Raju S. Bapi
Affiliations: | University of Hyderabad, Hyderabad, Telangana, India |
Area:
Neural Networks, Sequence learning, fMRI, BioInformaticsGoogle:
"Raju Bapi"Mean distance: 14.14 (cluster 29) | S | N | B | C | P |
Children
Sign in to add traineeKrishna P. Miyapuram | grad student | University of Hyderabad | |
V. S. Chandrasekhar Pammi | grad student | University of Hyderabad | |
Rakesh Sengupta | grad student | University of Hyderabad |
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Publications
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Bera K, Shukla A, Bapi RS. (2021) Cognitive and Motor Learning in Internally-Guided Motor Skills. Frontiers in Psychology. 12: 604323 |
Bera K, Shukla A, Bapi RS. (2021) Motor Chunking in Internally Guided Sequencing. Brain Sciences. 11 |
Wutz A, Shukla A, Bapi RS, et al. (2015) Expansion and Compression of Time Correlate with Information Processing in an Enumeration Task. Plos One. 10: e0135794 |
Wutz A, Shukla A, Bapi RS, et al. (2014) Subjective Distortions of Time Influence Rapid Information Accrual Procedia - Social and Behavioral Sciences. 126: 127-128 |
Miyapuram KP, Pamnani U, Doya K, et al. (2014) Inter Subject Correlation of Brain Activity during Visuo-Motor Sequence learning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8834: 35-41 |
Pammi VS, Miyapuram KP, Ahmed, et al. (2012) Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. Neuroimage. 59: 1180-9 |
Miyapuram KP, Doya K, Bapi RS. (2011) Chunking During Learning of Visuomotor Sequences with Spatial and Arbitrary Rules: Preliminary Findings Psychological Studies. 57: 22-28 |
Chakravarthy VS, Joseph D, Bapi RS. (2010) What do the basal ganglia do? A modeling perspective. Biological Cybernetics. 103: 237-53 |
Singh V, Miyapuram KP, Bapi RS. (2007) Detection of cognitive states from fMRI data using machine learning techniques Ijcai International Joint Conference On Artificial Intelligence. 587-592 |
Bapi RS, Miyapuram KP, Graydon FX, et al. (2006) fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32: 714-27 |