Group independent component analysis of resting state EEG in large normative samples

Abstract

EEG (Electroencephalography) resting state was studied by means of group blind source separation (gBSS), employing a test-retest strategy in two large-sample normative databases (N=57 and N=84). Using a BSS method in the complex Fourier domain and a model-driven distributed inverse solution we closely replicate both the spatial distribution and spectral pattern of seven source components. Norms were then constructed for their spectral power so as to allow testing patients against the norms. As compared to existing normative databases based on scalp spectral measures, the resulting tool defines a smaller number of features with very little inter-correlation. Furthermore, these features are physiologically meaningful as they relate the activity of several brain regions, forming a total of seven patterns, each with a peculiar spatial distribution and spectral profile. This new tool, that we name normative independent component analysis (NICA), may serve as an adjunct to diagnosis and assessment of abnormal brain functioning and aid in research on normal resting state networks.

Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer’s Disease Detected Using Quantitative Electroencephalography

“…Using recordings obtained at rest in 144 subjects, Congedo et al [80] reported seven sources distributed across the cortex, where three of them were also related to the Precuneus, that would serve to assessment and diagnosis of abnormal brain functioning. In our case, gICA helps to link differences between asymptomatic subjects at scalp level [22] and brain cortex, showing a region that can be reliably measured using inverse solution methods.…”

“…Similar to the approach given by Congedo et al [80] we obtained the spatial filters using young asymptomatic subjects. The differences between groups using the spatial filters obtained by gICA were validated by the positive results comparing SCr and Ctrl-2, which were not included in the gICA analysis, and were also confirmed by the wMNE results, that in our case served also as cross-validation results.…”

Brain Oscillatory Activity during Spatial Navigation: Theta and Gamma Activity Link Medial Temporal and Parietal Regions

“…BSS techniques combined with source localization provide a useful tool for exploring task-related EEG (eg. Delorme et al, 2007b), as well as applications in realtime EEG fields such as neurofeedback and brain-computer interfaces (Congedo, 2006) and clinical studies comparing patients to normative databases (Congedo et al, 2010).…”

“…More recently, the AJDC method has been extended to group data analysis to obtain a common set of filters describing the sample under study (Congedo et al, 2010).…”

Prediction of Treatment Response and the Effect of Independent Component Neurofeedback in Obsessive-Compulsive Disorder: A Randomized, Sham-Controlled, Double-Blind Study

“…In our study, the independent component NFB is based on the group EEG ICA of normal subjects that revealed 7 independent sources replicated in 2 normative databases [13]. The component of interest for this study is component number 1 as described in the study by Congedo et al [13] because it has been reported to differentiate between OCD patients and healthy controls [14].…”