Dynamics of Neural Circuits

John Hertz

Nordita, Copenhagen, Denmark

Abstract: Neural circuitry is highly diverse, but almost all of it shares certain universal features, notably high connectivity and competition between excitation and inhibition. Another feature whose imortance has been widely recognized and studied recently is synaptic adaptation: Effective connection strengths between neurons change on the several-hundred-ms timescale, and this additional layer of dynamics has consequences for the network dynamics. In this talk I will describe two general universality classes of the network dynamics that occur as a result of excitatory-inhibitory conpetition and show the way information may be encoded in the different cases. In the first, neuronal excitation-inhibition loops give rise to oscillatory dynamics, which can then be modulated by the slower synaptic dynamics. The antenna lobe, which encodes olfactory stimuli in insects, offers an interesting example of such a system. In the second class, exemplified by the neocortex of mammals, separately strong excitatory and inhibitory interactions in densely-connected networks lead to a self-consistent "balanced state" in which individual neurons fire irregularly and information is carried by the average firing of large populations. Synaptic adaptation can contribute to this information transmission, making the firing rates subject more to changes in inputs than to the input rates themselves, while generally enhancing the stability of the balanced state of the network.