N-way decomposition: Towards linking concurrent EEG and fMRI analysis during natural stimulus

Abstract

The human brain is intrinsically a high-dimensional and multi-variant system. Simultaneous EEG and fMRI recoding offers a powerful tool to examine the electrical activity of neuron populations at high temporal and frequency resolution, and concurrent blood oxygen level dependent (BOLD) responses at high spatial resolution. Joint analysis of EEG and fMRI data could thus help comprehensively understand the brain function at multiple scales. Such analysis, however, is challenging due to the limited knowledge on the coupling principle of neuronal-electrical and hemodynamic responses. A rich body of works have been done to model EEG-fMRI data during event related design and resting state, while few have explored concurrent data during natural stimulus due to the complexity of both stimulus and response. In this paper, we propose a novel method based on N-way decomposition to jointly analyze simultaneous EEG and fMRI data during natural movie viewing. Briefly, a 4-way tensor from the EEG data, constructed in four dimensions of time, frequency, channel and subject, is decomposed into group-wise rank one components by canonical polyadic decomposition (CPD). We then used the decomposed temporal features to constrain a 2-way sparse decomposition of fMRI data for network detection. Our results showed that the proposed method could effectively decode meaningful brain activity from both modalities and link EEG multi-way features with fMRI functional networks.