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Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex

Ide, Jaime S. ; Shenoy, Pradeep ; Yu, Angela J. ; Li, Chiang-shan R. (2013)
Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex.
In: Journal of Neuroscience, 33 (5)
doi: 10.1523/JNEUROSCI.2201-12.2013
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

The dorsal anterior cingulate cortex (dACC) has been implicated in a variety of cognitive control functions, among them the monitoring of conflict, error, and volatility, error anticipation, reward learning, and reward prediction errors. In this work, we used a Bayesian ideal observer model, which predicts trial-by-trial probabilistic expectation of stop trials and response errors in the stop-signal task, to differentiate these proposed functions quantitatively. We found that dACC hemodynamic response, as measured by functional magnetic resonance imaging, encodes both the absolute prediction error between stimulus expectation and outcome, and the signed prediction error related to response outcome. After accounting for these factors, dACC has no residual correlation with conflict or error likelihood in the stop-signal task. Consistent with recent monkey neural recording studies, and in contrast with other neuroimaging studies, our work demonstrates that dACC reports at least two different types of prediction errors, and beyond contexts that are limited to reward processing.

Typ des Eintrags: Artikel
Erschienen: 2013
Autor(en): Ide, Jaime S. ; Shenoy, Pradeep ; Yu, Angela J. ; Li, Chiang-shan R.
Art des Eintrags: Bibliographie
Titel: Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex
Sprache: Englisch
Publikationsjahr: Januar 2013
Ort: Washington, DC
Verlag: Society for Neuroscience
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Journal of Neuroscience
Jahrgang/Volume einer Zeitschrift: 33
(Heft-)Nummer: 5
DOI: 10.1523/JNEUROSCI.2201-12.2013
URL / URN: https://www.jneurosci.org/content/33/5/2039
Kurzbeschreibung (Abstract):

The dorsal anterior cingulate cortex (dACC) has been implicated in a variety of cognitive control functions, among them the monitoring of conflict, error, and volatility, error anticipation, reward learning, and reward prediction errors. In this work, we used a Bayesian ideal observer model, which predicts trial-by-trial probabilistic expectation of stop trials and response errors in the stop-signal task, to differentiate these proposed functions quantitatively. We found that dACC hemodynamic response, as measured by functional magnetic resonance imaging, encodes both the absolute prediction error between stimulus expectation and outcome, and the signed prediction error related to response outcome. After accounting for these factors, dACC has no residual correlation with conflict or error likelihood in the stop-signal task. Consistent with recent monkey neural recording studies, and in contrast with other neuroimaging studies, our work demonstrates that dACC reports at least two different types of prediction errors, and beyond contexts that are limited to reward processing.

Zusätzliche Informationen:

141 citations (Crossref) 2023-10-13; Publisher: Society for Neuroscience; Section: Articles

Fachbereich(e)/-gebiet(e): 03 Fachbereich Humanwissenschaften
03 Fachbereich Humanwissenschaften > Institut für Psychologie
Hinterlegungsdatum: 30 Okt 2023 06:40
Letzte Änderung: 01 Nov 2023 12:51
PPN: 512758875
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