Journal
FRONTIERS IN HUMAN NEUROSCIENCE
Volume 7, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnhum.2013.00508
Keywords
emotion; inhibitory control; Bayesian modeling; ideal observer model
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Funding
- NIMH NIH HHS [T32 MH018399] Funding Source: Medline
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The influence of emotion on higher-order cognitive functions, such as attention allocation, planning, and decision-making, is a growing area of research with important clinical applications. In this review, we provide a computational framework to conceptualize emotional influences on inhibitory control, an important building block of executive functioning. We first summarize current neuro-cognitive models of inhibitory control and show how Bayesian ideal observer model scan help reframe inhibitory control as a dynamic decision making process. Finally, we propose a Bayesian framework to study emotional influences on inhibitory control, providing several hypotheses that may be useful to conceptualize inhibitory control biases in mental illness such as depression and anxiety. To do so, we consider the neurocognitive literature pertaining to how affective states can bias inhibitory control, with particular attention to how valence and arousal may independently impact inhibitory control by biasing probabilistic representations of information (i.e., beliefs) and valuation processes (e.g., speed-error tradeoffs).
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