Building on the prior Projects, this last Project will take our investigations of the social decision-making system to the network level and investigate the influences among its components using techniques such as pharmacological inactivation, rare human lesion subjects, diffusion imaging, BOLD coherence and spike-field coherence. It will pave the way for major future efforts, beyond the scope of the present application, eventually to understand the complete functional architecture for social decision-making implemented by a spatially distributed neural system. Specifically, we will focus on how the components of the system identified in the other Projects (e.g., amygdala, dorsolateral and orbital prefrontal cortex) interact. This requires investigations of two kinds: (1) demonstration of the functional effects on one another (Aims 1-2), and (2) characterization of their connectivity (Aims 3-4). This Project features a very close integration of studies in humans and monkeys, uses a diverse set of approaches ranging from diffusion imaging to tracer studies to pharmacological inactivation and spike-field coherence, and leverages many of the data collected under the other Projects. There are four Specific Aims: (1) to characterize interactions between prefrontal and amygdala regions in monkeys and humans using spike-field coherence (collaboration with Dr Doris Tsao);(2) to investigate causal influences of the amygdala on the prefrontal cortex using reversible pharmacological inactivation in monkeys and study of rare human lesion subjects (collaboration with Dr. Richard Andersen);(3) to describe structural and functional connectivity networks in monkeys (4) to describe structural and functional connectivity networks in humans. This final Project thus extends the studies from the prior Projects to the network level, and brings together many of the PIs from the prior Projects.
Many mental illnesses are thought to arise from abnormal connectivity between different brain regions, rather than merely pathology within a region. Autism, for instance, is now often thought of as a disconnection syndrome. This Project will provide important data towards understanding mental illnessess in which abnormal long-range connectivity plays a role in pathology.
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