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References

Use this page for the literature behind the package and research program.

For implementation status per paper, see literature.md.

For BibTeX, see research/papers/_shared_assets/bibliography/references.bib.

The package implements and experiments with ideas from these papers; it should not be cited as the proof of the theory itself.

Tier 1 — Foundational Assembly Calculus

  • Papadimitriou, C. H., and Vempala, S. S. (2019). Random Projection in the Brain and Computation with Assemblies of Neurons. ITCS 2019. https://doi.org/10.4230/LIPIcs.ITCS.2019.57

  • Papadimitriou, C. H. (2019). A Calculus for Brain Computation. CCNeuro proceedings. https://ccneuro.org/2019/proceedings/0000998.pdf

  • Papadimitriou, C. H., Vempala, S. S., Mitropolsky, D., Collins, M., and Maass, W. (2020). Brain Computation by Assemblies of Neurons. PNAS, 117(25), 14464–14472. https://doi.org/10.1073/pnas.2001893117

  • Dabagia, M., Vempala, S. S., and Papadimitriou, C. H. (2022). Assemblies of Neurons Learn to Classify Well-Separated Distributions. COLT 2022 / arXiv:2110.03171. https://arxiv.org/abs/2110.03171

  • Dabagia, M., Papadimitriou, C. H., and Vempala, S. S. (2024/2025). Computation with Sequences of Assemblies in a Model of the Brain. ALT 2024 extended abstract; full version arXiv:2306.03812; journal version Neural Computation 37(1):193–233. https://arxiv.org/abs/2306.03812

Tier 2 — NEMO / Language / Cognition

  • Mitropolsky, D., Collins, M. J., and Papadimitriou, C. H. (2021). A Biologically Plausible Parser. TACL 9:1374–1388. https://doi.org/10.1162/tacl_a_00432

  • Mitropolsky, D., Ejaz, A., Shi, M., Yannakakis, M., and Papadimitriou, C. H. (2022). Center-Embedding and Constituency in the Brain and a New Characterization of Context-Free Languages. NALOMA III / arXiv:2206.13217. https://arxiv.org/abs/2206.13217

  • d'Amore, F., Mitropolsky, D., Crescenzi, P., Natale, E., and Papadimitriou, C. H. (2022). Planning with Biological Neurons and Synapses. AAAI 2022. https://doi.org/10.1609/aaai.v36i1.19875

  • Mitropolsky, D., and Papadimitriou, C. H. (2023). The Architecture of a Biologically Plausible Language Organ. arXiv:2306.15364. https://arxiv.org/abs/2306.15364

  • Dabagia, M., Mitropolsky, D., Papadimitriou, C. H., and Vempala, S. S. (2024). Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies. arXiv:2406.07715. https://arxiv.org/abs/2406.07715

  • Mitropolsky, D., and Papadimitriou, C. H. (2025). Simulated Language Acquisition in a Biologically Realistic Model of the Brain. arXiv:2507.11788. https://doi.org/10.48550/arXiv.2507.11788

Tier 3 — Field Extensions (2025–2026)

  • Onasch, S., Miehl, C., Miękus, M. M., and Gjorgjieva, J. (2025). Assembly-based Computations through Contextual Dendritic Gating of Plasticity. bioRxiv. https://doi.org/10.1101/2025.07.22.666089

  • Hoff, L., Soroka, G., Guimarães, M., Villavicencio, A., and Idiart, M. (2026). Formation of Artificial Neural Assemblies by Biologically Plausible Inhibition Mechanisms. arXiv:2603.12416. https://arxiv.org/abs/2603.12416

  • Ting, T. V., Sethu, V., and Dang, A. (2026). Beyond Deep Learning: Speech Segmentation and Phone Classification with Neural Assemblies. arXiv:2603.16923. https://arxiv.org/abs/2603.16923

  • Kopadi, E., and Kalles, D. (2026). Causal Learning with Neural Assemblies. arXiv:2604.26919. https://arxiv.org/abs/2604.26919

Reference Implementations

Neuroscience Foundations

  • Hebb, D. O. (1949). The Organization of Behavior: A Neuropsychological Theory. Wiley.

  • Buzsáki, G. (2010). Neural syntax: cell assemblies, synapsembles, and readers. Neuron, 68(3), 362–385.

  • Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. PNAS, 79(8), 2554–2558.

  • Olshausen, B. A., and Field, D. J. (1997). Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision Research, 37(23), 3311–3325.