Tyler Bonnen
Memory and Learning; Sensation and Perception; Behavioral and Cognitive Neuroscience
Specific Research Areas
Computational models of perception and memory; Neuro-AI
Research Synopsis
Perception and memory are interlocking cognitive functions, yet they are often studied in isolation. My lab integrates methods from neuroscience, psychology, and computer science in order to develop unified perceptual-mnemonic models. By designing such "stimulus-computable" models (i.e., systems that process raw sensory data like humans do), we aim to formalize and evaluate theories of neural function that lead to more human-like computational models. Our goal is to develop models that operate at scale—explaining not experimental data, but the rich perceptual and memory abilities that are a hallmark of human intelligence.
I welcome graduate students from psychology, neuroscience, and computer science who are interested in interdisciplinary approaches to understanding the brain and behavior.
Asssistant Professor Tyler Bonnen will be considering new graduate students for admission for Fall 2026.
PhD, Computational Cognitive Neuroscience, Stanford University
Research Fellow, Department of Brain and Cognitive Sciences, MIT
BA, Comparative Literature & Chemistry, Columbia University
AA, Chemical Engineering, Miami Dade Community College
Bonnen, T., Yamins, D.L.K., & Wagner, A.D. (2021). When the ventral visual stream is not enough: A deep learning account of medial temporal lobe involvement in perception. Neuron
Bonnen, T., & Eldridge, M.A.G. (2023). Inconsistencies between human and macaque lesion data can be resolved with a stimulus-computable model of the ventral visual stream. eLife
Bonnen, T., Wagner, A.D., & Yamins, D.L.K. (2025). Medial temporal cortex supports compositional visual inferences. Cognition.
Bonnen, T., Fu, S., Bai, Y., O'Connell, T., Friedman, Y., Kanwisher, N., Tenenbaum, J.B., & Efros, A.A. (2024). Evaluating multiview object consistency in humans and image models. Neural Information Processing Systems (NeurIPS)
Stephanie Fu, Tyler Bonnen, Devin Guillory, Trevor Darrell (2025) Hidden in plain sight: VLMs overlook their visual representations, Conference on Language Modeling (COLM)
Justin Kerr, Kush Hari, Ethan Weber, Chung Min Kim, Brent Yi, Tyler Bonnen, Ken Goldberg, Angjoo Kanazawa (2025) Eye, Robot: Learning to Look to Act with a BC-RL Perception-Action Loop. Conference on Robot Learning (CORL)