2. Dissecting the spatio-temporal connectivity dynamics of the stimulation induced signal

COEX 

The brain is a complex, nonlinear, multiscale, and intricately interconnected physical system, whose laws of motion and principles of organization have proven challenging to understand with currently available measurement techniques. In such epistemic circumstances, the application of systematic perturbations, and measurement of their effects, is a central tool in the scientific armory. We employed a combination stimulus-evoked high-density electroencephalography data along with a whole-brain connectome-based computational modeling approach to answer questions around the physiological origin of the stimulus-evoked potentials. Initially, we employed a `virtual dissection' approach to study the extent to which model-generated stimulus-evoked stimulation patterns at the primary stimulation site relied on recurrent incoming connections from the rest of the brain, and at what times. These in-silico interventions resulted in substantial reductions in late stimulus-evoked responses when pivotal connections were inactivated. This indicates that network properties are essential for shaping late stimulus-evoked activity.
However, the spontaneous activity in the resting human brain exhibits well-organized spatiotemporal patterns which form the so-called resting-state networks (RSNs) and prior research has revealed a hierarchical organization of these networks, ranging from high-order multimodal networks to low-order networks. In this framework, we further characterized the effects observed for late stimulus-evoked responses, demonstrating how they are highly dependent on whole-brain integrity for high-order networks and mainly restricted to intrinsic network properties when the stimulus is delivered to low-order networks. Finally, subject-specific estimation of model neurophysiological parameters underscores the role of local parameters in evoked responses when stimulation is delivered to low-order networks, while multimodal networks rely on global brain properties. Overall our results, and the framework for investigating such questions that we are introducing here, have clear and practical relevance to basic and clinical research, but also have broader implications for the scientific understanding of functional brain organization.