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Encoding visual stimuli with a population of Hodgkin-Huxley neurons

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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.

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Figure 1

References

  1. 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.

  2. 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

  3. 3.

    Lazar AA: Population Encoding with Hodgkin-Huxley Neurons. IEEE Transactions on Information Theory. 2010, 56 (2): to appear

  4. 4.

    Kim AJ, Lazar AA: Recovery of Stimuli Encoded with a Hodgkin-Huxley Neuron Using Conditional PRCs. In Phase Response Curves in Neuroscience, Springer. Edited by: Nathan W. Schultheiss, Astrid Prinz, and Rob Butera. 2010, to appear

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Acknowledgements

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

Author information

Correspondence to Aurel A Lazar.

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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 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lazar, A.A., Zhou, Y. Encoding visual stimuli with a population of Hodgkin-Huxley neurons. BMC Neurosci 11, P180 (2010) doi:10.1186/1471-2202-11-S1-P180

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Keywords

  • Visual Stimulus
  • Receptive Field
  • Neural Circuit
  • Lateral Geniculate Nucleus
  • Natural Scene