Vince D. Calhoun
Georgia Institute of Technology
PsychologyPattern recognitionFunctional magnetic resonance imagingIndependent component analysisSchizophrenia
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Publications 1101
#1Victor M. Vergara (Georgia Institute of Technology)H-Index: 1
#1Victor M. VergaraH-Index: 10
Last. Vince D. CalhounH-Index: 93
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Abstract Background Clustering analysis is employed in brain dynamic functional connectivity (dFC) to cluster the data into a set of dynamic states. These states correspond to different patterns of functional connectivity that iterate through time. Although several clustering validity index (CVI) methods to determine the best clustering partition exists, the appropriateness of methods to apply in the case of dynamic connectivity analysis has not been determined. New Method Currently employed ind...
#1Brittany Taylor (UNMC: University of Nebraska Medical Center)
Last. Tony W. WilsonH-Index: 22
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Abstract Fluid intelligence, the ability to problem-solve in novel situations, is linked to higher-order cognitive abilities, and to academic achievement in youth. Previous research has demonstrated that fluid intelligence and the underlying neural circuitry continues to develop throughout adolescence. Neuroimaging studies have predominantly focused on identifying the spatial distribution of brain regions associated with fluid intelligence, with only a few studies examining the temporally-sensit...
#1Rajikha Raja (Georgia Institute of Technology)
#2Arvind Caprihan (The Mind Research Network)H-Index: 30
Last. Vince D. Calhoun (Georgia Institute of Technology)H-Index: 93
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Abstract Background Vascular cognitive impairment and dementia (VCID) and Alzheimer's disease are predominant diseases among the aging population resulting in decline of various cognitive domains. Diffusion weighted MRI (DW-MRI) has been shown to be a promising aid in the diagnosis of such diseases. However, there are various models of DW-MRI and the interpretation of diffusion metrics depends on the model used in fitting data. Most previous studies are entirely based on parameters calculated fr...
#1Yuntong Bai (Tulane University)
#2Pascal Zille (Tulane University)H-Index: 3
Last. Yu-Ping Wang (Tulane University)H-Index: 22
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Objective: Integration of multiple datasets is a hot topic in many fields. When studying complex mental disorders, great effort has been dedicated to fusing genetic and brain imaging data. However, an increasing number of studies have pointed out the importance of epigenetic factors in the cause of psychiatric diseases. In this study, we endeavor to fill the gap by combining epigenetics (e.g., DNA methylation) with imaging data (e.g., fMRI) to identify biomarkers for schizophrenia (SZ). Methods:...
#1Katrina L. Grasby (QIMR: QIMR Berghofer Medical Research Institute)H-Index: 7
#2Neda Jahanshad (SC: University of Southern California)H-Index: 42
Last. Mary Agnes B. McMahon (SC: University of Southern California)
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INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with hu...
#1Shuang GaoH-Index: 2
#2Vince D. CalhounH-Index: 93
Last. Jing Sui
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#1Lara M. Wierenga (LEI: Leiden University)H-Index: 4
#2Gaelle E. Doucet (ISMMS: Icahn School of Medicine at Mount Sinai)H-Index: 17
Last. Ole A. Andreassen (University of Oslo)H-Index: 89
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For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy indivi...
#1Ashkan Faghiri (UNM: University of New Mexico)
#1Ashkan Faghiri (UNM: University of New Mexico)H-Index: 1
Last. Adrian Preda (UNM: University of New Mexico)H-Index: 5
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Abstract Background Dynamic functional network connectivity (dFNC) of the brain has attracted considerable attention recently. Many approaches have been suggested to study dFNC with sliding window Pearson correlation (SWPC) being the most well-known. SWPC needs a relatively large sample size to reach a robust estimation but using large window sizes prevents us to detect rapid changes in dFNC. New method Here we first calculate the gradients of each time series pair and use the magnitude of these...
#1Robert Christian Wolf (Heidelberg University)H-Index: 31
#2Mahmoud Rashidi (Heidelberg University)H-Index: 1
Last. Dusan Hirjak (Heidelberg University)H-Index: 15
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Motor abnormalities in schizophrenia spectrum disorders (SSD) have increasingly attracted scientific interest in the past years. However, the neural mechanisms underlying parkinsonism in SSD are unclear. The present multimodal magnetic resonance imaging (MRI) study examined SSD patients with and without parkinsonism, as defined by a Simpson and Angus Scale (SAS) total score of >/=4 (SAS group, n = 22) or <4 (non-SAS group, n = 22). Parallel independent component analysis (p-ICA) was used to exam...