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CBI Seminar 29.10: Stephanie Jones "Interpreting the Mechanisms and Meaning of MEG/EEG signals with the Human Neocortical Neurosolver (HNN) software"

We are very happy to announce that the next speaker in the Centre for Bioelectric Interfaces (CBI) online seminar series is going to be our U.S colleague, Dr. Stephanie R. Jones, Associate Professor at Brown University!

CBI Seminar 29.10: Stephanie Jones "Interpreting the Mechanisms and Meaning of MEG/EEG signals with the Human Neocortical Neurosolver (HNN) software"

During our seminar, the Associate Professor at Brown University, Stephanie R. Jones will tell us about Human Neocortical Neurosolver (HNN) software, its functionality, key features, and relevance of this new neural modelling tool. Her speech entitled "Interpreting the Mechanisms and Meaning of MEG/EEG signals with the Human Neocortical Neurosolver (HNN) software" will be held on October 29 at 17:00 (MSK). For registration proceed https://cbi.timepad.ru/event/1460830/ 

Stephanie R. Jones, PhD is Associate Professor in Department of Neuroscience at BrownUniversity. She received her doctorate in mathematics from Boston University, followed bytraining in neuroscience and human magneto- and electro-encephalography (MEG/EEG) atMassachusetts General Hospital. Her research program integrates these disciplines to developbiophysically principled computational neural models that bridge the critical gap between humanMEG/EEG brain imaging signals and their underlying cellular and network level generators. Shecollaborates extensively with animal neurophysiologists, cognitive neuroscientists, and cliniciansto develop data-constrained models that are translationally relevant. Her group has recentlydeveloped their unique neural modeling into a user-friendly software tool for researchers andclinicians to interpret the circuit origin of their human MEG/EEG data: Human NeocorticalNeurosolver. Most recently, Dr. Jones’s group has expanded their interdisciplinary program tothe field of non-invasive brain stimulation. A primary goal is to translate an understanding of thenetwork mechanism underlying non-invasively measured brain signals into brain stimulationstrategies to improve disrupted brain function.