Integrated multi-echo denoising strategy improves identification of inherent language laterality.
PURPOSE
Although increasingly used in both neuroscience and clinical studies, a major challenge facing resting-state FMRI (rs-FMRI) still lies in isolating BOLD signal fluctuations resulting from neuronal activity from noise. In this study, we investigated the effect of a newly proposed denoising approach, integrated multi-echo rs-FMRI analysis, on language mapping.


METHODS
Multiband multi-echo rs-FMRI data were acquired, along with language task FMRI that identified language areas in the left hemisphere of 12 subjects. The language laterality and specificity of the language mapping given by seed-based correlation analysis were compared among the rs-FMRI data sets pre-processed using 3 different approaches: multi-echo data with integrated multi-echo independent component analysis, denoising that uses the TE-dependency of each signal component to judge its origin, and multi-echo and single-echo data with conventional denoising. The laterality index was automatically computed without setting any threshold to minimize the arbitrariness and to ensure the generality of the result.


RESULTS
A repeated measures analysis of variance followed by post hoc tests showed that optimal combination of the 3-echo data succeeded in increasing the correlation within the targeted language system. With the physically principled multi-echo denoising approach, the integrated strategy further succeeded in revealing areas of synchronization more specific to the language system compared with conventional denoising approach, which eventually improved the identification of the laterality of the system.


CONCLUSION
By successfully reducing non-specific correlations spreading over the brain, integrated multi-echo approach improved language mapping and identification of the laterality of the system using rs-FMRI.
['Amemiya|Shiori|S|0000-0002-2132-1642', 'Yamashita|Hiroshi|H|', 'Takao|Hidemasa|H|', 'Abe|Osamu|O|']
D000328:Adult D000465:Algorithms D001921:Brain D001931:Brain Mapping D003198:Computer Simulation D004292:Dominance, Cerebral D017352:Echo-Planar Imaging D005260:Female D006801:Humans D007091:Image Processing, Computer-Assisted D007802:Language D008279:Magnetic Resonance Imaging D008297:Male D015233:Models, Statistical D009474:Neurons D015203:Reproducibility of Results
laterality resting-state FMRI language mapping