Felix Körber

Intro

I develop machine-learning and information-theoretic methods for analyzing neural time series, with a particular interest in real-time neural decoding, brain-computer interfaces and predictive coding. My research spans EEG and ECoG analysis, deep learning and compartmental biophysical modelling.

Take a look at my projects, or read more about me and my CV.

Projects

EEG Foundation Models for Real-Time Motor Imagery Decoding

Telluride Neuromorphic Workshop, 2026
Trained classifiers and fine-tuned a REVE foundation model with LoRA for real-time motor imagery decoding of LSL-streamed EEG.

Spectral Transfer Entropy Reveals Predictive-Coding Network Dynamics

Master's thesis, supervised by Alessandro Tavano, 2026
Developed MNE and IDTxl pipelines to investigate predictive coding dynamics in marmoset ECoG data through multivariate transfer entropy.

Short-Term Plasticity and Pattern Separation in Compartmental Granule Cell Models

Master's thesis, supervised by Peter Jedlicka, 2026
Fitted short-term plasticity dynamics of dentate granule cells using TREES and NEURON to study input transformations and pattern separation.

Transformer-Based MEG Language Decoding

LibriBrain Competition, 2025
Using transformer-based encoding of MEG data to decode periods of silence vs. speech perception.

Crossmodal Variational Autoencoders for Integration of Structural and Functional Brain Imaging

Bachelor's thesis, supervised by Christian Fiebach, 2023
Developed crossmodal VAEs for latent-space alignment between functional and structural brain properties.

About and CV

Education

• M.Sc. Interdisciplinary Neuroscience, Goethe University Frankfurt, 10/2024 - Present
• M.Sc. Psychology, Goethe University Frankfurt, 09/2023 - 03/2026. Final grade 1.5, thesis 1.0
• B.Sc. Psychology, Goethe University Frankfurt, 10/2020 - 07/2023. Final grade 1.4, thesis 1.0

Work Experience

• Research Assistant, Ernst Strüngmann Institute (ESI), 05/2026 - Present. Compartmental modelling with NEURON and TREES.
• Research Assistant, Goethe University, 04/2021 - Present. Neural data analysis, EEG/MEG acquisition and preprocessing, machine learning.

Skills

• Neural data: M/EEG & ECoG analysis, M/EEG acquisition, MNE-Python, neural decoding
• Machine learning: PyTorch, TensorFlow, scikit-learn, Transformers, RNNs, VAEs
• Programming: Python, MATLAB, R, Git, HPC
• Modelling: NEURON, TREES

Advanced Training

• Telluride Neuromorphic AI Workshop 2026
• Brain Dynamics Academy 2025 (EBRAINS)
• Neuromatch Academy 2023 (Computational Neuroscience)

Scholarship

• Studienstiftung des deutschen Volkes (German Academic Scholarship Foundation), since 01/2020

• Download CV

Contact

• Instagram
• GitHub

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