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      Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias

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      a , 1 , 2 , 1 , b , 1 , 2 , 3
      Nature Communications
      Nature Publishing Group

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          Abstract

          While judging their sensory environments, decision-makers seem to use the uncertainty about their choices to guide adjustments of their subsequent behaviour. One possible source of these behavioural adjustments is arousal: decision uncertainty might drive the brain's arousal systems, which control global brain state and might thereby shape subsequent decision-making. Here, we measure pupil diameter, a proxy for central arousal state, in human observers performing a perceptual choice task of varying difficulty. Pupil dilation, after choice but before external feedback, reflects three hallmark signatures of decision uncertainty derived from a computational model. This increase in pupil-linked arousal boosts observers' tendency to alternate their choice on the subsequent trial. We conclude that decision uncertainty drives rapid changes in pupil-linked arousal state, which shape the serial correlation structure of ongoing choice behaviour.

          Abstract

          Decision uncertainty is often associated with higher order cognition and can impact choices. Here the authors show that post-decision pupil dilation scales with uncertainty and predicts a change in upcoming choice patterns.

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          Most cited references33

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          Conflict monitoring and cognitive control.

          A neglected question regarding cognitive control is how control processes might detect situations calling for their involvement. The authors propose here that the demand for control may be evaluated in part by monitoring for conflicts in information processing. This hypothesis is supported by data concerning the anterior cingulate cortex, a brain area involved in cognitive control, which also appears to respond to the occurrence of conflict. The present article reports two computational modeling studies, serving to articulate the conflict monitoring hypothesis and examine its implications. The first study tests the sufficiency of the hypothesis to account for brain activation data, applying a measure of conflict to existing models of tasks shown to engage the anterior cingulate. The second study implements a feedback loop connecting conflict monitoring to cognitive control, using this to simulate a number of important behavioral phenomena.
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            Pupil fluctuations track fast switching of cortical states during quiet wakefulness.

            Neural responses are modulated by brain state, which varies with arousal, attention, and behavior. In mice, running and whisking desynchronize the cortex and enhance sensory responses, but the quiescent periods between bouts of exploratory behaviors have not been well studied. We found that these periods of "quiet wakefulness" were characterized by state fluctuations on a timescale of 1-2 s. Small fluctuations in pupil diameter tracked these state transitions in multiple cortical areas. During dilation, the intracellular membrane potential was desynchronized, sensory responses were enhanced, and population activity was less correlated. In contrast, constriction was characterized by increased low-frequency oscillations and higher ensemble correlations. Specific subtypes of cortical interneurons were differentially activated during dilation and constriction, consistent with their participation in the observed state changes. Pupillometry has been used to index attention and mental effort in humans, but the intracellular dynamics and differences in population activity underlying this phenomenon were previously unknown.
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              Neural correlates, computation and behavioural impact of decision confidence.

              Humans and other animals must often make decisions on the basis of imperfect evidence. Statisticians use measures such as P values to assign degrees of confidence to propositions, but little is known about how the brain computes confidence estimates about decisions. We explored this issue using behavioural analysis and neural recordings in rats in combination with computational modelling. Subjects were trained to perform an odour categorization task that allowed decision confidence to be manipulated by varying the distance of the test stimulus to the category boundary. To understand how confidence could be computed along with the choice itself, using standard models of decision-making, we defined a simple measure that quantified the quality of the evidence contributing to a particular decision. Here we show that the firing rates of many single neurons in the orbitofrontal cortex match closely to the predictions of confidence models and cannot be readily explained by alternative mechanisms, such as learning stimulus-outcome associations. Moreover, when tested using a delayed reward version of the task, we found that rats' willingness to wait for rewards increased with confidence, as predicted by the theoretical model. These results indicate that confidence estimates, previously suggested to require 'metacognition' and conscious awareness are available even in the rodent brain, can be computed with relatively simple operations, and can drive adaptive behaviour. We suggest that confidence estimation may be a fundamental and ubiquitous component of decision-making.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                03 March 2017
                2017
                : 8
                : 14637
                Affiliations
                [1 ]Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf , Hamburg 20246, Germany
                [2 ]Department of Psychology, University of Amsterdam , Amsterdam 1018 WT, The Netherlands
                [3 ]Amsterdam Brain and Cognition (ABC), University of Amsterdam , Amsterdam 1018 WT, The Netherlands
                Author notes
                Author information
                http://orcid.org/0000-0001-5270-6513
                http://orcid.org/0000-0002-1946-7765
                Article
                ncomms14637
                10.1038/ncomms14637
                5337963
                28256514
                561756e4-7d4e-497c-94c2-4f45afd813a9
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 22 March 2016
                : 17 January 2017
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