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Dissociation and integration of outcome and state uncertainty signals in cognitive control.

Signals related to uncertainty are frequently observed in regions of the cognitive control network, including anterior cingulate/medial prefrontal cortex (ACC/mPFC), dorsolateral prefrontal cortex (dlPFC), and anterior insular cortex. Uncertainty generally refers to conditions in which decision vari...

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Published in:Cognitive, Affective & Behavioral Neuroscience Vol. 23; no. 3; pp. 691 - 705
Main Authors: Alexander, William H., Deraeve, James, Vassena, Eliana
Format: Journal Article
Published: Springer Nature Jun2023
Online Access:View this record in EBSCOhost
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      dt: Jun2023
      vid: 23
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      pub: Springer Nature
      place: New York, New York
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        10.3758/s13415-023-01091-7
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        atl: Dissociation and integration of outcome and state uncertainty signals in cognitive control.
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          Alexander, William H.
          Deraeve, James
          Vassena, Eliana
        affil: Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, FL, USA
      sug:
      ab: Signals related to uncertainty are frequently observed in regions of the cognitive control network, including anterior cingulate/medial prefrontal cortex (ACC/mPFC), dorsolateral prefrontal cortex (dlPFC), and anterior insular cortex. Uncertainty generally refers to conditions in which decision variables may assume multiple possible values and can arise at multiple points in the perception-action cycle, including sensory input, inferred states of the environment, and the consequences of actions. These sources of uncertainty are frequently correlated: noisy input can lead to unreliable estimates of the state of the environment, with consequential influences on action selection. Given this correlation amongst various sources of uncertainty, dissociating the neural structures underlying their estimation presents an ongoing issue: a region associated with uncertainty related to outcomes may estimate outcome uncertainty itself, or it may reflect a cascade effect of state uncertainty on outcome estimates. In this study, we derive signals of state and outcome uncertainty from mathematical models of risk and observe regions in the cognitive control network whose activity is best explained by signals related to state uncertainty (anterior insula), outcome uncertainty (dlPFC), as well as regions that appear to integrate the two (ACC/mPFC).
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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