"Staircase" Model for a Neural Integrator

Model for a robust neural integrator

Alexei A. Koulakov, Sridhar Raghavachari, Adam Kepecs and John E. Lisman
Nature Neuroscience , August 2002 Volume 5 Number 8 pp 775-782

Integrator circuits in the brain show persistent firing that reflects the sum of previous excitatory and inhibitory inputs from external sources. Integrator circuits have been implicated in parametric working memory, decision making and motor control. Previous work has shown that stable integrator function can be achieved by an excitatory recurrent neural circuit, provided synaptic strengths are tuned with extreme precision (better than 1% accuracy). Here we show that integrator circuits can function without fine tuning if the neuronal units have bistable properties. Two specific mechanisms of bistability are analyzed, one based on local recurrent excitation, the other on the voltage-dependence of the NMDA (N-methyl-D-aspartate) channel. Neither circuit requires fine tuning to perform robust integration, and the latter actually exploits the variability of neuronal conductances.

[Article] [Supplementary methods - PDF] [Supplementary methods - PS]

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Pictorial illustration of how the model works.

Here are some additional simulations for the NMDAR-based model not included in the paper.

If you want to run your own simulations we have constructed a baby-integrator with just 6 neurons. Click here .

Last updated: Mon Jul 29 14:51:30 EDT 2002 (kepecs@brandeis.edu)