The ultimate goal of neuroscience is the understanding of the mechanisms underlying brain function in health and disease, potentially enabling novel interventions for neuropsychiatric disorders and perhaps even for the loss of consciousness. Given that the human brain consists of billions of interacting non-linear elements (primarily neurons and synapses), a deeper understanding of brain function will come from carefully studying the dynamics of the brain as a complex, dynamical system.

This project aims to investigate the dynamical complexity and mechanisms underlying

different brain states (such as awake, cognition, sleep, anesthesia, and disease) by analyzing how the brain responds to external perturbations and to internal events (ignition).

Specifically, we hypothesize that the analysis of the global dynamical response of the whole brain to such perturbations is different for different brain states, and that this reveals fundamental properties of the underlying communication and processing (cognition) characteristics of that particular brain state. This novel framework will allow us to go beyond the mere description of particular brain states, and to focus on the communication and processing features of the whole brain as well as of each of its local areas.

Our key idea is to use recent brain-modeling theoretical advances developed in our lab and constrain them by experimental data obtained using the perturbation and ignition protocols (DTI/DSI, fMRI, and MEG in healthy humans and disease, complemented with LFP and simultaneous neuronal recordings in monkeys and ferrets). The resulting whole-brain model will then be taken off line and its ignition and perturbation properties investigated in detail. We hypothesize that the recovery of the model from these perturbation protocols provides key information about the level of effective communication in the underlying brain dynamics. A profound understanding of these operations will help elucidate the mechanistic principles underlying higher brain functions and their breakdown in neuropsychiatric diseases.

Reference: PSI2016-75688 (AEI/FEDER)

30/12/2016 - 29/12/2019