Marlene Meyer
Donders Institute for Brain, Cognition, and Behaviour, Radboud University, The Netherlands
Babies on the move: How to deal with movements in infant EEG research
Electroencephalography (EEG) is one of the most established tools used in developmental cognitive neuroscience research with infants and young children. EEG is non-invasive, allows measuring neural activity with high temporal resolution, and has contributed important insights on social-cognitive development. However, infant EEG research also faces many challenges, particularly the amount and variety of movements infants make during EEG recordings. While adults are typically instructed to reduce their body and specifically eye-movements to a minimum during EEG recordings, movements during infant EEG recordings are unavoidable and often leave challenging artifacts in the data. In this talk, I will describe the movements encountered in infant EEG data and I will discuss ways to reduce movements during testing, to exclude movements in data analysis, and how to potentially make use of movements as focus of interest.
Integrating Movement into the Neuroscience of Music and Social Interaction
Giacomo Novembre
Neuroscience of Perception and Action Lab, Italian Institute of Technology, Rome, Italy
Music and dance are universally acknowledged as essential elements of human social interaction, yet neuroscience currently lacks sufficient tools to fully explore their biological foundations. To move this research forward, I propose that neuroscience must: (i) prioritize behavioral analysis, particularly movement, and develop robust methods to handle its inherent multidimensional complexity; (ii) holistically integrate behavioral and neural approaches; (iii) refine computational methods to untangle overlapping neural processes during naturalistic behaviors; (iv) adopt a comparative perspective, for example by examining different developmental stages; and (v) extend measurement practices into ecologically valid, real-world environments. In this keynote, I will discuss recent studies from my laboratory addressing these critical challenges and demonstrate how focusing on movement enriches our neuroscientific understanding of music, dance, and social interactions.
Organization of neurophysiological and motion data for open and reproducible science
The Brain Imaging Data Structure (BIDS) aims to make neuroimaging and behavioural data interoperable across different laboratories by standardizing data representation and metadata structure. This promotes findable, accessible, interoperable, reusable (FAIR) data management, ultimately boosting the reproducibility of research. The hands-on session will consist of a talk and a DIY part. The talk will introduce the motivation for using BIDS for data curation and how it helps individual researchers and group leaders. The hands-on part can have dual tracks demonstrating how to convert data sets of different modalities (EEG and motion) using Python and/or Matlab respectively. Concretely, the session will start with a tutorial for converting example data snippets into BIDS, allowing participants to modify the scripts to convert their own data sets into BIDS.
Julius Welzel
Kiel University, Germany
The do’s and don'ts of multimodal data acquisition in everyday life
Recent technological advances have made it possible to record EEG not only in the lab but also in everyday life — during office work, while shooting basketball hoops, or even while swimming. These recordings hold immense potential to deepen our understanding of brain activity in rich, real-world scenarios. However, moving beyond the controlled lab environment also introduces serious challenges: How do we separate meaningful neural signals from overwhelming noise? How do we avoid drawing entirely incorrect conclusions based on non-neural artifacts?
Recording EEG "in the wild" requires us to look beyond the brain. To interpret data meaningfully, we must consider the context in which brain activity unfolds — the surrounding acoustic environment, the individual’s movements, or the presence of others, to name just a few. Fortunately, a growing range of tools — such as IMU motion sensors, microphones, and cameras — allows us to capture some of this complexity. However, making optimal use of these data streams requires careful synchronization and thoughtful integration with EEG recordings.
In this hands-on workshop, we will share lessons learned from our extensive work with mobile EEG, including practical examples and common pitfalls. Participants will explore:
- Smartphone-based tools to access and record from built-in sensors
- Methods for synchronizing and validating multimodal data streams using the Lab Streaming Layer (LSL)
- Our custom-built standalone EEG/audio system — the nEEGlace — enabling integrated recordings on the go
We will demonstrate use cases, highlight technical do’s and don’ts, and leave ample time for open discussion and hands-on exploration. Whether you are just getting started or already working with mobile EEG, this workshop will help you navigate the complexities of multimodal recordings beyond the lab.
Martin Bleicher
University of Oldenburg, Germany
Melanie Klapprott
University of Oldenburg, Germany
The interlocking of micro eye- and head-movements with internal working-memory processes—and their neural basis
To understand human cognition and behaviour, it is vital to understand the foundational processes by which humans retain, select, and transform internal representations ‘in mind’. Gaining access to these core internal working-memory processes, however, is not trivial. I will start my talk by showing how these internal working-memory processes can be read out from directional biases in miniscule eye movements known as microsaccades – an accessible peripheral “fingerprint” of attentional computations upstream in the brain’s oculomotor system. I will show how this extends to micro movements of the head and unpack the theoretical implications of these findings. I next adopt a pragmatic perspective, delineating how microsaccade biases can be leveraged as a powerful signal to track core internal working-memory processes across space and time, bringing novel opportunities for uncovering the principles of working-memory use in dynamic settings and in active behaving humans. Finally, I will address how spatial biases in microsaccades relate to neural modulations by covert spatial attention, arguing for a functional but not obligatory link.
Freek van Ede
Institute for Brain and Behavior Amsterdam, Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, The Netherlands
Excursion at the Frauenhofer IMTE
At the AI-Motion Labs in the Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, we offer a unique research facility that offers advanced motion analysis by using a modular, high-tech treadmill (M-Gait, Motek Medical BV, NL) and multi-directional robotic 3D body weight support system (FLOAT, Reha-Stim Medtec AG, CH). Both systems are designed to enable safe, comprehensive and innovative movement analysis and gait rehabilitation. We believe in the potential of these tailored cutting-edge technologies together with AI-supported learning techniques in tomorrow’s healthcare. We thus contribute to the development and validation of approaches tailored to our clients' needs while also innovating new methodologies that enhance patient outcomes and improve overall health management.
Gerrit Bücken
Frauenhofer IMTE
Anne Katrin Brust
Frauenhofer IMTE