𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Spatial independent component analysis of functional magnetic resonance imaging time-series: characterization of the cortical components

✍ Scribed by E. Formisano; F. Esposito; N. Kriegeskorte; G. Tedeschi; F. Di Salle; R. Goebel


Book ID
114296307
Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
899 KB
Volume
49
Category
Article
ISSN
0925-2312

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Improved application of independent comp
✍ Zhiying Long; Kewei Chen; Xia Wu; Eric Reiman; Danling Peng; Li Yao πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 827 KB

## Abstract Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficul

Comparison of three methods for generati
✍ Vincent J. Schmithorst; Scott K. Holland πŸ“‚ Article πŸ“… 2004 πŸ› John Wiley and Sons 🌐 English βš– 597 KB

## Abstract ## Purpose To evaluate the relative effectiveness of three previously proposed methods of performing group independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. ## Materials and Methods Data were generated via computer simulation. Components were

Independent component analysis of dynami
✍ Tong San Koh; Choon Hua Thng; Juliana T.S. Ho; Puay Hoon Tan; Helmut Rumpel; Jam πŸ“‚ Article πŸ“… 2008 πŸ› John Wiley and Sons 🌐 English βš– 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

Detecting functional nodes in large-scal
✍ Christine Ecker; Emanuelle Reynaud; Steven C. Williams; Michael J. Brammer πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 605 KB

## Abstract This study aimed to demonstrate how a regional variant of principal component analysis (PCA) can be used to delineate the known functional subdivisions of the human visual system. Unlike conventional eigenimage analysis, PCA was carried out as a second‐level analysis subsequent to model