World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
65
Citations
19035
World Ranking
3084
National Ranking
1435

Computer Science

D-Index
59
Citations
17681
World Ranking
3368
National Ranking
1630

Overview

Stephen I. Ryu is affiliated with Stanford University in the United States. Their research primarily focuses on neuroscience and medicine, with subfields concentrating on cognitive neuroscience, surgery, pathology and forensic medicine, and biomedical engineering.

The main topics addressed in their body of work include:

  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Motor Control and Adaptation
  • Neural and Behavioral Psychology Studies
  • Spinal Fractures and Fixation Techniques
  • Spine and Intervertebral Disc Pathology
  • Cervical and Thoracic Myelopathy

Stephen I. Ryu has published multiple papers, with recent works including:

  • "Causal Role of Motor Preparation during Error-Driven Learning" (2020) in Neuron
  • "Learning leaves a memory trace in motor cortex" (2024) in Current Biology
  • "Structure in Neural Activity during Observed and Executed Movements Is Shared at the Neural Population Level, Not in Single Neurons" (2020) in Cell Reports
  • "Learning alters neural activity to simultaneously support memory and action" (2022) in bioRxiv (Cold Spring Harbor Laboratory)
  • "Skill-specific changes in cortical preparatory activity during motor learning" (2020) in bioRxiv (Cold Spring Harbor Laboratory)

Frequent co-authors in their research collaborations include:

  • Krishna V. Shenoy
  • Matthew D. Golub
  • Saurabh Vyas
  • Daniel J. O'Shea
  • Darby M. Losey

Stephen I. Ryu's publications are often found in journals such as:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Neuron
  • Current Biology
  • Cell Reports
  • Global Spine Journal

Best Publications

  • Neural population dynamics during reaching

    Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Justin D. Foster

  • Stimulus onset quenches neural variability: a widespread cortical phenomenon

    Mark M. Churchland;Byron M. Yu;Byron M. Yu;John P. Cunningham;Leo P. Sugrue;Leo P. Sugrue

  • A high-performance brain–computer interface

    Gopal Santhanam;Stephen I. Ryu;Byron M. Yu;Afsheen Afshar

  • Cortical activity in the null space: permitting preparation without movement

    Matthew T Kaufman;Mark M Churchland;Stephen I Ryu;Krishna V Shenoy

  • Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity

    Byron M Yu;John P Cunningham;Gopal Santhanam;Stephen I. Ryu

  • Neural constraints on learning

    Patrick T. Sadtler;Kristin M. Quick;Matthew D. Golub;Steven M. Chase

  • Inferring single-trial neural population dynamics using sequential auto-encoders.

    Chethan Pandarinath;Daniel J. O’Shea;Jasmine Collins;Rafal Jozefowicz;Rafal Jozefowicz

  • A high-performance neural prosthesis enabled by control algorithm design

    Vikash Gilja;Paul Nuyujukian;Cindy A Chestek;John P Cunningham;John P Cunningham

  • Neural Variability in Premotor Cortex Provides a Signature of Motor Preparation

    Mark M. Churchland;Byron M. Yu;Stephen I. Ryu;Gopal Santhanam

  • Cortical Preparatory Activity: Representation of Movement or First Cog in a Dynamical Machine?

    Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Stephen I. Ryu;Stephen I. Ryu

  • Image-guided hypo-fractionated stereotactic radiosurgery to spinal lesions.

    Stephen I. Ryu;Steven D. Chang;Daniel H Kim;Martin J. Murphy

  • Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex

    Cynthia A Chestek;Vikash Gilja;Paul Nuyujukian;Justin D Foster

  • Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

    Alex H. Williams;Tony Hyun Kim;Forea Wang;Saurabh Vyas

  • A theory of multineuronal dimensionality, dynamics and measurement

    Gao P;Trautmann E;Yu B;Santhanam G

  • Wireless Neural Recording With Single Low-Power Integrated Circuit

    R.R. Harrison;R.J. Kier;C.A. Chestek;V. Gilja

  • Single-Trial Neural Correlates of Arm Movement Preparation

    Afsheen Afshar;Gopal Santhanam;Byron M. Yu;Byron M. Yu;Stephen I. Ryu;Stephen I. Ryu

  • Accurate Estimation of Neural Population Dynamics without Spike Sorting.

    Eric M. Trautmann;Eric M. Trautmann;Sergey D. Stavisky;Subhaneil Lahiri;Katherine C. Ames;Katherine C. Ames

  • Learning by neural reassociation.

    Matthew D. Golub;Matthew D. Golub;Patrick T. Sadtler;Patrick T. Sadtler;Emily R. Oby;Emily R. Oby;Kristin M. Quick;Kristin M. Quick

  • The Largest Response Component in the Motor Cortex Reflects Movement Timing but Not Movement Type.

    Matthew T. Kaufman;Jeffrey S. Seely;David Sussillo;Stephen I. Ryu

  • Making brain-machine interfaces robust to future neural variability.

    David Sussillo;Sergey D. Stavisky;Jonathan C. Kao;Stephen I. Ryu;Stephen I. Ryu

  • Mixture of trajectory models for neural decoding of goal-directed movements

    Byron M. Yu;Caleb Kemere;Gopal Santhanam;Afsheen Afshar

Frequent Co-Authors

Krishna V. Shenoy
Krishna V. Shenoy Stanford University
Byron M. Yu
Byron M. Yu Carnegie Mellon University
John P. Cunningham
John P. Cunningham Columbia University
Mark M. Churchland
Mark M. Churchland Columbia University
Maneesh Sahani
Maneesh Sahani University College London
Teresa H. Meng
Teresa H. Meng Stanford University
Surya Ganguli
Surya Ganguli Stanford University
Karl Deisseroth
Karl Deisseroth Stanford University
William T. Newsome
William T. Newsome Stanford University
Jaimie M. Henderson
Jaimie M. Henderson Stanford University

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