Neurocolloquium

Journal Club

Instructors: Mathis Lamarre, Anuja Negi, Fatma Deniz

Overview

Language English
Credits 3 ECTS
Lecture Period April 13 – July 18, 2026
Time Thursdays @ 2:30-4:00pm
Location MAR 5.044
ISIS link


Content

In the neurocolloquium, we read and discuss recent scientific publications from the field of computational cognitive neuroscience. A particular focus will be on literature that uses methods from the field of computer science and artificial intelligence as a means of modelling brain functions – in particular language – as represented in functional Magnetic Resonance Imaging (fMRI) data.

Learning outcomes

Students will become familiar with topics and debates within the field of language research and cognitive neuroscience. Furthermore, they will learn to read and discuss scientific articles and gain an understanding of how computational approaches can be applied to brain research.

Structure

Each week, one paper will be read in advance and discussed together in detail. At the beginning of the course, each student will be assigned one paper for which they will prepare a small presentation of the methods section which they will present prior to the discussion. Depending in the scope of these method sections, presentations should be around 10-15 minutes and should be accompanied by slides.

Schedule

Date Paper Presenter
Apr 16, 2026 Introduction to brain encoding and decoding models: part I Chris
Apr 23, 2026 Papers selection + Introduction to brain encoding and decoding models: part II Mathis
Apr 30, 2026 Conversation content is organized across multiple timescales in the brain Mathis
May 07, 2026 Hierarchical Brain–LLM Alignment Reveals Layer-Specific Neural Representations of Second Language Proficiency Peter
May 14, 2026 Holiday - No class -
May 21, 2026 Temporal structure of natural language processing in the human brain corresponds to layered hierarchy of large language models Sarah
May 28, 2026 Hierarchical dynamic coding coordinates speech comprehension in the human brain Anuja
Jun 04, 2026 Causal Interpretation of Neural Network Computations with Contribution Decomposition Omar
Jun 11, 2026 Why AI systems don’t learn and what to do about it Lessons on autonomous learning from cognitive science Mathis
Jun 18, 2026 Text-to-music generation models capture musical semantic representations in the human brain Peter
Jun 25, 2026 A foundation model to predict and capture human cognition Anuja
Jul 02, 2026 A foundation model of vision, audition, and language for in-silico neuroscience Omar
Jul 09, 2026 Modeling the language cortex with form-independent and enriched representations of sentence meaning reveals remarkable semantic abstractness Sarah
Jul 16, 2026 The Platonic Representation Hypothesis Chris
Jul 16, 2026 Revisiting the Platonic Representation Hypothesis: An Aristotelian View Chris