Higher-order correlations in common input shapes the output spiking activity of a neural population
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Publication:1620505
DOI10.1016/j.physa.2016.12.002zbMath1400.92022OpenAlexW2566738875MaRDI QIDQ1620505
Fernando Montani, Lisandro Montangie
Publication date: 13 November 2018
Published in: Physica A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physa.2016.12.002
information geometryhigher-order correlationsextended central limit theoremlarge neural ensembleneuronal inputsspiking outputs
Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural networks for/in biological studies, artificial life and related topics (92B20)
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Cites Work
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- Geometry of \(q\)-exponential family of probability distributions
- Scale invariance and related properties of \(q\)-Gaussian systems
- On a \(q\) -central limit theorem consistent with nonextensive statistical mechanics
- A multivariate extension of Hoeffding's lemma
- Statistical modelling of higher-order correlations in pools of neural activity
- Possible generalization of Boltzmann-Gibbs statistics.
- A Unified Approach to the Study of Temporal, Correlational, and Rate Coding
- Causal information quantification of prominent dynamical features of biological neurons
- A symbolic information approach to determine anticipated and delayed synchronization in neuronal circuit models
- Critical Truths About Power Laws
- The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex
- Saddlepoint Approximations with Applications
- Generating Spike Trains with Specified Correlation Coefficients
- Synchronous Firing and Higher-Order Interactions in Neuron Pool
- On some models for multivariate binary variables parallel in complexity with the multivariate Gaussian distribution
- Information-Geometric Measure for Neural Spikes
- Generalization of symmetric α-stable Lévy distributions for q>1
- Asymptotically scale-invariant occupancy of phase space makes the entropy S q extensive
- Central limit theorem and deformed exponentials
- On Information and Sufficiency
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