Information Geometry of Interspike Intervals in Spiking Neurons

DOI10.1162/089976605774320593zbMath1079.92013OpenAlexW2116399098WikidataQ81326745 ScholiaQ81326745MaRDI QIDQ3370751

Kayushi Ikeda

Publication date: 8 February 2006

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/089976605774320593

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Neural biology (92C20) Statistical aspects of information-theoretic topics (62B10)

Related Items

Information-Geometric Measures as Robust Estimators of Connection Strengths and External Inputs, Capacity of a Single Spiking Neuron Channel, Estimating Instantaneous Irregularity of Neuronal Firing, Influence of External Inputs and Asymmetry of Connections on Information-Geometric Measures Involving Up to Ten Neuronal Interactions, Unnamed Item, Information-Geometric Measures for Estimation of Connection Weight Under Correlated Inputs, Estimating Spiking Irregularities Under Changing Environments

Cites Work

• Information geometry of estimating functions in semi-parametric statistical models
• Attractor Reliability Reveals Deterministic Structure in Neuronal Spike Trains
• Statistical inference under multiterminal rate restrictions: a differential geometric approach
• Conditional likelihood and unconditional optimum estimating equations
• Information geometry on hierarchy of probability distributions
• Differences in Spiking Patterns Among Cortical Neurons