Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Papers from the intersection of deep learning and neuroscience
| Date | Stars |
|---|---|
| 2026-07-31 | 448 |
| 2026-08-06 | 450 |
Today
+2 stars today
This week
— stars this week
This month
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Momentum
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growth rate 0.00%/day
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# Awesome NeuroAI Papers [](https://github.com/sindresorhus/awesome)
> A curated list of [Papers](https://github.com/CYHSM/awesome-neuro-ai-papers#papers) & [Reviews](https://github.com/CYHSM/awesome-neuro-ai-papers#reviews) from the intersection of deep learning and neuroscience
This list is providing an overview of recent publications connecting neuroscience & computer science research. As both fields are growing rapidly this list is only presenting a small subset of relevant papers. In case important papers are missing please send a [pull request](https://github.com/CYHSM/awesome-neuro-ai-papers/pulls).
# Papers
Pesnot Lerousseau, J., & Summerfield, C. [**Shared sensitivity to data distribution during learning in humans and transformer networks**](https://www.nature.com/articles/s41562-025-02359-3) Nature Human Behaviour (2025)
d'Ascoli, S., Rapin, J., Benchetrit, Y., Banville, H., & King, J. R. [**TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction**](https://www.arxiv.org/abs/2507.22229) arXiv (2025)
Evanson, L., Bulteau, C., Chipaux, M., Dorfmüller, G., Ferrand-Sorbets, S., Raffo, E., Rosenberg, S., Bourdillon, P., King, J. R. [**Emergence of Language in the Developing Brain**](https://ai.meta.com/research/publications/emergence-of-language-in-the-developing-brain/) arXiv (2025)
Granier, A., & Senn, W. [**Multihead self-attention in cortico-thalamic circuits**](https://arxiv.org/abs/2504.06354) arXiv (2025)
Hagendorff, T., Dasgupta, I., Binz, M., Chan, S. C., Lampinen, A., Wang, J. X., ... & Schulz, E. [**Machine psychology**](https://arxiv.org/abs/2303.13988) arXiv (2025)
Banville, H., Benchetrit, Y., d'Ascoli, S., Rapin, J., & King, J. R. [**Scaling laws for decoding images from brain activity**](https://arxiv.org/abs/2501.15322) arXiv (2025)
AlKhamissi, B., Tuckute, G., Bosselut, A., & Schrimpf, M. [**The LLM Language Network: A neuroscientific approach for identifying causally task-relevant units**](https://arxiv.org/abs/2411.02280) arXiv (NAACL 2025)
Rathi, N., Mehrer, J., AlKhamissi, B., Binhuraib, F. S., Blauch, N. M., Pienkowski, M., & Schrimpf, M. [**TopoLM: Brain-Like Spatio-Functional Organization in a Topographic Language Model**](https://arxiv.org/abs/2410.11516) arXiv (ICLR 2025)
Yu, M., Wang, D., Shan, Q., & Wan, A. [**The super weight in large language models**](https://arxiv.org/abs/2411.07191) arXiv (2024)
Mineault, P., Baset, Z. A., Bena, J., Berent, I., Broad, A., Deo, R., ... & Zador, A. [**NeuroAI for AI Safety**](https://arxiv.org/abs/2411.18526) arXiv (2024)
Hwang, J., Hong, Z.-W., Chen, E. R., Boopathy, A., Agrawal, P., & Fiete, I. R. [**Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building**](https://arxiv.org/html/2307.05793v3) arXiv (2024)
Bricken, T., Templeton, A., Batson, J., Chen, B., Jermyn, A., Conerly, T., ... & Olah, C. [**Towards monosemanticity: Decomposing language models with dictionary learning**](https://transformer-circuits.pub/2023/monosemantic-features/index.html) Transformer Circuits Thread (2023)
Veerabadran, V., Goldman, J., Shankar, S., Cheung, B., Papernot, N., Kurakin, A., ... & Elsayed, G. F. [**Subtle adversarial image manipulations influence both human and machine perception**](https://www.nature.com/articles/s41467-023-40499-0) Nature Communications (2023)
Spieler, A., Rahaman, N., Martius, G., Schölkopf, B., & Levina, A. [**The ELM Neuron: an Efficient and Expressive Cortical Neuron Model Can Solve Long-Horizon Tasks**](https://arxiv.org/pdf/2306.16922.pdf) arXiv (2023)
Schneider, S., Lee, J. H., & Mathis, M. W. [**Learnable latent embeddings for joint behavioral and neural analysis**](https://arxiv.org/abs/2204.00673) arXiv (2022)
Raju, R. V., Guntupalli, J. S., Zhou, G., Lázaro-Gredilla, M., & George, D. [**SpaceExcerpt of 25,866 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:5f39d84e4d76ec86, llm:description: 'Papers from the intersection of deep learning and neuroscience' (curated list of papers)
matched fp:5f39d84e4d76ec86, llm:description: 'Papers from the intersection of deep learning and neuroscience' (curated list of papers)
matched fp:5f39d84e4d76ec86, llm:description: 'Papers from the intersection of deep learning and neuroscience' (curated list of papers)
matched fp:5f39d84e4d76ec86, llm:description: 'Papers from the intersection of deep learning and neuroscience' (curated list of papers)