Work

A Machine Learning Approach for Real-time Cortical State Estimation

Year: 2023

Type: dataset

Abstract: Data and code to accompany "A Machine Learning Approach for Real-time Cortical State Estimation" by Weiss*, Borsa*, Pala, Sederberg, and Stanley, under review.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.8057802

Authors: Weiss, David A, Borsa, Adriano MF, Pala, Aurelie, Sederberg, Audrey J, Stanley, Garrett B

Institutions: Georgia Institute of Technology, Emory University, University of Minnesota

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funders: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering

Awards: Crossing space and time: uncovering the nonlinear dynamics of multimodal and multiscale brain activity, CRCNS: Closed-Loop Computational Neuroscience for Causally Dissecting Circuits, Thalamocortical state control of tactile sensing: Mechanisms, Models, and Behavior, Feedback and feedforward gating of sensory signaling through timing in the thalamocortical loop, Integration of Tactile Information across Brain Hemispheres, The Neuronal Correlates and Computations underlying Bilateral Tactile Perception, Interhemispheric interactions underlying bilateral somatosensation, Training in Computational Neural Engineering

OpenAlex ID: W4393726566

Cites:

Cited by: 1

Related to: 10