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Multimodal imaging of neuropsychiatric disorders (MIND) COBRE
Juan Bustillo, Vince Calhoun
Background: A critical barrier to our understanding the neural mechanisms associated with
psychosis and mood disorders is the inability to integrate multiple approaches (functional,
structural and genetic) into a brain-based clinical assessment of neuropsychiatric disorders.
Developing our knowledge of symptomatic similarities and differences that cut across diagnostic
categories will allow a deeper understanding of our patients, and will promote more accurate
diagnosis and treatment.
Objective: To improve the understanding the neural basis of psychotic and affective disorders will
lead to improved diagnosis and treatment.
Methods: Five projects supported by extensive clinical, biostatistics/neuroinformatics, and data
analysis cores are focusing on distinct, but related, aspects of psychosis and mood disorders.
Project 1 utilizes advanced data fusion methods to evaluate the ability of multimodal brain imaging
data to differentiate patient groups and perform individualized prediction. Project 2 is an
expansion of a program of genetic research involving the use of advanced multivariate methods
to evaluate the shared and unique aspects of genetic influences on brain structural networks.
Project 3 uses a mobile MRI system to study psychotic symptoms and mentalizing (understanding
the mental states of others) in incarcerated criminal offenders. Project 4 studies auditory verbal
hallucination (AVH-)related neural networks fMRI and MEG. Project 5 uses a longitudinal design
to study brain networks related to major depression and relapse after treatment with
electroconvulsive therapy (ECT).
Results: Project 1 has detected multimodal biomarkers related to schizophrenic cognitive deficits
by combining three imaging modalities and predicted ECT treatment outcomes. Project 2 has
developed pipelines to process single nucleotide polymorphisms and copy number variant data
and the methods to combine imaging data with genetics in patients with schizophrenia. Project 3
has identified mentalizing impairments associated with persecutory and grandiose delusions that
are related to distinct patterns of functional connectivity. Project 4 identified AVH-related neural
networks shared by fifteen participants in thalamic, lateral inferior prefrontal, and auditory cortex
networks. Project 5 identified normalization of aberrant pre-ECT medial temporal lobe structural
and functional connectivity related to ECT response among subjects with a depressive episode.
Conclusion: The projects are utilizing novel data analysis methods to identify both state and trait
biomarkers associated with psychotic and affective disorders.
Funding: The work for this was funded by the NIGMS COBRE award P20GM103472.