Orientation selectivity using fast feed-forward inhibition

Orientation selectivity using fast feed-forward inhibition
Following a flashed stimulus, I show that a simple neurophysiological mechanism in the primary visual system can generate orientation selectivity based on the first incoming spikes. A biological model of the lateral geniculate nucleus generates an asynchronous wave of spikes, with the most strongly activated neurons firing first. Geniculate activation leads to both the direct excitation of a cortical pyramidal cell and disynaptic feed-forward inhibition. The mechanism provides automatic gain control, so the cortical neurons respond over a wide range of stimulus contrasts. It also demonstrates the biological plausibility of a new computationally efficient neural code: latency rank order coding.

Article: Delorme, A. (2003) Early Cortical Orientation Selectivity: How Fast Shunting Inhibition Decodes the Order of Spike Latencies. Journal of Computational Neuroscience, 15, 357-365. Author's PDF, journal's link.
Recent experimental evidences agreeing with this model:
Monier, C., Chavane, F., Baudot, P., Graham, L., and Fregnac, Y. (2003) Orientation and direction selectivity of excitatory and inhibitory inputs in visual cortical neurons: A diversity of combinations produces spike tuning, Neuron, 37, 663-680.

Johansson R.C., Birznieks, I. (2004) First spikes in ensembles of human tactile afferents code complex spatial fingertip events, Nature Neuroscience, 7(2), 170-177.

Neuron's simulation files:

basic_model.hoc
contains the code for the main model (requires data files in the archive below). Implementation of a large number of converging input (with latencies of discharge read from a data file) to a single cortical neuron.

delorme_model.tar.gz
contains a variety of Neuron source files for neural model presented in the article and some data files for latency of discharge of neurons in the LGN. See 1ST_README.txt file in archive for how to run the model or access the content of the archive here.

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basic_model.hoc	contains the code for the main model (requires data files in the archive below). Implementation of a large number of converging input (with latencies of discharge read from a data file) to a single cortical neuron.
delorme_model.tar.gz	contains a variety of Neuron source files for neural model presented in the article and some data files for latency of discharge of neurons in the LGN. See 1ST_README.txt file in archive for how to run the model or access the content of the archive here.