Krishna V. Shenoy

31.2k citations

207 papers · 16.6k indexed · 10 hit papers · h-index 68

Cognitive Neuroscience top 0.05%
- EEG and Brain-Computer Interfaces 154
- Neural dynamics and brain function 91
- Motor Control and Adaptation 27
- Visual perception and processing mechanisms 13
Cellular and Molecular Neuroscience top 0.05%
- Neuroscience and Neural Engineering 131
Human-Computer Interaction top 0.5%
Computational Mathematics top 2%
Neurology top 1%
Electrical and Electronic Engineering
- Advanced Memory and Neural Computing 46
Biomedical Engineering
- Muscle activation and electromyography studies 46
Artificial Intelligence
- Neural Networks and Applications 11

Co-authors: Mark M. Churchland Stephen I. Ryu Matthew T. Kaufman Paul Nuyujukian Gopal Santhanam David Sussillo Byron M. Yu John P. Cunningham
Cited by: Cognitive Neuroscience Cellular and Molecular Neuroscience Human-Computer Interaction
Journals: Nature (8 papers)Science (1 paper)Cell (2 papers)
Partner nations: United States United Kingdom Russia

In The Last Decade

Krishna V. Shenoy

204 papers receiving 16.3k citations

Hit Papers

10 papers align trajectories log scale

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

2023 Nature
2022 Nature Neuroscience
2021 Nature
2020 Annual Review of Neuroscience
2018 Nature Methods
2017 eLife
2014 Nature Neuroscience
2013 Annual Review of Neuroscience
2013 Nature
2012 Nature

Peers

Countries citing papers authored by Krishna V. Shenoy

Since Specialization

Citations

This map shows the geographic impact of Krishna V. Shenoy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Krishna V. Shenoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krishna V. Shenoy more than expected).

Fields of papers citing papers by Krishna V. Shenoy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Krishna V. Shenoy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Krishna V. Shenoy. The network helps show where Krishna V. Shenoy may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Krishna V. Shenoy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Krishna V. Shenoy Line = papers co-authored together Krishna V. Shenoy links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	The dynamics and geometry of choice in the premotor cortex Nature ·Mikhail Genkin,Krishna V. Shenoy,Chandramouli Chandrasekaran,Tatiana A. Engel	2025	6
2	Initial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex Nature Communications ·Pierre Boucher,Tian Wang,Laura Carceroni,Gary A. Kane,Krishna V. Shenoy,Chandramouli Chandrasekaran	2023	10
3	Cell-type-specific population dynamics of diverse reward computations Cell ·Emily Sylwestrak,YoungJu Jo,Sam Vesuna,Xiao Wang,Blake Holcomb,Rebecca H. Tien,Doo Kyung Kim,Lief E. Fenno,Charu Ramakrishnan,William E. Allen,Ritchie Chen,Krishna V. Shenoy,David Sussillo,Karl Deisseroth	2022	33
4	Decoding and perturbing decision states in real time Nature ·Diogo Peixoto,Jessica R. Verhein,Roozbeh Kiani,Jonathan C. Kao,Paul Nuyujukian,Chandramouli Chandrasekaran,Julian Brown,Sania Fong,Stephen I. Ryu,Krishna V. Shenoy,William T. Newsome	2021	52
5	Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex eLife ·Eric Lee,Hymavathy Balasubramanian,Alexandra Tsolias,Stephanie Anakwe,Maria Medalla,Krishna V. Shenoy,Chandramouli Chandrasekaran	2021	42
6	A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces Nature Biomedical Engineering ·Samuel R. Nason,Alex K. Vaskov,Matthew S. Willsey,Elissa Welle,Hyochan An,Philip P. Vu,Autumn J. Bullard,Chrono S. Nu,Jonathan C. Kao,Krishna V. Shenoy,Taekwang Jang,Hun-Seok Kim,David Blaauw,Parag G. Patil,Cynthia A. Chestek	2020	78
7	Organizing recurrent network dynamics by task-computation to enable continual learning UCL Discovery (University College London) ·Lea Duncker,Laura Driscoll,Krishna V. Shenoy,Maneesh Sahani,David Sussillo	2020	20
8	Principled BCI Decoder Design and Parameter Selection Using a Feedback Control Model Scientific Reports ·Francis R. Willett,Daniel R. Young,Brian Murphy,William D. Memberg,Christine H Blabe,Chethan Pandarinath,Sergey D. Stavisky,Paymon G. Rezaii,Jad Saab,Benjamin L. Walter,Jennifer A. Sweet,Jonathan P. Miller,Jaimie M. Henderson,Krishna V. Shenoy,John D. Simeral,Beata Jarosiewicz,Leigh R. Hochberg,Robert F. Kirsch,A. Bolu Ajiboye	2019	30
9	Frequency Shifts and Depth Dependence of Premotor Beta Band Activity during Perceptual Decision-Making Journal of Neuroscience ·Chandramouli Chandrasekaran,Iliana E. Bray,Krishna V. Shenoy	2019	21
10	Development of an optogenetic toolkit for neural circuit dissection in squirrel monkeys Scientific Reports ·Daniel J. O’Shea,Paul Kalanithi,Emily Ferenczi,Brian Hsueh,Chandramouli Chandrasekaran,Werapong Goo,Ilka Diester,Charu Ramakrishnan,Matthew T. Kaufman,Stephen I. Ryu,Kristen W. Yeom,Karl Deisseroth,Krishna V. Shenoy	2018	22
11	Closed-loop cortical control of virtual reach and posture using Cartesian and joint velocity commands Journal of Neural Engineering ·Daniel R. Young,Francis R. Willett,William D. Memberg,Brian Murphy,Paymon G. Rezaii,Benjamin L. Walter,Julia Sweet,Jonathan P. Miller,Krishna V. Shenoy,Leigh R. Hochberg,Robert F. Kirsch,A. Bolu Ajiboye	2018	17
12	A Comparison of Intention Estimation Methods for Decoder Calibration in Intracortical Brain–Computer Interfaces IEEE Transactions on Biomedical Engineering ·Francis R. Willett,Brian Murphy,Daniel R. Young,William D. Memberg,Christine H Blabe,Chethan Pandarinath,Brian Franco,Jad Saab,Benjamin L. Walter,Jennifer A. Sweet,Jonathan P. Miller,Jaimie M. Henderson,Krishna V. Shenoy,John D. Simeral,Beata Jarosiewicz,Leigh R. Hochberg,Robert F. Kirsch,A. Bolu Ajiboye	2017	19
13	ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings Journal of Neural Engineering ·Daniel J. O’Shea,Krishna V. Shenoy	2017	26
14	Augmenting intracortical brain-machine interface with neurally driven error detectors Journal of Neural Engineering ·Nir Even-Chen,Sergey D. Stavisky,Jonathan C. Kao,Stephen I. Ryu,Krishna V. Shenoy	2017	19
15	Signal-independent noise in intracortical brain–computer interfaces causes movement time properties inconsistent with Fitts’ law Journal of Neural Engineering ·Francis R. Willett,Brian Murphy,William D. Memberg,Christine H Blabe,Chethan Pandarinath,Benjamin L. Walter,Jennifer A. Sweet,Jonathan P. Miller,Jaimie M. Henderson,Krishna V. Shenoy,Leigh R. Hochberg,Robert F. Kirsch,A. Bolu Ajiboye	2017	11
16	The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type eNeuro ·Matthew T. Kaufman,Jeffrey Seely,David Sussillo,Stephen I. Ryu,Krishna V. Shenoy,Mark M. Churchland	2016	133
17	The need for calcium imaging in nonhuman primates: New motor neuroscience and brain-machine interfaces Experimental Neurology ·Daniel J. O’Shea,Eric M. Trautmann,Chandramouli Chandrasekaran,Sergey D. Stavisky,Jonathan C. Kao,Maneesh Sahani,Stephen I. Ryu,Karl Deisseroth,Krishna V. Shenoy	2016	32
18	Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1 PLoS Computational Biology ·Jeffrey Seely,Matthew T. Kaufman,Stephen I. Ryu,Krishna V. Shenoy,John P. Cunningham,Mark M. Churchland	2016	37
19	High-dimensional neural spike train analysis with generalized count linear dynamical systems Neural Information Processing Systems ·Yuanjun Gao,Lars Buesing,Krishna V. Shenoy,John P. Cunningham	2015	11
20	A Brain-Machine Interface with an Innovative Spiking Neural Network Decoder Open Repository and Bibliography (University of Liège) ·Julie Dethier,Paul Nuyujukian,Shauki Elassaad,Krishna V. Shenoy,Kwabena Boahen	2011	1

About Krishna V. Shenoy

Krishna V. Shenoy is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computational Mathematics, having authored 207 papers that have together received 16.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (154 papers), Neuroscience and Neural Engineering (131 papers), Neural dynamics and brain function (91 papers), Advanced Memory and Neural Computing (46 papers), Muscle activation and electromyography studies (46 papers), Motor Control and Adaptation (27 papers), Visual perception and processing mechanisms (13 papers) and Neural Networks and Applications (11 papers). The work is most often cited by research in Cognitive Neuroscience (14.5k citations), Cellular and Molecular Neuroscience (8.1k citations) and Human-Computer Interaction (512 citations). Krishna V. Shenoy has collaborated with scholars based in United States, United Kingdom and Russia. Frequent co-authors include Mark M. Churchland, Stephen I. Ryu, Stephen I. Ryu, Matthew T. Kaufman, Paul Nuyujukian, Gopal Santhanam, David Sussillo, Byron M. Yu, John P. Cunningham and Maneesh Sahani. Their work appears in journals such as Nature, Science and Cell.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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