The potential of brain rhythms to gauge the vulnerability of an individual to developing chronic pain

Talks

Translational endophenotypes (neuromarkers) in neurodevelopmental disorders: From mouse to man in CLN3 (Batten) disease
Prof. John J. Foxe
Done
Language mapping on patients with parenchymatous tumor in language eloquent areas
Jimmy Landry Zepa Yotedje
Done
The Berger’s discovery revisited: How and why the brain’s dominant rhythm relates to cognition
Tzvetan Popov, PhD
Done
Electrophysiological measures as biomarkers of disease progression and outcome in psychoses
Prof. Giorgio Di Lorenzo
Done
Principles and challenges of fMRI-based ‘brain reading’
Prof. John-Dylan Haynes
Done
Two clinical applications of hdEEG: Kinesthetic illusion and consciousness in sleep
Jan Hubený, Ing.
Done
Neural markers of motor cognition: What do we know and what’s next?
Claudia Gianelli, PhD
Done
High-fidelity continuous monitoring of physiology anywhere with RDS
Louis Mayaud, PhD
Done
Clinical brain-computer interfaces: Challenges and new applications
Prof. Surjo Soekadar, MD
Done
Real brains in virtual worlds
Prof. Klaus Gramann
Done

11/4/22, 3:00 PM - 11/4/22, 3:30 PM (Europe/Amsterdam) (30 minutes)

Prof. Ali Mazaheri

Associate Professor, Director of Undergraduate Studies Centre for Human Brain Health, School of Psychology, University of Birmingham

I completed my B.Sc and M.Sc degree in Neuroscience at the University of Toronto, Canada. I obtained my PhD degree at the Donders Institute for Cognitive Neuroimaging, Nijmegen, The Netherlands. After a post-doctoral fellowship at the University of California, Davis, I was appointed as an Assistant Professor at the Academic Medical Centre, University of Amsterdam. I am currently an Associate Professor at the School of Psychology, University of Birmingham (United Kingdom), and a Principal Investigator at the Centre for Human Brain Health.

A significant predictor of whether an individual will get chronic pain is the acute pain experienced immediately after surgery. If clinicians can pre-operatively identify which patients are highly pain sensitive, they can take pre-emptive steps to minimize it and prevent its chronification. Here I will present evidence that an individual’s resting peak frequency of alpha activity, measured using EEG , can predict their sensitivity to pain after surgery.