Ibd 2023
Interpretable brain data workshop
8-9 June, 2023, Stockholm, Sweden
View of Stockholm-170351.jpg from Wikimedia Commons by Jonatan Svensson Glad, CC-BY-SA 4.0
Topics
Neuroscience - Human Data - Electro/magneto-encephalography (E/MEG) - Magnetic Resonance Imaging (MRI) - Dynamical Models - Functional Connectivity - Machine Learning - Statistical Analysis
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 spread across a wide range of scales, both spatial and temporal. Moreover, working with neuroscientific data involves dealing with a large amount of data, which is usually noisy and have many subject-specific properties. To address these difficulties experts from different fields must work together in order to produce meaningful knowledge from brain imaging data. Being able to interpret brain data is not only important to have a better scientific understanding of how the brain works, but is especially relevant to design better diagnostic protocols and treatments for patients with neurological diseases.The aim of this workshop is to bring together people involved in different parts of the process of transforming human brain recordings into interpretable results. We will mainly focus on scientists working with electro/magneto-encephalography (E/MEG) and Magnetic Resonance Imaging (MRI) data. During the event, leading researchers in the field will introduce participants to novel techniques for data analysis and interpretation. There will also be activities to encourage dialogue among participants and to promote the emergence of new fruitful collaborations among them.
Speaker Presentations
Program
| Day | Time | Topic | Keynote Speaker |
|---|---|---|---|
| June 8 | Morning | Modelling Session | Gustavo Deco |
| June 8 | Afternoon | Data Analysis Session | Peter Fransson |
| June 8 | Evening | Social Activity | -- |
| June 9 | Morning | Brain Imaging Session | Axel Thielscher |
| June 9 | Afternoon | Hands-On | -- |
| June 9 | Evening | Social Activity | -- |
Keynote Speakers
Gustavo Deco (Virtual Speaker) - Research Professor at ICREA and Professor at the Pompeu Fabra UniversityGoogle Scholar
Talk Title:: The Thermodynamics of MindAbstract: We propose a unified theory of brain function called ‘Thermodynamics of Mind’ which provides a natural, parsimonious way to explain the underlying computational mechanisms. The theory uses tools from non equilibrium thermodynamics to describe the hierarchical dynamics of brain states over time. Crucially, the theory combines correlative (model-free) measures with causal generative models to provide solid causal inference for the underlying brain mechanisms. The model-based framework is a powerful way to use regional neural dynamics within the hierarchical anatomical brain connectivity to understand the underlying mechanisms for shaping the temporal unfolding of whole-brain dynamics in brain states. As such this model-based framework fitted to empirical data can be exhaustively investigated to provide objectively strong causal evidence of the underlying brain mechanisms orchestrating brain states.
Peter Fransson - Professor at Karolinska InstitutetGoogle Scholar
Talk Title:: Network-models of functional neuroimaging data - a brief introduction and some recent developmentsAbstract: In this talk I will provide a brief history of the field of network neuroscience, in particular when applied to functional neuroimaging data. Common model principles as well as limitations and challenges for the field will be discussed. Additionally, I will discuss some recent methodological development to study time-varying properties of brain network activity.
Axel Thielscher - Professor, Technical University of Denmark & Senior Researcher, DRCMRGoogle Scholar
Talk Title:: Personalized volume conductor modeling to interprete and guide transcranial brain stimulation and electroencephalography researchAbstract: Non-invasive transcranial brain stimulation (TBS) requires an accurate steering of the externally generated currents towards the target area to enable an unambiguous interpretation of the behavioral and physiological stimulation effects. In electroencephalography (EEG), the interpretability of the recordings benefits from an accurate localization of the neural sources that underlie the recorded scalp potentials. TBS and EEG are quite different and complementary methods, but share the same fundamental physics, where the term "volume conduction" describes the impact of the various tissue compartments in the human head on the electric current flow caused by the internal or external sources. My talk will focus on personalized volume conductor models of the human head, derived from structural magnetic resonance images. I will start by summarizing our work on the automated generation of these models and their validation using MR imaging. I will then give an overview of their various applications in TBS and EEG research, ranging from the quantification and optimization of the individually applied TBS dose to EEG source localization. The results will highlight the relevance of anatomically detailed models.
Invited Speakers
Áine Byrne - Assistant Professor at University College DublinGoogle Scholar
Talk Title:: Population-level models of neural activity that include a dynamic synchrony variableAbstract: Electrophysiological brain recordings are dominated by oscillatory activity, spanning a wide range of temporal scales. These oscillations exhibit both spontaneous and event-driven fluctuations in amplitude, which are believed to arise from a change in the synchrony of underlying neuronal population firing patterns. Previous population level models of neural activity, such as the Wilson-Cowan model, have failed to account for these fluctuations as they do not explicitly track the within-population synchrony. Starting with a network of synaptically coupled quadratic integrate-and-fire neurons, we use the Ott-Antonsen ansatz to reduce the population to a few variable model, which takes the form of a Wilson–Cowan style model coupled to dynamic equation for the population synchrony. As in the original Wilson–Cowan framework, the population firing rate is at the heart of our new model; however, in a significant departure from the sigmoidal firing rate function approach, the population firing rate is now obtained as a real-valued function of the complex valued population synchrony measure. To highlight the usefulness of this next generation Wilson–Cowan style model I will show how it can be deployed in a number of neurobiological contexts, providing understanding of the changes in power-spectra observed in EEG/MEG neuroimaging studies of motor-cortex during movement, insights into patterns of functional-connectivity observed during rest and their disruption by transcranial magnetic stimulation, and to describe wave propagation across cortex.