期刊论文详细信息
Frontiers in Computational Neuroscience
Spike-Timing Dependent Plasticity Effect on the Temporal Patterning of Neural Synchronization
Joel Zirkle1  Leonid L. Rubchinsky2 
[1] Department of Mathematical Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN, United States;Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, United States;
关键词: STDP;    synaptic plasticity;    intermittency;    synchronization;    phase-locking;    neural oscillations;   
DOI  :  10.3389/fncom.2020.00052
来源: DOAJ
【 摘 要 】

Neural synchrony in the brain at rest is usually variable and intermittent, thus intervals of predominantly synchronized activity are interrupted by intervals of desynchronized activity. Prior studies suggested that this temporal structure of the weakly synchronous activity might be functionally significant: many short desynchronizations may be functionally different from few long desynchronizations even if the average synchrony level is the same. In this study, we used computational neuroscience methods to investigate the effects of spike-timing dependent plasticity (STDP) on the temporal patterns of synchronization in a simple model. We employed a small network of conductance-based model neurons that were connected via excitatory plastic synapses. The dynamics of this network was subjected to the time-series analysis methods used in prior experimental studies. We found that STDP could alter the synchronized dynamics in the network in several ways, depending on the time scale that plasticity acts on. However, in general, the action of STDP in the simple network considered here is to promote dynamics with short desynchronizations (i.e., dynamics reminiscent of that observed in experimental studies). Complex interplay of the cellular and synaptic dynamics may lead to the activity-dependent adjustment of synaptic strength in such a way as to facilitate experimentally observed short desynchronizations in the intermittently synchronized neural activity.

【 授权许可】

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