This Phase II COBRE project is a natural extension of our Phase I COBRE on multimodal neuroimaging in schizophrenia. In the next evolution we will build on our success in Phase I to include a wider range of disease categories making the overarching theme of the Phase II COBRE the use of multimodal neuroimaging to better understand the neural mechanisms of psychosis and mood disorders. The Mind Research Network (MRN) houses an Elekta MEG System, a high density EEG lab, and a 3T Siemens Trio MRl scanner. Additional resources include a centralized neuroinformatics system, a strong IT management plan, and state-of-the-art image analysis tools. The Phase II COBRE will provide support to five outstanding junior investigators through the assistance of strong senior mentors. The five projects each focus on distinct, but related, aspects of psychosis and mood disorders. Project 1 will utilize advanced data fusion methods to evaluate the ability of multimodal brain imaging data to differentiate patient groups and to push beyond discrete diagnostic categories by identifying individuals in intermediate positions on the continuum. Project 2 is an expansion of the pilot genetic program from the Phase I to evaluate the shared and unique aspects of genetic influence on brain structural networks using advanced multivariate methods. Project 3 will focus on the lens of social cognition and evaluate functional networks in patients while perceiving facial and vocal emotions. The ability of both structural and functional networks to differentiate groups and predict outcomes will be evaluated. Project 4 will focus on auditory hallucinations using MEG and fMRI. Evaluation of the ability to predict hallucinations from the imaging data as well as the impact of transcranial direct current stimulation (tDCS) on the identified brain networks will be investigated. And finally, Project 5 will use a longitudinal desin to study brain networks related to major depression and relapse after treatment with electro-convulsive therapy (ECT). We will continue with the cores established during the Phase I project including administration, clinical assessment, and mentoring (ACAM), multimodal data acquisition (MDA), algorithm and data analysis (ADA), and biostatistics and neuro-informatics (BNI). These cores have begun to serve MRN and the greater community, as well as other institutions including extension collaborations with IDeA funded projects in New Mexico and other states. A highly successful pilot project program will be continued. We believe this Phase II COBRE is extremely well-positioned to establish New Mexico as one of the premier brain imaging sites. We include an extensive educational, mentoring, and faculty development program to carefully mentor and establish junior investigators as independently funded investigators, thus fulfilling the ultimate goals of the COBRE program.
This Phase II COBRE project is a natural extension of our Phase I COBRE on multimodal neuroimaging in schizophrenia. We expand Phase I work (cognitive functioning) to include interpersonal functioning (i.e., social cognition), the neuronal basis of hallucinations, and most importantly treatment response across a spectrum of disorders (SZ, BP and major depression). Our projects will utilize advanced approaches to identify biomarkers and to evaluate their predictive utility.
|Zille, Pascal; Calhoun, Vince D; Stephen, Julia M et al. (2017) Fused estimation of sparse connectivity patterns from rest fMRI. Application to comparison of children and adult brains. IEEE Trans Med Imaging :|
|Meng, Xing; Jiang, Rongtao; Lin, Dongdong et al. (2017) Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. Neuroimage 145:218-229|
|Bernard, Jessica A; Goen, James R M; Maldonado, Ted (2017) A case for motor network contributions to schizophrenia symptoms: Evidence from resting-state connectivity. Hum Brain Mapp 38:4535-4545|
|Gupta, Cota Navin; Castro, Eduardo; Rachkonda, Srinivas et al. (2017) Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia. Front Psychiatry 8:179|
|Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing et al. (2017) Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. Neuroimage 145:137-165|
|He, Hao; Sui, Jing; Du, Yuhui et al. (2017) Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders. Brain Struct Funct 222:4051-4064|
|Vergara, Victor M; Mayer, Andrew R; Damaraju, Eswar et al. (2017) The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA. Neuroimage 145:365-376|
|Faghiri, Ashkan; Stephen, Julia M; Wang, Yu-Ping et al. (2017) Changing brain connectivity dynamics: From early childhood to adulthood. Hum Brain Mapp :|
|de Lacy, N; Doherty, D; King, B H et al. (2017) Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum. Neuroimage Clin 15:513-524|
|Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas et al. (2017) Multimodal neural correlates of cognitive control in the Human Connectome Project. Neuroimage 163:41-54|
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