The DiCarlo Lab at MIT

Publications

2024
Benjamin Peters
James J. DiCarlo
Todd Gureckis
Ralf Haefner
Leyla Isik
Joshua Tenenbaum
Talia Konkle
Thomas Naselaris
Kimberly Stachenfeld
Zenna Tavares
Doris Tsao
Ilker Yildirim
Nikolaus Kriegeskorte
How does the primate brain combine generative and discriminative computations in vision?

https://arxiv.org/pdf/2401.06005.pdf

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Abstract: How does the primate brain combine generative and discriminative computations in vision?

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2024
Xie, Yudi
Alter, Esther
Schwartz, Jeremy
DiCarlo, James J.
Learning only a handful of latent variables produces neural-aligned CNN models of the ventral stream

Computational and Systems Neuroscience (COSYNE)

https://hdl.handle.net/1721.1/153744

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Abstract: Learning only a handful of latent variables produces neural-aligned CNN models of the ventral stream

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2024
DiCarlo, James
Bashivan, Pouya
Kar, Kohitij
Software and Methods for Controlling Neural Responses in Deep Brain Regions

https://patents.google.com/patent/US20240082534A1/en

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Abstract: Software and Methods for Controlling Neural Responses in Deep Brain Regions

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2024
Margalit, Eshed
Lee, Hyodong
Finzi, Dawn
DiCarlo, James J.
Grill-Spector, Kalanit
Yamins, Daniel L K
A unifying framework for functional organization in early and higher ventral visual cortex

Neuron

https://linkinghub.elsevier.com/retrieve/pii/S0896627324002794

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Abstract: A unifying framework for functional organization in early and higher ventral visual cortex
2024
Ferguson, Michael E.
Jerry Ngo
Lee, Michael J.
James J. DiCarlo
Martin Schrimpf
How Well is Visual Search Asymmetry predicted by a Binary-Choice, Rapid, Accuracy-based Visual-search, Oddball-detection (BRAVO) task?.

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Abstract: How Well is Visual Search Asymmetry predicted by a Binary-Choice, Rapid, Accuracy-based Visual-search, Oddball-detection (BRAVO) task?.
2023
Lee, Michael J.
DiCarlo, James J.
An empirical assay of view-invariant object learning in humans and comparison with baseline image-computable models

bioRxiv

https://www.biorxiv.org/content/biorxiv/early/2023/01/02/2022.12.31.522402.full.pdf

Google Scholar
Abstract: An empirical assay of view-invariant object learning in humans and comparison with baseline image-computable models
2023
Zador, Anthony
Escola, Sean
Richards, Blake
Ölveczky, Bence
Bengio, Yoshua
Boahen, Kwabena
Botvinick, Matthew
Chklovskii, Dmitri
Churchland, Anne
Clopath, Claudia
DiCarlo, James
Ganguli, Surya
Hawkins, Jeff
örding, Konrad
Koulakov, Alexei
LeCun, Yann
Lillicrap, Timothy
Marblestone, Adam
Olshausen, Bruno
Pouget, Alexandre
Savin, Cristina
Sejnowski, Terrence
Simoncelli, Eero
Solla, Sara
Sussillo, David
Tolias, Andreas S.
Tsao, Doris
Catalyzing next-generation Artificial Intelligence through NeuroAI

Nature Communications

https://www.nature.com/articles/s41467-023-37180-xhttps://www.nature.com/articles/s41467-023-37180-x.pdfhttps://www.nature.com/articles/s41467-023-37180-x.pdfhttps://www.nature.com/articles/s41467-023-37180-x

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Abstract: Catalyzing next-generation Artificial Intelligence through NeuroAI

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2023
Gaziv, Guy
Lee, Michael J.
DiCarlo, James J.
Robustified ANNs Reveal Wormholes Between Human Category Percepts

arXiv

https://arxiv.org/pdf/2308.06887.pdf

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Abstract: Robustified ANNs Reveal Wormholes Between Human Category Percepts

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2023
Margalit, Eshed
Lee, Hyodong
Finzi, Dawn
DiCarlo, James J.
Grill-Spector, Kalanit
Yamins, Daniel LK
A Unifying Principle for the Functional Organization of Visual Cortex

bioRxiv

https://www.biorxiv.org/content/10.1101/2023.05.18.541361v1.full.pdf

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Abstract: A Unifying Principle for the Functional Organization of Visual Cortex

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2023
Mieczkowski, Elizabeth
Abate, Alex
De Faria, Willian
Lydic, Kirsten
DiCarlo, James
Kanwisher, Nancy
Apurva Ratan Murty, N.
fROI-level computational models enable broad-scale experimental testing and expose key divergences between models and brains

Journal of Vision

https://doi.org/10.1167/jov.23.9.5788

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Abstract: fROI-level computational models enable broad-scale experimental testing and expose key divergences between models and brains
2023
Gaziv, Guy
Lee, Michael J.
DiCarlo, James J.
Strong and Precise Modulation of Human Percepts via Robustified ANNs

Neural Information Processing Systems

https://openreview.net/pdf?id=5GmTI4LNqX

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Abstract: Strong and Precise Modulation of Human Percepts via Robustified ANNs

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2023
DiCarlo, James J.
Yamins, Daniel L K
Ferguson, Michael E.
Fedorenko, Evelina
Bethge, Matthias
Bonnen, Tyler
Schrimpf, Martin
Let’s move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human visionAbstract

Behavioral and Brain Sciences

https://www.cambridge.org/core/product/identifier/S0140525X23001607/type/journal_article

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Abstract: Let’s move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human visionAbstract

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2023
Kohitij Kar
James J. DiCarlo
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates

arXiv

https://arxiv.org/pdf/2312.05956.pdf

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Abstract: The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates

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2023
Michael Kuoch
Chi-Ning Chou
Nikhil Parthasarathy
Joel Dapello
James J. DiCarlo
Haim Sompolinsky
Sueyeon Chung
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds

Conference on Parsimony and Learning (Proceedings Track)

https://openreview.net/forum?id=MxBS6aw5Gd

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Abstract: Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds

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2023
Lee, Michael J.
DiCarlo, James J.
Kietzmann, Tim Christian
How well do rudimentary plasticity rules predict adult visual object learning?

PLOS Computational Biology

https://dx.plos.org/10.1371/journal.pcbi.1011713

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Abstract: How well do rudimentary plasticity rules predict adult visual object learning?

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2023
DiCarlo, James J.
Lee, Michael J.
Kietzmann, Tim Christian
How well do rudimentary plasticity rules predict adult visual object learning?

PLOS Computational Biology

https://dx.plos.org/10.1371/journal.pcbi.1011713

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Abstract: How well do rudimentary plasticity rules predict adult visual object learning?

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2022
Geiger, Franziska
Schrimpf, Martin
Marques, Tiago
DiCarlo, James J.
Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream

International Conference on Learning Representations 2022 Spotlight

https://openreview.net/pdf?id=g1SzIRLQXMM

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Abstract: Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream

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2022
Guo, Chong
Lee, Michael J.
Leclerc, Guillaume
Dapello, Joel
Rao, Yug
Madry, Aleksander
DiCarlo, James J.
Adversarially trained neural representations may already be as robust as corresponding biological neural representations

arXiv

https://arxiv.org/abs/2206.11228v1

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Abstract: Adversarially trained neural representations may already be as robust as corresponding biological neural representations

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2022
Dapello, Joel
Kar, Kohitij
Schrimpf, Martin
Geary, Robert
Ferguson, Michael
Cox, David D.
DiCarlo, James J.
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness

bioRxiv

https://www.biorxiv.org/content/10.1101/2022.07.01.498495v1.full.pdf

Google Scholar
Abstract: Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness
2022
Bagus, Ayu Marliawaty I Gusti
Marques, Tiago
Sanghavi, Sachi
DiCarlo, James J.
Schrimpf, Martin
Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units

SVHRM Workshop at Neural Information Processing Systems (NeurIPS)

https://openreview.net/pdf?id=iPF7mhoWkOl

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Abstract: Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units

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