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The potential of brain rhythms to gauge the vulnerability of an individual to developing chronic pain
Prof. Ali MazaheriDone
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Principles and challenges of fMRI-based ‘brain reading’
Prof. John-Dylan HaynesDone
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High-fidelity continuous monitoring of physiology anywhere with RDS
Louis Mayaud, PhDDone
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Real world AI in neurosciences for the benefit of doctors and patients
Stephane Doyen, PhDDone
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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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Phase-amplitude coupling in EEG as a Parkinsonian biomarker
Prof. Thomas R. KnöscheDone
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Real brains in virtual worlds
Prof. Klaus GramannDone
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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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Two clinical applications of hdEEG: Kinesthetic illusion and consciousness in sleep
Jan Hubený, Ing.Done
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Multi-center validation of dry vs. gel-based EEG cap performance
Prof. Patrique FiedlerDone
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.