about
Functional clustering drives encoding improvement in a developing brain network during awake visual learningTransformation of stimulus correlations by the retinaEfficient coding of spatial information in the primate retina.Statistics of the vestibular input experienced during natural self-motion: implications for neural processing.Gibbs distribution analysis of temporal correlations structure in retina ganglion cells.Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy DataCholinergic shaping of neural correlations.Fast, scalable, Bayesian spike identification for multi-electrode arrays.A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields.Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neuronsHigh-fidelity coding with correlated neurons.Stimulus-dependent maximum entropy models of neural population codes.Searching for collective behavior in a large network of sensory neuronsThe sign rule and beyond: boundary effects, flexibility, and noise correlations in neural population codes.Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MTColumnar architecture improves noise robustness in a model cortical network.Searching for simplicity in the analysis of neurons and behaviorA simple model of optimal population coding for sensory systems.Decoding thalamic afferent input using microcircuit spiking activity.Evolution of bow-tie architectures in biology.Dynamics of multistable states during ongoing and evoked cortical activity.Error-Robust Modes of the Retinal Population Code.Robust information propagation through noisy neural circuits.Population rate dynamics and multineuron firing patterns in sensory cortexRate and timing of cortical responses driven by separate sensory channels.Stimuli Reduce the Dimensionality of Cortical Activity.Intermediate intrinsic diversity enhances neural population codingA pairwise maximum entropy model accurately describes resting-state human brain networks.Missing mass approximations for the partition function of stimulus driven Ising modelsCoding Properties of Mouse Retinal Ganglion Cells with Dual-Peak Patterns with Respect to Stimulus Intervals.Information theory of adaptation in neurons, behavior, and mood.Spatiotemporal computations of an excitable and plastic brain: neuronal plasticity leads to noise-robust and noise-constructive computations.Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network.Optimizing Neural Information Capacity through Discretization.Functional connectivity models for decoding of spatial representations from hippocampal CA1 recordings.Population activity statistics dissect subthreshold and spiking variability in V1.Predicting single-neuron activity in locally connected networks.Optimal sparse approximation with integrate and fire neurons.Evolution of new regulatory functions on biophysically realistic fitness landscapes.PRANAS: A New Platform for Retinal Analysis and Simulation.
P2860
Q27320518-9E7806EC-D71D-4D33-B39B-5A146E869617Q27323776-53CFC4DA-D7A1-4CD8-B627-61CE02A806A2Q29544930-35325A7B-4967-4594-A871-8AACFAD07CA0Q30423171-72EB976F-ABB4-4F55-AC77-5A14692349DBQ30524323-4F4A6AF1-4F87-46FD-A602-80C929F8D9FAQ31037999-D70841BB-7923-424B-A10A-BA195B33B6EAQ33782471-670AA172-CAA8-454B-80A0-1C8885DEAB4EQ33974843-970DC48C-DBF0-4D09-A7A9-B8053C8991BDQ34064180-0712DED6-B473-48EB-B6F2-726DC7492F45Q34118991-9D5E2C17-A1C0-4D8C-9E89-EA4CB929871AQ34549456-A4792DA3-DB37-414D-ADA2-285CD130F209Q34629073-B6A56886-9D61-419A-84DC-7D3792752431Q35082161-7F351E6C-6925-4FE9-9692-FC77BF393830Q35105564-F9D0ED27-BAB3-4F51-8447-E6BD5088CA6EQ35140312-ACE45556-DA96-473B-89A1-C8682D5F177BQ35191340-15032730-C952-4A0C-8B2A-5F81D428C33EQ35222934-F62AE45F-16A6-4356-B0F7-63C058D3F1CEQ35224371-17DB8CD5-75DA-4B3A-9785-0C14A130ABDDQ35560359-0B4FE3AD-E0FC-402D-B8BB-DC74B7D5B81EQ35583653-9585D8DA-9E08-4177-ADDE-7006FD5AC802Q35649505-67BBA72A-8E90-4C13-B1B3-2E5E2EED92C4Q36194956-4BD75B2F-6192-42A0-967D-C8E2DBF08C4EQ36349659-B353FB53-1BCD-4272-B2CB-798E46CD2B9AQ36460663-475FFE41-890B-42BD-9947-2669E491EBC6Q36585893-95546527-7615-4402-B676-198F412B4FDEQ36587078-5D9F27BF-DB58-41B5-8A2B-11BF5F0A8230Q36855195-489DC3C2-6B90-4719-9B63-3108C229231FQ36864556-12FCDC5D-E2D3-49DD-97D3-15F631C8176CQ37039665-4AC74F1C-9363-41A6-BB93-ECD23E4E87B6Q37104531-5CE5C5D1-602A-42E1-AC8B-652361D32894Q37695525-276FA543-09F6-4593-8DF0-F67A78598941Q38374156-D7A2B561-E6BF-42F7-8FFC-E467AFFEDD2BQ38646714-4F3E715D-FB9F-45BF-9854-CB73E98D0E54Q38736240-B75D1F9F-2BB9-4E46-98DA-F2311E204312Q38796643-C7B005E6-CDB7-41B1-B66A-9B134822F450Q38905225-D20DA8A5-DADA-4C44-8B1E-7722F4F779C7Q39191401-C0D1C800-1D63-4C5B-B697-C68A0DF7D968Q40196326-64681316-3A8F-42F0-B368-5E608244F766Q41309636-CB448161-A75F-4D81-8EF5-3B37E0E644DEQ41622505-E7198C29-AE0F-4B34-AD75-3C3063ED0C50
P2860
description
2010 nî lūn-bûn
@nan
2010 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Optimal population coding by noisy spiking neurons
@ast
Optimal population coding by noisy spiking neurons
@en
Optimal population coding by noisy spiking neurons
@nl
type
label
Optimal population coding by noisy spiking neurons
@ast
Optimal population coding by noisy spiking neurons
@en
Optimal population coding by noisy spiking neurons
@nl
prefLabel
Optimal population coding by noisy spiking neurons
@ast
Optimal population coding by noisy spiking neurons
@en
Optimal population coding by noisy spiking neurons
@nl
P2860
P356
P1476
Optimal population coding by noisy spiking neurons
@en
P2093
Jason S Prentice
Vijay Balasubramanian
P2860
P304
14419-14424
P356
10.1073/PNAS.1004906107
P407
P577
2010-07-26T00:00:00Z