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

Tan, Francisca M. and Caballero-Gaudes, César and Mullinger, Karen J. and Cho, Siu-Yeung and Zhang, Yaping and Dryden, Ian L. and Francis, Susan T. and Gowland, Penny A. (2017) Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates. Human Brain Mapping . ISSN 1097-0193 (In Press)

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Abstract

Most 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 function (left/right fingers, left/right toes, swallowing and eye blinks). We validated the framework using simultaneous Electromyography-fMRI experiments and motor tasks with short and long duration, and random inter-stimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events was 77 �} 13% and 74 �} 16% respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55 and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this paper discusses methodological implications and improvements to increase the decoding performance.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
University of Nottingham, UK > Faculty of Science > School of Physics and Astronomy
Depositing User: Eprints, Support
Date Deposited: 07 Aug 2017 13:24
Last Modified: 07 Aug 2017 13:30
URI: http://eprints.nottingham.ac.uk/id/eprint/44731

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