Detecting low-frequency functional connectivity in fMRI using a self-organizing map (SOM) algorithm.
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.
Peltier
Scott J
SJ
Department of Applied Physics, University of Michigan, Ann Arbor, Michigan, USA. speltier@bme.emory.edu
Polk
Thad A
TA
Noll
Douglas C
DC
D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D008279:Magnetic Resonance Imaging; D009044:Motor Cortex / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology