BRAINNET+ 2024
Brainnet + Interpretable brain data workshop
In-person & Virtual
13-15 May, 2024, Stockholm, Sweden
View of Stockholm-170351.jpg from Wikimedia Commons by Jonatan Svensson Glad, CC-BY-SA 4.0
Topics
Neuroscience - Complex Networks - Dynamical Models - Functional Connectivity - Machine Learning - Statistical Analysis
Electro/magneto-encephalography (E/MEG) - Magnetic Resonance Imaging (MRI)
About
Human brain data is complex, and the process of going from raw recordings to meaningful information is highly non-trivial. Information processing in the brain is distributed over a wide range of scales, both spatial and temporal. Moreover, working with neural data involves dealing with large amounts of data that are typically noisy and have many subject-specific properties. To overcome these difficulties and generate meaningful knowledge from brain recordings, experts from different fields must work together.The BrainNet workshop brings together researchers working on the analysis or modeling of human brain recordings, with a particular focus on electroencephalography (E/MEG) and magnetic resonance imaging (MRI) data. It aims to foster collaboration among participants who employ, or are interested in employing, methods derived from Complex Networks, Statistics, Dynamical Systems, Topology, Machine Learning, or a combination of these disciplines.
WORKSHOP PROGRAM
The workshop will consist of:
Keynote speaker presentations: Longer presentations by established researchers giving an overview of their area of research.
Invited speaker presentations: Talks given by researchers presenting their latest results.
Contributed talks: Selected from abstracts submitted by participants interested in presenting at the workshop.
Flash talks: Short 5-minute talks that all participants should give to introduce themselves and the topics they are working on or are interested in.
Keynote Speakers
David Dahmen
Institute for Advanced Simulation, Research Centre JülichGoogle Scholar
Talk Title:: Physics approaches to the collective dynamics of heterogeneous neural networksAbstract: The brain is an immense network of neurons, whose dynamics underlie its complex information processing capabilities. A neuronal network shares many features with disordered systems in physics, as it is composed of many constituents that interact heterogeneously and in a nonlinear fashion. In this talk, I demonstrate how to use field-theoretic tools from statistical physics to study the dynamical and functional consequences of network heterogeneity and obtain predictions for spatio-temporal correlation patterns, the hallmarks of collective behavior in biological and artificial neural networks. I further compare these predictions to recordings of parallel spiking activity in different cortical areas.
Jacobo Diego Sitt
Paris Brain Institute (ICM), INSERM, ICM institute, Pitie-Salpetriere HospitalGoogle Scholar
Talk Title:: Latest Developments in Neurophysiology of States of Consciousness: From Mechanistic Principles to Novel Diagnostic and Therapeutic ToolsAbstract: Uncovering the neural mechanisms that allow conscious access to information is a significant challenge of neuroscience. An incomplete list of still open questions includes: What are the necessary brain computational properties to permit access to a stream of conscious content? What is the relationship between conscious perception, self-awareness, and multisensory processing of bodily signals? How do these processes change when the brain transitions to an ‘unconscious’ state (like sleep, anesthesia, or pathological conditions)? Can we externally trigger state-of-consciousness (SOC) transitions through stimulation? In this presentation, I will present my work focusing on these relevant scientific and clinical questions.I will present our latest developments, including different pre-clinical and clinical experimental models (brain injuries and/or anesthesia), neuroimaging methods (EEG, fMRI, or brain/body interactions) and stimulation techniques (tES, auditory/somatosensory/visual stimulation). Overall, I will try to demonstrate that the integration of multimodal neural information provides critical information to characterize the state-of-consciousness in physiological
and pathological conditions and might help to predict novel optimal therapeutic strategies.
Marcel Oberlaender
Max Planck Institute for Neurobiology of BehaviorGoogle Scholar
Talk Title: Towards brain-wide simulations of sensation and perception in rodentsAbstract: My research aims to unravel cellular and circuit mechanisms by which the cerebral cortex transforms sensory signals into perception, and ultimately into behavior. To achieve this ambitions goal, my lab develops anatomically and functionally realistic models of the thalamocortical, cortical and subcortical circuits in the rodent brain that process tactile information from the facial whiskers. Based on these models, we perform multi-scale simulations to mimic empirically observed signal flows during whisker-based behaviors. With these simulations, we disentangle in silico – and then test via manipulations in vivo – how the interplay between cellular and circuit mechanisms implements tactile sensation, perception, and behavior.
Marcus Kaiser
Professor of Neuroinformatics, School of Medicine, University of Nottingham, UK
Visiting Professor, Shanghai Jiao Tong University, China
Google Scholar
Talk Title:: The Human Connectome in Health and Disease: How the Spatial Organisation of Brain Networks Influences CognitionAbstract: 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. I will outline some characteristic network features, their link with brain function, and how they differ for some brain disorders. In particular, I will highlight the impact of the spatial organisation of brain networks and the role of delays on brain dynamics and brain performance. Finally, I will outline how interventions based on connectome information and computational models might be able to improve cognitive function for brain and mental health conditions.