Resources
This project is committed to open science and the broad dissemination of its results. All developed methods, code, and relevant resources will be made publicly available to support transparency, reproducibility, and further research.
Code
The project will release open-source implementations of the developed algorithms for analysing neural representations in deep learning models. These tools will include detailed documentation and examples to facilitate their use by researchers and practitioners.
Data
Where applicable, the project will rely on publicly available datasets, including large-scale biological neural recordings and standard machine learning benchmarks. Processed data and derived results will be shared in accordance with open science and data management principles.
Documentation
& tutorials
To encourage adoption, the project will provide accessible documentation and tutorials explaining how to use the developed tools and how to interpret their outputs.
Funded by the European Union under the Horizon Europe research and innovation programme.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No 211063187