Postsynaptic Potential Energy as Determinant of Synaptic Plasticity - Chen, Huanwen; Xie, Lijuan; Wang, Yijun; Zhang, Hang (Frontiers in Computational Neuroscience, 2022)
Metabolic energy can be used as a unifying principle to control neuronal activity. However, whether and how metabolic energy alone can determine the outcome of synaptic plasticity remains unclear. In this study, a computational model of synaptic plasticity that is completely determined by energy is proposed. A simple quantitative relationship between synaptic plasticity and postsynaptic potential energy is established. Synaptic weight is directly proportional to the difference between the baseline potential energy and the suprathreshold potential energy and is constrained by the maximum energy supply. Results show that the energy constraint improves the performance of synaptic plasticity and avoids setting the hard boundary of synaptic weights. With the same set of model parameters, our model can reproduce several classical experiments in homo and heterosynaptic plasticity. The proposed model can explain the interaction mechanism of Hebbian and homeostatic plasticity at the cellular level. Homeostatic synaptic plasticity at different time scales coexists. Homeostatic plasticity operating on a long time scale is caused by heterosynaptic plasticity, and that on the same time scale as Hebbian synaptic plasticity is caused by the constraint of energy supply.