2020 |
Purcell, John Randall |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Neural Circuity of Risk Aversion and Reward Processing in Psychotic Disorders @ Indiana University Bloomington
PROJECT SUMMARY/ABSTRACT Psychotic disorders such as schizophrenia and schizoaffective disorder are chronic conditions characterized by pervasive cognitive impairment, hallucinations, delusions, aberrant affective processing, and decreases in reward/goal pursuit. Listed as the 8th leading cause of disability world-wide, psychotic disorders are also associated with substantial financial burden (e.g. national cost of $155.7 billion in 2013). Psychosis symptom severity has been associated with poor decision-making with respect to processing risk and reward. While typically thought of as detrimental, risk-taking in moderation is actually beneficial, as it often results in gaining new or additional rewards or resources (i.e., nothing ventured, nothing gained). This inability to optimize decision-making in psychotic disorders has been associated with more severe symptomatology, suggesting a possible target for remediating the burden of the illness. Leveraging functional magnetic resonance imaging (fMRI) and neurocomputational modeling, the proposed research will determine whether decreased activation and connectivity between the dorsal anterior cingulate cortex and other brain regions is associated with disadvantageous decision-making in psychotic disorders. Specifically, it will determine whether this decision-making deficit is best accounted for by risk perception or reward processing circuits separately, or the combination of these circuits. It is hypothesized that psychotic disorders will be associated with decreased neural activation in, and connectivity between, circuits that subserve risk-perception, such as the dorsal anterior cingulate cortex, anterior insula, dorsolateral prefrontal cortex, and reward processing, such as the dorsal anterior cingulate cortex, striatum, and orbitofrontal cortex. Neurocomputational modeling will isolate three critical risk-processing variables that cannot be identified via behavioral data alone and identify how differences in task behavior implicates contributions from specific brain regions. The proposed plan will provide targeted training in advanced neuroscience methods, computational modeling, and clinical translational science. Altogether, the proposal will establish the critical foundation necessary to establish a program of research integrating clinical psychological science of psychotic disorders with neuroimaging and computational modeling. Long-term this will lead to advances in our understanding of the neural mechanisms contributing to the etiology of psychotic disorders, which may, in turn, be explored as novel targets of intervention.
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