AUTHOR=Biau Emmanuel , Kotz Sonja A. TITLE=Lower Beta: A Central Coordinator of Temporal Prediction in Multimodal Speech JOURNAL=Frontiers in Human Neuroscience VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2018.00434 DOI=10.3389/fnhum.2018.00434 ISSN=1662-5161 ABSTRACT=

How the brain decomposes and integrates information in multimodal speech perception is linked to oscillatory dynamics. However, how speech takes advantage of redundancy between different sensory modalities, and how this translates into specific oscillatory patterns remains unclear. We address the role of lower beta activity (~20 Hz), generally associated with motor functions, as an amodal central coordinator that receives bottom-up delta-theta copies from specific sensory areas and generate top-down temporal predictions for auditory entrainment. Dissociating temporal prediction from entrainment may explain how and why visual input benefits speech processing rather than adding cognitive load in multimodal speech perception. On the one hand, body movements convey prosodic and syllabic features at delta and theta rates (i.e., 1–3 Hz and 4–7 Hz). On the other hand, the natural precedence of visual input before auditory onsets may prepare the brain to anticipate and facilitate the integration of auditory delta-theta copies of the prosodic-syllabic structure. Here, we identify three fundamental criteria based on recent evidence and hypotheses, which support the notion that lower motor beta frequency may play a central and generic role in temporal prediction during speech perception. First, beta activity must respond to rhythmic stimulation across modalities. Second, beta power must respond to biological motion and speech-related movements conveying temporal information in multimodal speech processing. Third, temporal prediction may recruit a communication loop between motor and primary auditory cortices (PACs) via delta-to-beta cross-frequency coupling. We discuss evidence related to each criterion and extend these concepts to a beta-motivated framework of multimodal speech processing.