Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Ann M Hermundstad"'
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 6, p e1011104 (2023)
To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about t
Externí odkaz:
https://doaj.org/article/768ec50f05c744159db6add53b662f3e
Autor:
Brad K Hulse, Hannah Haberkern, Romain Franconville, Daniel Turner-Evans, Shin-ya Takemura, Tanya Wolff, Marcella Noorman, Marisa Dreher, Chuntao Dan, Ruchi Parekh, Ann M Hermundstad, Gerald M Rubin, Vivek Jayaraman
Publikováno v:
eLife, Vol 10 (2021)
Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) ena
Externí odkaz:
https://doaj.org/article/a51912fc28054783ad9182b56a3a6ef3
Publikováno v:
PLoS ONE, Vol 16, Iss 8, p e0256034 (2021)
Identifying coordinated activity within complex systems is essential to linking their structure and function. We study collective activity in networks of pulse-coupled oscillators that have variable network connectivity and integrate-and-fire dynamic
Externí odkaz:
https://doaj.org/article/2cef5d55b516414f8cd6bf0abb8a87ed
Autor:
Tiberiu Tesileanu, Mary M Conte, John J Briguglio, Ann M Hermundstad, Jonathan D Victor, Vijay Balasubramanian
Publikováno v:
eLife, Vol 9 (2020)
Previously, in Hermundstad et al., 2014, we showed that when sampling is limiting, the efficient coding principle leads to a ‘variance is salience’ hypothesis, and that this hypothesis accounts for visual sensitivity to binary image statistics. H
Externí odkaz:
https://doaj.org/article/0d00073e7af34c77a68a26c4d8fbdfce
Autor:
Wiktor F Młynarski, Ann M Hermundstad
Publikováno v:
eLife, Vol 7 (2018)
Behavior relies on the ability of sensory systems to infer properties of the environment from incoming stimuli. The accuracy of inference depends on the fidelity with which behaviorally relevant properties of stimuli are encoded in neural responses.
Externí odkaz:
https://doaj.org/article/e239b4d8ffaf4d5c9db6c13ccfbb4d7f
Autor:
Ann M Hermundstad, John J Briguglio, Mary M Conte, Jonathan D Victor, Vijay Balasubramanian, Gašper Tkačik
Publikováno v:
eLife, Vol 3 (2014)
Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range
Externí odkaz:
https://doaj.org/article/64f2749f6ab849e8ba861fb88fdc1152
Autor:
Ann M Hermundstad, Kevin S Brown, Danielle S Bassett, Elissa M Aminoff, Amy Frithsen, Arianne Johnson, Christine M Tipper, Michael B Miller, Scott T Grafton, Jean M Carlson
Publikováno v:
PLoS Computational Biology, Vol 10, Iss 5, p e1003591 (2014)
The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which
Externí odkaz:
https://doaj.org/article/c7603084e9d24877bed6a24abdbb44ef
Publikováno v:
PLoS Computational Biology, Vol 7, Iss 6, p e1002063 (2011)
The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network archite
Externí odkaz:
https://doaj.org/article/ee8ce64ee4c044f4a62b0be947a4809d
Autor:
Tzuhsuan Ma, Ann M Hermundstad
When foraging in dynamic and uncertain environments, animals can benefit from basing their decisions on smart inferences about hidden properties of the world. Typical theoretical approaches to understand the strategies that animals use in such settin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f902548e0c0b6933d74896abe89a1881
https://doi.org/10.1101/2022.08.10.503471
https://doi.org/10.1101/2022.08.10.503471
Autor:
Kamesh, Krishnamurthy, Ann M, Hermundstad, Thierry, Mora, Aleksandra M, Walczak, Vijay, Balasubramanian
Publikováno v:
Frontiers in Computational Neuroscience. 16
Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circui
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5343818dd1e6099388f8b57dabcd9ec4
https://doi.org/10.3389/fncom.2022.917786
https://doi.org/10.3389/fncom.2022.917786