Abstract
The neurophysiological view considers the working memory (WM) as a persistence of neural information in the cerebral cortex [1], that external stimulation will activate some pyramidal cells and their continuous activation after stimulus being removed indicates the memory of stimulus, but with the fading of activities, memory will be gradually decaying. More and more studies [2] have shown that the mechanism of neural activities persisting and decaying is not only related to the structure of neural circuits, but also closely related to the synaptic mechanisms. In this paper, we design the neural computational circuit of persistence of neural activities by combining the synaptic mechanism and the structure of neural circuit. Firstly, in the aspect of circuit structure, the recurrent circuit of pyramidal neurons was used as the main circuit to achieve the persistence, and then an auxiliary circuit was designed to regulate the firing rate of main circuit to achieve the “decaying” of neural activities; Secondly, in the computational circuit, we consider the mechanism of synaptic depression and slow synapse. From the structure of neural circuits and synaptic mechanism, we try to explore the neural computational mechanism of neural information persisting and decaying over the time, which is beneficial to explore the true neural mechanism of WM.
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Acknowledgments
This work was supported by the NSFC project (Project Nos. 61771146 and 61375122), and (in part) by Shanghai Science and Technology Development Funds (13dz2260200, 13511504300).
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Dawei, D., Weihui, Zihao, S. (2018). A Bio-Feasible Computational Circuit for Neural Activities Persisting and Decaying. In: Kůrková, V., Manolopoulos, Y., Hammer, B., Iliadis, L., Maglogiannis, I. (eds) Artificial Neural Networks and Machine Learning – ICANN 2018. ICANN 2018. Lecture Notes in Computer Science(), vol 11140. Springer, Cham. https://doi.org/10.1007/978-3-030-01421-6_37
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DOI: https://doi.org/10.1007/978-3-030-01421-6_37
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