Biomag 2021 Prelude
The Biomag 2021 Prelude event took place on Tuesday 1 September 2020.
Speaker presentations will be for 20 minutes each, with a further 10 minutes for questions. The sessions will be chaired by:
- Saskia Haegens, Principal Investigator, Department of Psychiatry, Columbia University
- Olaf Hauk (Chair of Awards Committee), Senior Investigator Scientist, MRC Cognition and Brain Sciences Unit, University of Cambridge
- Caroline Witton (Co-chair of Awards Committee), Aston University
Ole Jensen, Chair of Biomag 2021, University of Birmingham
|14.10||Keynote: New frontiers in MEG & electrophysiology for brain decoding and imaging|
Sylvain Baillet, Professor, Neurology & Neurosurgery, Biomedical Engineering, and Computer Science, Tier-1 Canada Research Chair of Neural Dynamics of Brain Systems, Director, MEG Core Unit, McConnell Brain Imaging Centre, Associate Dean (Research), Faculty of Medicine, Montreal Neurological Institute, McGill University
Abstract: A difficult research question in systems neuroscience concerns the mechanistic elucidation of information integration in brain networks: How do sensory inputs modify the ongoing activity of the brain? What is the nature of competitive signaling between bottom-up inputs vs. top-down modulations in perception and behavior? How are these mechanisms altered in disease?
We recently proposed a model of systems dynamics in hierarchical brain networks based on polyrhythmic oscillatory brain activity. This mechanistic framework implements a generic form of contextual predictive inference of input signals into brain networks. In essence, this vision is aligned with the principles of perceptual inference, which predict that spontaneous brain activity during resting wakefulness constantly implements the self’s representation of its environment.
Inspired by this framework, I will review a series of neurophysiological data that account for this hypothesis in a diversity of brain functions with an emphasis on auditory, language and multimodal perception. In particular, we recently proposed to train artificial neural networks on naturalistic stimuli to produce encoding models of neural activity that account for contextual uncertainty and prediction errors in perception. I will show how we used this approach to reveal the corresponding brain signaling pathways for natural speech processing.
Biography: Sylvain Baillet is Professor of Neurology & Neurosurgery, Biomedical Engineering and Computer Science at the Montreal Neurological Institute, and holds the Tier-1 Canada Research Chair of Neural Dynamics of Brain Systems at McGill University.
His main research contributions are in neuroimaging methods and multiscale, quantitative electrophysiology, with emphasis on magnetoencephalography (MEG) for time-resolved brain imaging, with transfers to EEG. He has initiated impactful open-source software developments (Brainstorm), efforts for data harmonization (MEG-BIDS) and data sharing (the Open MEG Archive/OMEGA). As program leader, Sylvain founded 2 MEG core units in Canada and the US and was Director of the McConnell Brain Imaging Centre at the MNI in 2013-17.
More info: https://www.mcgill.ca/neuro/sylvain-baillet-phd
You may also follow his peregrinations on Twitter @sylvain_baillet.
|14.40||Mid Career Award Winner: Interpreting the cell and circuit level origin of MEG/EEG signals with the Human Neocortical Neurosolver (HNN) software|
Dr. Stephanie Jones, PhD, Associate Professor, Department of Neuroscience, Brown University
Abstract: Magneto- and electro-encephalography (M/EEG) are the leading methods to non-invasively record human neural dynamics with millisecond resolution. However, it can be extremely difficult to infer the underlying cellular and circuit level origins, hindering the utility of M/EEG for translational neuroscience discovery. To address this need, we developed the Human Neocortical Neurosolver (HNN): a new user-friendly neural modeling tool designed to help researchers and clinicians interpret M/EEG data (https://hnn.brown.edu, Neymotin et al., eLife 2020). I will give an overview of the theory behind the development of HNN, demonstrate its use, and discuss strengths and limitations in relation to other M/EEG neural modeling software.
Biography: Stephanie R. Jones, PhD is Associate Professor in Department of Neuroscience at Brown University. She received her doctorate in mathematics from Boston University, followed by training in neuroscience and human magneto- and electro-encephalography (MEG/EEG) at Massachusetts General Hospital. Her research program integrates these disciplines to develop biophysically principled computational neural models that bridge the critical gap between human MEG/EEG brain imaging signals and their underlying cellular and network level generators. She collaborates extensively with animal neurophysiologists, cognitive neuroscientists, and clinicians to develop data constrained models that are translationally relevant. Her group developed their unique neural modeling into a user-friendly software tool for researchers and clinicians to interpret the circuit origin of their human MEG/EEG data: Human Neocortical Neurosolver. A primary focus of her research is to understand the role of non-invasively measured brain rhythms in sensory and motor processing. A goal is to translate an understanding of the network mechanism underlying rhythms into brain stimulation strategies to improve disrupt brain function.
|15.20||Keynote: Visceral signals, brain dynamics and cognition|
Catherine Tallon-Baudry, Dr, Ecole Normale Supérieure & Inserm
Abstract: The heart and gastro-intestinal tract intrinsically generate their own electrical activity and continuously send ascending signals to the brain. I will show how visceral inputs contribute to shaping brain dynamics at rest, and that the neural monitoring of cardiac inputs has meaningful cognitive correlates.
Biography: Catherine Tallon-Baudry is a senior cognitive neuroscientist working at the Department of Cognitive Sciences at Ecole Normale Supérieure in Paris. After having long worked on brain oscillations and visual cognition, she began developing and testing the idea that the neural monitoring of visceral signals from the heart and stomach might contribute to the biological implementation of the self.
|15.50||James Zimmerman Prize winner: Synthetic Gradiometers for Biomagnetism|
Dr. Jiri Vrba, Retired
Abstract: Jiri will outline development of noise cancellation by higher-order SQUID gradiometers for MEG (or other) applications. This development was based on their previous experience with mobile SQUID devices which provided an important foundation for design of robust synthetic 3rd-order gradiometer MEG detectors suitable for either a shielded or, under certain conditions, unshielded operation. Jiri will discuss the concept of gradiometer synthesis, compare gradiometers with adaptive systems, outline parameters necessary for successful shielded and unshielded MEG operation and indicate when the unshielded operation is possible.
Biography: Jiri obtained his MSc in 1965 at the Faculty of Technical and Nuclear Physics of Charles University in Prague, Czechoslovakia. After working for 2 years at the Institute of Solid State Physics in Prague, he moved to Canada to study low temperature physics at the University of Alberta, where he obtained PhD in 1971. Jiri was a Research Associate at the Universities of Alberta, Simon Fraser, and British Columbia.
Between 1974 and 2007 he worked at CTF Systems Inc., later VSM MedTech Ltd., where he held positions of Research Scientist, Vice President for Research, Director of Research, and Chief Technology Officer. In 1989 Jiri was a member of Ad-hoc committee to review High Temperature Superconductivity Project at National Research Council of Canada., and in 2005 he received NSERC Synergy Award for Innovation.
Between 2007 and 2012 Jiri was consultant to Elekta-Neuromag and University of Arkansas for Medical Sciences. His hobbies are hiking and photography.