Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models

DOI10.1162/neco_a_01021zbMath1414.92126arXiv1602.07389OpenAlexW2963396462WikidataQ49683023 ScholiaQ49683023MaRDI QIDQ5380878

Jonathan W. Pillow, Alison I. Weber

Publication date: 6 June 2019

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

Full work available at URL: https://arxiv.org/abs/1602.07389

zbMATH Keywords

neuron responsedynamic spiking behaviorsPoisson generalized linear models

Mathematics Subject Classification ID

Neural biology (92C20)

Related Items (6)

Firing-rate models for neurons with a broad repertoire of spiking behaviors ⋮ Stability of point process spiking neuron models ⋮ A biophysical and statistical modeling paradigm for connecting neural physiology and function ⋮ Capturing Spike Variability in Noisy Izhikevich Neurons Using Point Process Generalized Linear Models ⋮ Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations ⋮ Omitted variable bias in GLMs of neural spiking activity

Cites Work

• Predicting spike timing of neocortical pyramidal neurons by simple threshold models
• Nonconvergence in Logistic and Poisson Models for Neural Spiking
• Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model
• Learning Quadratic Receptive Fields from Neural Responses to Natural Stimuli
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