Zobrazeno 1 - 10
of 163
pro vyhledávání: '"Peter E. Latham"'
Autor:
Naoki Hiratani, Peter E. Latham
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
How can rodents make sense of the olfactory environment without supervision? Here, the authors formulate olfactory learning as an integrated Bayesian inference problem, then derive a set of synaptic plasticity rules and neural dynamics that enables n
Externí odkaz:
https://doaj.org/article/f6df5da2e76146c792e6313cc3b56b26
Publikováno v:
Entropy, Vol 15, Iss 8, Pp 3109-3129 (2013)
Maximum entropy models have become popular statistical models in neuroscience and other areas in biology and can be useful tools for obtaining estimates of mutual information in biological systems. However, maximum entropy models fit to small data se
Externí odkaz:
https://doaj.org/article/6edb23c86838413d97d5db1ef1ef10db
Autor:
C. Randy Gallistel, Peter E. Latham
Publikováno v:
Timing & Time Perception. 11:29-89
Bayesian parameter estimation and Shannon’s theory of information provide tools for analysing and understanding data from behavioural and neurobiological experiments on interval timing—and from experiments on Pavlovian and operant conditioning, b
Autor:
Laurence Aitchison, Peter E. Latham, Jean-Pascal Pfister, Jannes Jegminat, Jorge Aurelio Menendez, Alexandre Pouget
Publikováno v:
Nature Neuroscience. 24:565-571
Learning, especially rapid learning, is critical for survival. However, learning is hard; a large number of synaptic weights must be set based on noisy, often ambiguous, sensory information. In such a high-noise regime, keeping track of probability d
Autor:
Peter E. Latham, Naoki Hiratani
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
Nature Communications
Nature Communications
Many experimental studies suggest that animals can rapidly learn to identify odors and predict the rewards associated with them. However, the underlying plasticity mechanism remains elusive. In particular, it is not clear how olfactory circuits achie
Autor:
Claudia Clopath, Krishnagopal S, Marcus Hutter, Dimitar Kostadinov, Michael Häusser, Joel Veness, Agnieszka Grabska-Barwinska, Eren Sezener, Matthew Botvinick, Peter E. Latham, David Budden, Maxime Beau
The dominant view in neuroscience is that changes in synaptic weights underlie learning. It is unclear, however, how the brain is able to determine which synapses should change, and by how much. This uncertainty stands in sharp contrast to deep learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60261cf720352120caff5e16f28ce12f
https://doi.org/10.1101/2021.03.10.434756
https://doi.org/10.1101/2021.03.10.434756
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 1, p e1009808 (2022)
Sensory processing is hard because the variables of interest are encoded in spike trains in a relatively complex way. A major goal in studies of sensory processing is to understand how the brain extracts those variables. Here we revisit a common enco
Autor:
Laurence, Aitchison, Jannes, Jegminat, Jorge Aurelio, Menendez, Jean-Pascal, Pfister, Alexandre, Pouget, Peter E, Latham
Publikováno v:
Nature neuroscience. 24(4)
Learning, especially rapid learning, is critical for survival. However, learning is hard; a large number of synaptic weights must be set based on noisy, often ambiguous, sensory information. In such a high-noise regime, keeping track of probability d
Publikováno v:
Trends in Neurosciences
More often than not, action potentials fail to trigger neurotransmitter release. And even when neurotransmitter is released, the resulting change in synaptic conductance is highly variable. Given the energetic cost of generating and propagating actio
If the brain processes incoming data efficiently, information should degrade little between early and later neural processing stages, and so information in early stages should match behavioral performance. For instance, if there is enough information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c4bd6f4b1b71dcc097923a14ecdf8c0
https://doi.org/10.1101/842724
https://doi.org/10.1101/842724