Stochastic computations in cortical microcircuit models.
about
Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral InhibitionCoordination Dynamics in Cognitive NeuroscienceTowards a "canonical" agranular cortical microcircuit.NEVESIM: event-driven neural simulation framework with a Python interfaceAn event-based architecture for solving constraint satisfaction problems.Decoding subjective decisions from orbitofrontal cortexThe anchoring bias reflects rational use of cognitive resources.Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.Rhythmic Inhibition Allows Neural Networks to Search for Maximally Consistent States.Event-driven contrastive divergence: neural sampling foundationsCortical Neuroprosthesis Merges Visible and Invisible Light Without Impairing Native Sensory Function.Using Stochastic Spiking Neural Networks on SpiNNaker to Solve Constraint Satisfaction Problems.Solving Constraint-Satisfaction Problems with Distributed Neocortical-Like Neuronal Networks.
P2860
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P2860
Stochastic computations in cortical microcircuit models.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
Stochastic computations in cortical microcircuit models.
@en
Stochastic computations in cortical microcircuit models.
@nl
type
label
Stochastic computations in cortical microcircuit models.
@en
Stochastic computations in cortical microcircuit models.
@nl
prefLabel
Stochastic computations in cortical microcircuit models.
@en
Stochastic computations in cortical microcircuit models.
@nl
P2860
P1476
Stochastic computations in cortical microcircuit models.
@en
P2093
Stefan Habenschuss
Zeno Jonke
P2860
P304
P356
10.1371/JOURNAL.PCBI.1003311
P577
2013-11-14T00:00:00Z