| Closed-loop decoder adaptation shapes neural plasticity for skillful neuroprosthetic control AL Orsborn, HG Moorman, SA Overduin, MM Shanechi, DF Dimitrov, ... Neuron 82 (6), 1380-1393, 2014 | 274 | 2014 |
| Brain–machine interfaces from motor to mood MM Shanechi Nature neuroscience 22 (10), 1554-1564, 2019 | 222 | 2019 |
| Mood variations decoded from multi-site intracranial human brain activity OG Sani, Y Yang, MB Lee, HE Dawes, EF Chang, MM Shanechi Nature biotechnology 36 (10), 954-961, 2018 | 201 | 2018 |
| Direct electrical stimulation of lateral orbitofrontal cortex acutely improves mood in individuals with symptoms of depression VR Rao, KK Sellers, DL Wallace, MB Lee, M Bijanzadeh, OG Sani, ... Current Biology 28 (24), 3893-3902. e4, 2018 | 156 | 2018 |
| On the importance of phase in human speech recognition G Shi, MM Shanechi, P Aarabi IEEE transactions on audio, speech, and language processing 14 (5), 1867-1874, 2006 | 144 | 2006 |
| Robust brain-machine interface design using optimal feedback control modeling and adaptive point process filtering MM Shanechi, AL Orsborn, JM Carmena PLoS computational biology 12 (4), e1004730, 2016 | 122 | 2016 |
| Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification OG Sani, H Abbaspourazad, YT Wong, B Pesaran, MM Shanechi Nature Neuroscience 24 (1), 140-149, 2021 | 117 | 2021 |
| Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation Y Yang, S Qiao, OG Sani, JI Sedillo, B Ferrentino, B Pesaran, ... Nature biomedical engineering 5 (4), 324-345, 2021 | 116 | 2021 |
| Rapid control and feedback rates enhance neuroprosthetic control MM Shanechi, AL Orsborn, HG Moorman, S Gowda, S Dangi, ... Nature communications 8 (1), 13825, 2017 | 107 | 2017 |
| Neural population partitioning and a concurrent brain-machine interface for sequential motor function MM Shanechi, RC Hu, M Powers, GW Wornell, EN Brown, ZM Williams Nature neuroscience 15 (12), 1715-1722, 2012 | 98 | 2012 |
| A real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design MM Shanechi, ZM Williams, GW Wornell, RC Hu, M Powers, EN Brown PloS one 8 (4), e59049, 2013 | 91 | 2013 |
| A control-theoretic system identification framework and a real-time closed-loop clinical simulation testbed for electrical brain stimulation Y Yang, AT Connolly, MM Shanechi Journal of neural engineering 15 (6), 066007, 2018 | 84 | 2018 |
| A cortical–spinal prosthesis for targeted limb movement in paralysed primate avatars MM Shanechi, RC Hu, ZM Williams Nature communications 5 (1), 3237, 2014 | 76 | 2014 |
| Feedback-controlled parallel point process filter for estimation of goal-directed movements from neural signals MM Shanechi, GW Wornell, ZM Williams, EN Brown IEEE Transactions on Neural Systems and Rehabilitation Engineering 21 (1 …, 2012 | 66 | 2012 |
| Brain–machine interface control algorithms MM Shanechi IEEE Transactions on Neural Systems and Rehabilitation Engineering 25 (10 …, 2016 | 58 | 2016 |
| Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior H Abbaspourazad, M Choudhury, YT Wong, B Pesaran, MM Shanechi Nature communications 12 (1), 607, 2021 | 54 | 2021 |
| A brain-machine interface for control of medically-induced coma MM Shanechi, JJ Chemali, M Liberman, K Solt, EN Brown PLoS computational biology 9 (10), e1003284, 2013 | 54 | 2013 |
| Continuous closed-loop decoder adaptation with a recursive maximum likelihood algorithm allows for rapid performance acquisition in brain-machine interfaces S Dangi, S Gowda, HG Moorman, AL Orsborn, K So, M Shanechi, ... Neural computation 26 (9), 1811-1839, 2014 | 49 | 2014 |
| First-in-human prediction of chronic pain state using intracranial neural biomarkers P Shirvalkar, J Prosky, G Chin, P Ahmadipour, OG Sani, M Desai, ... Nature neuroscience 26 (6), 1090-1099, 2023 | 46 | 2023 |
| Dynamic network modeling and dimensionality reduction for human ECoG activity Y Yang, OG Sani, EF Chang, MM Shanechi Journal of neural engineering 16 (5), 056014, 2019 | 46 | 2019 |
