Brain Cortical Area Characterization and Machine Learning-Based Measure of Rasmussen’s S-R-K Model

the results demonstrate the possibility of objectively measuring the different S, R and K levels in terms of brain activations. Furthermore, such evidence is consistent with the scientific literature in terms of cognitive functions corresponding to the different levels of cognitive control.

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Publication Details

Journal
Brain Sciences
Published
2025-09-12
DOI
https://doi.org/10.3390/brainsci15090981
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
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article

Brain Cortical Area Characterization and Machine Learning-Based Measure of Rasmussen’s S-R-K Model

Fabio Babiloni, Andrea Giorgi, Stefano Bonelli, Alessia Vozzi et al.
Brain Sciences
EEG and Brain-Computer Interfaces
article

Brain Cortical Area Characterization and Machine Learning-Based Measure of Rasmussen’s S-R-K Model

Fabio Babiloni, Andrea Giorgi, Stefano Bonelli, Alessia Vozzi, Gianluca Di Flumeri, Daniele Germano, Pietro Aricò, Géraud Granger, Jean-Paul Imbert, Gianluca Borghini, Fabrice Drogoul, Vincenzo Ronca, Rossella Capotorto, Daniele Amore
article en

Abstract

the results demonstrate the possibility of objectively measuring the different S, R and K levels in terms of brain activations. Furthermore, such evidence is consistent with the scientific literature in terms of cognitive functions corresponding to the different levels of cognitive control.

Brain SciencesVol. 15(9)
École Nationale de l’Aviation Civile (FR), Eurocontrol (FR), European Brain Research Institute (IT), Deep Blue (Italy) (IT), Eurocontrol (BE), Hangzhou Dianzi University (CN), Sapienza University of Rome (IT)
Openalex Percentile: Top 75%
EEG and Brain-Computer Interfaces
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Brain Cortical Area Characterization and Machine Learning-Based Measure of Rasmussen’s S-R-K Model — Fabio Babiloni, Andrea Giorgi, et al. · Brain Sciences (2025) | TGRS Research Map | TGRS