Multimodal contribution to speech perception revealed by independent component analysis : a single-sweep EEG case study

In this single-sweep electroencephalographic case study, independent component analysis (ICA) was used to investigate multimodal processes underlying the enhancement of speech intelligibility in noise (for monosyllabic English words) by visualizing facial motion concordant with the audio speech signal. Wavelet analysis of the single-sweep IC activation waveforms revealed increased high-frequency energy for two ICs underlying the visual enhancement effect. For one IC, current source density analysis localized activity mainly to the superior temporal gyrus, consistent with principles of multimodal integration. For the other IC, activity was distributed across multiple cortical areas perhaps reflecting global mappings underlying the visual enhancement effect.