An awesome repository & A comprehensive survey on interpretability of LLM attention heads.

Computational Cognitive Neuroscience textbook

Biologically based neural network simulations of the brain written in Go with a 3D GUI powered by Cogent Core.

Simulations for the Computational Cognitive Neuroscience textbook

An Awesome List of Cognitive Science Resources

[ICLR'25] ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

Go implementation of Leabra algorithm for biologically-based models of cognition, based on emergent framework (with Python interface)

Multi-voxel pattern analyses methods based on ML & DL to decode the category of visual stimuli viewed by a human subject based on their recorded brain activity in fMRI form

Visual Search in Natural Scenes benchmark

Neural drift-diffusion model (NDDM) is a repository to integrate simultaneously both single-trial EEG measures and behavioral performance (response time and accuracy) to understand cognition.

A complete Python framework to perform real-time fMRI decoded neurofeedback experiments

This repository contains the collection of Cognitive Science computation modeling projects made for the DTU Human-Centered AI course 02458: Cognitive Modeling

脑电波：视觉感受区电位信号(LFP)与视觉刺激之间关系研究（盲信号处理）

Paper and code for High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns

Analyze brain surface/volume (gifti, cifti, nifti) in R and extract networks

[eLife 2020] "Comprehension of computer code relies primarily on domain-general executive brain regions" by Anna A. Ivanova, Shashank Srikant, Yotaro Sueoka, Hope H. Kean, Riva Dhamala, Una-May O'Reilly, Marina U. Bers, Evelina Fedorenko

Teaching materials for BayesCog workshop, UKE Hamburg (Part 2).

Example code accompanying the sternberg concept cell data release for Kyzar et al. (2024)

Critical review of neuroscientific insights on creativity, ideation, and problem-solving. Explores cognitive enhancement strategies and applications in innovation. Published on Zenodo with DOI: https://doi.org/10.5281/zenodo.13895946

Notes de cours pour PSY3018 - Méthodes en neurosciences cognitives