NONLINEAR NEURONAL MODE ANALYSIS OF ACTION-POTENTIAL ENCODING IN THE COCKROACH TACTILE SPINE NEURON

Neuronal mode analysis is a recently developed technique for modelling the behavior of nonlinear systems whose outputs consist of action pot entials. The system is modelled as a set of parallel linear filters, o r modes, which feed into a multi-input threshold. The characteristics of the principal modes and the multi-input threshold device can be der ived from Laguerre function expansions of the computed first- and seco nd-order Volterra kernels when the system is stimulated with a randoml y varying input. Neuronal mode analysis was used to model the encoder properties of the cockroach tactile spine neuron, a nonlinear, rapidly adapting, sensory neuron with reliable behavior. The analysis found t wo principal modes, one rapid and excitatory, the other slower and inh ibitory. The two modes have analogies to two of the pathways in a bloc k-structured model of the encoder that was developed from previous phy siological investigations of the neuron. These results support the blo ck-structured model and offer a new approach to identifying the compon ents responsible for the nonlinear dynamic properties of this neuronal encoder.