https://scholars.lib.ntu.edu.tw/handle/123456789/625587
標題: | Impaired Bayesian learning for cognitive control in cocaine dependence | 作者: | Ide J.S Hu S Zhang S ANGELA YU-CHEN LIN Li C.S.R. |
關鍵字: | Bayesian modeling; Cocaine addiction; Cognitive control; Conflict monitoring; Post-error slowing; Sequential effect | 公開日期: | 2015 | 卷: | 151 | 起(迄)頁: | 220-227 | 來源出版物: | Drug and Alcohol Dependence | 摘要: | Background: Cocaine dependence is associated with cognitive control deficits. Here, we apply a Bayesian model of stop-signal task (SST) performance to further characterize these deficits in a theory-driven framework. Methods: A "sequential effect" is commonly observed in SST: encounters with a stop trial tend to prolong reaction time (RT) on subsequent go trials. The Bayesian model accounts for this by assuming that each stop/go trial increases/decreases the subject's belief about the likelihood of encountering a subsequent stop trial, P(stop), and that P(stop) strategically modulates RT accordingly. Parameters of the model were individually fit, and compared between cocaine-dependent (CD, n= 51) and healthy control (HC, n= 57) groups, matched in age and gender and both demonstrating a significant sequential effect (p<. 0.05). Model-free measures of sequential effect, post-error slowing (PES) and post-stop slowing (PSS), were also compared across groups. Results: By comparing individually fit Bayesian model parameters, CD were found to utilize a smaller time window of past experiences to anticipate P(stop) (p<. 0.003), as well as showing less behavioral adjustment in response to P(stop) (p<. 0.015). PES (p= 0.19) and PSS (p= 0.14) did not show group differences and were less correlated with the Bayesian account of sequential effect in CD than in HC. Conclusions: Cocaine dependence is associated with the utilization of less contextual information to anticipate future events and decreased behavioral adaptation in response to changes in such anticipation. These findings constitute a novel contribution by providing a computationally more refined and statistically more sensitive account of altered cognitive control in cocaine addiction. © 2015 Elsevier Ireland Ltd. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929965103&doi=10.1016%2fj.drugalcdep.2015.03.021&partnerID=40&md5=6b4e3285f56878ba695bba2a1ab36f5a https://scholars.lib.ntu.edu.tw/handle/123456789/625587 |
ISSN: | 03768716 | DOI: | 10.1016/j.drugalcdep.2015.03.021 | SDG/關鍵字: | adaptive behavior; adult; anticipation; Article; Bayesian learning; cocaine dependence; cognitive defect; controlled study; effect size; executive function; female; human; learning disorder; major clinical study; male; post error slowing; post stop slowing; priority journal; response time; sequential effect; statistical parameters; stop signal task; task performance; alcoholism; algorithm; Bayes theorem; cocaine dependence; cognition; complication; drug effects; educational status; learning; prospective study; psychology; reaction time; Adult; Alcoholism; Algorithms; Bayes Theorem; Cocaine-Related Disorders; Cognition; Educational Status; Female; Humans; Learning; Male; Prospective Studies; Reaction Time |
顯示於: | 環境工程學研究所 |
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