This MERIT extension application builds on the Pi's major findings during the prior funding period to extend prior themes. A major conclusion, consistent with emerging literature is that different functional brain networks Identified through independent component analysis (ICA) of BOLD activation associated with a variety of functional MRI paradigms are commonly engaged across many tasks, In controls and schizophrenia patients. These include networks subserving complex focused attention, """"""""brain idling"""""""" (in the resting state and default mode), working memory/executive decision-making, set maintenance and language. These circuits are focused around four major neural nodes, and using approaches such as functional network connectivity, (FNC) one can demonstrate disrupted relationships among these circuits in schizophrenia that seem to plausibly constitute the neural basis of """"""""disconnectivity."""""""" We capitalize on our continuing focus on heteromodal association cortical regions as well as continuing to study functional MRI tasks based around semantic knowledge and """"""""Theory of Mind """"""""that we hypothesize are central to schizophrenia formal thought disorder, but have not been explored in depth using the analytic tools available to our group. Finally we will combine the use of functional and anatomical connectivity analysis techniques, singly and in combination, (the latter using fusion techniques across imaging modalities, including novel combinations of Diffusion Tensor Imaging with fMRI), to elucidate relationships between cognitive system dysfunction leading to symptoms and neural network abnormalities.

Public Health Relevance

Schizophrenia is a common, disabling brain-based disorder commonly hypothesized to be due to """"""""disconnection"""""""" between different brain regions, although this has not been demonstrated directly. This proposal seeks to elucidate the nature of the """"""""disconnection"""""""" by examining connections among different brain circuits, using structural and functional MRI and diffusion tensor imaging.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Method to Extend Research in Time (MERIT) Award (R37)
Project #
5R37MH043775-20
Application #
8102055
Study Section
Special Emphasis Panel (NSS)
Program Officer
Rumsey, Judith M
Project Start
1988-08-01
Project End
2013-05-31
Budget Start
2011-06-01
Budget End
2012-05-31
Support Year
20
Fiscal Year
2011
Total Cost
$656,324
Indirect Cost
Name
Hartford Hospital
Department
Type
DUNS #
065533796
City
Hartford
State
CT
Country
United States
Zip Code
06102
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van Erp, Theo G M; Walton, Esther; Hibar, Derrek P et al. (2018) Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biol Psychiatry 84:644-654
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Du, Yuhui; Pearlson, Godfrey D; Lin, Dongdong et al. (2017) Identifying dynamic functional connectivity biomarkers using GIG-ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder. Hum Brain Mapp 38:2683-2708
Yang, Genevieve J; Murray, John D; Wang, Xiao-Jing et al. (2016) Functional hierarchy underlies preferential connectivity disturbances in schizophrenia. Proc Natl Acad Sci U S A 113:E219-28
Yu, Qingbao; Wu, Lei; Bridwell, David A et al. (2016) Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study. Front Hum Neurosci 10:476
Anticevic, Alan; Savic, Aleksandar; Repovs, Grega et al. (2015) Ventral anterior cingulate connectivity distinguished nonpsychotic bipolar illness from psychotic bipolar disorder and schizophrenia. Schizophr Bull 41:133-43
Du, Yuhui; Pearlson, Godfrey D; Liu, Jingyu et al. (2015) A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders. Neuroimage 122:272-80
Yu, Qingbao; Erhardt, Erik B; Sui, Jing et al. (2015) Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia. Neuroimage 107:345-55

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