A new method to infer higher-order spike correlations from membrane potentials

DOI10.1007/s10827-013-0446-8zbMath1382.92077OpenAlexW2132758478WikidataQ42590814 ScholiaQ42590814MaRDI QIDQ1704686

Clemens Boucsein, Imke C. G. Reimer, Benjamin Staude, Stefan Rotter

Publication date: 13 March 2018

Published in: Journal of Computational Neuroscience (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10827-013-0446-8

zbMATH Keywords

shot noise processcorrelated neuronal groupsintracellular recordingpresynaptic populationsubthreshold activity

Mathematics Subject Classification ID

Neural biology (92C20) Biophysics (92C05)

Uses Software

• NEURON

Cites Work

• A multichannel shot noise approach to describe synaptic background activity in neurons
• Exact digital simulation of time-invariant linear systems with applications to neuronal modeling
• Decomposition of neuronal assembly activity via empirical de-Poissonization
• The High-Conductance State of Cortical Networks
• The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
• Generation of Correlated Spike Trains
• Spike Train Statistics and Dynamics with Synaptic Input from any Renewal Process: A Population Density Approach
• Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons
• The general cumulants for a filtered point process
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