Work

Human learning of noninvasive brain–computer interfaces via manifold geometry

Year: 2026

Type: article

Source: Nature Neuroscience

DOI: 10.1038/s41593-026-02311-2

Authors: Erica L. Busch, E. Chandra Fincke, Guillaume Lajoie, Smita Krishnaswamy, Nicholas B. Turk-Browne

Institutions: Yale University, Mila - Quebec Artificial Intelligence Institute, Université de Montréal

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, Alfred P. Sloan Foundation, Canadian Institute for Advanced Research, National Institutes of Health, National Institute of Mental Health, National Institute of General Medical Sciences

Awards: TRIPODS+X:RES: Investigations at the Interface of Data Science and Neuroscience, Graduate Research Fellowship Program (GRFP), G328145712, Deciphering Genetic and Epigenetic Regulatory Logic of Germ Layer Differentiation with Manifold Learning, Finding emergent structure in multi-sample biological data with the dual geometry of cells and features , CAREER: Deep representation learning for exploration and inference in biomedical data, Computational, Neural, and Behavioral Studies of Competition-Dependent Learning

OpenAlex ID: W7163991143

FWCI: 17.57

Cites: 83

Cited by: 7

Related to: 10