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Generalized Linear Models for Point Process Analyses of Neural Spiking Activity

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Encyclopedia of Computational Neuroscience

Definition

Point process-generalized linear model. An adaptation of the generalized linear model framework to point processes using local Bernoulli or local Poisson models to analyze the relationship between neural spiking activity and relevant covariates such as putative stimuli and spike history.

Detailed Description

Most systems neuroscience experiments entail applying a stimulus and measuring the response which is commonly the spiking activity of one or more neurons (Brown et al. 2004; Paninski 2004; Truccolo et al. 2005; see entries “Spike Train,” “Spike Train Analysis: Overview”). The typical objective of the experiment is to define how spiking activity in a given brain area changes in response to the stimulus under a range of different conditions. From a statistical standpoint, this type of experimental design requires a regression model in which the observations can be spiking activity and the regressors can be the stimulus and any other relevant covariates. The generalized...

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Author information

Authors and Affiliations

  1. Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E25-519, Cambridge, 02139, MA, USA

    Emery N. Brown

  2. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Zhe Chen & Emery N. Brown

  3. Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA

    Emery N. Brown

  4. Department of Psychiatry, Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA

    Zhe Chen

Authors
  1. Zhe Chen
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  2. Emery N. Brown
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Corresponding author

Correspondence to Zhe Chen .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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Chen, Z., Brown, E.N. (2014). Generalized Linear Models for Point Process Analyses of Neural Spiking Activity. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_393-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_393-1

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

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