Response characteristics of a neuron model to a periodic input

1974 ◽  
Vol 16 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Shunsuke Sato ◽  
Masaaki Hatta ◽  
Jin-Ichi Nagumo
Keyword(s):  
Neuron Model ◽  
Response Characteristics ◽  
Periodic Input

Smoothing Facilitates the Detection of Coupled Responses in Psychophysiological Time Series

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Electrodermal Activity ◽  
Moving Average ◽  
Type I ◽  
Facial Electromyography ◽  
Response Characteristics ◽  
Smoothing Methods ◽  
Response Systems ◽  
Different Response

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

Interpreting Open- and Closed-Loop Transfer Relations Between Cardiorespiratory Parameters: Lessons Learned from a Computer Model of Beat-to-Beat Cardiovascular Regulation

1997 ◽  
Vol 36 (04/05) ◽  
pp. 237-240
Author(s):  
P. Hammer ◽  
D. Litvack ◽  
J. P. Saul
Keyword(s):  
Computer Model ◽  
Closed Loop ◽  
Computer Models ◽  
Cardiovascular Regulation ◽  
Cardiovascular Control ◽  
Lessons Learned ◽  
Multiple Systems ◽  
Response Characteristics ◽  
Similarities And Differences

Abstract:A computer model of cardiovascular control has been developed based on the response characteristics of cardiovascular control components derived from experiments in animals and humans. Results from the model were compared to those obtained experimentally in humans, and the similarities and differences were used to identify both the strengths and inadequacies of the concepts used to form the model. Findings were confirmatory of some concepts but contrary to some which are firmly held in the literature, indicating that understanding the complexity of cardiovascular control probably requires a combination of experiments and computer models which integrate multiple systems and allow for determination of sufficiency and necessity.

Low Capacity Implementation of a Pulse-Type Chaotic Neuron Model

2016 ◽  
Vol 136 (10) ◽  
pp. 1424-1430 ◽  
Author(s):  
Yoshiki Sasaki ◽  
Katsutoshi Saeki ◽  
Yoshifumi Sekine
Keyword(s):  
Neuron Model ◽  
Pulse Type ◽  
Chaotic Neuron

Hydroelastic Response Characteristics of a Pontoon Type VLFS in Waves

1998 ◽  
Vol 1998 (183) ◽  
pp. 211-218 ◽  
Author(s):  
Yoshio Iwahashi ◽  
Shigeo Ohmatsu ◽  
Takashi Tsubogo
Keyword(s):  
Response Characteristics ◽  
Hydroelastic Response
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