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Principles and challenges of fMRI-based ‘brain reading’
Prof. John-Dylan HaynesDone
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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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The Berger’s discovery revisited: How and why the brain’s dominant rhythm relates to cognition
Tzvetan Popov, PhDDone
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Advances in closed-loop neuromodulation
David HaslacherDone
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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
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Real world AI in neurosciences for the benefit of doctors and patients
Stephane Doyen, 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
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Clinical brain-computer interfaces: Challenges and new applications
Prof. Surjo Soekadar, MDDone
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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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Welcome Address
Martijn SchreuderDone
Alexander Sack is Professor of Brain Stimulation and Applied Cognitive Neuroscience at Maastricht University. Sack is
one of the world’s foremost pioneers and influential leaders in brain stimulation research and a renowned expert in combining brain
stimulation with brain imaging techniques. Sack repeatedly made theoretical & methodological scientific breakthroughs on these
topics, publishing >200 articles in highest ranking journals. His group pioneered the development of simultaneously implemented
TMS-fMRI-EEG during cognitive behavior, allowing to apply brain-stimulation while recording the individual brain network (fMRI) and
oscillation (EEG) responses of cognitively engaged participants. Prof. Dr. Sack has received several grants and awards, enabling
him to develop a larger scale interdisciplinary basic research project on neural network communication mechanisms and to translate
these findings into clinical applications for treating various neuropsychiatric brain disorders.
In my talk I will first give an overview of the 35 year long journey that TMS has taken from a basic research tool to an
effective and reimbursed mental health therapy. This journey is maybe the prime example of a neuroscience-based application. I will
describe what we learned , what we know , and what we miss. This will also show that the journey of TMS is far from being over yet.
But what is our next stop?
To be a bit more concrete:
Transcranial Magnetic Stimulation (TMS) is one of the most versatile noninvasive neuromodulation techniques, increasingly used in
basic research to study brain-behavior-relationships and in clinical practice for treating various mental disorders such as depression.
Unfortunately, TMS-induced effects have proven to be notoriously unreliable, with large intra- and inter-subject variability, hindering
its reproducibility on single-subject-level. To improve its scientific reliability and clinical efficacy, it is imperative to gain a fundamental
understanding of the TMS-induced brain network effects underlying these (differences in) mental changes. Our group has successfully
demonstrated that concurrent TMS+fMRI can reveal how TMS signals propagate through connected cortico-subcortical-networks.
However, concurrent TMS+fMRI studies ignore ongoing fluctuations in neural communication efficacy (oscillatory states) that affect how
different network nodes interact. We propose to overcome this fundamental limitation by using the pioneering approach of concurrent
TMS+EEG+fMRI, enabling us to apply TMS at predefined oscillatory state moments (phases) or amplitudes (power) and probe state dependent
gating of TMS signals within brain-wide functional networks.
We use this innovation to study in healthy volunteers how the exact individual location as well as individual oscillatory brain state affect
the signal propagation of TMS within targeted networks, opening an exciting noninvasive avenue of network research into dynamic brain
circuits and their dysfunction. Importantly, this knowledge can then be directly translated to the clinic by developing and evaluating new
patient-tailored TMS depression protocols, replacing the current one-size-fits-all approach by adaptive personalized brain stimulation
protocols for patients suffering from treatment-resistant-depression (TRD).
Sounds nice, I know, but will this solve all our problems? I am afraid not.