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The decision to engage cognitive control is driven by expected reward-value: neural and behavioral evidence.

ABSTRACT: Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card Sorting Task, Go/No-Go task) and created novel 'free-choice' versions in which human subjects were free to select an automatic, pre-potent action, or an action requiring rule-based cognitive control, and earned varying amounts of money based on their choices. Our findings demonstrated that subjects' decision to engage cognitive control was driven by an explicit representation of monetary rewards expected to be obtained from rule-use. Subjects rarely engaged cognitive control when the expected outcome was of equal or lesser value as compared to the value of the automatic response, but frequently engaged cognitive control when it was expected to yield a larger monetary outcome. Additionally, we exploited fMRI-adaptation to show that the lateral prefrontal cortex (LPFC) represents associations between rules and expected reward outcomes. Together, these findings suggest that individuals are more likely to act in a reflective, rule-based manner when they expect that it will result in a desired outcome. Thus, choosing to exert cognitive control is not simply a matter of reason and willpower, but rather, conforms to standard mechanisms of value-based decision making. Finally, in contrast to current models of LPFC function, our results suggest that the LPFC plays a direct role in representing motivational incentives.

SUBMITTER: Dixon ML

PROVIDER: S-EPMC3526643 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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The decision to engage cognitive control is driven by expected reward-value: neural and behavioral evidence.

Dixon Matthew L ML Christoff Kalina K

PloS one 20121219 12

Cognitive control is a fundamental skill reflecting the active use of task-rules to guide behavior and suppress inappropriate automatic responses. Prior work has traditionally used paradigms in which subjects are told when to engage cognitive control. Thus, surprisingly little is known about the factors that influence individuals' initial decision of whether or not to act in a reflective, rule-based manner. To examine this, we took three classic cognitive control tasks (Stroop, Wisconsin Card So ...[more]

PMID: 23284730

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Project description:Negative symptoms are a core feature of schizophrenia, but their pathogenesis remains unclear. Negative symptoms are defined by the absence of normal function. However, there must be a productive mechanism that leads to this absence.To test a reinforcement learning account suggesting that negative symptoms result from a failure in the representation of the expected value of rewards coupled with preserved loss-avoidance learning.Participants performed a probabilistic reinforcement learning paradigm involving stimulus pairs in which choices resulted in reward or in loss avoidance. Following training, participants indicated their valuation of the stimuli in a transfer test phase. Computational modeling was used to distinguish between alternative accounts of the data.A tertiary care research outpatient clinic.In total, 47 clinically stable patients with a diagnosis of schizophrenia or schizoaffective disorder and 28 healthy volunteers participated in the study. Patients were divided into a high-negative symptom group and a low-negative symptom group.The number of choices leading to reward or loss avoidance, as well as performance in the transfer test phase. Quantitative fits from 3 different models were examined.Patients in the high-negative symptom group demonstrated impaired learning from rewards but intact loss-avoidance learning and failed to distinguish rewarding stimuli from loss-avoiding stimuli in the transfer test phase. Model fits revealed that patients in the high-negative symptom group were better characterized by an "actor-critic" model, learning stimulus-response associations, whereas control subjects and patients in the low-negative symptom group incorporated expected value of their actions ("Q learning") into the selection process.Negative symptoms in schizophrenia are associated with a specific reinforcement learning abnormality: patients with high-negative symptoms do not represent the expected value of rewards when making decisions but learn to avoid punishments through the use of prediction errors. This computational framework offers the potential to understand negative symptoms at a mechanistic level.

Dataset Information

The decision to engage cognitive control is driven by expected reward-value: neural and behavioral evidence.

Publications

The decision to engage cognitive control is driven by expected reward-value: neural and behavioral evidence.

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