Diffeomorphometry applied to functional connectivity in schizophrenia using ultrahigh resolution MRI

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Project Summary Schizophrenia is a disorder with a life-time world-wide prevalence of ~0.5% and devastating consequences for affected individuals, their families, and society. Improved understanding of the disruptions in cortical circuitry thought to underlie schizophrenia could go a long way toward addressing challenges in understanding the pathophysiology of schizophrenia, as well as the challenges of improving schizophrenia nosology, diagnosis, and treatment. Our guiding hypothesis is that schizophrenia is a consequence of cortical-cortical and cortical-subcortical functional dysconnectivity, and particularly the circuitry between the thalamus and the cortex. Understanding this dysconnectivity could have profound implications for the field. In this proposal, we will develop a new and potentially power method for the analysis of functional connectivity between thalamic subregions and deep and superficial layers of the cortex, using a sophisticated mathematical approach (diffeomorphometry) to precisely determine the thickness of the cortex at specified regions of the brain. In Aim 1, we will optimize this method for both resting and activated thalamocortical connectivity, using ultra-high field strength (7 Tesla) fMRI. In Aim 2, we will test the protocols developed in Aim 1 in 20 individuals with schizophrenia compared to 20 healthy controls. We will determine if subdividing the cortex using the diffeomorphometric approach will more clearly delineate the dysconnectivity in patients, with the potential benefit that investigations can use smaller sample sizes, and that more subtle clinical factors associated with aberrant connectivity can be discerned. In addition, this improved resolution at the cortex may facilitate more nuanced understanding of the specific thalamic origins of aberrant signals and the differences in dysconnectivity across different cortical layers. Overall, the goal is to establish methods that can be used to further develop functional connectivity as a biomarker useful in nosology and prognosis, and in the prediction and monitoring of treatment response.