Detecting low-frequency functional connectivity in fMRI using a self-organizing map (SOM) algorithm
✍ Scribed by Scott J. Peltier; Thad A. Polk; Douglas C. Noll
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 385 KB
- Volume
- 20
- Category
- Article
- ISSN
- 1065-9471
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✦ Synopsis
Abstract
Low‐frequency oscillations (<0.08 Hz) have been detected in functional MRI studies, and appear to be synchronized between functionally related areas. A current challenge is to detect these patterns without using an external reference. Self‐organizing maps (SOMs) offer a way to automatically group data without requiring a user‐biased reference function or region of interest. Resting state functional MRI data was classified using a self‐organizing map (SOM). Functional connectivity between the left and right motor cortices was detected in five subjects, and was comparable to results from a reference‐based approach. SOMs are shown to be an attractive option in detecting functional connectivity using a model‐free approach. Hum. Brain Mapping 20:220–226, 2003. © 2003 Wiley‐Liss, Inc.