Information and Integration lab

Overview

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

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.

Uri Hasson, Principal Investigator
Le Minh Nhut Truong (PhD student)
Dario Pesenti (previously intern, now PhD student CIMeC with prof. Stefano Teso)
Icaro Re Depaolini (Master's student)
Stella Fritz (Master's student)
Daniil Kirillov (Master's student)
Gerrit Sanders (intern)
Pooya Varnoosfaderaniv (previously intern)
Giulia Lund (previously intern)
Natalia Flechas Manrique (previously intern)
Anna Bavaresco (previously Master's student, now PhD student Uni. Amsterdam)
Priya Tarigopula (previously Master's student, now PhD student Uni. Oslo)

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

Bavaresco, A., Truong, N., & Hasson, U. (2025). Modeling human concepts with subspaces in deep vision models. ACM Transactions on Interactive Intelligent Systems.
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).

Dr. Howard Nusbaum; the University of Chicago