Abstract
Transcranial magnetic stimulus (TMS) is a non-invasive remedy which had reported the ability in easing the motor disorders caused by neural diseases by inducing modifications in synaptic plasticity. TMS stimulate neurons by a massive but transient magnetic pulse, which creating an electromagnetic induction current within the focus. As a surgery-free method, it has been popular in brain research of medicine and research field. However, the detailed mechanism of TMS-induced plasticity change is still a mystery. In this study, we built a spiking neural network model of primary motor cortex to simulate the cortical activity and synaptic plasticity responding to TMS stimulations. At the same time, we develop a new hypothesis with single neuron circuit to describe the mechanism of plasticity change induced by TMS. The results are archived in the thesis written by Mr. Li-Rui Chen. (Title: A model of synaptic plasticity at multiple temporal scales for the neuronal plasticity induced by repetitive transcranial magnetic stimulations.) The cortical network model we built could emulate the full-featured activity aroused by TMS in the motor cortex. In model prediction, it also exhibits a reasonable response and activity. The results in this thesis support that our network model have good potential in the studying of TMS-induced responses, although it needs more parameter tuning. After that, we could apply it further to the study of the response of TMS in different neural diseases model, which is also the ultimate goal we expect to achieve from this first small step.