D.NemethOur new publication is now available.
We employed a combination of RIDE (residue iteration decomposition) and MVPA (multivariate pattern analysis) on EEG data to demonstrate that probability information can be decoded both as modality-specific and modality-independent neural representation in sequence learning.
https://doi.org/10.1093/cercor/bhad079
We employed a combination of RIDE (residue iteration decomposition) and MVPA (multivariate pattern analysis) on EEG data to demonstrate that probability information can be decoded both as modality-specific and modality-independent neural representation in sequence learning.
https://doi.org/10.1093/cercor/bhad079
Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning
Abstract. Probabilistic sequence learning supports the development of skills and enables predictive processing. It remains contentious whether visuomotor sequen