The utility of the white noise method in characterizing neuro-sensory systems is limited by several factors. Because of the difficulty in calculating and interpreting kernels of order 3 and higher, applications of white noise analysis have generally been limited to first- and second-order system descriptions. This limits the accurate application of the method to systems that are weakly nonlinear. Also, it is difficult to go from h1 and h2 to meaningful conclusions about the anatomy and physiology of the NSUS. Because there are so few other effective systems characterization methods available to study nonlinear systems (e.g., inverse describing functions, triggered correlation), white noise analysis is expected to be used in the future to characterize and model other weakly nonlinear neuro-sensory systems.
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