Zobrazeno 1 - 10
of 124
pro vyhledávání: '"ALEXANDRE POUGET"'
Autor:
Michael Schartner, Jeff M. Beck, Justine Laboyrie, Laurent Riquier, Stephanie Marchand, Alexandre Pouget
Publikováno v:
Communications Chemistry, Vol 6, Iss 1, Pp 1-10 (2023)
Abstract Connecting chemical properties to various wine characteristics is of great interest to the science of olfaction as well as the wine industry. We explored whether Bordeaux wine chemical identities and vintages (harvest year) can be inferred f
Externí odkaz:
https://doaj.org/article/4086ac9e53a24662a96aac74035d0f79
Autor:
Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Körding, Alexei Koulakov, Yann LeCun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-7 (2023)
Abstract Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test
Externí odkaz:
https://doaj.org/article/f641a9b5999f446baa1b1e8548582333
Autor:
Michael Schartner, Jeff M. Beck, Justine Laboyrie, Laurent Riquier, Stephanie Marchand, Alexandre Pouget
Publikováno v:
Communications Chemistry, Vol 7, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/70607942dc9042bc9f118ed654a1bdb2
Autor:
André G. Mendonça, Jan Drugowitsch, M. Inês Vicente, Eric E. J. DeWitt, Alexandre Pouget, Zachary F. Mainen
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
Here, the authors show that rats’ performance on olfactory decision tasks is best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain sensory evidence. The results suggest that learning is a criti
Externí odkaz:
https://doaj.org/article/cdd0caa3d0de4532b42841435d503f3e
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 2, p e1008138 (2021)
Skilled behavior often displays signatures of Bayesian inference. In order for the brain to implement the required computations, neuronal activity must carry accurate information about the uncertainty of sensory inputs. Two major approaches have been
Externí odkaz:
https://doaj.org/article/fcc9f49da7dc4e048456e4add5a7b93d
Publikováno v:
Nature Communications, Vol 7, Iss 1, Pp 1-12 (2016)
Drift diffusion models (DDM) are fundamental to our understanding of perceptual decision-making. Here, the authors show that DDM can implement optimal choice strategies in value-based decisions but require sufficient knowledge of reward contingencies
Externí odkaz:
https://doaj.org/article/98fd03651eaf41778076aa1f9e46c473
Autor:
Kaushik J Lakshminarasimhan, Alexandre Pouget, Gregory C DeAngelis, Dora E Angelaki, Xaq Pitkow
Publikováno v:
PLoS Computational Biology, Vol 14, Iss 9, p e1006371 (2018)
Studies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional role of brain
Externí odkaz:
https://doaj.org/article/efa4e7c671e0432cb6af403715d42e9c
Publikováno v:
F1000Research, Vol 6 (2017)
In this method article, we show how to estimate of the number of retinal ganglion cells (RGC), and the number of lateral genicular nucleus (LGN) and primary visual cortex (V1) neurons involved in visual orientation discrimination tasks. We reported t
Externí odkaz:
https://doaj.org/article/d68c0c2e77324b239f6034232c9740df
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 4, p e1005497 (2017)
Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these populati
Externí odkaz:
https://doaj.org/article/cbce68af3d6f448b8adb250f410f3ec2
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 6, p e1004218 (2015)
Neural responses are known to be variable. In order to understand how this neural variability constrains behavioral performance, we need to be able to measure the reliability with which a sensory stimulus is encoded in a given population. However, su
Externí odkaz:
https://doaj.org/article/6430ddabc2ef475190291a77f144c8c7