Abstract The capacity for self-control is critical to adaptive functioning, yet our knowledge of the underlying processes and mechanisms is presently only inchoate. Theoretical work in economics has suggested a model of self-control centering on two key assumptions: (1) a division within the decision-maker between two ‘selves’ with differing preferences; (2) the idea that self-control is intrinsically costly. Neuroscience has recently generated findings supporting the ‘dual-self’ assumption. The idea of self-control costs, in contrast, has remained speculative. We report the first independent evidence for self-control costs. Through a neuroimaging meta-analysis, we establish an anatomical link between self-control and the registration of cognitive effort costs. This link predicts that individuals who strongly avoid cognitive demand should also display poor self-control. To test this, we conducted a behavioral experiment leveraging a measure of demand avoidance along with two measures of self-control. The results obtained provide clear support for the idea of self-control costs.

Citation: Kool W, McGuire JT, Wang GJ, Botvinick MM (2013) Neural and Behavioral Evidence for an Intrinsic Cost of Self-Control. PLoS ONE 8(8): e72626. https://doi.org/10.1371/journal.pone.0072626 Editor: Sarah Frances Brosnan, Georgia State University, United States of America Received: April 9, 2013; Accepted: July 10, 2013; Published: August 27, 2013 Copyright: © 2013 Kool et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was completed with support from the National Institute of Mental Health (grant MH062196) and the Templeton Foundation (grant 36751). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Materials and Methods Participants Fifty students from the Princeton University (31 females, 18–24 years) participated, providing informed consent and receiving $10 plus whatever bonus was received in the ITC task following procedures approved by the Princeton University Institutional Review Board. Procedure All participants performed an ITC task and the DST, with order counterbalanced across participants, followed by completion of the Self-Control Scale [3]. Both the ITC task and the DST were programmed using Matlab and the Psychophysics Toolbox [23], [24]. In the ITC task, all participants were presented with an identical sequence of 100 unique choice trials. In each trial, participants chose between two monetary offers, one involving a smaller sum to be delivered immediately following the experiment, the other a larger sum to be conferred after a specified delay. To construct the offer sequence, immediate rewards were sampled from a normal distribution with mean $8 and standard deviation of $2 (range $3.01–$12.85). The delayed option was between 5% and 50% larger than the immediate option (range $3.93–$16.69) and was available after a period ranging between two and ten weeks, in one-week increments. Participants were (truthfully) informed that one of their selections, from a randomly chosen trial, would be awarded as an Amazon gift card at the selected time-point. The DST was drawn without modification from Kool et al. [19]. The task was divided into eight runs of 75 trials, each featuring a visually contrasting pair of choice targets (Figure 2). The position and appearance of the targets remained fixed within each run but varied across runs, always appearing along the perimeter of a virtual circle, and separated by an angular distance of 45 degrees. Participants were told they were free to sample from either target, but that if they developed a preference they should feel free select one more than the other. Selection of a target revealed an Arabic numeral. Depending on the color of the numeral (blue or yellow), the participant used a key-press to render either a parity (odd/even) judgment or magnitude (less/greater than five) judgment. During each run, the numerals in one (high-demand) target switched color relative to the previous trial – requiring an effortful stimulus-response remapping – with a probability of 0.9. In the other (low-demand) target, colors switched with a probability of 0.1. Participants’ demand-avoidance score was computed as the proportion of trials on which the low-demand cue was selected. The Self-Control Scale [3] is a 36-item questionnaire that measures self-regulatory behavior throughout four domains: thoughts, emotions, impulses and performance. It comprises a list of statements (e.g., ‘I am always on time’), whose self-relevance participants rate using a five-point scale.

Discussion In sum, the results of this individual-differences study confirmed an inverse relationship between cognitive demand avoidance and the efficacy of self-control. Together with the finding that cognitive effort costs and self-control relate to common areas within dlPFC, this result lends considerable support to the idea that the exertion of self-control carries intrinsic subjective costs. As discussed in the Introduction, the cost of self-control plays a pivotal role in the influential dual-self model that has emerged from economics, empowering that model to account for a wide range of behavioral effects [5]–[7]. The present findings bolster the psychological plausibility of the dual-self model, providing empirical confirmation for one of its key stipulations, that self-control carries an intrinsic cost. The precise characterization of control costs has in fact taken two subtly different forms in economic dual-self models. In some models, a cost attaches directly to the exertion of top-down control [5]; others frame the cost of control as an opportunity cost, arising when self-control requires the short-term ‘self’ to forego tempting immediate reward [25]. These two possibilities are difficult to differentiate empirically, since control demands will generally increase with temptation [17]. However, the present results offer differential support for the idea that self-control exertion carries an inherent cost, since this view (but not the opportunity-cost alternative) provides an explanation for why self-control should correlate with demand avoidance in the DST. By validating the notion of self-control costs, our findings also indirectly support the other key tenet of the economic model, the idea that choice is governed by two ‘selves’ with differing preferences, and that self-control reflects the ascendency of one of these selves – the one with more patient preferences – over the other3. This notion, and the dual modes of valuation that it implies, is not universal among formal models of self-control. Indeed, theories involving a single, fixed utility function remain widely considered4, especially in work on ITC [14], [15]. However, in contrast to the dual-self framework, such a perspective provides no obvious entrypoint for effort costs, since it includes no distinct self-control function to which such costs might attach. In addition to its longstanding role in economic models, the notion of self-control costs has very recently begun to appear in psychological theories of self-control failure and ‘ego depletion.’ For many years, work in this area has been dominated by the idea that self-control draws on a limited resource – possibly glucose [26], [27] – and that impulsive behavior arises when this resource is depleted, making the exertion of self-control impossible [28], [29]. Over time, however, accumulating empirical observations have placed an increasing strain on the resource account [30]–[32], contributing to an emerging trend toward motivation-based theories of self-control failure. Under this emerging perspective, self-control failures arise not from an inability to self-regulate, but from a decision not to do so, based on a cost-benefit analysis that takes into account the intrinsic cost of self-control [31], [32]. The present results provide additional encouragement for this reformulation, inviting further research into the details and dynamics of the relevant cost-benefit analyses [33]. Together with its implications for psychological and economic models, the present findings add to recent neuroscientific evidence implicating the dlPFC in self-control and ITC. Despite the relevant findings reviewed earlier, some important negative results have left room for uncertainty, especially in the case of ITC [14], [15]. Our results indirectly support the relevance of dlPFC, by providing evidence that self-control and ITC are associated with effort costs, costs that the dlPFC has been shown to index [21]. At a broader level, the present findings establish a new bridge between neuroscientific research on self-control and parallel research on effort costs and demand avoidance, prompting further investigations into the relationship between these two domains. For example, future work could employ fMRI or transcranial magnetic stimulation methods to more directly test for the role of dlPFC in representing effort costs during self-control. One possibility would be to measure individual differences in dlPFC sensitivity to cognitive effort and predict individual differences in behavior and prefrontal activity during self-control (and vice versa). In addition, the current results suggest that other forms of decision making that depend on activity in dlPFC may show similar sensitivities to individual differences in effort costs. For example, one might predict that an aversion to cognitive effort predicts less utilitarian moral reasoning [34] and increased reliance on habit or model-free reinforcement learning [35], since these cognitive functions are dependent on computation implemented by the dlPFC. Notes This effect appeared in McClure et al. [9] as a statistical trend. Nevertheless, that paper concluded that activity within a network including the dlPFC “is associated with choice, such that lesser activity…predict[s] a greater likelihood of choosing the sooner, lesser option” (p. 5801). According to one view, stemming from McClure et al. [10] the dlPFC participates in one of two competing systems, each of which carries its own representation of choice value. Under a contrasting account stemming from Hare et al. [8], the brain carries only a single representation of value, but one that is subject to top-down modulation by the dlPFC. Despite the important differences between these theories as accounts of neural implementation, it is important to note that they are both entirely consistent with the more abstract dual-self framework. Under both neuroscientific theories, self-control depends upon the activity of a distinct mechanism, which overrides the behavioral preferences arising from a second, more basic, system. This scenario aligns precisely with the dual-self model, regardless of whether the override operation occurs through competition or through modulation. As explained in Note 2, this idea is equally consistent with neuroscientific accounts positing direct competition between independent value representations [10], or top-down modulation of a single representation of value [8]. The single-utility view is commonly attributed to Kable and Glimcher [14], [15], and their proposals can be so interpreted. However, as Hare and colleagues [8] noted, the model advanced by Kable and Glimcher [15] does not explicitly rule out top-down modulation of value representations. In fact, Kable and Glimcher [14] explicitly left open the possibility that top-down modulation, perhaps driven by dlPFC, might play a role. Some caution is thus required in framing the debate.

Acknowledgments Thanks to Samuel McClure and Todd Hare for access to neuroimaging data and John M White for useful discussions regarding experimental design. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.

Author Contributions Conceived and designed the experiments: WK GJW MMB. Performed the experiments: WK GJW. Analyzed the data: WK JTM. Wrote the paper: WK JTM MMB.