Connectivity analysis of EEG multichannel data


The human brain is definitely one of the most complex natural systems in the world. Founded on the "brain specialization concept", most studies aimed at exploring the brain regions responsible for different brain tasks in the past years. However, the emergence of "brain integration concept" directed many researches in recent years toward the brain connectivity. The brain connectivity is divided into three general categories: Structural connectivity, Functional connectivity and Effective connectivity. The structural connectivity depicts the existence of nerve fibers connecting different brain regions. The functional connectivity shows the statistical undirected interdependences among the activity of brain regions. The effective connectivity characterizes the effect that each brain region exerts over another region and represents causal (hence directed) relations among brain regions. EEG is an interesting modality for brain functional/effective connectivity analysis owing to its high temporal resolution, and despite its limitations in terms of spatial resolution and volume conduction effect. Designing methods for functional/effective brain connectivity analysis to capture complex brain dynamics by multichannel EEG data is a hot challenging field in neuroscience. Such methods can help neurologists to expand their knowledge of brain function and investigate the brain disorders like autism, Alzheimer, Schizophrenia, epilepsy, etc.

Research team: Mr. Ali Khadem