Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Rodney J Douglas"'
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 8, p e1010382 (2022)
During brain development, billions of axons must navigate over multiple spatial scales to reach specific neuronal targets, and so build the processing circuits that generate the intelligent behavior of animals. However, the limited information capaci
Externí odkaz:
https://doaj.org/article/5d32e385a3d74adb979215f5d6647d9d
Autor:
Roman Bauer, Frédéric Zubler, Sabina Pfister, Andreas Hauri, Michael Pfeiffer, Dylan R Muir, Rodney J Douglas
Publikováno v:
PLoS Computational Biology, Vol 10, Iss 12, p e1003994 (2014)
The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less
Externí odkaz:
https://doaj.org/article/ebafa0b30bec4f85a5173c05f07ea63e
Autor:
Frederic Zubler, Andreas Hauri, Sabina Pfister, Roman Bauer, John C Anderson, Adrian M Whatley, Rodney J Douglas
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 8, p e1003173 (2013)
Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes
Externí odkaz:
https://doaj.org/article/d417ae5c7cb645a2914330fd2fb52f43
Autor:
Albert Cardona, Stephan Saalfeld, Johannes Schindelin, Ignacio Arganda-Carreras, Stephan Preibisch, Mark Longair, Pavel Tomancak, Volker Hartenstein, Rodney J Douglas
Publikováno v:
PLoS ONE, Vol 7, Iss 6, p e38011 (2012)
A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For
Externí odkaz:
https://doaj.org/article/cb094fa841bf4fa09b6925752f8100fd
Autor:
Federico Brandalise, Rodney J. Douglas, Michael Pfeiffer, Marie Moulinier, Suraj Honnuraiah, Saray Soldado Magraner, Urs Gerber
Publikováno v:
Journal of Neurophysiology. 123:90-106
Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ef8daa87538cda7a2fd5d705e0f40ff
https://doi.org/10.1152/jn.00506.2019
https://doi.org/10.1152/jn.00506.2019
Autor:
Rodney J. Douglas, Henry Kennedy, Andreas Hauri, Sabina Pfister, Gabriela Michel, Frédéric Zubler, Colette Dehay
Publikováno v:
bioRxiv
Sparse data describing mouse cortical neurogenesis were used to derive a model gene regulatory network (GRN) that is then able to control the quantitative cellular dynamics of the observed neurogenesis. Derivation of the network begins by estimating
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e4666cb8f8eef7a6236a64a2c750676
Finding actions that satisfy the constraints imposed by both external inputs and internal representations is central to decision making. We demonstrate that some important classes of constraint satisfaction problems (CSPs) can be solved by networks c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2abc15e41fe491032045b10dc155f55c
http://arxiv.org/abs/1801.04515
http://arxiv.org/abs/1801.04515
Autor:
Saray Soldado Magraner, Michael Pfeiffer, Federico Brandalise, Suraj Honnuraiah, Urs Gerber, Rodney J. Douglas
Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::258c906b6b43acb1f41f7d63e3c8c098
https://doi.org/10.1101/084152
https://doi.org/10.1101/084152
Autor:
Kevan A. C. Martin, Rodney J. Douglas
Publikováno v:
Computational Theories and their Implementation in the Brain: The legacy of David Marr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8b253570931906358711fca3a9442bb
https://doi.org/10.1093/acprof:oso/9780198749783.003.0008
https://doi.org/10.1093/acprof:oso/9780198749783.003.0008
Publikováno v:
Neural Computation
We introduce a framework for decision making in which the learning of decision making is reduced to its simplest and biologically most plausible form: Hebbian learning on a linear neuron. We cast our Bayesian-Hebb learning rule as reinforcement learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b672367efab642eb0209eeb2c873efc
https://doi.org/10.1162/neco.2010.03-09-980
https://doi.org/10.1162/neco.2010.03-09-980