Structural classification of multi-input biological nonlinear systems

Structural classification and parameter estimation results that are applicable to multi-input nonlinear biological systems are presented. To use these methods properly, it is necessary first to establish that the structure of the system under study belongs to one of the broad structural classes examined; such a priori constraints would generally be inferred from the known anatomical and physiochemical properties of the system. Using the methods presented, input-output measurements are used to restrict the structural classification of the system further and to estimate the parameters of the classified model. Ongoing efforts to identify the spatiotemporal nonlinear networks that underlie the extracellularly recorded (spike) responses of visual cortical neurons to photic stimulation are discussed