Neural Encoding with Deep Neural Networks
Course: SoSe 2026, University of Osnabrück. Building brain encoding models that predict fixation-aligned MEG responses from DNN visual features. Core challenge: generalise from 5 training subjects to a held-out participant (subject 60) using the AVS dataset.
Working repo: meg-encoding-course-tbd | Reference repo: MEG-Encoding-Course
Course Notes
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BrainEncoding26 Challenge – Course Overview — dataset, challenge structure, pipeline, notebook overview
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BrainEncoding26 – Research Ideas & Implementation — 6 PyTorch-ready ideas from recent literature (CLIP backbone, multi-layer features, dual-stream, MLP head, subject adapters, contrastive alignment)
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ab welcher fixation prefrontal correaltion
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schauen varianz zwischen den subjects
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reduced rank regression
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cocalc
Questions & Ideas
- What if we look at this dataset whether subjects remembered the image — then maybe if you take crops of fixation or non-fixation and ask again you could try to see whether the periphery of an image contributes to remembering an image
see also
Tags: neuroscience science neural-encoding meg
Superlink: 050 🧠Neuroscience
610 🤖Artificial Intelligence, Künstliche Intelligenz
410 👨💻Uni und Lernen
Created: 2026-04-20 13:39