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Updated: Jun 17, 2025

Disruption of Frontal Lobe Neural Synchrony During Cognitive Control by Alcohol Intoxication
Published on: February 6, 2019
Alcohol, flexible behavior, and the prefrontal cortex: Functional changes underlying impaired cognitive flexibility
Kathryn E Nippert1, Courtney P Rowland2, Elena M Vazey3
1Neuroscience and Behavior Graduate Program, University of Massachusetts Amherst, Amherst, MA, 01003, USA.
Abstract:
Cognitive flexibility enables individuals to alter their behavior in response to changing environmental demands, facilitating optimal behavior in a dynamic world. The inability to do this, called behavioral inflexibility, is a pervasive behavioral phenotype in alcohol use disorder (AUD), driven by disruptions in cognitive flexibility. Research has repeatedly shown that behavioral inflexibility not only results from alcohol exposure across species but can itself be predictive of future drinking. Like many high-level executive functions, flexible behavior requires healthy functioning of the prefrontal cortex (PFC). The scope of this review addresses two primary themes: first, we outline tasks that have been used to investigate flexibility in the context of AUD or AUD models. We characterize these based on the task features and underlying cognitive processes that differentiate them from one another. We highlight the neural basis of flexibility measures, focusing on the PFC, and how acute or chronic alcohol in humans and non-human animal models impacts flexibility. Second, we consolidate findings on the molecular, physiological and functional changes in the PFC elicited by alcohol, that may contribute to cognitive flexibility deficits seen in AUD. Collectively, this approach identifies several key avenues for future research that will facilitate effective treatments to promote flexible behavior in the context of AUD, to reduce the risk of alcohol related harm, and to improve outcomes following AUD. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".
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