Inés Schönmann

Room: MAR 5.021
Email: i.schoenmann@tu-berlin.de
Office hours: on appointment

Research Interests

I focus on studying human visual perception in a way that it reflects the realities of biological and behavioural data while also relating meaningfully to the human experience. Furthermore, I am interested in the role predictive processes play when processing language in naturalistic settings.

Curriculum Vitae

Professional and Academic Experience

10/23 – 10/24 Research Assistant, Einstein Centre for Neuroscience & Technical University Berlin: Using natural language processing tools for stimulus preselection, study planning and analysis of fMRI data.
09/22 – 08/23 Research Assistant, Predictive Brain Lab, Donders Institute: Conceptualisation and realisation of an MEG encoding study probing the scope of linguistic predictions during naturalistic listening paradigms using various NLP libraries and tools.
09/22 – 04/23 Teaching Assistant, Brain & Cognition Course, Radboud University: Supervising workgroups, correcting assignments, and teaching.
02/22 – 08/22 Research Assistant, Behavioural Science Institute, Radboud University: Data analysis and writing of a research article for a project predicting future reading comprehension skills in children.
08/21 – 08/22 Student Assistant, Neural Information Processing, University of Tübingen: Preparing English lecture and presentation materials in LaTeX.
04/19 – 08/21 Research Assistant, Experimental Cognitive Science, University of Tübingen: Programming for online experiments. Analysing fMRI data. Editing research articles. Conducting behavioural, EEG and fMRI experiments.

Education

2021 – 2023 M.Sc. in Cognitive Neuroscience, Radboud University, Nijmegen: Thesis: “Factors Driving Neural Correlates of Next-Word Prediction during Natural Language Processing: An MEG Encoding Study” Concentration: Language and Communication Lectures in Complexity Analysis, Computational Psycholinguistic, Language Acquisition, Production and Comprehension, Academic Writing, Neuroanatomy and Neuroimaging
2018 – 2021 B.Sc. in Cognitive Science, University of Tübingen, Tübingen: Thesis: “Similarity Judgements of Natural Images: Instructions Affect Observers’ Decision Criteria and Consistency” Lectures in Mathematics, Computer Science, Neural Networks, (Computational) Neuroscience, Linguistics, Psychology, and Statistics
2014 – 2017 B.A. in International Politics, Sciences Po Paris, Paris: Lectures in Academic Writing, Economy, History, Law, International Relations and Sociology

Awards and Grants

2023 PhD Fellowship Grant at the Einstein Centre for Neuroscience Berlin

2023 Contributed Talk at the Cognitive Computational Neuroscience Conference, Oxford

2019 Research Grant at the Forum Scientiarum, University of Tübingen

2015 Research Grant at the Babel Initiative, Sciences Po Paris

Publications

Schönmann, I., de Lange, F. P., & Heilbron, M. (2023). Probing next-word and long-distance prediction using encoding modelling and MEG. Conference on Cognitive Computational Neuroscience.

Schönmann, I., Künstle, D.-E., & Wichmann, F. A. (2022). Using an odd-one-out design affects consistency, agreement and decision criteria in similarity judgement tasks involving natural images. Journal of Vision, 22(14), 3232–3232.

Schönmann, I., Szewczyk, J., de Lange, F. P., & Heilbron, M. (2025). Stimulus dependencies—rather than next-word prediction—can explain pre-onset brain encoding in naturalistic listening designs. eLife.