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Broadly, our group is interested in cognitive neuroscience of psychiatric illness. We seek to better understand, at the neural system level, the mechanisms behind cognitive and affective deficits in neuropsychiatric illness. Specifically, the research in our group focuses on understanding these processes in schizophrenia, bipolar illness and addiction. We use a combination of tools to better understand the underlying systems involved in processing affective stimuli and their interaction with circuits involved in goal-directed cognitive operations such as working memory.
Methodologically, our lab harnesses the combination of task-based, resting-state, pharmacological functional neuroimaging, as well as computational modeling approaches. Combining these approaches allows us to mechanistically understand neural circuit dysfunction in psychiatric disorders. Our experimental approaches depend on the combination of these tools to better understand the mechanistic links between dysfunction at the microcircuit level and complex cognitive and affective disturbances. The overarching objective of the lab is to better characterize the underlying neural circuit dysfunction in complex mental illness such as schizophrenia, with the aim of developing better neural markers and informing rationally-guided pharmacological treatments. The lab is also a close affiliate of the Center for the Translational Neuroscience of Alcoholism (CTNA) and collaborates closely with Dr. John Krystal's research groups.
NIMH highlights Anticevic Lab research in a sampling of summer science
Anticevic Lab receives the 2012 NIH Director’s Early Independence Award (DP5)
Anticevic Lab is awarded a 5-year grant to better characterize the neural mechanisms behind cognitive impairment in schizophrenia via the combination of pharmacological neuroimaging, computational modeling and non-invasive neuroimaging of clinical populations. The pharmacological work is done collaboratively with Dr. John H. Krystal and Dr. Peter T. Morgan. Computational modeling is being developed collaboratively with Dr. Xiao-Jing Wang and John D. Murray.