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Gopikrishna Deshpande
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2020 – today
- 2024
- [j30]Gopikrishna Deshpande
, Janzaib Masood
Interpretable Deep Learning for Neuroimaging-Based Diagnostic Classification. IEEE Access 12: 55474-55490 (2024) - 2022
- [j29]Adam M. Goodman
Stress-Induced Changes in Effective Connectivity During Regulation of the Emotional Response to Threat. Brain Connect. 12(7): 629-638 (2022) - [j28]Gopikrishna Deshpande
Functional parcellation of the hippocampus based on its layer-specific connectivity with default mode and dorsal attention networks. NeuroImage 254: 119078 (2022) - 2021
- [j27]Madhura Ingalhalikar
Functional Connectivity-Based Prediction of Autism on Site Harmonized ABIDE Dataset. IEEE Trans. Biomed. Eng. 68(12): 3628-3637 (2021) - [c6]Da Yan, Shengbin Wu, Mirza Tanzim Sami, Abdullateef Ibrahim Almudaifer, Zhe Jiang
Improving Brain Dysfunction Prediction by GAN: A Functional-Connectivity Generator Approach. IEEE BigData 2021: 1514-1522 - [c5]Yueen Ma, Da Yan, Cheng Long, D. Rangaprakash, Gopikrishna Deshpande
Predicting Autism Spectrum Disorder from Brain Imaging Data by Graph Convolutional Network. IJCNN 2021: 1-8 - 2020
- [j26]D. Rangaprakash, Toluwanimi Odemuyiwa, D. Narayana Dutt, Gopikrishna Deshpande
Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment. Brain Informatics 7(1): 19 (2020) - [j25]N. Chaitra
Diagnostic prediction of autism spectrum disorder using complex network measures in a machine learning framework. Biomed. Signal Process. Control. 62: 102099 (2020) - [j24]Mohammed A. Syed
DisConICA: a Software Package for Assessing Reproducibility of Brain Networks and their Discriminability across Disorders. Neuroinformatics 18(1): 87-107 (2020)
2010 – 2019
- 2019
- [j23]Sinan Zhao, D. Rangaprakash
Deterioration from healthy to mild cognitive impairment and Alzheimer's disease mirrored in corresponding loss of centrality in directed brain networks. Brain Informatics 6(1): 8 (2019) - 2018
- [j22]Xinyu Zhao, D. Rangaprakash, Bowen Yuan, Thomas S. Denney Jr., Jeffrey S. Katz, Michael N. Dretsch, Gopikrishna Deshpande
Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning. Frontiers Appl. Math. Stat. 4: 25 (2018) - [j21]Jing Zhang
Probabilistic Methods in Computational Neuroscience. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 535-536 (2018) - 2017
- [j20]Karthik Ramakrishnan Sreenivasan, Xiaowei Zhuang, Sarah J. Banks
Olfactory Network Differences in Master Sommeliers: Connectivity Analysis Using Granger Causality and Graph Theoretical Approach. Brain Connect. 7(2): 123-136 (2017) - [j19]Sreenath P. Kyathanahally
Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data. Frontiers Neuroinformatics 11: 74 (2017) - [j18]Sreenath P. Kyathanahally
A Realistic Framework for Investigating Decision Making in the Brain With High Spatiotemporal Resolution Using Simultaneous EEG/fMRI and Joint ICA. IEEE J. Biomed. Health Informatics 21(3): 814-825 (2017) - 2016
- [j17]Benjamin M. Hampstead
Patterns of effective connectivity during memory encoding and retrieval differ between patients with mild cognitive impairment and healthy older adults. NeuroImage 124: 997-1008 (2016) - [j16]Jennifer L. Robinson, Nouha Salibi, Gopikrishna Deshpande
Functional connectivity of the left and right hippocampi: Evidence for functional lateralization along the long-axis using meta-analytic approaches and ultra-high field functional neuroimaging. NeuroImage 135: 64-78 (2016) - 2015
- [j15]Yunzhi Wang, Veena Chattaraman, Hyejeong Kim, Gopikrishna Deshpande
Predicting Purchase Decisions Based on Spatio-Temporal Functional MRI Features Using Machine Learning. IEEE Trans. Auton. Ment. Dev. 7(3): 248-255 (2015) - [j14]Gopikrishna Deshpande
Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data. IEEE Trans. Cybern. 45(12): 2668-2679 (2015) - [j13]Karthik Ramakrishnan Sreenivasan, Martin Havlicek, Gopikrishna Deshpande
Nonparametric Hemodynamic Deconvolution of fMRI Using Homomorphic Filtering. IEEE Trans. Medical Imaging 34(5): 1155-1163 (2015) - [c4]Guo-Rong Wu, Gopikrishna Deshpande
Retrieving the Hemodynamic Response Function in resting state fMRI: Methodology and application. EMBC 2015: 6050-6053 - [c3]Vajarala Ashikh, Gopikrishna Deshpande
Clustering of dynamic functional connectivity features obtained from functional Magnetic Resonance Imaging data. ICACCI 2015: 308-312 - 2014
- [j12]Dimitrios Kapogiannis, Gopikrishna Deshpande
Brain Networks Shaping Religious Belief. Brain Connect. 4(1): 70-79 (2014) - [j11]Hao Jia, Xiaoping Hu
Behavioral Relevance of the Dynamics of the Functional Brain Connectome. Brain Connect. 4(9): 741-759 (2014) - [j10]Muriah D. Wheelock
Threat-related learning relies on distinct dorsal prefrontal cortex network connectivity. NeuroImage 102: 904-912 (2014) - 2013
- [j9]D. Rangaprakash
Phase Synchronization in Brain Networks derived from Correlation between Probabilities of Recurrences in Functional MRI Data. Int. J. Neural Syst. 23(2) (2013) - 2012
- [j8]Gopikrishna Deshpande
Investigating Effective Brain Connectivity from fMRI Data: Past Findings and Current Issues with Reference to Granger Causality Analysis. Brain Connect. 2(5): 235-245 (2012) - 2011
- [j7]Gopikrishna Deshpande
Instantaneous and causal connectivity in resting state brain networks derived from functional MRI data. NeuroImage 54(2): 1043-1052 (2011) - [j6]Simon Lacey, Henrik Hagtvedt
Art for reward's sake: Visual art recruits the ventral striatum. NeuroImage 55(1): 420-433 (2011) - [j5]Krish Sathian
Dual pathways for haptic and visual perception of spatial and texture information. NeuroImage 57(2): 462-475 (2011) - 2010
- [j4]Gopikrishna Deshpande
Object familiarity modulates effective connectivity during haptic shape perception. NeuroImage 49(3): 1991-2000 (2010) - [j3]Gopikrishna Deshpande
Effect of hemodynamic variability on Granger causality analysis of fMRI. NeuroImage 52(3): 884-896 (2010) - [j2]Gopikrishna Deshpande
Assessing and Compensating for Zero-Lag Correlation Effects in Time-Lagged Granger Causality Analysis of fMRI. IEEE Trans. Biomed. Eng. 57(6): 1446-1456 (2010)
2000 – 2009
- 2008
- [j1]Gopikrishna Deshpande
Effective connectivity during haptic perception: A study using Granger causality analysis of functional magnetic resonance imaging data. NeuroImage 40(4): 1807-1814 (2008) - 2006
- [c2]Gopikrishna Deshpande
Directed Transfer Function Analysis of fMRI Data to Investigate Network Dynamics. EMBC 2006: 671-674 - [c1]Gopikrishna Deshpande, Stephen LaConte, Scott Peltier, Xiaoping Hu:
Connectivity Analysis of Human Functional MRI Data: From Linear to Nonlinear and Static to Dynamic. MIAR 2006: 17-24
Coauthor Index
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last updated on 2024-10-23 20:32 CEST by the dblp team
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