Dynamical analysis of Josephson junction neuron model driven by a thermal signal and its digital implementation based on microcontroller

2021 ◽  
Vol 94 (12) ◽  
Author(s):  
Noel Freddy Fotie Foka ◽  
Balamurali Ramakrishnan ◽  
André Rodrigue Tchamda ◽  
Sifeu Takougang Kingni ◽  
Karthikeyan Rajagopal ◽  
...  
Keyword(s):  
Josephson Junction ◽  
Neuron Model ◽  
Dynamical Analysis ◽  
Digital Implementation ◽  
Model Driven ◽  
Thermal Signal

Dynamical Response of Electrical Activities in Digital Neuron Circuit Driven by Autapse

2017 ◽  
Vol 27 (12) ◽  
pp. 1750187 ◽  
Author(s):  
Guodong Ren ◽  
Ping Zhou ◽  
Jun Ma ◽  
Ning Cai ◽  
Ahmed Alsaedi ◽  
...  
Keyword(s):  
Electromagnetic Induction ◽  
Numerical Scheme ◽  
Neuron Model ◽  
Biological Function ◽  
Digital Circuit ◽  
Dynamical Analysis ◽  
Dynamical Response ◽  
Neuron Models ◽  
Model Driven ◽  
Electrical Activities

Neuron models are available for computational neurodynamics and the main dynamical properties can be reproduced in the numerical scheme for further dynamical analysis. During model setting, some important biophysical factors should be considered and thus reliable neuron models can be approached. In this paper, a neuron model driven by autapse connection is investigated with the effect of electromagnetic induction being considered as well. A digital neuronal circuit is designed by using FPGA, the dynamical response and biological function of autapse connection. It is found that positive feedback in autapse can modulate the oscillating behaviors in the digital circuit, which could be effective for further investigation on digital neuronal network.

scholarly journals Digital Implementation of the Two-Compartmental Pinsky–Rinzel Pyramidal Neuron Model

2018 ◽  
Vol 12 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Elahe Rahimian ◽  
Soheil Zabihi ◽  
Mahmood Amiri ◽  
Bernabe Linares-Barranco
Keyword(s):  
Pyramidal Neuron ◽  
Neuron Model ◽  
Digital Implementation

scholarly journals Digital implementation of Hodgkin–Huxley neuron model for neurological diseases studies

2017 ◽  
Vol 23 (1) ◽  
pp. 10-14 ◽  
Author(s):  
Timothée Levi ◽  
Farad Khoyratee ◽  
Sylvain Saïghi ◽  
Yoshiho Ikeuchi
Keyword(s):  
Neuron Model ◽  
Neurological Diseases ◽  
Digital Implementation

Statistics of a neuron model driven by asymmetric colored noise

2015 ◽  
Vol 91 (2) ◽  
Author(s):  
Finn Müller-Hansen ◽  
Felix Droste ◽  
Benjamin Lindner
Keyword(s):  
Neuron Model ◽  
Colored Noise ◽  
Model Driven

scholarly journals Implementation of a neuron model using FPGAS

2003 ◽  
Vol 1 (03) ◽  
Author(s):  
M. A. Bañuelos-Saucedo ◽  
J. Castillo-Hernández ◽  
S. Quintana-Thierry ◽  
R. Damián-Zamacona ◽  
J. Valeriano-Assem ◽  
...  
Keyword(s):  
Neuron Model ◽  
Parallel Architecture ◽  
Recognition System ◽  
Activation Function ◽  
Control Problems ◽  
Digital Implementation ◽  
Field Programmable ◽  
Simulation Results ◽  
And Control ◽  
Present Simulation

Artificial neural networks base their processing capabilities in a parallel architecture, and this makes them useful to solve pattern recognition, system identification, and control problems. In this paper, we present a FPGA (Field Programmable Gate Array) based digital implementation of a McCulloch-Pitts type of neuron model with three types of non-linear activation function: step, ramp-saturation, and sigmoid. We present the VHDL language code used to implement the neurons as well as to present simulation results obtained with Xilinx Foundation 3.0 software. The results are analyzed in terms of speed and percentage of chip usage.

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