GABA GLOBAL APPROACH TO BRAIN ACTIVITY: FROM COGNITION TO DISEASE

• I.P.: Ingo Fischer
• Fecha de inicio: 7 de mayo de 2009
• Fecha de final: 31 de diciembre de 2009

Synchronization is a ubiquitous phenomenon in Nature, and has been considered as one of the engines of life in complex biological
systems. Its study has originated new fundamental insights and analysis tools in both local and global dynamical models stemming
from divergent disciplines. This proposal aims at determining 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. Specifically, the present proposal addresses the phenomenon of neuronal synchronization, at a wide range of
spatial scales, as a major orchestrator of brain integration processes. 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 will 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 will 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 to be very useful in the characterization of complex systems in generic models, and now will be applied for a better
understanding of how higher cerebral functions arise in the normal brain. Results from this approach are expected to contribute in
the early diagnosis of Alzheimer’s disease and in the anticipation of epileptic seizures. Additionally, they will also revert into new
paradigms and an increased knowledge of the collective dynamics of other complex networks, in fields such as sociology and
engineering.

Investigadores

Ingo Fischer