Hum Brain Mapp. 2003 Dec;20(4):220-6.

Detecting low-frequency functional connectivity in fMRI using a self-organizing map (SOM) algorithm.

Author information

1: Department of Applied Physics, University of Michigan, Ann Arbor, Michigan, USA. speltier@bme.emory.edu

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.