Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add filters








Language
Year range
1.
Chinese Journal of General Practitioners ; (6): 299-301, 2016.
Article in Chinese | WPRIM | ID: wpr-494244
2.
Journal of Biomedical Engineering ; (6): 1241-1245, 2009.
Article in Chinese | WPRIM | ID: wpr-244652

ABSTRACT

We have investigated the effects of high frequency (HF) signal on firing activity in a biologically realistic system--the noisy Hodgkin-Huxley (HH) neuron model via numerical simulations. The results show that when the HF amplitude to frequency ratio (AFR) increases, the firing rate is diminished and stochastic resonance disappears, even the HH neuron model is processing a stimulus of its most sensitive frequency. When the noise intensity is strong, the vibration resonance can be observed. Moreover, the fluctuation around the resting potential will be replaced by an oscillation of the same high frequency with the increasing AFR. The inhibition of the firing activity is consistent with the results of experiment in vivo that HF current can stop the transmission of action potential in peripheral nerve. This study is of functional significance to the biomedical research on the damages caused by electro-pollution in vivo and signal processing.


Subject(s)
Humans , Action Potentials , Artifacts , Computer Simulation , Models, Neurological , Neurons , Physiology , Stochastic Processes
3.
Journal of Biomedical Engineering ; (6): 912-916, 2009.
Article in Chinese | WPRIM | ID: wpr-294541

ABSTRACT

In nonlinear systems, noise can improve the responses of the systems with appropriate noise intensity. This phenomenon is called stochastic resonance. Biological neural systems are noisy and stochastic resonance has been found in them experimentally and theoretically. Now many researches focus on the signal transmission and processing in neural models. So this paper introduces the researches of stochastic resonance in noisy neural models. Then the recent research achievement and progress are reviewed in the following three aspects: noise; the development of stochastic resonance; and neural network. At last, the foreground of the study is discussed.


Subject(s)
Humans , Models, Neurological , Neurons , Physiology , Nonlinear Dynamics , Signal Transduction , Stochastic Processes
SELECTION OF CITATIONS
SEARCH DETAIL