De-noising with a SOCK can improve the performance of event-related ICA
Kaushik Bhaganagarapu, Graeme D Jackson, David F Abbott
FRONTIERS IN NEUROSCIENCE | FRONTIERS MEDIA SA | Published : 2014
Event-related ICA (eICA) is a partially data-driven analysis method for event-related fMRI that is particularly suited to analysis of simultaneous EEG-fMRI of patients with epilepsy. EEG-fMRI studies in epileptic patients are typically analyzed using the general linear model (GLM), often with assumption that the onset and offset of neuronal activity match EEG event onset and offset, the neuronal activation is sustained at a constant level throughout the epileptiform event and that associated fMRI signal changes follow the canonical HRF. The eICA method allows for less constrained analyses capable of detecting early, non-canonical responses. A key step of eICA is the initial deconvolution whi..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.