Behavioral dysregulation is a risk factor for alcohol dependence and likely contributes to failed treatment attempts after the onset of alcohol dependence. Regulation over behavior is a complex process that relies on several functional circuits within the brain that are used to weigh costs and benefits of decisions. The degree to which neural circuits involved in behavioral regulation are affected in alcohol dependence remain largely unknown. To address this dearth of knowledge the proposed study aims to 1) integrate real-time tastant delivery with tasks known to engage regions important for alcohol dependence such as the ventral striatum, anterior cingulate cortex, and inferior frontal gyrus and 2) determine how functional connectivity patterns differ in alcohol dependent individuals compared to social drinkers, in order to determine the mechanisms that underlie automatic and controlled responses to cues that predict alcohol. Alcohol dependent and social drinkers will complete neurocognitive tasks that assess reward sensitivity while undergoing functional magnetic resonance imaging (fMRI) to determine those brain regions that are affected in alcohol dependence, and to better understand how functional connectivity patterns may differ in alcohol dependent individuals.
Alcohol dependence is associated with a reduced ability to control behavior in a goal-directed manner, and this poor behavioral regulation may be particularly salient when in the presence of alcohol cues. The current research aims to examine the neural mechanisms that contribute behavioral dysregulation in alcohol dependence. Findings from this work may be important for identifying neural markers that help predict risk for future alcohol dependence.
|Steele, Vaughn R; Maurer, J Michael; Arbabshirani, Mohammad R et al. (2018) Machine Learning of Functional Magnetic Resonance Imaging Network Connectivity Predicts Substance Abuse Treatment Completion. Biol Psychiatry Cogn Neurosci Neuroimaging 3:141-149|