Overview | Research Directions | Members | Publications | Ongoing collaborations | Web


We have a broad interest in higher-level brain functions, their relation to lower-level computations, and the role of context.

Research Directions

  • Study of relation between knowledge represented in neural networks and knowledge in humans;
  • uncertainty and predictive processes: what are the principles that organize the brain’s responses to uncertainty, and how these support predictive processes;
  • neurobiology of language: organization and interactions between brain systems that support language comprehension.



For a complete list see Uri Hasson personal page

Master's students (in bold) are first authors and co-authors on these two recent publications:

  • Flechas, M. N., & Bao, W., Herbelot, A., & Hasson, U. (2023). Enhancing Interpretability using human similarity judgements to prune word embeddings. Full paper presented at BlackboxNLP (EMNLP2023).
  • Tarigopula, P., Fairhall, S., & Bavaresco, A., & Truong, N., & Hasson, U. (2023). Improved prediction of behavioral and neural similarity spaces using pruned DNNs. Neural Networks, 168.
  • Bao, W., & Hasson, U. (2024). Identifying and interpreting non-aligned human conceptual representations using language modeling. Full paper presented at ICLR 2024 Workshop on Representational Alignment.
  • Truong, N., Pesenti, D., & Hasson, U. (2024). Explaining human comparisons using alignment-importance heatmaps. Full paper presented at ICLR 2024 Workshop on Representational Alignment.

Two Master's students contributed to this granted Patent application:

  • Metodo e mezzi per la produzione di sequenze a livelli richiesti di interessantezza / Hasson, Uri; Notaro, Giuseppe; Eperon, Alexander Charles Leslie; Sartorato, Nicola; Minati, Ludovico. - (2024).

Ongoing collaborations

Dr. Howard Nusbaum; the University of Chicago


Research group webpage