Andreas Pedroni

This paper develops a deep learning model to automate scoring of the Rey-Osterrieth Complex Figure (ROCF) drawings, outperforming human raters and clinicians in accuracy and consistency.

The paper investigates age-related changes in EEG alpha power by decomposing signals into aperiodic and adjusted components across three samples of young and elderly individuals.

Automagic provides standardized preprocessing and quality assessment for EEG data to address artifact contamination and improve replicability in large-scale studies.

An open-source Matlab plugin for EEGlab provides both a graphical user interface and multi-subject scripting for reproducible electroencephalography (EEG) microstate analysis, accompanied by a methodological overview and tutorial.

This study uses eye tracking and EEG to decompose Symbol Search performance into cognitive components, finding that efficient performance depends more on memory encoding than general processing speed.