Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Aran, Nayebi"'
Autor:
Aran Nayebi, Nathan C L Kong, Chengxu Zhuang, Justin L Gardner, Anthony M Norcia, Daniel L K Yamins
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 10, p e1011506 (2023)
Studies of the mouse visual system have revealed a variety of visual brain areas that are thought to support a multitude of behavioral capacities, ranging from stimulus-reward associations, to goal-directed navigation, and object-centric discriminati
Externí odkaz:
https://doaj.org/article/31d61b78409b402496caf43eccb439ec
Recent work has claimed that the emergence of grid cells from trained path-integrator circuits is a more fragile phenomenon than previously reported. In this note we critically assess the main analysis and simulation results underlying this claim, wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::355848cf8256b24160dc0075d85ec414
https://doi.org/10.1101/2022.11.14.516537
https://doi.org/10.1101/2022.11.14.516537
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Autor:
Hidenori, Tanaka, Aran, Nayebi, Niru, Maheswaranathan, Lane, McIntosh, Stephen A, Baccus, Surya, Ganguli
Publikováno v:
Adv Neural Inf Process Syst
Recently, deep feedforward neural networks have achieved considerable success in modeling biological sensory processing, in terms of reproducing the input-output map of sensory neurons. However, such models raise profound questions about the very nat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::83a70b04e17b50f16350f27228827feb
https://pubmed.ncbi.nlm.nih.gov/35283616
https://pubmed.ncbi.nlm.nih.gov/35283616
Publikováno v:
2022 Conference on Cognitive Computational Neuroscience.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::158a4f08bf7f2d326eb6f92f71e1905d
https://doi.org/10.32470/ccn.2022.1289-0
https://doi.org/10.32470/ccn.2022.1289-0
Autor:
Aran Nayebi, Alexander Attinger, Malcolm G. Campbell, Kiah Hardcastle, Isabel I.C. Low, Caitlin S. Mallory, Gabriel C. Mel, Ben Sorscher, Alex H. Williams, Surya Ganguli, Lisa M. Giocomo, Daniel L.K. Yamins
Medial entorhinal cortex (MEC) supports a wide range of navigational and memory related behaviors. Well-known experimental results have revealed specialized cell types in MEC — e.g. grid, border, and head-direction cells — whose highly stereotypi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7177cb34613cd11edcd25f18aea3ef00
https://doi.org/10.1101/2021.10.30.466617
https://doi.org/10.1101/2021.10.30.466617
Autor:
Aran Nayebi, Javier Sagastuy-Brena, Daniel M. Bear, Kohitij Kar, Jonas Kubilius, Surya Ganguli, David Sussillo, James J. DiCarlo, Daniel L. K. Yamins
Publikováno v:
Neural computation. 34(8)
The computational role of the abundant feedback connections in the ventral visual stream is unclear, enabling humans and nonhuman primates to effortlessly recognize objects across a multitude of viewing conditions. Prior studies have augmented feedfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25402cf988f3e63f2aac0cf5c409f1fe
https://pubmed.ncbi.nlm.nih.gov/35798321
https://pubmed.ncbi.nlm.nih.gov/35798321
Autor:
Justin L. Gardner, Daniel L. K. Yamins, Nathan C. L. Kong, Aran Nayebi, Anthony M. Norcia, Chengxu Zhuang
Task-optimized deep convolutional neural networks are the most quantitatively accurate models of the primate ventral visual stream. However, such networks are implausible as models of the mouse visual system because mouse visual cortex has both lower
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0a36fe202afefaa6e93db20783e131a
https://doi.org/10.1101/2021.06.16.448730
https://doi.org/10.1101/2021.06.16.448730
Autor:
Maozhen Qin, Haining Zhong, Tianyi Mao, Bart C. Jongbloets, Dale A. Fortin, Aran Nayebi, Surya Ganguli, Joshua B. Melander
SUMMARYCortical function relies on the balanced activation of excitatory and inhibitory neurons. However, little is known about the organization and dynamics of shaft excitatory synapses onto cortical inhibitory interneurons, which cannot be easily i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2985ab02b17553cdf26481d90d2f25d4
https://doi.org/10.1101/2021.04.04.438418
https://doi.org/10.1101/2021.04.04.438418
Autor:
David Sussillo, Javier Sagastuy-Brena, Jonas Kubilius, Surya Ganguli, Aran Nayebi, Daniel M. Bear, James J. DiCarlo, Kohitij Kar, Daniel L. K. Yamins
The ventral visual stream (VVS) is a hierarchically connected series of cortical areas known to underlie core object recognition behaviors, enabling humans and non-human primates to effortlessly recognize objects across a multitude of viewing conditi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be1accfde6fb922fd82dc4a57a1aeef6
https://doi.org/10.1101/2021.02.17.431717
https://doi.org/10.1101/2021.02.17.431717
Autor:
James J. DiCarlo, Daniel L. K. Yamins, Chengxu Zhuang, Martin Schrimpf, Michael C. Frank, Aran Nayebi, Siming Yan
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Primates show remarkable ability to recognize objects. This ability is achieved by their ventral visual stream, multiple hierarchically interconnected brain areas. The best quantitative models of these areas are deep neural networks trai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c01ff6b65a6b7134f4be264067227a13
https://doi.org/10.1073/pnas.2014196118
https://doi.org/10.1073/pnas.2014196118