- Poster Presentation
- Open Access
Encoding visual stimuli with a population of Hodgkin-Huxley neurons
© Lazar and Zhou; licensee BioMed Central Ltd. 2010
Published: 20 July 2010
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  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  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.
The work presented here was supported by AFOSR under grant number FA9550-09-1-0350.
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