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This article is part of the supplement: Nineteenth Annual Computational Neuroscience Meeting: CNS*2010

Open Access Poster Presentation

Encoding visual stimuli with a population of Hodgkin-Huxley neurons

Aurel A Lazar* and Yiyin Zhou

Author Affiliations

Department of Electrical Engineering, Columbia University, New York, NY, USA

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BMC Neuroscience 2010, 11(Suppl 1):P180  doi:10.1186/1471-2202-11-S1-P180

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/11/S1/P180


Published:20 July 2010

© 2010 Lazar and Zhou; licensee BioMed Central Ltd.

Poster Presentation

In recent years the increasing availability of multi-electrode recordings has led to the application of neural decoding techniques to the recovery of complex stimuli such as natural scenes. A linear decoding algorithm was presented in [1] for the reconstruction of natural scenes with recognizable moving objects using recordings from a neural population of the cat’s Lateral Geniculate Nucleus (LGN).

Most of the current models of encoding in the early visual system (retina, LGN, V1) consist of a linear receptive field followed by a non-linear spike generation mechanism. In [2] we considered a neural circuit architecture consisting of receptive fields in cascade with an equal number of spiking neural circuits. The neural circuits investigated were integrate-and-fire neurons and ON-OFF neurons with random thresholds and feedback. We demonstrated for the first time a decoding algorithm for natural scenes and shown its dependence on the noise level.

Methods

We investigate a neural encoding architecture for visual stimuli consisting of classical receptive fields (center surround or Gabor) in cascade with an ensemble of Hodgkin-Huxley neurons. Recovery of stimuli encoded with an ensemble of Hodgkin-Huxley neurons with known phase response curves was achieved based on the I/O equivalence between Hodgkin-Huxley neurons and Project-Integrate-and-Fire neurons in [3]. The ensemble of Hodgkin-Huxley neurons considered here is assumed to have unknown phase response curves [4]. We provide a visual stimulus reconstruction algorithm based on the spike times generated by the ensemble of Hodgkin-Huxley neurons and demonstrate its performance using natural video sequences (movies). Fig. 1 shows a sample time instant (a frame of a movie) of the reconstructed (left) and the original (right) visual stimulus.

Acknowledgements

The work presented here was supported by AFOSR under grant number FA9550-09-1-0350.

References

  1. Stanley GB, Li FF, Dan Y: Reconstruction of Natural Scenes from Ensemble Responses in the Lateral Geniculate Nucleus.

    J Neurosci 1999, 19(18):8036-8042. PubMed Abstract | Publisher Full Text OpenURL

  2. Lazar AA, Pnevmatikakis EA, Zhou Y: Encoding of Natural Scenes with Neural Circuits with Random Thresholds.

    BNET Technical Report #06-09, Department of Electrical Engineering, Columbia University, New York, NY 2009. OpenURL

  3. Lazar AA: Population Encoding with Hodgkin-Huxley Neurons.

    IEEE Transactions on Information Theory 2010., 56(2)

    to appear

    PubMed Abstract | PubMed Central Full Text OpenURL

  4. Kim AJ, Lazar AA: Recovery of Stimuli Encoded with a Hodgkin-Huxley Neuron Using Conditional PRCs.

    In In Phase Response Curves in Neuroscience, Springer Edited by Nathan W. Schultheiss, Astrid Prinz, and Rob Butera. 2010.

    to appear

    OpenURL