Brain functional connectivity and sEEG signal processing
Functional connectivity is defined as the “temporal correlations between spatially remote neurophysiological events” (Friston et al., 1993a). Effective connectivity is defined as “the influence that one neural system exerts over another either directly or indirectly” (Friston et al., 1993b). Comparing functional with effective connectivity is crucial to understand the difference between descriptions of patterns of neural activity and possible explanations of their origins. In particular, functional connectivity reduces to testing the null hypothesis that activity in two regions shares no mutual information. Mutual information is a statistical description of the degree to which two regions demonstrate similar behaviour or statistical interdependence (Cover and Thomas, 1991). By contrast, characterising brain activity in terms of effective connectivity involves detecting causal interactions among neural elements. A straightforward approach to assess effective connectivity requires perturbing a subset of neurons and detecting the response to this local perturbation in the rest of the system (Paus T). Measuring functional connectivity only requires observing the spontaneous activity of the brain and is generally more practical, on the other hand, the presence of temporal correlation does not always grant that two groups of neurons are interacting. For example two groups of neurons, A and B, may share mutual information just because they receive a common input by a third group of neurons C. However, in this case, perturbing A would have no effects on B and effective connectivity would be null. The aim of the present work is to explore the relationships between functional connectivity and effective connectivity in the human cerebral cortex. To accomplish to this task we are working onto sEEG resting state potentials and iEEG registration sessions over patients affected by drug resistant focal epilepsy.
Stereo-electroencephalography (sEEG) is an biological signals acquisition methods that relies on intra cerebral electrodes implanted into the brain that record deep neural potentials. sEEG allows to avoid volume conduction and to obtain an excellent Signal to Noise Ratio recording activity directly from the grey matter of the human brain. Using sEEG recordings can be useful to compare functional and effective connectivity. The acronym iEEG stands for intra-cerebral electroencephalography stimulation that is a highly invasive technique that aims to evaluate the influence of a stimulation in a specific brain region over the entire cerebral cortex.
Indeed, functional connectivity can be measured applying mutual-information technique or Granger causality directly on segments of resting state sEEG activity. Effective connectivity, instead, can be measured applying a perturbational approach using sEEG synchronized with electrical intracerebral stimulation. This two techniques can be cross-validated a posteriori and mutual information of resting-state, once validated using perturbational approach, could be used to obtain an interactive 3D atlas map of human brain.