Predicting the responses of mechanoreceptor neurons to physiological inputs by nonlinear system identification

The nonlinear dynamic properties of action potential encoding were studied in mechanosensory neurons innervating the slits of a slit-sense organ in th e tropical wandering spider, Cupiennius salei. The organ contains two types of neurons that are morphologically similar but have different dynamic pro perties. Type A neurons produce only one or two action potentials in respon se to a mechanical or electrical stimulus of any suprathreshold amplitude, while type B neurons can fire prolonged bursts of action potentials in resp onse to similar stimuli. Neurons were stimulated with pseudorandomly modula ted intracellular current while recording the resultant fluctuations in mem brane potential and action potentials. A parallel cascade method was used t o estimate a third-order Volterra series to describe the nonlinear dynamic relationship between membrane potential and action potentials. Kernels meas ured for the two types of neurons had reproducible forms that showed differ ences between the two neuron types. The measured kernels were able to predi ct the responses of the neurons to novel pseudorandomly modulated inputs wi th reasonable fidelity. However, the Volterra series did not adequately pre dict the difference in responses to step depolarizations. (C) 2001 Biomedic al Engineering Society.