Abstract
This study is a “morphosis” of the presented modified stochastic synaptic model (MSSM) with major validations using evidences from a number of clinical as well computational studies addressing the general question of copying the dynamics of synaptic transmission. The MSSM represents a, relatively, complex model-compilation of the synaptic connecting process with a focus on copying the relevant biophysical details in order to capture to the computational capacity of biological neural circuitry. The use of MSSM in large scale simulations has been mainly challenged due to the heavy mathematical functional execution, and more importantly due its sensitivity to high (>60 Hz) input firing rates. The presented analysis addresses both aspects with slightly new implementation of the model. It shows that the new understanding about vesicles dynamics helps the MSSM to present a richer repertoire of dynamics and meets the required functional synaptic heterogeneity.
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Ellatihy, K., Bogdan, M. (2017). Enhancements on the Modified Stochastic Synaptic Model: The Functional Heterogeneity. In: Lintas, A., Rovetta, S., Verschure, P., Villa, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2017. ICANN 2017. Lecture Notes in Computer Science(), vol 10613. Springer, Cham. https://doi.org/10.1007/978-3-319-68600-4_45
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DOI: https://doi.org/10.1007/978-3-319-68600-4_45
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