Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness.
about
Decorrelation of neural-network activity by inhibitory feedbackMechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate modelFrom spiking neuron models to linear-nonlinear models.Designing optimal stimuli to control neuronal spike timing.Impact of network structure and cellular response on spike time correlations.Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.Applying the multivariate time-rescaling theorem to neural population models.Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.Emergent properties of interacting populations of spiking neurons.Modeling Population Spike Trains with Specified Time-Varying Spike Rates, Trial-to-Trial Variability, and Pairwise Signal and Noise CorrelationsCorrelation-based analysis and generation of multiple spike trains using hawkes models with an exogenous input.A Markov model for the temporal dynamics of balanced random networks of finite size.Analytical approximations of the firing rate of an adaptive exponential integrate-and-fire neuron in the presence of synaptic noise.A theoretical framework for analyzing coupled neuronal networks: Application to the olfactory system.Practical approximation method for firing-rate models of coupled neural networks with correlated inputs.Fluctuations and information filtering in coupled populations of spiking neurons with adaptation.Theory of correlation in a network with synaptic depression.Optimal sequential detection of stimuli from multiunit recordings taken in densely populated brain regions.Kv7 channels regulate pairwise spiking covariability in health and disease.Nonequilibrium dynamics of stochastic point processes with refractoriness.Inverse statistical problems: from the inverse Ising problem to data science
P2860
Q28484831-FD0C8276-3F14-4C9E-887C-9105E6321756Q33705229-BE9A480D-14E2-477B-AE56-1BF7A65D92C3Q33809361-3C128D10-7A3F-4803-A34A-22E6BE2152F1Q33879357-242AB6DE-36EA-4CC4-B216-C2E52E8C5CFFQ34211424-5E53B100-A2C6-45D3-A0B9-9D8E15646608Q34440608-74DA25BB-D16E-43CC-A675-D23C762A6EECQ34958946-0972C1E6-8E1F-4973-BEDD-523623719135Q36350771-FEBA1F8D-3659-44BD-9C1C-EA92FAFF224CQ39670979-20843A67-29E2-4B83-B65A-DFB6C45D2625Q41178860-8ECF3C9D-DFB3-41B3-A6A5-8CE62345F3FEQ41328771-868AD8D5-5F2D-483B-9A6E-648E967C2B7EQ41807816-A6BB7B08-FEE2-4B46-98CB-20D81121C54EQ42055758-D011F4EF-12C3-4096-ABD6-4663DEE6FD8CQ42703017-5FEEC16F-E624-4383-8C68-4DDE76EFCBDCQ45068444-D2867448-B698-491C-A06F-6FFCBEDED510Q47735868-F37C2F08-B877-4ADC-B102-E930232E9089Q48717002-28506093-6CBC-43B8-8235-AF871C0BFEBBQ48782946-6DB3FE6C-C1F5-44B5-AB79-5E880E643D4DQ51090363-9DCE7622-3FA7-4706-A466-4AB3D89F17C9Q51656682-2D03A14A-6416-4523-B75C-743F9A3DD7EDQ58250031-2D80BF46-60C2-4325-A35C-286AD4F5FB4D
P2860
Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
2009年學術文章
@zh-hant
name
Mean-field approximations for ...... ns with Markov refractoriness.
@en
Mean-field approximations for ...... ns with Markov refractoriness.
@nl
type
label
Mean-field approximations for ...... ns with Markov refractoriness.
@en
Mean-field approximations for ...... ns with Markov refractoriness.
@nl
prefLabel
Mean-field approximations for ...... ns with Markov refractoriness.
@en
Mean-field approximations for ...... ns with Markov refractoriness.
@nl
P2860
P1433
P1476
Mean-field approximations for ...... ns with Markov refractoriness.
@en
P2093
Kamiar Rahnama Rad
P2860
P304
P356
10.1162/NECO.2008.04-08-757
P577
2009-05-01T00:00:00Z