This MEGIN Masterclass webinar presented by Sylvain Baillet, PhD, will discuss, "A difficult research question in systems neuroscience concerns the mechanistic elucidation of information integration by the brain: How do sensory inputs interact with ongoing neural activity? What is the nature of the convergence or tension between external inputs and the mental representations of our environment? How are these mechanisms altered in disease? We recently proposed a model of systems dynamics in hierarchical brain networks based on polyrhythmic oscillatory brain activity. This mechanistic framework implements a generic form of contextual predictive inference of the input signals of brain networks. In essence, this vision is aligned with the principles of perceptual inference, which predict that spontaneous brain activity during wakefulness constantly implements the self’s representation of its environment and the possible consequences of its actions.
Inspired by this framework, I will review a series of neurophysiological data that account for this hypothesis in a diversity of brain functions. In particular, we recently proposed to train artificial neural networks on naturalistic stimuli to produce encoding models of neural activity that account for contextual uncertainty and prediction errors in perception. I will show how we used this approach to reveal the corresponding brain signaling pathways for natural speech processing.
Biosketch available here - https://www.neurospeed-bailletlab.org/sylvain-baillet
Related recent papers: Shafiei G, Baillet S, Misic B (2022) Human Electromagnetic and Haemodynamic Networks Systematically Converge in Unimodal Cortex and Di- verge in Transmodal Cortex, PLoS Biology Aug 1;20(8):e3001735 Samiee S, Vuvan D, Florin E, Albouy P, Peretz I, Baillet S (2022) Cross-frequency Brain Network Dynamics Support Pitch Change Detection, Journal of Neuroscience, May 4;42(18):3823-3835 Albouy P, Martinez-Moreno ZE, [Zatorre RJ, Baillet S] (2022) Supra- Modality of Neural Entrainment: Rhythmic Visual Stimulation Causally Enhances Manipulation Abilities in Auditory Working Memory, Science Advances, 8(8):eabj9782 da Silva Castanheira J, Orozco Perez HD, Misic B, Baillet S (2021) Brief Segments of Neurophysiological Activity Enable Individual Differentiation, Nature Communications, 12: 5713 Lennert T, Samiee S, Baillet S (2021) Coupled Oscillations Enable Rapid Temporal Recalibration to Audiovisual Asynchrony, Communications Biology, 4:559 Donhauser P & Baillet S (2020) Two Distinct Neural Time Scales for Predictive Speech Processing, Neuron, Jan 22;105(2):385-393.e9 Morillon B & Baillet S (2017) Motor Origin of Temporal Predictions in Auditory Attention, Proc Natl Acad Sci, 114 (42):E8913-E8921 Albouy P, Weiss A, Baillet S & Zatorre RJ (2017) Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance, Neuron, Apr 94(1):193–206 Baillet S (2017) MEG for Brain Electrophysiology & Imaging, Nature Neuroscience, 20(3): 327–339
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*MEGIN does not endorse any applications or treatments mentioned at this event. TRIUX™ neo is intended to non-invasively locate regions of epileptic activity within the brain and, in conjunction with other diagnostic data, in neurosurgical planning. All other applications are research in nature.