Mark Churchland

Mark Churchland

Columbia University in the City of New York

H-index: 43

North America-United States

About Mark Churchland

Mark Churchland, With an exceptional h-index of 43 and a recent h-index of 34 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of Neuroscience.

His recent articles reflect a diverse array of research interests and contributions to the field:

Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Identifying Interpretable Latent Factors with Sparse Component Analysis

Formation of Anisotropic Conducting Interlayer for High‐Resolution Epidermal Electromyography Using Mixed‐Conducting Particulate Composite

Preparatory activity and the expansive null-space

Simple decoding of behavior from a complicated neural manifold

The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks

Large-scale high-density brain-wide neural recording in nonhuman primates

Systems, methods, and media for decoding observed spike counts for spiking cells

Mark Churchland Information

University

Position

Professor of Neuroscience

Citations(all)

11423

Citations(since 2020)

6152

Cited By

7699

hIndex(all)

43

hIndex(since 2020)

34

i10Index(all)

54

i10Index(since 2020)

47

Email

University Profile Page

Columbia University in the City of New York

Google Scholar

View Google Scholar Profile

Mark Churchland Skills & Research Interests

Neuroscience

Top articles of Mark Churchland

Title

Journal

Author(s)

Publication Date

Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Advances in Neural Information Processing Systems

Yizi Zhang

Tianxiao He

Julien Boussard

Charles Windolf

Olivier Winter

...

2024/2/13

Identifying Interpretable Latent Factors with Sparse Component Analysis

bioRxiv

Andrew J Zimnik

K Cora Ames

Xinyue An

Laura Driscoll

Antonio H Lara

...

2024/2/6

Formation of Anisotropic Conducting Interlayer for High‐Resolution Epidermal Electromyography Using Mixed‐Conducting Particulate Composite

Advanced Science

Zifang Zhao

Han Yu

Duncan J Wisniewski

Claudia Cea

Liang Ma

...

2024/4/10

Preparatory activity and the expansive null-space

Mark M Churchland

Krishna V Shenoy

2024/3/5

Simple decoding of behavior from a complicated neural manifold

BioRxiv

Sean M Perkins

John P Cunningham

Qi Wang

Mark M Churchland

2023/4/6

The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks

Neuron

Brian DePasquale

David Sussillo

LF Abbott

Mark M Churchland

2023/3/1

Large-scale high-density brain-wide neural recording in nonhuman primates

bioRxiv

Eric M Trautmann

Janis K Hesse

Gabriel M Stine

Ruobing Xia

Shude Zhu

...

2023/2/3

Systems, methods, and media for decoding observed spike counts for spiking cells

2023/11/23

DREDge: robust motion correction for high-density extracellular recordings across species

bioRxiv

Charlie Windolf

Han Yu

Angelique C Paulk

Domokos Meszéna

William Muñoz

...

2023/10/29

Krishna V. Shenoy (1968–2023)

Nature Neuroscience

Mark M Churchland

Paul Nuyujukian

2023/5

Cortical control of virtual self-motion using task-specific subspaces

Journal of Neuroscience

Karen E Schroeder

Sean M Perkins

Qi Wang

Mark M Churchland

2022/1/12

Flexible neural control of motor units

Nature neuroscience

Najja J Marshall

Joshua I Glaser

Eric M Trautmann

Elom A Amematsro

Sean M Perkins

...

2022/11

Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity

Elife

Shreya Saxena

Abigail A Russo

John Cunningham

Mark M Churchland

2022/5/27

Neural latents benchmark'21: evaluating latent variable models of neural population activity

arXiv preprint arXiv:2109.04463

Felix Pei

Joel Ye

David Zoltowski

Anqi Wu

Raeed H Chowdhury

...

2021/9/9

Independent generation of sequence elements by motor cortex

Nature neuroscience

Andrew J Zimnik

Mark M Churchland

2021/3

Postural control of arm and fingers through integration of movement commands

Elife

Scott T Albert

Alkis M Hadjiosif

Jihoon Jang

Andrew J Zimnik

Demetris S Soteropoulos

...

2020/2/11

Neural control of virtual ego-motion enabled by an opportunistic decoding strategy

bioRxiv

Karen E Schroeder

Sean M Perkins

Qi Wang

Mark M Churchland

2020

Neural trajectories in the supplementary motor area and motor cortex exhibit distinct geometries, compatible with different classes of computation

Neuron

Abigail A Russo

Ramin Khajeh

Sean R Bittner

Sean M Perkins

John P Cunningham

...

2020/8/19

Generation of rapid sequences by motor cortex

bioRxiv

Andrew J Zimnik

Mark M Churchland

2020/6/10

See List of Professors in Mark Churchland University(Columbia University in the City of New York)

Co-Authors

H-index: 111
L F Abbott

L F Abbott

Columbia University in the City of New York

H-index: 83
Krishna V Shenoy

Krishna V Shenoy

Stanford University

H-index: 79
Stephen G Lisberger

Stephen G Lisberger

Duke University

H-index: 61
Stephen Ryu

Stephen Ryu

Stanford University

H-index: 53
Maneesh Sahani

Maneesh Sahani

University College London

H-index: 49
John Cunningham

John Cunningham

Columbia University in the City of New York

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