Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates.

ABSTRACT: Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fing

SUBMITTER: Tan FM 

PROVIDER: S-EPMC5632561 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature