Skip to main content

A cell-type-specific dynamic Bayesian network model for spontaneous and optogenetically evoked activity in the primary visual cortex

Reciprocal interaction between excitatory and inhibitory neurons within and between layers of the cerebral cortex is a major element of brain function. Ensemble extracellular recording techniques using mircroelectrode arrays have permitted recording spiking activity of many neurons simultaneously to characterize network function [1]. Identifying the type of neurons in these recordings is not straightforward due to the variability in extracellular spike shapes, and the irregularities often observed in their interspike interval characteristics. In this study, we used optogenetic tools to genetically target fast spiking interneurons in the primary visual cortex of mice [2]. We modulated their spiking activity by illuminating the region with very short pulses (<1 ms) of light (~470 nm wavelength)in mice primary visual cortex. Using Dynamic Bayesian Network analysis [3], we assessed the effective connectivity between the recorded neurons in the presence and absence of light stimuli under distinct cortical states observed under light anesthesia. DBNs could identify the effective connectivity between putative excitatory pyramidal cells and inhibitory interneurons. These findings suggest a novel and unprecedented way to identify cortical neuronal circuits and characterize the dynamics of their computations in vivo.


  1. Haider B, Duque A, Hasenstaub AR, McCormick DA: Neocortical Network Activity In Vivo Is Generated through a Dynamic Balance of Excitation and Inhibition. Journal of Neuroscience. 2006, 26: 4535-4545. 10.1523/JNEUROSCI.5297-05.2006.

    Article  CAS  PubMed  Google Scholar 

  2. Cardin JA, Carlen M, Meletis K, Knoblich U, Zhang F, Deisseroth K, Tsai L: Targeted optogenetic stimulation and recording of neurons in vivo using cell-type-specific expression of Channelrhodopsin-2. Nature Protocols. 2010, 5: 247-254. 10.1038/nprot.2009.228.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. Eldawlatly S, Zhou Y, Jin R, Oweiss KG: On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles. Neural Computation. 2010, 22: 158-189. 10.1162/neco.2009.11-08-900.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Karim G Oweiss.

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Mohebi, A., Cardin, J.A. & Oweiss, K.G. A cell-type-specific dynamic Bayesian network model for spontaneous and optogenetically evoked activity in the primary visual cortex. BMC Neurosci 12 (Suppl 1), O5 (2011).

Download citation

  • Published:

  • DOI: