| Tracking whole-brain connectivity dynamics in the resting state EA Allen, E Damaraju, SM Plis, EB Erhardt, T Eichele, VD Calhoun Cerebral cortex 24 (3), 663-676, 2014 | 2990 | 2014 |
| Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls MR Arbabshirani, S Plis, J Sui, VD Calhoun Neuroimage 145, 137-165, 2017 | 943 | 2017 |
| Deep learning for neuroimaging: a validation study SM Plis, DR Hjelm, R Salakhutdinov, EA Allen, HJ Bockholt, JD Long, ... Frontiers in neuroscience 8, 229, 2014 | 678 | 2014 |
| Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data A Aliper, S Plis, A Artemov, A Ulloa, P Mamoshina, A Zhavoronkov Molecular pharmaceutics 13 (7), 2524-2530, 2016 | 631 | 2016 |
| Analysis of multimodal neuroimaging data F Biessmann, S Plis, FC Meinecke, T Eichele, KR Muller IEEE reviews in biomedical engineering 4, 26-58, 2011 | 193 | 2011 |
| Restricted Boltzmann machines for neuroimaging: an application in identifying intrinsic networks RD Hjelm, VD Calhoun, R Salakhutdinov, EA Allen, T Adali, SM Plis NeuroImage 96, 245-260, 2014 | 181 | 2014 |
| Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning A Abrol, Z Fu, M Salman, R Silva, Y Du, S Plis, V Calhoun Nature communications 12 (1), 353, 2021 | 176 | 2021 |
| Deep residual learning for neuroimaging: an application to predict progression to Alzheimer’s disease A Abrol, M Bhattarai, A Fedorov, Y Du, S Plis, V Calhoun, ... Journal of neuroscience methods 339, 108701, 2020 | 162 | 2020 |
| Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks H Jang, SM Plis, VD Calhoun, JH Lee NeuroImage 145, 314-328, 2017 | 141 | 2017 |
| Impact of autocorrelation on functional connectivity MR Arbabshirani, E Damaraju, R Phlypo, S Plis, E Allen, S Ma, ... Neuroimage 102, 294-308, 2014 | 116 | 2014 |
| Group-level component analyses of EEG: validation and evaluation RJ Huster, SM Plis, VD Calhoun Frontiers in neuroscience 9, 254, 2015 | 102 | 2015 |
| Learning to run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments Ł Kidziński, SP Mohanty, CF Ong, Z Huang, S Zhou, A Pechenko, ... The NIPS'17 Competition: Building Intelligent Systems, 121-153, 2018 | 100 | 2018 |
| Independent component analysis for brain fMRI does indeed select for maximal independence VD Calhoun, VK Potluru, R Phlypo, RF Silva, BA Pearlmutter, A Caprihan, ... PloS one 8 (8), e73309, 2013 | 95 | 2013 |
| COINSTAC: a privacy enabled model and prototype for leveraging and processing decentralized brain imaging data SM Plis, AD Sarwate, D Wood, C Dieringer, D Landis, C Reed, SR Panta, ... Frontiers in neuroscience 10, 365, 2016 | 94 | 2016 |
| Modular organization of functional network connectivity in healthy controls and patients with schizophrenia during the resting state Q Yu, SM Plis, EB Erhardt, EA Allen, J Sui, KA Kiehl, G Pearlson, ... Frontiers in systems neuroscience 5, 103, 2012 | 93 | 2012 |
| Quantitative EEG biomarkers for mild traumatic brain injury JD Lewine, S Plis, A Ulloa, C Williams, M Spitz, J Foley, K Paulson, ... Journal of Clinical Neurophysiology 36 (4), 298-305, 2019 | 89 | 2019 |
| Disrupted correlation between low frequency power and connectivity strength of resting state brain networks in schizophrenia Q Yu, J Sui, J Liu, SM Plis, KA Kiehl, G Pearlson, VD Calhoun Schizophrenia research 143 (1), 165-171, 2013 | 86 | 2013 |
| Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data SC Jun, JS George, J Paré-Blagoev, SM Plis, DM Ranken, DM Schmidt, ... NeuroImage 28 (1), 84-98, 2005 | 80 | 2005 |
| Automated interpretation of clinical electroencephalograms using artificial intelligence J Tveit, H Aurlien, S Plis, VD Calhoun, WO Tatum, DL Schomer, V Arntsen, ... JAMA neurology 80 (8), 805-812, 2023 | 73 | 2023 |
| Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation AD Sarwate, SM Plis, JA Turner, MR Arbabshirani, VD Calhoun Frontiers in neuroinformatics 8, 35, 2014 | 67 | 2014 |
Vince D. CalhounDirector-Translational Research in Neuroimaging and Data Science (TReNDS;GSU/GAtech/Emory)Verified email at gsu.edu
