Original Research ARTICLE
Underlying Mechanisms of Cooperativity, Input Specificity, and Associativity of Long-Term Potentiation through a Positive Feedback of Local Protein Synthesis
- 1Beihang University, China
- 2Tsinghua University, China
Long-term potentiation (LTP) is a specific form of activity-dependent synaptic plasticity that is a leading mechanism of learning and memory in mammals. The properties of cooperativity, input specificity, and associativity are essential for LTP; however, the underlying mechanisms are unclear. Here, based on experimentally observed phenomena, we introduce a computational model of synaptic plasticity in a pyramidal cell to explore the mechanisms responsible for the cooperativity, input specificity, and associativity of LTP. The model is based on molecular processes involved in synaptic plasticity and integrates gene expression involved in the regulation of neuronal activity. In the model, we introduce a local positive feedback loop of protein synthesis at each synapse, which is essential for bimodal response and synapse specificity. Bifurcation analysis of the local positive feedback loop of brain-derived neurotrophic factor (BDNF) signaling illustrates the existence of bistability, which is the basis of LTP induction. The local bifurcation diagram provides guidance for the realization of LTP, and the projection of whole system trajectories onto the two-parameter bifurcation diagram confirms the predictions obtained from bifurcation analysis. Moreover, model analysis shows that pre- and postsynaptic components are required to achieve the three properties of LTP. This study provides insights into the mechanisms underlying the cooperativity, input specificity, and associativity of LTP, and the further construction of neural networks for learning and memory.
Keywords: Long-Term Potentiation, cooperativity, Input specificity, Associativity, local positive feedback
Received: 03 Oct 2017;
Accepted: 28 Mar 2018.
Edited by:Florentin Wörgötter, Georg-August-Universität Göttingen, Germany
Reviewed by:Clive R. Bramham, University of Bergen, Norway
Christian Tetzlaff, Max-Planck-Institut für Dynamik und Selbstorganisation, Germany
Zhijie Wang, Donghua University, China
Copyright: © 2018 Hao, Yang and Lei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Dr. Zhuoqin Yang, Beihang University, Beijing, China, email@example.com
Dr. Jinzhi Lei, Tsinghua University, Beijing, China, firstname.lastname@example.org