Mutual inclusivity improves decision-making by smoothing out choice's competitive edge.

Decisions form a central bottleneck to most tasks, one that people often experience as costly. Past work proposes mitigating those costs by lowering one's threshold for deciding. Here, we test an alternative solution, one that targets the basis for most choice costs: that choosing one option sacrifices others (mutual exclusivity). Across 5 studies (N = 462), we test whether this tension can be relieved by framing choices as inclusive (allowing selection of more than one option, as in buffets). We find that inclusivity makes choices more efficient, by selectively reducing competition between potential responses as participants accumulate information for each of their options. Inclusivity also made participants feel less conflicted, especially when they couldn't decide which good option to keep or which bad option to get rid of. These inclusivity benefits were also distinguishable from the effects of manipulating decision threshold (increased urgency), which improved choices but not experiences thereof.

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account.

A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require caution. Adapting to these changing goals require corresponding adjustments in cognitive control (e.g., levels of attention, response thresholds). However, adjusting our control to meet new goals comes at a cost: we are better at achieving a goal in isolation than when transitioning between goals. The source of these control adjustment costs remains poorly understood, and the bulk of our understanding of such costs comes from settings in which participants transition between discrete task sets, rather than performance goals. Across four experiments, we show that adjustments in continuous control states incur a performance cost, and that a dynamical systems model can explain the source of these costs. Participants performed a single cognitively demanding task under varying performance goals (e.g., to be fast or to be accurate). We modeled control allocation to include a dynamic process of adjusting from one's current control state to a target state for a given performance goal. By incorporating inertia into this adjustment process, our model accounts for our empirical findings that people under-shoot their target control state more (i.e., exhibit larger adjustment costs) when (a) goals switch rather than remain fixed over a block (Study 1); (b) target control states are more distant from one another (Study 2); (c) less time is given to adjust to the new goal (Study 3); and (d) when anticipating having to switch goals more frequently (Study 4). Our findings characterize the costs of adjusting control to meet changing goals, and show that these costs can emerge directly from cognitive control dynamics. In so doing, they shed new light on the sources of and constraints on flexibility in human goal-directed behavior.

Make or break: The influence of expected challenges and rewards on the motivation and experience associated with cognitive effort exertion.

Challenging goals can induce harder work but also greater stress, in turn potentially undermining goal achievement. We sought to examine how mental effort and subjective experiences thereof interact as a function of challenge level and the size of the incentives at stake. Participants performed a task that rewarded individual units of effort investment (correctly performed Stroop trials) but only if they met a threshold number of correct trials within a fixed time interval (challenge level). We varied this challenge level (Study 1, N = 40), and the rewards at stake (Study 2, N = 79), and measured variability in task performance and self-reported affect across task intervals. Greater challenge and higher rewards facilitated greater effort investment but also induced greater stress, while higher rewards (but less challenge) simultaneously induced greater positive affect. Current findings further our understanding of task demands and incentives on mental effort exertion and wellbeing.

Motivational context determines the impact of aversive outcomes on mental effort allocation.

It is well known that people will exert effort on a task if sufficiently motivated, but how they distribute these efforts across different strategies (e.g., efficiency vs. caution) remains uncertain. Past work has shown that people invest effort differently for potential positive outcomes (rewards) versus potential negative outcomes (penalties). However, this research failed to account for differences in the context in which negative outcomes motivate someone - either as punishment or reinforcement. It is therefore unclear whether effort profiles differ as a function of outcome valence, motivational context, or both. Using computational modeling and our novel Multi-Incentive Control Task, we show that the influence of aversive outcomes on one's effort profile is entirely determined by their motivational context. Participants (N:91) favored increased caution in response to larger penalties for incorrect responses, and favored increased efficiency in response to larger reinforcement for correct responses, whether positively or negatively incentivized.

Cognitive Control as a Multivariate Optimization Problem.

A hallmark of adaptation in humans and other animals is our ability to control how we think and behave across different settings. Research has characterized the various forms cognitive control can take-including enhancement of goal-relevant information, suppression of goal-irrelevant information, and overall inhibition of potential responses-and has identified computations and neural circuits that underpin this multitude of control types. Studies have also identified a wide range of situations that elicit adjustments in control allocation (e.g., those eliciting signals indicating an error or increased processing conflict), but the rules governing when a given situation will give rise to a given control adjustment remain poorly understood. Significant progress has recently been made on this front by casting the allocation of control as a decision-making problem. This approach has developed unifying and normative models that prescribe when and how a change in incentives and task demands will result in changes in a given form of control. Despite their successes, these models, and the experiments that have been developed to test them, have yet to face their greatest challenge: deciding how to select among the multiplicity of configurations that control can take at any given time. Here, we will lay out the complexities of the inverse problem inherent to cognitive control allocation, and their close parallels to inverse problems within motor control (e.g., choosing between redundant limb movements). We discuss existing solutions to motor control's inverse problems drawn from optimal control theory, which have proposed that effort costs act to regularize actions and transform motor planning into a well-posed problem. These same principles may help shed light on how our brains optimize over complex control configuration, while providing a new normative perspective on the origins of mental effort.

Aversive motivation and cognitive control.

Aversive motivation plays a prominent role in driving individuals to exert cognitive control. However, the complexity of behavioral responses attributed to aversive incentives creates significant challenges for developing a clear understanding of the neural mechanisms of this motivation-control interaction. We review the animal learning, systems neuroscience, and computational literatures to highlight the importance of experimental paradigms that incorporate both motivational context manipulations and mixed motivational components (e.g., bundling of appetitive and aversive incentives). Specifically, we postulate that to understand aversive incentive effects on cognitive control allocation, a critical contextual factor is whether such incentives are associated with negative reinforcement or punishment. We further illustrate how the inclusion of mixed motivational components in experimental paradigms enables increased precision in the measurement of aversive influences on cognitive control. A sharpened experimental and theoretical focus regarding the manipulation and assessment of distinct motivational dimensions promises to advance understanding of the neural, monoaminergic, and computational mechanisms that underlie the interaction of motivation and cognitive control.

Dissociable influences of reward and punishment on adaptive cognitive control.

To invest effort into any cognitive task, people must be sufficiently motivated. Whereas prior research has focused primarily on how the cognitive control required to complete these tasks is motivated by the potential rewards for success, it is also known that control investment can be equally motivated by the potential negative consequence for failure. Previous theoretical and experimental work has yet to examine how positive and negative incentives differentially influence the manner and intensity with which people allocate control. Here, we develop and test a normative model of control allocation under conditions of varying positive and negative performance incentives. Our model predicts, and our empirical findings confirm, that rewards for success and punishment for failure should differentially influence adjustments to the evidence accumulation rate versus response threshold, respectively. This dissociation further enabled us to infer how motivated a given person was by the consequences of success versus failure.

Association of functioning and quality of life with objective and subjective measures of sleep and biological rhythms in major depressive and bipolar disorder.

OBJECTIVE: Disruptions in biological rhythms and sleep are a core aspect of mood disorders, with sleep and rhythm changes frequently occurring prior to and during mood episodes. Wrist-worn actigraphs are increasingly utilized to measure ambulatory activity rhythm and sleep patterns. METHODS: A comprehensive study using subjective and objective measures of sleep and biological rhythms was conducted in 111 participants (40 healthy volunteers [HC], 38 with major depressive disorder [MDD] and 33 with bipolar disorder [BD]). Participants completed 15-day actigraphy and first-morning urine samples to measure 6-sulfatoxymelatonin levels. Sleep and biological rhythm questionnaires were administered: Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN), Munich Chronotype Questionnaire (MCTQ), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Actigraph data were analyzed for sleep and daily activity rhythms, light exposure and likelihood of transitioning between rest and activity states. RESULTS: Mood groups had worse subjective sleep quality (PSQI) and biological rhythm disruption (BRIAN) and higher objective mean nighttime activity than controls. Participants with BD had longer total sleep time, higher circadian quotient and lower 6-sulfatoxymelatonin levels than HC group. The MDD group had longer sleep onset latency and higher daytime probability of transitioning from rest to activity than HCs. Mood groups displayed later mean timing of light exposure. Multiple linear regression analysis with BRIAN scores, circadian quotient, mean nighttime activity during rest and daytime probability of transitioning from activity to rest explained 43% of variance in quality-of-life scores. BRIAN scores, total sleep time and probability of transitioning from activity to rest explained 52% of variance in functioning (all p < 0.05). CONCLUSIONS: Disruption in biological rhythms is associated with poorer functioning and quality of life in bipolar and MDD. Investigating biological rhythms and sleep using actigraphy variables, urinary 6-sulfatoxymelatonin and subjective measures provide evidence of widespread sleep and circadian system disruptions in mood disorders.

Performance of the biological rhythms interview for assessment in neuropsychiatry: An item response theory and actigraphy analysis.

BACKGROUND: Biological rhythm disturbances are widely associated with the pathophysiology of mood disorders. The Biological Rhythms Interview for Assessment in Neuropsychiatry (BRIAN) is a self-report that indexes rhythm disturbance in sleep, activity, social and eating patterns. The aim of this study was to perform an Item Response Theory (IRT) analysis of the BRIAN and investigate its associations with objective sleep and rhythm disturbance measures. METHODS: 103 subjects (31 bipolar, 32 major depression and 40 healthy volunteers) wore an actiwatch for fifteen days, and completed a first morning urine sample and the BRIAN on day 15. IRT analysis assessed individual BRIAN items and their relationship to total score. Individual actiwatch records were processed to produce a sequence of transitions between rest/activity, and a likelihood of transitioning between states was calculated to investigate sleep-wake dynamics. Cosinor analysis produced daily activity rhythms (DARs). Spearman correlations were used to assess the association between sleep/DAR variables and the BRIAN. RESULTS: IRT analyses showed that 11 of 18 BRIAN items displayed a high level of discrimination between item options across a range of BRIAN total scores. Total BRIAN score correlated with wake after sleep onset, total activity count during sleep, and urinary 6-sulphatoxymelatonin. BRIAN Activity domain correlated with the daytime transition probability from rest to activity. LIMITATIONS: The sample size may have been underpowered for the graded-response model employed in IRT. The study lacked an objective comparison for BRIAN eating and social domain. CONCLUSION: The present study reveals the BRIAN displays promising external validity compared to objective parameters of circadian rhythmicity.