Surface-based mixed effects multilevel analysis of grouped human electrocorticography

摘要: Abstract Electrocorticography (ECoG) in humans yields data with unmatched spatio-temporal resolution that provides novel insights into cognitive operations. However, the broader application of ECoG has been confounded by difficulties accurately depicting individual and performing statistically valid population-level analyses. To overcome these limitations, we developed methods for registering to cortical topology. We integrated this technique surface-based co-registration a mixed-effects multilevel analysis (MEMA) control variable surface anatomy sparse coverage across patients, as well intra- inter-subject variability. applied MEMA (SB-MEMA) face-recognition task dataset (n = 22). Compared against existing techniques, SB-MEMA yielded results much more consistent meta-analyses face-specific activation studies. anticipate will greatly expand role studies human cognition, enable generation brain activity maps accurate multimodal comparisons.