Chapter Summary

A major challenge in studying any neuro-sensory system is to obtain a general mathematical model of the system input/output behavior. (The rationale for finding a model of a complex nonlinear system should now be abundantly clear to the reader.) In simplest terms, the input stimulus to the system can be controlled, and spikes or graded potentials recorded from one or more interneurons that are causally driven

FIGURE 8.3-9 (A) First-order kernels for the system: Noise-modulated light ^ GC (spike frequency output). Three input conditions were used: (1) entire RF stimulated; (2) center of RF illuminated with spot; (3) annulus of light illuminated peripheral RF. (B) —♦— is the h1 kernel for the system: Noise-modulated light to the entire RF ^ HC (positive peak is from hyperpolarization). —x— is the h1 kernel for the system: Noise current injected intracellularly to a HC ^ GC spike frequency output. Note the difference in h1 peak polarities. (From Marmarelis, P.Z. and K.I. Naka, J. Neurophysiol., 36(4): 619, 1973. With permission.)

FIGURE 8.3-9 (A) First-order kernels for the system: Noise-modulated light ^ GC (spike frequency output). Three input conditions were used: (1) entire RF stimulated; (2) center of RF illuminated with spot; (3) annulus of light illuminated peripheral RF. (B) —♦— is the h1 kernel for the system: Noise-modulated light to the entire RF ^ HC (positive peak is from hyperpolarization). —x— is the h1 kernel for the system: Noise current injected intracellularly to a HC ^ GC spike frequency output. Note the difference in h1 peak polarities. (From Marmarelis, P.Z. and K.I. Naka, J. Neurophysiol., 36(4): 619, 1973. With permission.)

by the input receptor(s). These input/output signals can be used to create mathematical models describing the neuro-sensory system. Very often one can gather clues about why a neuro-sensory system behaves the way it does from neuroanatomical studies, and from the way the neuro-sensory system behavior changes when it is given certain drugs, such as TTX or TEA.

This chapter has described three methods of characterizing neuro-sensory systems. In Section 8.1 discussed that a qualitative statistical tool, the JPST diagram, that can be used to make putative, parsimonious models for neural interactions. The JPST does not yield a mathematical description of the input/output behavior of a neuro-sensory system; rather, it leads to a structural model whose properties can be examined with neural modeling software such as GENESIS or XNBC validate the model. (If it quacks like a duck, it may be a duck.)

The triggered correlation algorithm (TCA), introduced in Section 8.2, was shown to be applicable in neuro-sensory systems with narrow-band or tuned behavior operating on the stimulus. Thus, it has application in auditory systems that exhibit frequency selectivity. (Hypothetically, the TCA could also be used in visual systems exhibiting spatial frequency selectivity.) The TCA was shown not to give useful results if the bandpass Q is low. The TCA yields an equivalent linear weighting function for the frequency selectivity of the neuro-sensory system. Since the TCA

Was this article helpful?

0 0
Peripheral Neuropathy Natural Treatment Options

Peripheral Neuropathy Natural Treatment Options

This guide will help millions of people understand this condition so that they can take control of their lives and make informed decisions. The ebook covers information on a vast number of different types of neuropathy. In addition, it will be a useful resource for their families, caregivers, and health care providers.

Get My Free Ebook


Post a comment