Workshop EEG MVPA - Decoding EEG data with intermixed signals using temporal signal decomposition and multivariate pattern-analysis

The MEMO Team cordially invites you to the following workshop:

Decoding EEG data with intermixed signals using temporal signal decomposition and multivariate pattern-analysis
by
Ádám Takács (PhD), Carl Gustav Carus University Hospital at TU Dresden

Date: May 15. Monday
Place: Neurocampus

Program: 
10.30-12.00 Lecture: How to combine temporal signal decomposition with multivariate pattern-analysis
Room: Neurocampus F22 (If there are too many audience: Amphi)

14.00-16.00 Practical session: Decoding sequential regularities from temporally decomposed EEG data
Room: Neurocampus F28


I can find here three related articles that are worth reading before the workshop:
 Takács, Á., Yu, S., Mückschel, M., & Beste, C. (2022). Protocol to decode representations from EEG data with intermixed signals using temporal signal decomposition and multivariate pattern-analysis. STAR protocols, 3(2), 101399.  

 https://www.sciencedirect.com/science/article/pii/S2666166722002799

Takacs, A., Mückschel, M., Roessner, V., & Beste, C. (2020). Decoding stimulus–response representations and their stability using EEG-based multivariate pattern analysis. Cerebral Cortex Communications, 1(1), tgaa016.

https://academic.oup.com/cercorcomms/article/1/1/tgaa016/5831171

Vékony, T., Takács, Á., Pedraza, F., Haesebaert, F., Tillmann, B., Mihalecz, I., ... & Nemeth, D. (2023). Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning. Cerebral Cortex, bhad079.
 

https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhad079/7081423?login=false