Thank you for attending the CNSP2025 Workshop on September 2-3, 2025!

CNSP2025 Workshop Programme

Keynote talks:

• Jean-Rémi King – Emergence of language in the human brain
• Sam Nastase – Unifying the structures of language in a neural population code

Talks:

• Dana Boebinger – Rapid and dynamic construction of acoustically invariant speech representations in the human auditory cortex
• Ashley Symons – Towards a behavioural measure of attentional capture by continuous natural speech

Tutorials:

• Aaron Nidiffer – Encoding/decoding models, multivariate analysis, models validation, etc. in the MATLAB mTRF-Toolbox, a beginner’s tutorial
• Hugo Weissbart – Bridging complexity in neural dynamics: Non-linear approaches to temporal response function analysis
• Maximilian Nentwich – Modelling recurrent connectivity and temporal response functions

You can download the detailed programme here: CNSP2025 PROGRAMME.

About:

Methodologies for neural signal processing in the case of natural scenes and sound perception.

• Talks from experts in the field
• Tutorials on encoding and decoding models for neural signal analysis
• Tutorial sessions on specific study cases and/or methodologies
• Q/A sessions and continuous support throughout the workshop

Who should attend?

• Researchers interested in studying natural speech or music perception with EEG/MEG/ECoG, but have no experience with ecologically-valid experiments.
• Researchers with experience in continuous sensory perception and tools such as the mTRF-Toolbox, who are interested in deepening their understanding and in expanding their set of tools.

Prerequisites

• Some experience with neural signal processing (e.g., EEG, MEG, or ECoG).
• Some programming experience (Matlab/Python) for the hands-on sessions.
• Practical interest in applying these notions to your research.

What will you learn?

• Theoretical insights into system identification and multivariate linear methods for neural signal analysis
• Practical guidelines on how to prepare, process, and interpret your data
• Practical knowledge of tools for neural signal analysis such as the mTRF-Toolbox