameworks like the process model (Inzlicht et al., 2014), the mental labour theory (Kool & Botvinick, 2018), the expected value of control (Shenhav et al., 2013;Shenhav, Cohen, & Botvinick, 2016) or the model of value based choice of self-control (Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017) could be utilized to facilitate our understanding of how mental effort is allocated and is linked to subsequent performance. ...
Two independent lines of research propose that exertion of mental effort can impair subsequent performance due to ego depletion or mental fatigue. In this meta-analysis, we unite these research fields to facilitate a greater exchange between the two, to summarize the extant literature and to highlight open questions. We performed a meta-analysis to quantify the effect of ego-depletion and mental fatigue on subsequent physical endurance performance (42 independent effect sizes). We found that ego-depletion or mental fatigue leads to a reduction in subsequent physical endurance performance (ES = -0.506 [95% CI: -0.649, -0.369]) and that the duration of prior mental effort exertion did not predict the magnitude of subsequent performance impairment (r = -0.043). Further, analyses revealed that effects of prior mental exertion are more pronounced in subsequent tasks that use isolation tasks (e.g., handgrip; ES = -0.719 [-0.946, -0.493]) compared to whole-body endurance tasks (e.g. cycling; coefficient = 0.338 [0.057, 0.621]) and that the observed reduction in performance is higher when the person-situation fit is low (ES for high person-situation fit = -0.355 [-0.529, -0.181], coefficient for low person-situation fit = -0.336 [-0.599, -0.073]). Taken together, the aggregate of the published literature on ego depletion or mental fatigue indicates that prior mental exertion is detrimental to subsequent physical endurance performance. However, this analysis also highlights several open questions regarding the effects’ mechanisms and moderators. Particularly, the surprising finding that the duration of prior mental exertion seems to be unrelated to subsequent performance impairment needs to be addressed systematically.
... Computational models treat value signals as evidence for or against a particular choice. These value signals accumulate over time (hence, 'evidence accumulation' (EA) signals) until one of them crosses its response threshold, at which point the appropriate choice option is selected (see Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017). Decision modelling has been applied to delineate decision-making deficits and abnormalities in other psychological disorders (e.g., Moustafa et al., 2015;Pirrone, Dickinson, Gomez, Stafford, & Milne, 2017), and VBDM has been applied to the study of cognitive regulation of food choice (Tusche & Henderson, 2018). ...
... We revisit this important distinction later. Contemporary accounts of VBDM posit that EA for a given choice option is the result of a value integration process that incorporates diverse sources of information about the overall utility of that response option, including its anticipated positive and negative consequences, financial and opportunity cost, effort, and so on (Berkman, 2018;Berkman et al., 2017;Levy & Glimcher, 2012;Rangel, Camerer, & Montague, 2008), although this is contentious (e.g., Busemeyer et al., 2019). According to one account (Berkman et al., 2017), delay to receipt of the outcome(s) of a response option is incorporated into this value integration process, such that evidence accumulates most rapidly for outcomes that are available immediately. ...
... Contemporary accounts of VBDM posit that EA for a given choice option is the result of a value integration process that incorporates diverse sources of information about the overall utility of that response option, including its anticipated positive and negative consequences, financial and opportunity cost, effort, and so on (Berkman, 2018;Berkman et al., 2017;Levy & Glimcher, 2012;Rangel, Camerer, & Montague, 2008), although this is contentious (e.g., Busemeyer et al., 2019). According to one account (Berkman et al., 2017), delay to receipt of the outcome(s) of a response option is incorporated into this value integration process, such that evidence accumulates most rapidly for outcomes that are available immediately. This account of self-control as a form of value-based choice therefore provides a computational account for the effects of hyperbolic discounting on choice and preference reversals. ...
Behavioral economics provides a general framework to explain the shift in behavioral allocation from substance use to substance-free activities that characterizes recovery from addiction, but it does not attempt to explain the internal processes that prompt those behavioral changes. In this article we outline a novel analysis of addiction recovery based on computational work on value-based decision making (VBDM), which can explain how people with addiction are able to overcome the reinforcement pathologies and decision-making vulnerabilities that characterize the disorder. The central tenet of this account is that shifts in molar reinforcer preferences over time from substance use to substance-free activities can be attributed to changes in evidence accumulation rates and response thresholds in the context of choices involving substance use and substance-free alternatives. We discuss how this account can be reconciled with the established mechanisms of action of psychosocial interventions for addiction and demonstrate how it has the potential to empirically address longstanding debates regarding the nature of impairments to self-control in addiction. We also highlight conceptual and methodological issues that require careful consideration in translating VBDM to addiction and recovery.
... Computational models treat value signals as evidence for or against a particular choice. These value signals accumulate over time (hence, 'evidence accumulation' (EA) signals) until one of them crosses its response threshold, at which point the appropriate choice option is selected (see Berkman, Hutcherson, Livingston, Kahn, & Inzlicht, 2017). Decision modelling has been applied to delineate decision-making deficits and abnormalities in other psychological disorders (e.g., Moustafa et al., 2015;Pirrone, Dickinson, Gomez, Stafford, & Milne, 2017), and VBDM has been applied to the study of cognitive regulation of food choice (Tusche & Henderson, 2018). ...
... We revisit this important distinction later. Contemporary accounts of VBDM posit that EA for a given choice option is the result of a value integration process that incorporates diverse sources of information about the overall utility of that response option, including its anticipated positive and negative consequences, financial and opportunity cost, effort, and so on (Berkman, 2018;Berkman et al., 2017;Levy & Glimcher, 2012;Rangel, Camerer, & Montague, 2008), although this is contentious (e.g., Busemeyer et al., 2019). According to one account (Berkman et al., 2017), delay to receipt of the outcome(s) of a response option is incorporated into this value integration process, such that evidence accumulates most rapidly for outcomes that are available immediately. ...
... Contemporary accounts of VBDM posit that EA for a given choice option is the result of a value integration process that incorporates diverse sources of information about the overall utility of that response option, including its anticipated positive and negative consequences, financial and opportunity cost, effort, and so on (Berkman, 2018;Berkman et al., 2017;Levy & Glimcher, 2012;Rangel, Camerer, & Montague, 2008), although this is contentious (e.g., Busemeyer et al., 2019). According to one account (Berkman et al., 2017), delay to receipt of the outcome(s) of a response option is incorporated into this value integration process, such that evidence accumulates most rapidly for outcomes that are available immediately. This account of self-control as a form of value-based choice therefore provides a computational account for the effects of hyperbolic discounting on choice and preference reversals. ...
Manuscript accepted for publication in Psychology of Addictive Behaviors, 30th August 2019
... [6][7][8][9][10]). Some other definitions include strategies that avoid tempting contexts; my definition treats these as outside the bounds of self- controlled behaviour [11,12]. Other scholars have considered that choices appearing to reflect poor self-control may have adaptive outcomes [13][14][15][16][17]. ...
... That is, it simply allows for a restatement of the core mystery of self-control. Another important view sees self-control as an economic decision-a comparison between two differently valued options-that is not different in any substantial way from other economic decisions ( [12]; see also [28][29][30]). While self- control decisions clearly are a type of economic decision, they are of a special type. ...
... Recent work in the field of self-control and in cognition more broadly has challenged the two-systems view on empiri- cal, theoretical and neuroscientific grounds [12,28,29,57,136,137]. Nonetheless, taking a cognitive control perspective on self-control suggests that this view has at least a few merits. ...
Self-control refers to the ability to deliberately reject tempting options and instead select ones that produce greater long-term benefits. Although some apparent failures of self-control are, on closer inspection, reward maximizing, at least some self-control failures are clearly disadvantageous and non-strategic. The existence of poor self-control presents an important evolutionary puzzle because there is no obvious reason why good self-control should be more costly than poor self-control. After all, a rock is infinitely patient. I propose that self-control failures result from cases in which well-learned (and thus routinized) decision-making strategies yield suboptimal choices. These mappings persist in the decision-makers’ repertoire because they result from learning processes that are adaptive in the broader context, either on the timescale of learning or of evolution. Self-control, then, is a form of cognitive control and the subjective feeling of effort likely reflects the true costs of cognitive control. Poor self-control, in this view, is ultimately a result of bounded optimality.
This article is part of the theme issue ‘Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications.
... These results further show that trait self-control is positively and negatively associated with exhaustion experiences dependent on various types of motivation, rather than a sole lack of energy resources, confirming the ego depletion effect Friese et al., 2018). Autonomous motivation energizes athletes' self-control competencies, for example due to the enhanced subjective value of athletes' goal attainment, thus confirm its' beneficial characteristics postulated in the SDT Ryan and Deci, 2000;Berkman et al., 2017). Autonomously motivated, as opposed to controlled motivated athletes, are likely to act in accordance with their values and needs, and unconflicted control their actions in a more flexible manner ). ...
... Is it possible that self-control resembles a muscle, which will be strengthened by repeated exercise ( ? Does athletes' self-control increase by providing an autonomy-supportive climate that enhances autonomous motivation (e.g., Berkman et al., 2017)? Is it possible to increase athletes' self-control strength through interventions where athletes and researchers discuss and work through important self-control processes, such as behavioral and emotional responses, self-management, enhanced focus, as well as thought and impulse control (e.g., see Dubuc-Charbonneau and Durand-Bush, 2015)? ...
The depletion of self-control competencies has been explained by an external shift in motivation, and recent research has emphasized that controlled types of motivation and self-control competencies are positively associated with exhaustion in youth athletes. Using the self-determination theory (SDT) and self-control theories, this study examined associations between athletes' motivation, self-control competencies, and exhaustion experiences throughout a competitive season. A total of 321 winter sport youth athletes (173 males, 98 females, and 50 unknown gender; aged 16 to 20 years, M = 17.98, SD = 0.89) participated in this 10-week longitudinal study, including three time points. Using Bayesian structural equation modeling, associations between athletes' reported level of motivation regulations, self-control, and exhaustion throughout their competitive season were examined in two mediation models. Constructs were associated in a conceptual and consistent manner. Simple mediation models showed credible indirect and direct effects of motivation on exhaustion via self-control within amotivation, and intrinsic, integrated, identified, and external regulation analyses. These credible effects were not replicated in the focused mediation model, when controlling for self-control and exhaustion autoregressive effects. However, direction of effects in both models was consistent and congruent. Findings consistently supported the interplay between motivation and exhaustion via self-control in youth athletes over an important competition period of the year. Autonomous and controlled motivation interacted with self-control and, respectively, predicted perceived exhaustion negatively and positively. Thus, autonomous self-control motives are important in preventing negative sport participation development over time. However, simple and focused mediation models showed different results, suggesting a necessity for accurate considerations of analytical methods chosen to investigate longitudinal mediation. Specifically, future studies need to carefully consider the time interval between measurement time points when investigating changes in dynamic psychological constructs, and include autoregressive longitudinal effects in order to predict change in levels of the outcome over time.
