CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains.
about
State-space analysis of time-varying higher-order spike correlation for multiple neural spike train dataNeuronal assembly detection and cell membership specification by principal component analysis.Beyond statistical significance: implications of network structure on neuronal activity.A maximum entropy test for evaluating higher-order correlations in spike counts.Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks.ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike TrainsDetection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.Stimuli Reduce the Dimensionality of Cortical Activity.Efficient identification of assembly neurons within massively parallel spike trains.Serial Spike Time Correlations Affect Probability Distribution of Joint Spike EventsFinding neural assemblies with frequent item set mining.Cell assemblies at multiple time scales with arbitrary lag constellations.The relevance of network micro-structure for neural dynamicsA generative spike train model with time-structured higher order correlations.Statistical evaluation of synchronous spike patterns extracted by frequent item set mining.A new method to infer higher-order spike correlations from membrane potentials.Higher-order correlations in non-stationary parallel spike trains: statistical modeling and inference.A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons.Neutral stability, rate propagation, and critical branching in feedforward networks.Distinguishing the causes of firing with the membrane potential slope.Multiple tests based on a gaussian approximation of the unitary events method with delayed coincidence count.Methods for identification of spike patterns in massively parallel spike trains.Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings.Understanding Neural Population Coding: Information Theoretic Insights from the Auditory SystemDesigning Workflows for the Reproducible Analysis of Electrophysiological Data
P2860
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P2860
CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
2009年论文
@zh
2009年论文
@zh-cn
name
CuBIC: cumulant based inferenc ...... ssively parallel spike trains.
@en
type
label
CuBIC: cumulant based inferenc ...... ssively parallel spike trains.
@en
prefLabel
CuBIC: cumulant based inferenc ...... ssively parallel spike trains.
@en
P2860
P1476
CuBIC: cumulant based inferenc ...... ssively parallel spike trains.
@en
P2093
Benjamin Staude
Stefan Rotter
P2860
P2888
P304
P356
10.1007/S10827-009-0195-X
P577
2009-10-28T00:00:00Z
P5875
P6179
1015166300