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Université Catholique de Louvain

Specialised in e-phys techniques to study nociception in humans

Université Catholique de Louvain
Institute of Neuroscience (IoNS)
53 Avenue Mounier (B1.53.04)
B1200, Brussels
BELGIUM
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Team Leader

Prof. Dr. André Mouraux

Professor of Medicine
Phone: +32 276 454 47
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Institute Presentation

The Institute of Neuroscience (IONS) of UCLouvain brings together all researchers working in the fields of cellular and molecular neurosciences (CEMO division), systems and cognitive neurosciences (COSY division) and clinical neurosciences (NEUR). The institute benefits from strong interactions with the Cliniques Universitaires Saint-Luc (CUSL). Within this institute, the Nociception Institute of Neuroscience (NOCIONS) research team headed by Prof. André Mouraux is a leading research group in the field of human pain neuroscience. Using non-invasive functional neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), combined with novel techniques to selectively activate specific classes of nociceptive afferents (temperature-controlled infrared laser stimulation, mechanical pinprick stimulation, electric stimulation) and neuromodulation (transcranial direct current stimulation, transcranial magnetic stimulation), the research conducted by NOCIONS aims at better understanding the neural processes underlying the perception of pain, the plastic changes in nociceptive pathways that occur after inflammation, injury or sustained nociceptive input, and their involvement in the development of chronic pain.

Because of its strong expertise in the use of EEG and related electrophysiological techniques to study nociception in both healthy human volunteers and patients suffering from chronic pain, partner UCL contributes to the QSPainRelief project by conducting a clinical study in patients suffering from disabling post-operative to assess the different effects of combinatorial treatments on the central nervous system using EEG and other non-invasive electrophysiological techniques and relate these effects to real-life clinical efficacy and safety. The data generated by this clinical study are used to calibrate the QSPainRelief model and to assess the efficacy of the model to predict response to combinatorial treatments.