A network model of inhibitory effects induced by transcranial magnetic stimulation

Abstract We have studied the inhibitory effects of transcranial magnetic stimulation (TMS) on a neural population. Because TMS can affect the electromagnetic activities inside our brain with high temporal resolution and noninvasively, it is widely used as a powerful tool both in the field of cognitive neuroscience and for clinical treatment. However, the neural mechanisms underlying these effects remain unclear, especially from a theoretical perspective. In our study, we employed a simple neural population model and computationally analyzed the responses to a TMS-like perturbation. When the perturbation was applied, the mean activity of the network transiently increased, and then decreased for a relatively long period followed by the loss of a localized activity pattern. When the afferent input had a strong transient component and a weak sustained component, there was a critical latency period during which the perturbation completely suppressed the network activity. These results suggest that the inhibitory effects typically observed in TMS studies can be yielded through dynamical interaction in a neural population.