Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Mikail Khona"'
Autor:
Gabriel Madirolas, Alid Al-Asmar, Lydia Gaouar, Leslie Marie-Louise, Andrea Garza-Enríquez, Valentina Rodríguez-Rada, Mikail Khona, Martina Dal Bello, Christoph Ratzke, Jeff Gore, Alfonso Pérez-Escudero
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-13 (2023)
Abstract Rules of thumb are behavioral algorithms that approximate optimal behavior while lowering cognitive and sensory costs. One way to reduce these costs is by simplifying the representation of the environment: While the theoretically optimal beh
Externí odkaz:
https://doaj.org/article/06f224b81e0e46de88fdf63fd19544ce
Autor:
Mikail, Khona, Ila R, Fiete
Publikováno v:
Nature reviews. Neuroscience. 23(12)
In this Review, we describe the singular success of attractor neural network models in describing how the brain maintains persistent activity states for working memory, corrects errors and integrates noisy cues. We consider the mechanisms by which si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::628ec0ca65a96409973e510ad493a17d
https://pubmed.ncbi.nlm.nih.gov/36329249
https://pubmed.ncbi.nlm.nih.gov/36329249
Research in Neuroscience, as in many scientific disciplines, is undergoing a renaissance based on deep learning. Unique to Neuroscience, deep learning models can be used not only as a tool but interpreted as models of the brain. The central claims of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b5f465fd5ec08ba664f89362daf31cd
https://doi.org/10.1101/2022.08.07.503109
https://doi.org/10.1101/2022.08.07.503109
Autor:
Gabriel Madirolas, Alid Al-Asmar, Lydia Gaouar, Leslie Marie-Louise, Andrea Garza-Enriquez, Mikail Khona, Christoph Ratzke, Jeff Gore, Alfonso Pérez-Escudero
Rules of thumb are behavioral algorithms that approximate optimal behavior while lowering cognitive and sensory costs. One way to reduce these costs is by reducing dimensionality: While the theoretically optimal behavior may depend on many environmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8305b9763eb94ac35448d0f6db01128d
https://doi.org/10.1101/2022.06.21.496406
https://doi.org/10.1101/2022.06.21.496406
The grid cell system is a paradigmatic example of the computational advantages of modular representations. Modular grid responses emerge along a strip of cortex with smooth gradients in several biophysical properties, within days of eye opening in ju
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bbc3b74abe4ad1c861972b677b8efbe
https://doi.org/10.1101/2021.10.28.466284
https://doi.org/10.1101/2021.10.28.466284
Publikováno v:
Scopus-Elsevier
We study how recurrent neural networks (RNNs) solve a hierarchical inference task involving two latent variables and disparate timescales separated by 1-2 orders of magnitude. The task is of interest to the International Brain Laboratory, a global co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cd52a26349ea9c32d90ca11e4a5af22
https://doi.org/10.1101/2020.06.09.142745
https://doi.org/10.1101/2020.06.09.142745