A Machine Learning Approach for Real-time Cortical State Estimation
Authors/Creators
- 1. Georgia Institute of Technology
- 2. Emory University
- 3. University of Minnesota
Description
Data and code to accompany "A Machine Learning Approach for Real-time Cortical State Estimation" by Weiss*, Borsa*, Pala, Sederberg, and Stanley, under review.
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The associated publication: "A Machine Learning Approach for Real-time Cortical State Estimation" by Weiss*, Borsa*, Pala, Sederberg, and Stanley, is under review. The data is unavailable until after publication.
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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