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Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence

Harlé, Katia M. ; Zhang, Shunan ; Ma, Ning ; Yu, Angela J. ; Paulus, Martin P. (2016)
Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence.
In: Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 1 (5)
doi: 10.1016/j.bpsc.2016.06.008
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Delineating the processes that contribute to the progression and maintenance of substance dependence is critical to understanding and preventing addiction. Several previous studies have shown inhibitory control deficits in individuals with stimulant use disorder. We used a Bayesian computational approach to examine potential neural deficiencies in the dynamic predictive processing underlying inhibitory function among recently abstinent methamphetamine-dependent individuals (MDIs), a population at high risk of relapse. Sixty-two MDIs were recruited from a 28-day inpatient treatment program at the San Diego Veterans Affairs Medical Center and compared with 34 healthy control subjects. They completed a stop-signal task during functional magnetic resonance imaging. A Bayesian ideal observer model was used to predict individuals' trial-to-trial probabilistic expectations of inhibitory response, P(stop), to identify group differences specific to Bayesian expectation and prediction error computation. Relative to control subjects, MDIs were more likely to make stop errors on difficult trials and had attenuated slowing following stop errors. MDIs further exhibited reduced sensitivity as measured by the neural tracking of a Bayesian measure of surprise (unsigned prediction error), which was evident across all trials in the left posterior caudate and orbitofrontal cortex (Brodmann area 11), and selectively on stop error trials in the right thalamus and inferior parietal lobule. MDIs are less sensitive to surprising task events, both across trials and upon making commission errors, which may help explain why these individuals may not engage in switching strategy when the environment changes, leading to adverse consequences.

Typ des Eintrags: Artikel
Erschienen: 2016
Autor(en): Harlé, Katia M. ; Zhang, Shunan ; Ma, Ning ; Yu, Angela J. ; Paulus, Martin P.
Art des Eintrags: Bibliographie
Titel: Reduced Neural Recruitment for Bayesian Adjustment of Inhibitory Control in Methamphetamine Dependence
Sprache: Englisch
Publikationsjahr: September 2016
Ort: Amsterdam
Verlag: Elsevier
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
Jahrgang/Volume einer Zeitschrift: 1
(Heft-)Nummer: 5
DOI: 10.1016/j.bpsc.2016.06.008
URL / URN: https://www.sciencedirect.com/science/article/pii/S245190221...
Kurzbeschreibung (Abstract):

Delineating the processes that contribute to the progression and maintenance of substance dependence is critical to understanding and preventing addiction. Several previous studies have shown inhibitory control deficits in individuals with stimulant use disorder. We used a Bayesian computational approach to examine potential neural deficiencies in the dynamic predictive processing underlying inhibitory function among recently abstinent methamphetamine-dependent individuals (MDIs), a population at high risk of relapse. Sixty-two MDIs were recruited from a 28-day inpatient treatment program at the San Diego Veterans Affairs Medical Center and compared with 34 healthy control subjects. They completed a stop-signal task during functional magnetic resonance imaging. A Bayesian ideal observer model was used to predict individuals' trial-to-trial probabilistic expectations of inhibitory response, P(stop), to identify group differences specific to Bayesian expectation and prediction error computation. Relative to control subjects, MDIs were more likely to make stop errors on difficult trials and had attenuated slowing following stop errors. MDIs further exhibited reduced sensitivity as measured by the neural tracking of a Bayesian measure of surprise (unsigned prediction error), which was evident across all trials in the left posterior caudate and orbitofrontal cortex (Brodmann area 11), and selectively on stop error trials in the right thalamus and inferior parietal lobule. MDIs are less sensitive to surprising task events, both across trials and upon making commission errors, which may help explain why these individuals may not engage in switching strategy when the environment changes, leading to adverse consequences.

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10 citations (Crossref) 2023-10-13

Fachbereich(e)/-gebiet(e): 03 Fachbereich Humanwissenschaften
03 Fachbereich Humanwissenschaften > Institut für Psychologie
Hinterlegungsdatum: 02 Nov 2023 11:13
Letzte Änderung: 02 Nov 2023 11:13
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