Description
In the self-learning systems lab, we are interested in investigating, describing, and improving the neurocognitive processes involved in reading (e.g., vision, orthographic codes, and lexical access) and language (e.g., temporal sampling, features of text generated by the Large Language Model). We use computational modeling to develop a theory for the mechanistic description of neurocognitive processes in reading. Our computational models are evaluated based on behavioral data (e.g., eye-tracking) and brain imaging data (e.g., M/EEG, fMRI). In addition, the computational descriptions allow us to improve applied measurement methods and statistical solutions for the individualized diagnosis and intervention of reading skills. Here, we use statistical and machine learning methods.
Adress:
Self-Learning Systems Lab, Humanwissenchaften-DP Heillpädagogik
Jun.-Prof. Dr. Benjamin Gagl
Frangenheimstraße 4, Postfach 6
50931 Köln, Deutschland