Dynamic models of neural spiking activity

Gabriela Czanner, Anna A. Dreyer, Uri T. Eden, Sylvia Wirth, Hubert H. Lim, Wendy Suzuki, Emery N. Brown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a state-space generalized linear model (SS-GLM) for characterizing neural spiking activity in multiple trials. We estimate the model parameters by maximum likelihood using an approximate Expectation-Maximization (EM) algorithm which employs a recursive point process filter, fixed-interval smoothing and state-space covariance algorithms. We assess model goodness-of-fit using the time-rescaling theorem and guide the choice of model order with Akaike's information criterion. We illustrate our approach in two applications. In the analysis of hippocampal neural activity recorded from a monkey performing a location-scene association task, we use the model to quantify the neural changes related to learning. In the analysis of primary auditory cortex responses to different levels of electrical stimulation in the rat midbrain, we use the method to analyze auditory threshold detection. Our findings have important implications for developing theoretically-sound and practical tools to characterize the dynamics of spiking activity.

Original languageEnglish (US)
Title of host publicationProceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Pages5812-5817
Number of pages6
DOIs
StatePublished - 2007
Event46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States
Duration: Dec 12 2007Dec 14 2007

Other

Other46th IEEE Conference on Decision and Control 2007, CDC
CountryUnited States
CityNew Orleans, LA
Period12/12/0712/14/07

Fingerprint

Dynamic models
Maximum likelihood
Rats
Acoustic waves

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

Czanner, G., Dreyer, A. A., Eden, U. T., Wirth, S., Lim, H. H., Suzuki, W., & Brown, E. N. (2007). Dynamic models of neural spiking activity. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 5812-5817). [4434689] https://doi.org/10.1109/CDC.2007.4434689

Dynamic models of neural spiking activity. / Czanner, Gabriela; Dreyer, Anna A.; Eden, Uri T.; Wirth, Sylvia; Lim, Hubert H.; Suzuki, Wendy; Brown, Emery N.

Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. 2007. p. 5812-5817 4434689.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Czanner, G, Dreyer, AA, Eden, UT, Wirth, S, Lim, HH, Suzuki, W & Brown, EN 2007, Dynamic models of neural spiking activity. in Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC., 4434689, pp. 5812-5817, 46th IEEE Conference on Decision and Control 2007, CDC, New Orleans, LA, United States, 12/12/07. https://doi.org/10.1109/CDC.2007.4434689
Czanner G, Dreyer AA, Eden UT, Wirth S, Lim HH, Suzuki W et al. Dynamic models of neural spiking activity. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. 2007. p. 5812-5817. 4434689 https://doi.org/10.1109/CDC.2007.4434689
Czanner, Gabriela ; Dreyer, Anna A. ; Eden, Uri T. ; Wirth, Sylvia ; Lim, Hubert H. ; Suzuki, Wendy ; Brown, Emery N. / Dynamic models of neural spiking activity. Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC. 2007. pp. 5812-5817
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