Biases in white noise analysis due to non-Poisson spike generation

Jonathan W. Pillow, Eero Simoncelli

Research output: Contribution to journalArticle

Abstract

White noise analysis methods for characterizing neurons typically ignore the dynamics of neural spike generation, assuming that spikes arise from an inhomogeneous Poisson process. We show that when spikes arise from a leaky integrate-and-fire mechanism, a classical white noise estimate of a neuron's temporal receptive field is significantly biased. We develop a modified estimator for linear characterization of such neurons, and demonstrate its effectiveness in simulation. Finally, we apply it to physiological data and show that spiking dynamics may account for changes observed in the receptive fields measured at different contrasts.

Original languageEnglish (US)
Pages (from-to)109-115
Number of pages7
JournalNeurocomputing
Volume52-54
DOIs
StatePublished - Jun 2003

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White noise
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Keywords

  • Spike generation
  • White noise analysis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Biases in white noise analysis due to non-Poisson spike generation. / Pillow, Jonathan W.; Simoncelli, Eero.

In: Neurocomputing, Vol. 52-54, 06.2003, p. 109-115.

Research output: Contribution to journalArticle

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