Paper Info
Title
Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: Simulations and application to finger tapping data
Abstract
Today, the concept of brain connectivity plays a central role in the neuroscience. While functional connectivity is defined as the temporal coherence between the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally between cortical sites. The most used method to estimate effective connectivity in neuroscience is the structural equation modeling (SEM), typically used on data related to the brain hemodynamic behavior. However, the use of hemodynamic measures limits the temporal resolution on which the brain process can be followed. The present research proposes the use of the SEM approach on the cortical waveforms estimated from the high-resolution EEG data, which exhibits a good spatial resolution and a higher temporal resolution than hemodynamic measures. We performed a simulation study, in which different main factors were systematically manipulated in the generation of test signals, and the errors in the estimated connectivity were evaluated by the analysis of variance (ANOVA). Such factors were the signal-to-noise ratio and the duration of the simulated cortical activity. Since SEM technique is based on the use of a model formulated on the basis of anatomical and physiological constraints, different experimental conditions were analyzed, in order to evaluate the effect of errors made in the a priori model formulation on its performances. The feasibility of the proposed approach has been shown in a human study using high-resolution EEG recordings related to finger tapping movements.
Year
DOI
Venue
2005
10.1109/TBME.2005.845371
Biomedical Engineering, IEEE Transactions
Keywords
Field
DocType
brain models,electroencephalography,neurophysiology,analysis of variance,brain connectivity,brain hemodynamic behavior,cortical connectivity,finger tapping,high-resolution EEG,neuroscience,structural equation modeling,Finger tapping movement,high-resolution EEG,structural equation modeling
Computer vision,Neurophysiology,Structural equation modeling,Pattern recognition,Computer science,A priori and a posteriori,Coherence (physics),Artificial intelligence,Image resolution,Temporal resolution,Electroencephalography,Analysis of variance
Journal
Volume
Issue
ISSN
52
5
0018-9294
Citations 
PageRank 
References 
17
1.86
6
Authors
4
Name
Order
Citations
PageRank
Laura Astolfi118317.84
Febo Cincotti219531.83
Claudio Babiloni310016.77
F Carducci414920.64