DocumentCode :
3573907
Title :
Memory and computing function of four-node neuronal network motifs
Author :
Huiyan Li ; Chen Liu ; Jiang Wang
Author_Institution :
Dept. of Autom. & Electr. Eng., Tianjin Univ. of Technol. & Educations, Tianjin, China
fYear :
2014
Firstpage :
5818
Lastpage :
5823
Abstract :
Four-node neuronal network motifs are widespread in neural networks. Their dynamical and functional roles are studied in this paper. By computational modeling, firing-rate model and integrate-and-fire neuron model with the chemical coupling are used to model two typical four-node neuronal network motifs. Numerical results show that the structures of the motifs and the properties of every node play the significant roles in the dynamics and functions. By analyzing the impacts of the input current and the neuronal excitability, several interesting phenomena, such as acceleration and delay of response and long- and short-term memory, are observed. In addition, it is shown that the large time constants can prolong short-term memory which plays important roles in almost all neural computation and cognition task. Furthermore, these motifs can accomplish simple calculations of subtractors and comparators.
Keywords :
cognitive systems; neural nets; chemical coupling; cognition; comparators; computational modeling; computing function; dynamical role; firing-rate model; four-node neuronal network motif; functional role; input current; integrate-and-fire neuron model; long-term memory; memory function; neural computation; neural network; neuronal excitability; response acceleration; response delay; short-term memory; subtractors; time constant; Biological neural networks; Biological system modeling; Complex networks; Computational modeling; Delays; Neurons; dynamics; four-neuron motifs; function; memory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7053714
Filename :
7053714
Link To Document :
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