Work place: College of Information Science and Technology, Donghua University, Shanghai, China
E-mail: shihaiboh@gmail.com
Website:
Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Computer Graphics and Visualization, Data Structures and Algorithms
Biography
Haibo Shi, born in China in 1985, earned B.S. degree in Pharmacology in 2007 from Zhejiang University of Traditional Chinese Medicine, Hangzhou, China, m.s. degree in Pattern Recognition and Intelligence System from Donghua University, Shanghai, China. His research interests are computational neuroscience, visual perception, and object recognition.
By Jinli Xie Zhijie Wang Haibo Shi
DOI: https://doi.org/10.5815/ijcnis.2011.04.03, Pub. Date: 8 Jun. 2011
The firing activity of a neuronal population is correlated, which has been linked to information coding and exchanging. Short-term synaptic plasticity allows synapses to increase (facilitate) or decrease (depress) over a wide range of time scales. It is critical to understand the characteristics and mechanisms of the correlated firing and the role of short-term synaptic plasticity in regulating firing activity. The short-term synaptic depression and facilitation are examined at the synapses in the inhibitory feedback loop of feedback neural networks. Numerical simulations reveal that the modulation of the correlated firing by dynamics of depression and facilitation is due to their effects on the synaptic strength. By varying synaptic time constants, the enhancement in either firing rate or intensity of oscillations can improve the correlated firing. Our study thus provides a general computational analysis of the sequential interaction of short-term plasticity with neuronal firing.
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