An automated method for identifying artifact in independent component analysis of resting-state fMRI
Kaushik Bhaganagarapu, Graeme D Jackson, David F Abbott
FRONTIERS IN HUMAN NEUROSCIENCE | FRONTIERS MEDIA SA | Published : 2013
An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal o..View full abstract
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Awarded by National Health and Medical Research Council of Australia
This study was supported by the National Health and Medical Research Council of Australia (Project Grants 368650 and 318900, Program Grant 628952, and a practitioner fellowship 527800 to Graeme D. Jackson), the Austin Hospital Medical Research Foundation, and the Operational Infrastructure Support Program of the State Government of Victoria, Australia.