Literature DB >> 34310712

Sequential gains and losses during gambling feedback: Differential effects in time-frequency delta and theta measures.

Matthew D Bachman1,2, Adreanna T M Watts3, Paul Collins4, Edward M Bernat3.   

Abstract

One critical aspect of reward-feedback is the impact of local outcome history-how past experiences with choices and outcomes influences current behavior and neural activity. Yet, prior event-related potential work in this area has been contentious. This study contributes to this field by using time-frequency measures to better isolate constituent processes. Specifically, we identify how theta and delta are differentially sensitive to local outcome history. Participants completed a binary monetary choice task while we collected EEG data. Unbeknownst to them, trial outcomes were manipulated into pre-determined sequences, ranging from one to eight gains or losses in a row. Analyses were arranged by sequence establishment (first 2 trials of a sequence) and continuation (prolonged sequences of 3-8 trials). During the establishment of a sequence, delta activity to gains and losses were virtually identical on the first (change) trial, demonstrating marked divergence only on the second trial. This difference grew throughout the continuation period, as delta activity was sustained with accruing gains but declined with multiple losses. Theta activity, conversely, demonstrated a maximal loss-gain difference on the change trial but was insensitive to the establishment of a new sequence. Differential theta activity between outcomes decreased as sequences continued, with theta activity increasing over accruing gains and remaining stable over losses. Results indicate that delta-gain and theta-loss signals are relatively stable across sequential outcomes. Furthermore, theta is most sensitive to loss-gain differences on the initial change trial, while delta is more sensitive to gain-loss differences with the continuation of a sequence.
© 2021 Society for Psychophysiological Research.

Entities:  

Keywords:  decision-making; feedback processing; oscillation/time frequency analyses; reward; sequential outcomes

Mesh:

Year:  2021        PMID: 34310712      PMCID: PMC8789948          DOI: 10.1111/psyp.13907

Source DB:  PubMed          Journal:  Psychophysiology        ISSN: 0048-5772            Impact factor:   4.348


  58 in total

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Journal:  J Exp Psychol Learn Mem Cogn       Date:  1992-07       Impact factor: 3.051

3.  Decomposing ERP time-frequency energy using PCA.

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

Authors:  W H Miltner; C H Braun; M G Coles
Journal:  J Cogn Neurosci       Date:  1997-11       Impact factor: 3.225

5.  Reward dysfunction in major depression: multimodal neuroimaging evidence for refining the melancholic phenotype.

Authors:  Dan Foti; Joshua M Carlson; Colin L Sauder; Greg H Proudfit
Journal:  Neuroimage       Date:  2014-07-01       Impact factor: 6.556

6.  The medial frontal cortex and the rapid processing of monetary gains and losses.

Authors:  William J Gehring; Adrian R Willoughby
Journal:  Science       Date:  2002-03-22       Impact factor: 47.728

7.  Utilizing time-frequency amplitude and phase synchrony measure to assess feedback processing in a gambling task.

Authors:  Adreanna T M Watts; Anne V Tootell; Spencer T Fix; Selin Aviyente; Edward M Bernat
Journal:  Int J Psychophysiol       Date:  2018-04-30       Impact factor: 2.997

8.  Mediofrontal negativities in the absence of responding.

Authors:  Franc C L Donkers; Sander Nieuwenhuis; Geert J M van Boxtel
Journal:  Brain Res Cogn Brain Res       Date:  2005-10-24

9.  Effects of reward context on feedback processing as indexed by time-frequency analysis.

Authors:  Adreanna T M Watts; Edward M Bernat
Journal:  Psychophysiology       Date:  2018-05-11       Impact factor: 4.016

10.  A reservoir of time constants for memory traces in cortical neurons.

Authors:  Alberto Bernacchia; Hyojung Seo; Daeyeol Lee; Xiao-Jing Wang
Journal:  Nat Neurosci       Date:  2011-02-13       Impact factor: 24.884

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