Phase-responsiveness transmission in a network of quadratic integrate-and-fire neurons
Document typeBachelor thesis
Rights accessOpen Access
In the study of the dynamics of neuronal networks, it is interesting to see how the interaction between neurons can elicit different behaviours in each individual one. Moreover, this can lead to the population exhibiting collective phenomena that is not intrinsic to a single cell, such as synchronization. In this project, we work with a large-scale network and a firing-rate model of quadratic integrate-and-fire (QIF) neurons. After studying the dynamics of the QIF model and computing its phase response curve (PRC), we propose an algorithm to describe the population through the PRCs. Our method is able to replicate the same dynamics we observe with the aforementioned models and it also serves us to gain more insight into the transmission of pulses and to explain how a network can maintain a state of synchronized firing.