𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Imaging human EEG dynamics using independent component analysis

✍ Scribed by Julie Onton; Marissa Westerfield; Jeanne Townsend; Scott Makeig

Publisher
Elsevier Science
Year
2006
Tongue
English
Weight
821 KB
Volume
30
Category
Article
ISSN
0149-7634

No coin nor oath required. For personal study only.

✦ Synopsis

This review discusses the theory and practical application of independent component analysis (ICA) to multi-channel EEG data. We use examples from an audiovisual attention-shifting task performed by young and old subjects to illustrate the power of ICA to resolve subtle differences between evoked responses in the two age groups. Preliminary analysis of these data using ICA suggests a loss of task specificity in independent component (IC) processes in frontal and somatomotor cortex during post-response periods in older as compared to younger subjects, trends not detected during examination of scalp-channel event-related potential (ERP) averages. We discuss possible approaches to component clustering across subjects and new ways to visualize mean and trial-by-trial variations in the data, including ERP-image plots of dynamics within and across trials as well as plots of event-related spectral perturbations in component power, phase locking, and coherence. We believe that widespread application of these and related analysis methods should bring EEG once again to the forefront of brain imaging, merging its high time and frequency resolution with enhanced cm-scale spatial resolution of its cortical sources.

📜 SIMILAR VOLUMES

EEG source imaging with spatio-temporal
EEG source imaging with spatio-temporal tomographic nonnegative independent component analysis
✍ Pedro A. Valdés-Sosa; Mayrim Vega-Hernández; José Miguel Sánchez-Bornot; Eduardo 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 596 KB

## Abstract This article describes a spatio‐temporal EEG/MEG source imaging (ESI) that extracts a parsimonious set of “atoms” or components, each the outer product of both a spatial and a temporal signature. The sources estimated are localized as smooth, minimally overlapping patches of cortical ac

Face representation using independent co
Face representation using independent component analysis
✍ Pong C. Yuen; J.H. Lai 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 510 KB

This paper addresses the problem of face recognition using independent component analysis (ICA). More speciÿcally, we are going to address two issues on face representation using ICA. First, as the independent components (ICs) are independent but not orthogonal, images outside a training set cannot

Nonlinear-analysis of human sleep EEG us
Nonlinear-analysis of human sleep EEG using detrended fluctuation analysis
✍ Jong-Min Lee; Dae-Jin Kim; In-Young Kim; Kwang Suk Park; Sun I. Kim 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 139 KB

Quantification of the fractal scaling properties of human sleep EEG dynamics was sought and each normal sleep stage was compared with that of sleep apnea. The fractal scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis. Six healthy subjects, aged

Interpreting variability in global SST d
Interpreting variability in global SST data using independent component analysis and principal component analysis
✍ Seth Westra; Casey Brown; Upmanu Lall; Inge Koch; Ashish Sharma 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 646 KB

## Abstract Component extraction techniques are used widely in the analysis and interpretation of high‐dimensional climate datasets such as global sea surface temperatures (SSTs). Principal component analysis (PCA), a frequently used component extraction technique, provides an orthogonal representa

Independent component analysis of dynami
Independent component analysis of dynamic contrast-enhanced magnetic resonance images of breast carcinoma: A feasibility study
✍ Tong San Koh; Choon Hua Thng; Juliana T.S. Ho; Puay Hoon Tan; Helmut Rumpel; Jam 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 699 KB

## Abstract ## Purpose To study the possibility of using independent component analysis (ICA) to identify breast lesions as separate hemodynamic sources on dynamic contrast‐enhanced (DCE) MR images, as depicted by the passage of contrast medium. ## Materials and Methods Six patients who were his