CNSP Workshops


CNSP2022 took place on the 18-20 July 2022 (sponsored by mBrainTrain). Please stay tuned for future workshops. Meanwhile, you can find more information on CNSP2022 below. Check out the videos of all the sessions of CNSP2022 here.
and the CNSP2022 booklet for further information. More resources from CNSP2022 (code, datasets and tutorials) can be found here.


Schedule:
The workshop schedule can be found here!


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

What's different than CNSP 2021?
  • You can propose tutorials and talks for the workshop (official call here)
  • Two tutorial tracks, one for beginners and one more advanced
  • A mini-session on best practices and challenges with data sharing
  • A mBrainTrain-sponsored student project (official call here)

Where, when and how much?
  • Online! 18-20 July
  • Podium presentations: Free for registered participants
  • Tutorial sessions: €20 registration fee

Participants?
  • 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.
  • A practical interest in applying these notions.

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


CNSP2021 lectures and tutorials
Check out the videos of all the sessions of CNSP2021 here.
and the CNSP2021 booklet for further information. More resources from CNSP2021 (code, datasets and tutorials) can be found here.

BYOD! (Bring your own dataset)
We will provide you with guidelines to prepare your own data for the practical sessions. We can then answer your specific question during the Q/A session on day 2.
Datasets will be available, if you don't have your own.

Sponsored by: