Shunting inhibition does not have a divisive effect on firing rates
Neural Computation
A spiking neuron model: applications and learning
Neural Networks
Exact Inferences in a Neural Implementation of a Hidden Markov Model
Neural Computation
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Many implementations of adaptive signal processing in thenervous system are likely to require a mechanism for gain controlat the single neuron level. To properly adjust the gain of anindividual neuron, it may be necessary to use information carriedby neurons in other parts of the system. The ability to adjust thegain of neurons in one part of the brain, using control signalsarising from another, has been observed in the electrosensorysystem of weakly electric fish, where descending pathways to afirst-order sensory nucleus have been shown to influence the gainof its output neurons. Although the neural circuitry associatedwith this system is well studied, the exact nature of the gaincontrol mechanism is not fully understood. In this paper, wepropose a mechanism based on the regulation of total membraneconductance via synaptic activity on descending pathways. Using asimple neural model, we show how the activity levels of pairedexcitatory and inhibitory control pathways can regulate the gainand baseline excitation of a target neuron.