| Computation through neural population dynamics S Vyas, MD Golub, D Sussillo, KV Shenoy Annual review of neuroscience 43 (1), 249-275, 2020 | 551 | 2020 |
| MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans AM Mendrik, KL Vincken, HJ Kuijf, M Breeuwer, WH Bouvy, J De Bresser, ... Computational intelligence and neuroscience 2015 (1), 813696, 2015 | 283 | 2015 |
| Unsupervised discovery of demixed, low-dimensional neural dynamics across multiple timescales through tensor component analysis AH Williams, TH Kim, F Wang, S Vyas, SI Ryu, KV Shenoy, M Schnitzer, ... Neuron 98 (6), 1099-1115. e8, 2018 | 274 | 2018 |
| Accurate estimation of neural population dynamics without spike sorting EM Trautmann, SD Stavisky, S Lahiri, KC Ames, MT Kaufman, DJ O’Shea, ... Neuron 103 (2), 292-308. e4, 2019 | 245 | 2019 |
| Neural population dynamics underlying motor learning transfer S Vyas, N Even-Chen, SD Stavisky, SI Ryu, P Nuyujukian, KV Shenoy Neuron 97 (5), 1177-1186. e3, 2018 | 134 | 2018 |
| In vivo interrogation of spinal mechanosensory circuits AJ Christensen, SM Iyer, A Francois, S Vyas, C Ramakrishnan, S Vesuna, ... Cell reports 17 (6), 1699-1710, 2016 | 79 | 2016 |
| Cortical preparatory activity indexes learned motor memories X Sun, DJ O’Shea, MD Golub, EM Trautmann, S Vyas, SI Ryu, KV Shenoy Nature 602 (7896), 274-279, 2022 | 76* | 2022 |
| Causal role of motor preparation during error-driven learning S Vyas, DJ O’Shea, SI Ryu, KV Shenoy Neuron 106 (2), 329-339. e4, 2020 | 62 | 2020 |
| Estimating physiological skin parameters from hyperspectral signatures S Vyas, A Banerjee, P Burlina Journal of biomedical optics 18 (5), 057008-057008, 2013 | 41 | 2013 |
| Structure and variability of delay activity in premotor cortex N Even-Chen, B Sheffer, S Vyas, SI Ryu, KV Shenoy PLoS computational biology 15 (2), e1006808, 2019 | 33 | 2019 |
| Large-scale high-density brain-wide neural recording in nonhuman primates EM Trautmann, JK Hesse, GM Stine, R Xia, S Zhu, DJ O’Shea, B Karsh, ... BioRxiv, 2023.02. 01.526664, 2023 | 28 | 2023 |
| Non-invasive estimation of skin thickness from hyperspectral imaging and validation using echography S Vyas, J Meyerle, P Burlina Computers in biology and medicine 57, 173-181, 2015 | 27 | 2015 |
| High-fidelity musculoskeletal modeling reveals that motor planning variability contributes to the speed-accuracy tradeoff M Al Borno, S Vyas, KV Shenoy, SL Delp Elife 9, e57021, 2020 | 23* | 2020 |
| Direct neural perturbations reveal a dynamical mechanism for robust computation DJ O’Shea, L Duncker, W Goo, X Sun, S Vyas, EM Trautmann, I Diester, ... bioRxiv, 2022.12. 16.520768, 2022 | 19 | 2022 |
| Computational modeling of skin reflectance spectra for biological parameter estimation through machine learning S Vyas, H Van Nguyen, P Burlina, A Banerjee, L Garza, R Chellappa Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2012 | 13 | 2012 |
| Hyperspectral signature analysis of skin parameters S Vyas, A Banerjee, L Garza, S Kang, P Burlina Medical Imaging 2013: Computer-Aided Diagnosis 8670, 867002, 2013 | 12 | 2013 |
| Neuronal complexity in subthalamic nucleus is reduced in Parkinson’s disease S Vyas, H Huang, JT Gale, SV Sarma, EB Montgomery IEEE Transactions on Neural Systems and Rehabilitation Engineering 24 (1), 36-45, 2015 | 11 | 2015 |
| Medical Imaging 2013: Computer‐Aided Diagnosis S Vyas, A Banerjee, L Garza, S Kang, P Burlina International Society for Optics and Photonics, 8670, 2013 | 10 | 2013 |
| Machine learning methods for in vivo skin parameter estimation S Vyas, A Banerjee, P Burlina Proceedings of the 26th IEEE International Symposium on Computer-Based …, 2013 | 9 | 2013 |
| Intraoperative ultrasound to stereocamera registration using interventional photoacoustic imaging S Vyas, S Su, R Kim, N Kuo, RH Taylor, JU Kang, EM Boctor Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and …, 2012 | 9 | 2012 |
Krishna V ShenoyStanford and Howard Hughes Medical InstituteVerified email at stanford.edu
