Literature DB >> 22120491

Frontal theta reflects uncertainty and unexpectedness during exploration and exploitation.

James F Cavanagh1, Christina M Figueroa, Michael X Cohen, Michael J Frank.   

Abstract

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward-learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices.

Mesh:

Year:  2011        PMID: 22120491      PMCID: PMC4296208          DOI: 10.1093/cercor/bhr332

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  45 in total

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2.  The electrophysiological dynamics of interference during the Stroop task.

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3.  Event-related brain potentials following incorrect feedback in a time-estimation task: evidence for a "generic" neural system for error detection.

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4.  Dorsal anterior cingulate cortex: a role in reward-based decision making.

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Journal:  Proc Natl Acad Sci U S A       Date:  2001-12-26       Impact factor: 11.205

5.  Role for cingulate motor area cells in voluntary movement selection based on reward.

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6.  Responses of human anterior cingulate cortex microdomains to error detection, conflict monitoring, stimulus-response mapping, familiarity, and orienting.

Authors:  Chunmao Wang; Istvan Ulbert; Donald L Schomer; Ksenija Marinkovic; Eric Halgren
Journal:  J Neurosci       Date:  2005-01-19       Impact factor: 6.167

7.  Feedback-related negativity codes prediction error but not behavioral adjustment during probabilistic reversal learning.

Authors:  Henry W Chase; Rachel Swainson; Lucy Durham; Laura Benham; Roshan Cools
Journal:  J Cogn Neurosci       Date:  2010-02-10       Impact factor: 3.225

8.  Subjective and model-estimated reward prediction: association with the feedback-related negativity (FRN) and reward prediction error in a reinforcement learning task.

Authors:  Naho Ichikawa; Greg J Siegle; Alexandre Dombrovski; Hideki Ohira
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9.  Medial frontal cortex and response conflict: evidence from human intracranial EEG and medial frontal cortex lesion.

Authors:  Michael X Cohen; K Richard Ridderinkhof; Sven Haupt; Christian E Elger; Juergen Fell
Journal:  Brain Res       Date:  2008-08-07       Impact factor: 3.252

10.  Neurons in posterior cingulate cortex signal exploratory decisions in a dynamic multioption choice task.

Authors:  John M Pearson; Benjamin Y Hayden; Sridhar Raghavachari; Michael L Platt
Journal:  Curr Biol       Date:  2009-09-03       Impact factor: 10.834

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  67 in total

Review 1.  The expected value of control: an integrative theory of anterior cingulate cortex function.

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2.  Cortical Oscillatory Mechanisms Supporting the Control of Human Social-Emotional Actions.

Authors:  Bob Bramson; Ole Jensen; Ivan Toni; Karin Roelofs
Journal:  J Neurosci       Date:  2018-05-23       Impact factor: 6.167

3.  Functionally dissociable influences on learning rate in a dynamic environment.

Authors:  Joseph T McGuire; Matthew R Nassar; Joshua I Gold; Joseph W Kable
Journal:  Neuron       Date:  2014-11-19       Impact factor: 17.173

4.  D1-dependent 4 Hz oscillations and ramping activity in rodent medial frontal cortex during interval timing.

Authors:  Krystal L Parker; Kuan-Hua Chen; Johnathan R Kingyon; James F Cavanagh; Nandakumar S Narayanan
Journal:  J Neurosci       Date:  2014-12-10       Impact factor: 6.167

5.  Electrophysiological correlates reflect the integration of model-based and model-free decision information.

Authors:  Ben Eppinger; Maik Walter; Shu-Chen Li
Journal:  Cogn Affect Behav Neurosci       Date:  2017-04       Impact factor: 3.282

6.  Frontal theta overrides pavlovian learning biases.

Authors:  James F Cavanagh; Ian Eisenberg; Marc Guitart-Masip; Quentin Huys; Michael J Frank
Journal:  J Neurosci       Date:  2013-05-08       Impact factor: 6.167

7.  Stimulus sequence context differentially modulates inhibition-related theta and delta band activity in a go/no-go task.

Authors:  Jeremy Harper; Stephen M Malone; Matthew D Bachman; Edward M Bernat
Journal:  Psychophysiology       Date:  2016-01-11       Impact factor: 4.016

8.  Abnormal approach-related motivation but spared reinforcement learning in MDD: Evidence from fronto-midline Theta oscillations and frontal Alpha asymmetry.

Authors:  Davide Gheza; Jasmina Bakic; Chris Baeken; Rudi De Raedt; Gilles Pourtois
Journal:  Cogn Affect Behav Neurosci       Date:  2019-06       Impact factor: 3.282

Review 9.  How cognitive theory guides neuroscience.

Authors:  Michael J Frank; David Badre
Journal:  Cognition       Date:  2014-12-08

10.  Reward feedback processing in children and adolescents: medial frontal theta oscillations.

Authors:  Michael J Crowley; Stefon J R van Noordt; Jia Wu; Rebecca E Hommer; Mikle South; R M P Fearon; Linda C Mayes
Journal:  Brain Cogn       Date:  2013-12-18       Impact factor: 2.310

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