Study on the influence of connection strength on the pacemaker in coupled neurons

The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. In this research, we study the minimal elements block of a learning system. We made a model with only two coupled neurons and studied the influence of connection strength between them. In particular, we found that if the post-synaptic neuron has no external stimuli, correlation remains low until a threshold that occurs about w = 0.15 or w = 0.4 depending on the neuron type testes. Varying types of neurons we find that spike bursts favours synchronization. In fact in all our tests, a pre-synaptic bursting neuron promote faster correlation against the other type of non-bursting neurons tested (regular and fast spiking). The presence of a threshold of connection strength w is a very interesting and previously unknown phenomenon that has implications of the fundamental process in learning and plasticity.