Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning

MEMO_CRNL

An new article of MEMO CRNL in Human Brain Mapping :

Takács A, Kóbor A, Kardos Z, et al. Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning. Hum Brain Mapp. 2021;1–20.

https://doi.org/10.1002/hbm.25427

 

A short abstract:

We investigated how humans are capable of acquiring multiple types of information presented in the same information stream. We focused in this study on statistical learning and rule-based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. We used here a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule-based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrated that concomitant but distinct aspects of information coded in the N2 time window play a role in these mechanisms: mismatch detection and response control underlie statistical learning and rule-based learning, respectively, albeit with different levels of time-sensitivity. The current findings deepen our understanding on the mechanisms of how humans are capable of learning multiple types of information from the same stimulus stream in a parallel fashion.