Model for a robust neural integrator

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, and 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.

The authors are grateful to C. Kaneko and H. Sompolinsky for encouragement and to S. Seung and his group for numerous helpful suggestions. A.A.K. and A. K. were supported by fellowships from

the Swartz and Alfred P. Sloan Foundations. We also acknowledge grants NIH 461434 and NSF 450578.

Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, 92037, California, USA

Department of Physics, University of Utah, 115 South 1400 East, Salt Lake City, 84112, Utah, USA

Volen Center for Complex Systems, Mailstop 013, Brandeis University, Waltham, 02454, Massachusetts, USA

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