Improved Similarity Measures for Small Sets of Spike Trains

DOI10.1162/NECO_a_00208zbMath1237.92016WikidataQ45773371 ScholiaQ45773371MaRDI QIDQ2887004

Felipe Gerhard, Wulfram Gerstner, Richard Naud, Skander Mensi

Publication date: 15 May 2012

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

Mathematics Subject Classification ID

Neural biology (92C20) Biomedical imaging and signal processing (92C55)

Related Items (6)

Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences ⋮ Multineuron spike train analysis with R-convolution linear combination kernel ⋮ A hidden Markov model for decoding and the analysis of replay in spike trains ⋮ Modulation of spike and burst rate in a minimal neuronal circuit with feed-forward inhibition ⋮ A New Class of Metrics for Spike Trains ⋮ A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations

Cites Work

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• The Time-Rescaling Theorem and Its Application to Neural Spike Train Data Analysis
• Firing patterns in the adaptive exponential integrate-and-fire model
• An introduction to the theory of point processes
• Predicting spike timing of neocortical pyramidal neurons by simple threshold models
• A Novel Spike Distance
• A Method for Selecting the Bin Size of a Time Histogram
• A Reproducing Kernel Hilbert Space Framework for Spike Train Signal Processing
• Metric-space analysis of spike trains: theory, algorithms and application
• Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces
• Spiking Neuron Models

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