Neural Traces 2024: Advanced M/EEG Methods and Clinical Applications Workshop
April 10-12, 2024 @ PTB Berlin, Germany
https://neuraltraces2024.org | Submission deadline: January 8, 2024 | Registration opening: February 1, 2024
Neural Traces is an onsite, three-day workshop on methods in electroencephalography and magnetoencephalography (M/EEG) and their clinical applications. Advances in M/EEG, and the methods employed to extract information from their corresponding signals, have increasingly contributed to our understanding of brain function and network connectivity. In this workshop, we review various methods that have been developed to enable accurate source imaging from these electrophysiological modalities. We also discuss M/EEG signal extraction and interpretation in the context of various neurological and psychiatric disorders.
We are soliciting extended abstract submissions for contributed oral and poster presentations.
Topics
Suitable submissions may cover but are not limited to the following topics:
I. Advanced M/EEG data analysis methods:
- Signal processing and time series modeling
- Forward and inverse modeling
- Machine learning and multivariate modeling
- Open science (software, data, standards, protocols, ...)
II. Clinical applications of M/EEG:
- Movement disorders
- Aging and dementia
- Psychiatric and developmental disorders
- Epilepsy
- Sleep and consciousness disorders
Submission guidelines
Title, author list and affiliations, 700-word (maximum) extended abstract outlining the study's background, approach, (preliminary) findings and significance, and references.
Optional: figure with a 150-word (maximum) description
Registration and on-site participation is required for presenters.
Please visit https://neuraltraces2024.org for abstract submission, registration, and further information about the workshop.
Important dates
- January 8, 2024: Abstract submission closes
- February 1, 2024: Workshop registration opens
Workshop hosts and support
Neural Traces 2024 is organized by the Brain and Data Science Group at Charité-Universitätsmedizin Berlin, the Machine Learning and Inverse Modeling Group at PTB Berlin, and the Uncertainty, Inverse Modeling and Machine Learning (UNIML) Group at Technische Universität Berlin. The Workshop is partially supported by the European Research Council (Funding ID: 758985) and the Helmholtz Fund.