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Event ANT Neuromeeting 2026 - Berlin starts on Jan 15, 2026, 8:00:00 AM (Europe/Berlin)
Cerebellar EEG oscillation in human vocalization
Location: Alte Kornkammer - 1/15/26, 11:00 AM - 1/15/26, 11:30 AM (Europe/Berlin) (30 minutes)
Cerebellar EEG oscillation in human vocalization
Prof. Dr. Guy Cheron
Université Libre de Bruxelles (ULB) and University of Mons (UMons), Belgium
Prof. Dr. Guy Cheron
Université Libre de Bruxelles (ULB) and University of Mons (UMons), Belgium
He is a neurophysiologist and as a Full Professor at the ULB, he runs the Laboratory of Neurophysiology and Movement Biomechanics (LNMB) from 1993 to 2020. He is the author or co-author of more than 200 papers in international journals, 20 chapters, and two books. Its Research Gate Score is 42.77, its h index is 47 and its citation impact is 8.136. He was initially trained in neuroscience under the supervision of Professor J.E. Desmedt at the Brain Unit Research of the ULB where he described new components of the somatosensory evoked potentials. In 1986, he discovered, together with E. Godaux, the localization of the oculomotor neural integrator (NI) in the nucleus prepositus of the cat, demonstrating for the first time the biological recognition that a brainstem neural network can perform mathematical integration crucial for the control of eye movements. From 1986 to 1997, they revealed the physiological mechanisms of the NI, which are now confirmed in different species. Cheron and collaborators were also the first to demonstrate the emergence of 160-200 Hz oscillation in the cerebellum of different mouse models presenting ataxia. In the field of brain computing interface, he was one of the PIs involved in the Mindwalker project resulting in the first European walking exoskeleton piloted by brain signals. In the field of neurocognitive science, G. Cheron was co-PI of Neurocog and Neurospat ESA missions performed in the International Space Station during which the LNMB team developed new sensorimotor paradigms (virtual reality) coupled with EEG dynamics. These neurotechnologies were successfully applied in the field of ADHD (NeuroATT Biowin project). In the field of human brain oscillations, this group recently demonstrated with Riemannian classification the possibility of recognizing the violent and festive mental state in a social context. G. Cheron and the LNMB teams are also involved in sports neuroscience research in which the relationships between movement and EEG dynamics are highlighted.

Since the cerebellum is involved in regulating different phases of respiration as well as in articulatory vocalization, we have undertaken the study of its contribution during the voluntary repetition of the syllable “pa” without resuming a normal respiratory cycle (long utterance exercise). Under these specific conditions, the cerebellar contribution should be more specifically related to the articulatory vocalization aspect rather than the respiratory one, given that the repetition of the syllable “pa” occurs solely during the long expiratory phase, during which subglottic pressure remains almost constant throughout the entire duration of expiration. We presently focused our analysis more specifically on the [pa] syllable production along with the long utterance exercise to identify the oscillatory nature of the cerebellar contribution to this speaking behavior during high density recording performed with ANT system coupled with aerodynamic signal captors. To enhance the relevance of identifying the neural generators of high frequency oscillation involved in each of 5 short articulatory phases of the syllable ‘pa’, we have, for the first time, compared the generators identified by swLORETA and those identified by the DIPFIT-EEGlab procedure. These two procedures are fundamentally different: swLORETA, based on a distributed solution to the inverse problem, uses an electrode-to-source transfer matrix, where each voxel is a potential source, whereas DIPFIT relies on a parametric modeling of EEG sources, explained by a small number of equivalent dipolar sources in the brain. We demonstrate that these two different mathematical procedures converge toward the identification in each individual participant of the same network of neural generators in which the cortical areas recognized in speech production are associated to the cerebellum.

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