Multi-modal understanding of brain and behavior


Shervin Safavi | Max Planck Institute for Biological Cybernetics, Germany
Roxana Zeraati | University of Tübingen, Germany


The brain operates across multiple interacting scales that are duly measured with different recording modalities: From genes (measured by transcriptomics) defining the role of individual neurons, to the activity of individual and population of neurons (measured by electrophysiology or Ca imaging), and eventually interacting brain areas forming the whole brain dynamics (measured by neuroimaging techniques such as fMRI). Different modalities provide insights into different aspects of brain function. Large-scale modalities are more helpful in understanding the principles of brain computation, whereas smaller-scale modalities provide better insights into underlying circuit mechanisms. Hence, to fully understand the mechanisms underlying brain function and ultimately behavior, we need to study different modalities simultaneously and uncover their relation to each other, and to behavior.

In this workshop, we bring together a unique group of experimental and computational experts who develop multi-modal and multi-scale experimental techniques, analysis methods, and computational models to understand various cognitive functions. Our speakers will discuss how multi-modal measurements and large-scale population recordings have transformed our understanding of brain function on a fundamental level, linking neural dynamics across different scales (from genes to the whole brain and behavior). They will introduce novel analysis methods and machine-learning techniques to uncover interpretable structures in such high-dimensional neural and behavioral data, and link neural signals that not only have different spatiotemporal resolutions but distinct mathematical natures (point processes versus continuous signals). Moreover, they will explain how computational models can link cellular and network mechanisms across different scales to form theories about multi-scale mechanisms underlying neural computation and behavior. Our aim is to stimulate discussions on the benefits and challenges of multi-modal studying of brain dynamics (more details in the attached schedule). We believe the complementary perspectives of our speakers synergized with discussions in our workshop would promote new research directions and collaborations that will broaden the extent of multi-modal brain research (e.g., using multi-modal data to build multi-scale models) to gain a more holistic understanding of brain function and cognition.

Schedule (CEST)

Tuesday, Sept 26


Roxana Zeraati, Shervin Safavi


Danielle Basset | University of Pennsylvania, USA
Designing local, meso, and global control signals for neural systems


Justine Hansen | McGill University, Canada 
Tools for multi-modal, multi-scale annotation of brain networks


Sofie Valk | Max Planck Institute for Human Cognitive and Brain Sciences, Germany
Heritability and plasticity of brain structure and function


30 min coffee break


Shervin Safavi | Max Planck Institute for Biological Cybernetics, Germany
Methods for cross-scale analysis of neural data


Maryam Shanechi | University of Southern California, USA
Multi-scale dynamical latent state models with multi-modal neural observations


Marius Pachitariu | Janelia Research Campus, USA
Identifying a neuronal workspace for behavioral generalization




End of first day

Wednesday, Sept 27


Introduction to day 2


Adrián Ponce-Alvarez | Polytechnic University of Catalonia, Spain
Collective activity of neural systems at different scales and in different brain states


Martin Vinck | Ernst Strüngmann Institute, Germany
Laminar and cell-type specificity of inter-areal interactions


30 min coffee break


Michael Schirner | Charité – Universitätsmedizin Berlin
Learning how network structure trades fast with deep decision-making for bio-inspired computing


Cecilia Gallego Carracedo | Imperial College London, UK
Building the bridge: Understanding the relationship between local field potentials and neural population dynamics


Panel discussion