Aberrant hemodynamic responses in autism: Implications for resting state fMRI functional connectivity studies

由 Yan, Wenjing, Rangaprakash, D., Deshpande, Gopikrishna
發表在 Neuroimage Clin (2018)

Estimated hemodynamic response function parameters obtained from resting state BOLD fMRI signals in subjects with autism spectrum disorder and matched healthy subjects

由 Yan, Wenjing, Rangaprakash, D., Deshpande, Gopikrishna
發表在 Data Brief (2018)

Deterioration from healthy to mild cognitive impairment and Alzheimer’s disease mirrored in corresponding loss of centrality in directed brain networks

由 Zhao, Sinan, Rangaprakash, D., Liang, Peipeng, Deshpande, Gopikrishna
發表在 Brain Inform (2019)

Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment

由 Rangaprakash, D., Odemuyiwa, Toluwanimi, Narayana Dutt, D., Deshpande, Gopikrishna
發表在 Brain Inform (2020)

Investigating Focal Connectivity Deficits in Alzheimer's Disease Using Directional Brain Networks Derived from Resting-State fMRI

由 Zhao, Sinan, Rangaprakash, D, Venkataraman, Archana, Liang, Peipeng, Deshpande, Gopikrishna
發表在 Front Aging Neurosci (2017)

A New Generation of Brain-Computer Interfaces Driven by Discovery of Latent EEG-fMRI Linkages Using Tensor Decomposition

由 Deshpande, Gopikrishna, Rangaprakash, D., Oeding, Luke, Cichocki, Andrzej, Hu, Xiaoping P.
發表在 Front Neurosci (2017)

Parameterized hemodynamic response function data of healthy individuals obtained from resting-state functional MRI in a 7T MRI scanner

由 Rangaprakash, D., Wu, Guo-Rong, Marinazzo, Daniele, Hu, Xiaoping, Deshpande, Gopikrishna
發表在 Data Brief (2018)

Dynamics of Segregation and Integration in Directional Brain Networks: Illustration in Soldiers With PTSD and Neurotrauma

由 Rangaprakash, D., Dretsch, Michael N., Katz, Jeffrey S., Denney Jr., Thomas S., Deshpande, Gopikrishna
發表在 Front Neurosci (2019)

FMRI hemodynamic response function (HRF) as a novel marker of brain function: applications for understanding obsessive-compulsive disorder pathology and treatment response

由 Rangaprakash, D, Tadayonnejad, Reza, Deshpande, Gopikrishna, O’Neill, Joseph, Feusner, Jamie D
發表在 Brain Imaging Behav (2021)

Hemodynamic response function parameters obtained from resting-state functional MRI data in soldiers with trauma

由 Rangaprakash, D., Dretsch, Michael N., Yan, Wenjing, Katz, Jeffrey S., Denney, Thomas S., Deshpande, Gopikrishna
發表在 Data Brief (2017)

Hemodynamic variability in soldiers with trauma: Implications for functional MRI connectivity studies

由 Rangaprakash, D., Dretsch, Michael N., Yan, Wenjing, Katz, Jeffrey S., Denney, Thomas S., Deshpande, Gopikrishna
發表在 Neuroimage Clin (2017)

Identifying neuropsychiatric disorders using unsupervised clustering methods: Data and code

由 Zhao, Xinyu, Rangaprakash, D., Denney, Thomas S., Katz, Jeffrey S., Dretsch, Michael N., Deshpande, Gopikrishna
發表在 Data Brief (2018)

Identifying disease foci from static and dynamic effective connectivity networks: Illustration in soldiers with trauma

由 Rangaprakash, D., Dretsch, Michael N., Venkataraman, Archana, Katz, Jeffrey S., Denney, Thomas S., Deshpande, Gopikrishna
發表在 Hum Brain Mapp (2017)

Supervised machine learning for diagnostic classification from large-scale neuroimaging datasets

由 Lanka, Pradyumna, Rangaprakash, D, Dretsch, Michael N, Katz, Jeffrey S, Denney, Thomas S, Deshpande, Gopikrishna
發表在 Brain Imaging Behav (2020)

Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning

由 Zhao, Xinyu, Rangaprakash, D., Yuan, Bowen, Denney, Thomas S., Katz, Jeffrey S., Dretsch, Michael N., Deshpande, Gopikrishna
發表在 Front Appl Math Stat (2018)

Dynamic brain connectivity is a better predictor of PTSD than static connectivity

由 Jin, Changfeng, Jia, Hao, Lanka, Pradyumna, Rangaprakash, D, Li, Lingjiang, Liu, Tianming, Hu, Xiaoping, Deshpande, Gopikrishna
發表在 Hum Brain Mapp (2017)

Strength and Temporal Variance of the Default Mode Network to Investigate Chronic Mild Traumatic Brain Injury in Service Members with Psychological Trauma

由 Dretsch, Michael N, Rangaprakash, D, Katz, Jeffrey S, Daniel, Thomas A, Goodman, Adam M, Denney, Thomas S, Deshpande, Gopikrishna
發表在 J Exp Neurosci (2019)

MALINI (Machine Learning in NeuroImaging): A MATLAB toolbox for aiding clinical diagnostics using resting-state fMRI data

由 Lanka, Pradyumna, Rangaprakash, D., Gotoor, Sai Sheshan Roy, Dretsch, Michael N., Katz, Jeffrey S., Denney, Thomas S., Deshpande, Gopikrishna
發表在 Data Brief (2020)

Aberrant Dynamic Connectivity for Fear Processing in Anorexia Nervosa and Body Dysmorphic Disorder

由 Rangaprakash, D., Bohon, Cara, Lawrence, Katherine E., Moody, Teena, Morfini, Francesca, Khalsa, Sahib S., Strober, Michael, Feusner, Jamie D.
發表在 Front Psychiatry (2018)

DisConICA: A Software Package for Assessing Reproducibility of Brain Networks and their Discriminability across Disorders

由 Syed, Mohammed A., Yang, Zhi, Rangaprakash, D., Hu, Xiaoping, Dretsch, Michael N., Katz, Jeffrey S., Denney, Thomas S., Deshpande, Gopikrishna
發表在 Neuroinformatics (2020)