Abstract
Action potential encoding in the cockroach tactile spine neuron can be represented as a single-input single-output nonlinear dynamic process. We have used a new functional expansion method to characterize the nonlinear behavior of the neural encoder. This method, which yields similar kernels to the Wiener method, is more accurate than the latter and is efficient enough to obtain reasonable kernels in less than 15 min using a personal computer. The input stimulus was band-limited white Gaussian noise and the output consisted of the resulting train of action potentials, which were unitized to give binary values. The kernels and the system input-output signals were used to identify a model for encoding comprising a cascade of dynamic linear, static nonlinear, and dynamic linear components. The two dynamic linear components had repeatable and distinctive forms with the first being low-pass and the second being high-pass. The static nonlinearity was fitted with a fifth-order polynomial function over several input amplitude ranges and had the form of a half-wave rectifier. The complete model gave a good approximation to the output of the neuron when both were subjected to the same novel white noise input signal.
Full text
PDF
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- French A. S. Dynamic properties of the action potential encoder in an insect mechanosensory neuron. Biophys J. 1984 Aug;46(2):285–289. doi: 10.1016/S0006-3495(84)84023-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- French A. S., Holden A. V., Stein R. B. The estimation of the frequency response function of a mechanoreceptor. Kybernetik. 1972 Jul;11(1):15–23. doi: 10.1007/BF00267761. [DOI] [PubMed] [Google Scholar]
- French A. S. Removal of rapid sensory adaptation from an insect mechanoreceptor neuron by oxidizing agents which affect sodium channel inactivation. J Comp Physiol A. 1987 Aug;161(2):275–282. doi: 10.1007/BF00615247. [DOI] [PubMed] [Google Scholar]
- French A. S., Wong R. K. Nonlinear analysis of sensory transduction in an insect mechanoreceptor. Biol Cybern. 1977 Jun 13;26(4):231–240. doi: 10.1007/BF00366595. [DOI] [PubMed] [Google Scholar]
- HODGKIN A. L., HUXLEY A. F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol. 1952 Aug;117(4):500–544. doi: 10.1113/jphysiol.1952.sp004764. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Korenberg M. J., French A. S., Voo S. K. White-noise analysis of nonlinear behavior in an insect sensory neuron: kernel and cascade approaches. Biol Cybern. 1988;58(5):313–320. doi: 10.1007/BF00363940. [DOI] [PubMed] [Google Scholar]
- Korenberg M. J. Identifying nonlinear difference equation and functional expansion representations: the fast orthogonal algorithm. Ann Biomed Eng. 1988;16(1):123–142. doi: 10.1007/BF02367385. [DOI] [PubMed] [Google Scholar]
- Marmarelis P. Z., Naka K. White-noise analysis of a neuron chain: an application of the Wiener theory. Science. 1972 Mar 17;175(4027):1276–1278. doi: 10.1126/science.175.4027.1276. [DOI] [PubMed] [Google Scholar]
- Sakuranaga M., Ando Y., Naka K. Dynamics of the ganglion cell response in the catfish and frog retinas. J Gen Physiol. 1987 Aug;90(2):229–259. doi: 10.1085/jgp.90.2.229. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Spekreijse H., Oosting H. Linearizing: a method for analysing and synthesizing nonlinear systems. Kybernetik. 1970 Apr;7(1):22–31. doi: 10.1007/BF00270331. [DOI] [PubMed] [Google Scholar]
- Stein R. B., French A. S., Holden A. V. The frequency response, coherence, and information capacity of two neuronal models. Biophys J. 1972 Mar;12(3):295–322. doi: 10.1016/S0006-3495(72)86087-9. [DOI] [PMC free article] [PubMed] [Google Scholar]