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Atypical neural processing in 22q11.2 Deletion Syndrome and schizophrenia: Towards neuromarkers of disease progression and risk
Prof. Sophie MolholmDone
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Multi-center validation of dry vs. gel-based EEG cap performance
Prof. Patrique FiedlerDone
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Two clinical applications of hdEEG: Kinesthetic illusion and consciousness in sleep
Jan Hubený, Ing.Done
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Neural markers of motor cognition: What do we know and what’s next?
Claudia Gianelli, PhDDone
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Electrophysiological measures as biomarkers of disease progression and outcome in psychoses
Prof. Giorgio Di LorenzoDone
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Language mapping on patients with parenchymatous tumor in language eloquent areas
Jimmy Landry Zepa YotedjeDone
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Phase-amplitude coupling in EEG as a Parkinsonian biomarker
Prof. Thomas R. KnöscheDone
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Schizophrenia: A temporal disorder?
Dr. Annemarie WolffDone
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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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Towards personalised neuromodulation in mental health: A non-invasive avenue of network research into dynamic brain circuits and their dysfunction
Prof. Marcus KaiserDone
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.