Detecting higher-order interactions among the spiking events in a group of neurons
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Publication:1896919
DOI10.1007/BF00199057zbMath0826.92008WikidataQ57988799 ScholiaQ57988799MaRDI QIDQ1896919
Publication date: 11 September 1995
Published in: Biological Cybernetics (Search for Journal in Brave)
invariancesignificance testsminimal graphMarkov fieldspike train datafrequency distribution of higher- order correlationsinteractions among groups of neuronsminimum relative entropy approximations
Related Items (16)
An information-geometric approach to a theory of pragmatic structuring ⋮ Information-Geometric Measure for Neural Spikes ⋮ A simple mechanism for beyond-pairwise correlations in integrate-and-fire neurons ⋮ Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina ⋮ Spatiotemporal Conditional Inference and Hypothesis Tests for Neural Ensemble Spiking Precision ⋮ Exact Solutions for Rate and Synchrony in Recurrent Networks of Coincidence Detectors ⋮ Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule ⋮ Conditional Mixture Model for Correlated Neuronal Spikes ⋮ Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance ⋮ Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons ⋮ Synchronous Firing and Higher-Order Interactions in Neuron Pool ⋮ Generation of Synthetic Spike Trains with Defined Pairwise Correlations ⋮ Modeling the Correlated Activity of Neural Populations: A Review ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Spatiotemporal Structure in Large Neuronal Networks Detected from Cross-Correlation
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