By: Alexandre Andrade
From: Univ. Lisbon
At: Instituto de Investigação Interdisciplinar, Anfiteatro
Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are currently (together with the magnetic counterpart of EEG, magnetoencephalography) the most widely used modalities for the in vivo, non-invasive assessment of human brain function. fMRI and M/EEG studies are most often concerned with the detection of brain regions activated by a task or stimulus or with the estimation of the temporal profile of responses evoked by a stimulus. In recent years, a growing emphasis is being placed on approaches that go beyond the classical paradigms and try to gather information about how the brain behaves as a whole, as opposed to site specific activation profiles. These approaches fall under two main topics: connectivity and complexity. Connectivity refers to how the execution of a task is supported by the interaction between distant brain regions, whereas complexity is related to the information content of a brain signal and ultimately to the interplay between different inputs that it receives. In this talk I will provide an overview of current research topics in connectivity and complexity analysis of the brain. I will present a sample of techniques that range from simple measures such as correlation and correlation dimension to more sophisticated ones such as Granger causality, empirical mode decomposition phase-locking, and multiscale entropy. I will also discuss recent efforts to bridge the gap between the concepts of connectivity and complexity using measures related to ânetwork complexityâ (e.g. modularity, small-worldness). I will try to explain what kind of insight these techniques (either new or newly applied to brain studies) can bring and why they are useful for the study of the normal and pathological brain.