Published November 20, 2023 | Version v3
Dataset Open

A Machine Learning Approach for Real-time Cortical State Estimation

Creators

  • 1. Georgia Institute of Technology
  • 2. Emory University
  • 3. University of Minnesota

Description

Data and code accompanying the following publication: Weiss, D. A., Borsa, A. M., Pala, A., Sederberg, A. J., & Stanley, G. B. (2024). A machine learning approach for real-time cortical state estimation. Journal of neural engineering, 21(1), 10.1088/1741-2552/ad1f7b. https://doi.org/10.1088/1741-2552/ad1f7b

Files

Code.zip

Files (2.3 GB)

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Additional details

Funding

National Institutes of Health
Thalamocortical state control of tactile sensing: Mechanisms, Models, and Behavior 5R01NS104928-05
National Institutes of Health
CRCNS: Closed-Loop Computational Neuroscience for Causally Dissecting Circuits 5R01NS115327-04
National Institutes of Health
Training in Computational Neural Engineering 1T32EB025816-01A1
National Institutes of Health
Feedback and feedforward gating of sensory signaling through timing in the thalamocortical loop 1RF1NS128896-01
Swiss National Science Foundation
Integration of Tactile Information across Brain Hemispheres P2ELP3_168506
National Institutes of Health
Crossing space and time: uncovering the nonlinear dynamics of multimodal and multiscale brain activity 1R01EB029857-01
Swiss National Science Foundation
The Neuronal Correlates and Computations underlying Bilateral Tactile Perception P300PA_177861
National Institutes of Health
Interhemispheric interactions underlying bilateral somatosensation 5R21NS112783-02

Dates

Updated
2023-11-17
Submitted
2023-06-19
Updated
2023-11-20