NEMO is a mathematical and computational model of the brain, meant to provide a concrete hypothesis as to how complex cognition can arise from the activity of neurons. Its exploration and development is an ongoing project, initiated by Christos Papadimitriou, Santosh Vempala, Max Dabagia, and Dan Mitropolsky.

This website outlines the NEMO model and collects the main results related to it. NEMO is far from a complete explanation about how intelligence arises from the brain, and is best considered a set of core assumptions that will likely be expanded in the future to yield a model that could genuinely explain cognition.

The content of this site draws from several papers (in chronological order):

• Christos Papadimitriou & Santosh Vempala: “Random Projection in the Brain and Computation with Assemblies of Neurons.” 10th Innovations in Theoretical Computer Science (2019).
• Christos Papadimitriou, Santosh Vempala, Daniel Mitropolsky, Michael Collins, & Wolfgang Maass: “Brain computation by assemblies of neurons.” Proceedings of the National Academy of Sciences (2020).
• Max Dabagia, Christos Papadimitriou, & Santosh Vempala: “Assemblies of neurons learn to classify well-separated distributions.” Conference on Learning Theory, PMLR (2022).
• Daniel Mitropolsky, Michael Collins, & Christos H. Papadimitriou: “A biologically plausible parser.” Transactions of the Association for Computational Linguistics (2021).
• Daniel Mitropolsky, Adiba Ejaz, Mirah Shi, Mihalis Yannakakis, & Christos Papadimitriou: “Center-embedding and constituency in the brain and a new characterization of context-free languages.” arXiv (2022).
• Francesco d’Amore, Daniel Mitropolsky, Pierluigi Crescenzi, Emanuele Natale, & Christos Papadimitriou: “Planning with biological neurons and synapses.” AAAI (2022).
• Daniel Mitropolsky & Christos Papadimitriou: “The Architecture of a Biologically Plausible Language Organ.” arXiv (2023).
• Max Dabagia, Christos Papadimitriou, Santosh Vempala: “Computation with Sequences of Assemblies in a Model of the Brain.” International Conference on Algorithmic Learning (2024); Neural Computation (2025).
• Max Dabagia, Daniel Mitropolsky, Christos Papadimitriou, & Santosh Vempala: “Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies.” arXiv (2024).