NSF PAR Search | NSF Public Access Repository

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

NETFORMER: AN INTERPRETABLE MODEL FOR RECOVERING DYNAMICAL CONNECTIVITY IN NEURONAL POPULATION DYNAMICS

Lu, Ziyu; Zhang, Wuwei; Le, Trung; Wang, Hao; Sumbul, Uygar; Shea-Brown, Eric; Mi, Lu (April 2025, ICLR)

Free, publicly-accessible full text available April 24, 2026
From lazy to rich to exclusive task representations in neural networks and neural codes

https://doi.org/10.1016/j.conb.2023.102780

Farrell, Matthew; Recanatesi, Stefano; Shea-Brown, Eric (December 2023, Current Opinion in Neurobiology)

Full Text Available
Connecting neural dynamics and computation across spatial and temporal scales. In: The Cerebral Cortex and Thalamus, M. Sherman and M. Usrey, Eds., Oxford Univ. Press 2023.

Mease, Rebecca A; Shea-Brown, Eric T; Fairhall, Adrienne L (November 2023, Oxford University Press)
Sherman, M; Usrey, M (Ed.)
Full Text Available
Attention for Causal Relationship Discovery from Biological Neural Dynamics

Lu, Ziyu; Tabassum, Anika; Kulkarni, Shruti; Mi, Lu; Kutz, Nathan; Shea-Brown, Eric; Lim, Seung-Hwan (December 2023, NeurIPS 2023 CRL Workshop)

Full Text Available
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules

Liu, Yuhan Helena; Ghosh, Arna; Richards, Blake Aaron; Shea-Brown, Eric Todd; Lajoie, Guillaume (January 2022, Advances in Neural Information Processing Systems)

Full Text Available
Computational Neuroscience: Mathematical and Statistical Perspectives

https://doi.org/10.1146/annurev-statistics-041715-033733

Kass, Robert E; Amari, Shun-Ichi; Arai, Kensuke; Brown, Emery N; Diekman, Casey O; Diesmann, Markus; Doiron, Brent; Eden, Uri T; Fairhall, Adrienne L; Fiddyment, Grant M; et al (March 2018, Annual Review of Statistics and Its Application)

Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience will need to appreciate and exploit the complementary strengths of mechanistic theory and the statistical paradigm.
more » « less
Full Text Available

Search for: All records