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Flexible joint modeling of mean and dispersion for the directional tuning of neuronal spike counts

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  • María Alonso‐Pena
  • Irène Gijbels
  • Rosa M. Crujeiras

Abstract

The study of how the number of spikes in a middle temporal visual area (MT/V5) neuron is tuned to the direction of a visual stimulus has attracted considerable attention over the years, but recent studies suggest that the variability of the number of spikes might also be influenced by the directional stimulus. This entails that Poisson regression models are not adequate for this type of data, as the observations usually present over/underdispersion (or both) with respect to the Poisson distribution. This paper makes use of the double exponential family and presents a flexible model to estimate, jointly, the mean and dispersion functions, accounting for the effect of a circular covariate. The empirical performance of the proposal is explored via simulations and an application to a neurological data set is shown.

Suggested Citation

  • María Alonso‐Pena & Irène Gijbels & Rosa M. Crujeiras, 2023. "Flexible joint modeling of mean and dispersion for the directional tuning of neuronal spike counts," Biometrics, The International Biometric Society, vol. 79(4), pages 3431-3444, December.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:4:p:3431-3444
    DOI: 10.1111/biom.13882
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    References listed on IDEAS

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    7. Christophe Croux & Irène Gijbels & Ilaria Prosdocimi, 2012. "Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models," Biometrics, The International Biometric Society, vol. 68(1), pages 31-44, March.
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