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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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Atypical neural processing in 22q11.2 Deletion Syndrome and schizophrenia: Towards neuromarkers of disease progression and risk
Prof. Sophie MolholmDone
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From one-size-fits-all psychiatry to stratified psychiatry: Brain markers and heart-brain-coupling
Martijn Arns, PhDDone
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Phase-amplitude coupling in EEG as a Parkinsonian biomarker
Prof. Thomas R. KnöscheDone
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High-fidelity continuous monitoring of physiology anywhere with RDS
Louis Mayaud, PhDDone
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Accelerated Intermittent Theta Burst Stimulation: Antidepressant and anti-suicidal effects
Roberto Goya-Maldonado, MDDone
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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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Real brains in virtual worlds
Prof. Klaus GramannDone
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Own data, not hardware
Cecilia Mazzetti, PhDDone
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Schizophrenia: A temporal disorder?
Dr. Annemarie WolffDone
Marcus Kaiser is leader of Neuroinformatics UK representing more than 600 researchers in the field (http://www. neuroinformatics.org.uk) and Chair of the Neuroinformatics Special Interest Group of the British Neuroscience Association. After studying biology and computer science, he obtained his PhD, funded by a fellowship from the German National Academic Foundation, from Jacobs University Bremen in 2005. In 2016, he was elected Fellow of the Royal Society of Biology. He is on the editorial boards of Network Neuroscience (MIT Press), PLOS Computational Biology, and Royal Society Open Science, and author of the first review on connectomics. Research interests are understanding the origin of brain disorders through modelling brain development and using models to inform therapeutic interventions, in particular using non-invasive brain stimulation (see http://www. dynamic-connectome.org).
The complete set of connections in the brain is called our connectome. Over the last 20 years we have found out more about how this network is organised and how this organisation is linked to brain function. For example, highly-connected brain regions (hubs) play critical roles in information processing and are involved in many brain diseases. I will outline how networks change for a range of brain disorders, from networks that produce seizures for epilepsy to networks that produce hallucinations in certain types of dementia. Given these changes, can we alter the structure of these networks and thereby improve cognition in patients? Brain stimulation is an option to achieve this and has been proposed as an alternative treatment to pharmaceutical drugs with a potential to reduce side effects and improve cognitive function. I will outline how computational models based on brain connectivity information can help to identify network targets and to find personalised stimulation protocols. In particular, I will highlight how focused ultrasound, a novel non-invasive technology for brain stimulation, can directly target deep-brain structures involved in emotion and memory processing opening up a way to new interventions. More information can also be found in my book ‘Changing Connectomes’ (MIT Press, 2020; https://mitpress.mit. edu/books/changing-connectomes).