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Real brains in virtual worlds
Prof. Klaus GramannDone
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Electrophysiological measures as biomarkers of disease progression and outcome in psychoses
Prof. Giorgio Di LorenzoDone
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Advances in closed-loop neuromodulation
David HaslacherDone
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Mapping and targeting with TMS
Prof. Thomas KnöscheDone
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Towards personalised neuromodulation in mental health: A non-invasive avenue of network research into dynamic brain circuits and their dysfunction
Prof. Alexander SackDone
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The Berger’s discovery revisited: How and why the brain’s dominant rhythm relates to cognition
Tzvetan Popov, PhDDone
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Own data, not hardware
Cecilia Mazzetti, PhDDone
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Welcome Address
Martijn SchreuderDone
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The condition and perturb approach, a new protocol for preoperative language mapping in patients with brain tumors: First results of intraoperative validation
Tammam Abboud, MDDone
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Principles and challenges of fMRI-based ‘brain reading’
Prof. John-Dylan HaynesDone
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.