Synchronization is a ubiquitous phenomenon in Nature, and has been identified as one of the main features of complex biological systems. Its study has originated new fundamental insights and analysis tools in both local and global dynamical models stemming from divergent disciplines. Neuronal synchronization, at a wide range of spatial scales, is considered a major orchestrator of brain integration processes. GABA aims to determine the functional role of normal and aberrant synchronization mechanisms in the emergence of higher cerebral functions in health and disease, by using tools borrowed from nonlinear dynamics and complexity theory. To that end, it is necessary to understand how local and long-range interactions scale up to a global activity in the brain.
To accomplish this goal, we recollect and analyze collective brain responses (multichannel-EEG, intracranial EEG, magnetoencephalographic recordings and local field potentials) and single-neuron activity under different normal and abnormal physiological conditions: from cognitive performance (sensory processing, attention, and memory in humans and non-human primates) to pathological mechanisms underlying Alzheimer’s disease and epilepsy. We apply linear and nonlinear methods, as well as tools from stochastic analysis and from the theories of complex networks and delayed dynamical systems. Such approaches have proven in the past to be very useful in the characterization of complex systems in generic models, and are here applied to obtain a better understanding of how higher cerebral functions arise in the normal brain. Results from this approach are expected to contribute to the early diagnosis of Alzheimer’s disease and to the anticipation of epileptic seizures. Additionally, insights arising within GABA are also expected to revert into new paradigms and an increased knowledge of the collective dynamics of other complex networks, in fields such as sociology and engineering.