Quantitative Neuroimaging in Psychosis; DTI Studies

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DESCRIPTION (provided by applicant): Evidence from multiple sources implicates dysfunction in distributed cortical networks in individuals with schizophrenia, defined both by aberrant activation provoked by defined cognitive tasks and by associated abnormal correlation of activity between different nodes in the activated network. These abnormal over- or under-activations are hypothesized to vary in response to task type and difficulty level, and to current symptom profile. The current proposal is a supplement to an existing MERIT award to the PI, that proposes to add Diffusion Tensor Imaging (DTI) to further enhance our ability to document abnormalities in a circuit that is dysfunctional in schizophrenia. The overall aim of the funded parent grant is to build on previously gathered data from the Pi's Lab that implicated dysfunction of the heteromodal association neocortical network (HASC) as playing a central role in the pathophysiology of schizophrenia, to better define and understand this dysfunction. This proposal combines expertise in clinical assessment, fMRI task development and data analysis, cognitive assessment and detailed quantitative structural brain measurement, with the proposed addition of DTI. The currently funded work utilizes functional MRI (fMRI) to dissect HASC dysfunction using a comprehensive battery of well-characterized cognitive activation paradigms, where task performance can be characterized both inside and outside the scanner. It examines a diverse population of 100 symptomatically, functionally and cognitively well-assessed patients with SZ on stable doses of second-generation antipsychotic medications, compared to 100 matched, exceptionally well characterized healthy control subjects. These latter are participating in an ongoing representative population study of usual aging, drawn from the same catchment areas as our patients. In addition to assessing fMRI activation patterns gathered using 3 cognitive probe tasks that activate different nodes in the HASC network, we are measuring volumes of the same brain regions using MRI morphometry, to explore structure/function relationships correlative^. We will also examine fMRI task-uncorrelated synchrony patterns to address possible between-group performance differences. We now propose to add DTI assessments to examine1 connectivity. These data will be entered into structural equation models to permit a thorough examination of multiple aspects of HASC brain dysfunction in SZ and explore how brain structure, function and connectivity abnormalities relate to putative underlying symptomatically- and cognitively-defined subtypes. In addition, novel data fusion techniques will be used to combine information across imaging modalities.