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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 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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Translational endophenotypes (neuromarkers) in neurodevelopmental disorders: From mouse to man in CLN3 (Batten) disease
Prof. John J. FoxeDone
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Principles and challenges of fMRI-based ‘brain reading’
Prof. John-Dylan HaynesDone
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Real world AI in neurosciences for the benefit of doctors and patients
Stephane Doyen, PhDDone
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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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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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High-fidelity continuous monitoring of physiology anywhere with RDS
Louis Mayaud, PhDDone
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Do I want to know? Artificial intelligence as a predictive tool in the diagnosis and treatment of cognitive impairment. Development of EEG-based functional network analyses
Prof. Ira Haraldsen, MDDone
David Haslacher studied computer science in Munich, artificial intelligence in Utrecht, and computational neuroscience in Tübingen. Since then, he has been developing the combination of transcranial alternating current stimulation with electro- and magnetoencephalography at the Clinical Neurotechnology Laboratory of the Charité – Universitätsmedizin Berlin. He is now finishing his PhD on closed-loop neuromodulation under the guidance of Surjo Soekadar, and is interested in developing more precise and effective treatments for psychiatric and neurological disorders.
Neuromodulation techniques such as transcranial alternating current stimulation (tACS) are a promising treatment approach for several neurological and psychiatric disorders, but suffer from variable effects due in part to their brain-state dependency. In this talk, I will show how electroencephalography (EEG) has become a useful tool to understand the immediate effects of tACS, and to implement closed-loop systems where tACS is adapted to ongoing brain oscillations in real-time. Finally, some potential clinical applications of such closed-loop approaches are discussed.