Schizophrenia Clinical Trial
Official title:
Structural and Functional Imaging of Neuropsychiatric Patients and Normal Volunteers With 3.0 Tesla MRI and Magnetoencephalography (MEG)
The purpose of this study is to use brain imaging technology to compare differences in brain structure, chemistry, and functioning in individuals with brain and mental disorders compared to healthy volunteers. Schizophrenia is a brain disorder that results from subtle changes and abnormalities in neurons. These deficits likely occur in localized regions of the brain and may result in widespread, devastating consequences. The neuronal abnormalities are inherited through a complex combination of genetic and environmental factors. Brain imaging technologies can be used to better characterize brain changes in individuals with schizophrenia. This study will use magnetic resonance imaging (MRI) scans to identify predictable, quantifiable abnormalities in neurophysiology, neurochemistry and neuroanatomy that characterize schizophrenia and other neurological and neuropsychiatric disorders.
This protocol is meant to provide a matrix for multiple, simultaneous brain imaging investigations using magnetic resonance imaging (MRI) at 3.0 Tesla (3T). We intend to study regional brain structure, physiology, and biochemistry in living human subjects, both healthy and ill. Based on multiple clinical, neuropathological, and functional neuroimaging studies, it is clear that schizophrenia is a brain disorder arising from subtle neuronal deficits (for lack of more specific terminology). These deficits likely arise in a few key regions such as dorsolateral prefrontal cortex and hippocampal formation, that result in widespread, multifaceted, and devastating clinical consequences. These neuronal deficits are clearly heritable, although in a complex fashion from multiple genes interacting in an epistatic fashion with each other and the environment. We hypothesize that these neuronal deficits, clearly resulting in quantifiable behavioral abnormalities in schizophrenic patients, will produce predictable, quantifiable aberrations in neurophysiology that we can "map" using magnetic resonance imaging. In spite of numerous functional imaging findings, clinical applications remain scarce and pathognomonic findings absent. Therefore, we do not anticipate that an approach based solely on any one modality is likely to significantly advance our knowledge base. Instead, we propose to create brain imaging datasets for individual human subjects predicated on 1) the appraisal of brain function from multiple domains simultaneously; 2) the characterization of brain function via summation and intercorrelation of these data; and 3) the digestion of these data based on the parsing of complex clinical phenomenology into quantifiable neurophysiological parameters. Thus, in addition to the identification of those parameters that best characterize and identify manifest schizophrenia (i.e., state variables), we hypothesize that some of these fundamental characteristics will be heritable. These fundamental characteristics, so-called endo- or intermediate phenotypes, represent powerful tools to find susceptibility genes and have already generated a number of linkage findings. ;
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