Multi-view manifold learning of human brain-state trajectories-Reference-Cited by-同舟云学术

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Multi-view manifold learning of human brain-state trajectories

Published:2023-03-27 Issue:3 Volume:3 Page:240-253
ISSN:2662-8457
Container-title:Nature Computational Science
language:en
Short-container-title:Nat Comput Sci

Author:

Busch Erica L.,Huang Jessie,Benz Andrew,Wallenstein Tom,Lajoie Guillaume,Wolf Guy,Krishnaswamy Smita^ORCID,Turk-Browne Nicholas B.

Funder

National Science Foundation

Canada CIFAR AI Chair; Canada Research Chair in Neural Computations and Interfacing

CIFAR

Canada CIFAR AI Chair, IVADO Professor research funds

Alfred P. Sloan Foundation

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Computer Science (miscellaneous)

Link

https://www.nature.com/articles/s43588-023-00419-0.pdf

Reference70 articles.

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2. Laurent, G. Olfactory network dynamics and the coding of multidimensional signals. Nat. Rev. Neurosci. 3, 884–895 (2002).

3. Churchland, M. M., Cunningham, J. P., Kaufman, M. T., Ryu, S. I. & Shenoy, K. V. Cortical preparatory activity: representation of movement or first cog in a dynamical machine? Neuron 68, 387–400 (2010).

4. Chang, L. & Tsao, D. Y. The code for facial identity in the primate brain. Cell 169, 1013–1028.e14 (2017).

5. Freiwald, W. A. & Tsao, D. Y. Functional compartmentalization and viewpoint generalization within the macaque face-processing system. Science 330, 845 (2010).

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