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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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Multi-center validation of dry vs. gel-based EEG cap performance
Prof. Patrique FiedlerDone
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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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The Berger’s discovery revisited: How and why the brain’s dominant rhythm relates to cognition
Tzvetan Popov, PhDDone
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Neural markers of motor cognition: What do we know and what’s next?
Claudia Gianelli, PhDDone
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Mapping and targeting with TMS
Prof. Thomas KnöscheDone
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Two clinical applications of hdEEG: Kinesthetic illusion and consciousness in sleep
Jan Hubený, Ing.Done
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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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Clinical brain-computer interfaces: Challenges and new applications
Prof. Surjo Soekadar, MDDone
After completing her undergraduate degree at the University of Toronto, Wolff continued her education at the University
of Regensburg (Germany), studying for a master’s degree in experimental and clinical neuroscience. She completed her thesis work
at the Royal College of Surgeons of Ireland on postsynaptic protein characterization (PSD-95) in schizophrenia. After its completion,
she began her PhD in Neuroscience in the Faculty of Medicine at the University of Ottawa (Canada). Changing directions, her work
there centered on interindividual variability of complex cognitive tasks in healthy human electrophysiology (EEG). Employing methods
of time-frequency analysis, neural dynamics and complexity, Wolff’s resulting work was awarded the Governor General’s Gold Medal
for academic excellence. Currently, she is finishing her postdoctoral research fellowship at the Institute for Mental Health Research
(Ottawa) where her work focuses on neural variability and dynamics in psychiatric disorders.
Currently, one quarter of all medical disorders are mental health disorders. Until now, medical science has lacked sufficient
understanding about the physical brain mechanisms and how they relate to the mind. And, more specifically, how the physical brain
mechanisms relate to the symptoms of disorders of the mind. If scientific brain biomarkers could be identified, they could be used for
a more precise diagnosis of mental disorders and more effective, individualized treatments. Using schizophrenia (SCZ) as an example,
recent EEG-derived research findings from NMHD scientists have identified biomarkers that relate to the clinical features of this disorder.
Linking the dynamics of spatial and temporal patterns in the brain, as measured using EEG, with symptom severity of SCZ - measured
with the PANSS subscales - the resulting stepwise linear regression models could be used to monitor treatment progress and/or
assess treatment efficacy. In sum, as shown in the case of SCZ, NMHD has used EEG research on neural dynamics to link the clinical
symptoms of this disorder to brain-based neural markers which could be used to evaluate treatment response or efficacy in individual
patients.