Time-Varying Dynamic Causal Modelling for Sequential Responses: Neural Mechanisms of Slow Cortical Potentials, Preparation, Planning and Beyond
This paper introduces DCM-SR, a novel generative framework that overcomes the limitations of conventional Dynamic Causal Modelling by enabling continuous, time-varying parameter estimation without data segmentation, thereby allowing for the principled decomposition of slow cortical potentials and the investigation of neural mechanisms underlying sequential cognitive processes like preparation and motor inhibition.