Publication

Found 360 results
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2025
Pramod, R. T., Mieczkowski, E., Fang, C. X., Tenenbaum, J. B. & Kanwisher, N. Decoding predicted future states from the brain’s “physics engine”. Science Advances 11, (2025).
Bono, S. et al. The Indoor-Training Effect: unexpected gains from distribution shifts in the transition function. (2025). at <https://arxiv.org/abs/2401.15856>
Tiwary, K. et al. What if Eye..? Computationally Recreating Vision Evolution. arXiv (2025). at <https://arxiv.org/abs/2501.15001>PDF icon 2501.15001v1.pdf (5.2 MB)
2024
Madan, S. et al. Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex. NeurIPS 2024 (2024).
Mahowald, K. et al. Dissociating language and thought in large language models. Trends in Cognitive Sciences 28, 517 - 540 (2024).
Peters, B. et al. How does the primate brain combine generative and discriminative computations in vision?. arXiv (2024). at <https://arxiv.org/abs/2401.06005>
Peters, B. et al. How does the primate brain combine generative and discriminative computations in vision?. arXiv (2024). at <https://arxiv.org/abs/2401.06005>
2023
Melloni, L. et al. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 18, e0268577 (2023).PDF icon journal.pone_.0268577.pdf (1.99 MB)
Melloni, L. et al. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 18, e0268577 (2023).PDF icon journal.pone_.0268577.pdf (1.99 MB)
Melloni, L. et al. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 18, e0268577 (2023).PDF icon journal.pone_.0268577.pdf (1.99 MB)
Melloni, L. et al. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 18, e0268577 (2023).PDF icon journal.pone_.0268577.pdf (1.99 MB)
Consortium, C. et al. An adversarial collaboration to critically evaluate theories of consciousness. bioRxiv (2023). doi:https://doi.org/10.1101/2023.06.23.546249
Consortium, C. et al. An adversarial collaboration to critically evaluate theories of consciousness. bioRxiv (2023). doi:https://doi.org/10.1101/2023.06.23.546249
Consortium, C. et al. An adversarial collaboration to critically evaluate theories of consciousness. bioRxiv (2023). doi:https://doi.org/10.1101/2023.06.23.546249
Consortium, C. et al. An adversarial collaboration to critically evaluate theories of consciousness. bioRxiv (2023). doi:https://doi.org/10.1101/2023.06.23.546249
O'Connell, T. P. et al. Approaching human 3D shape perception with neurally mappable models. arXiv (2023). at <https://arxiv.org/abs/2308.11300>
Dobs, K., Yuan, J., Martinez, J. & Kanwisher, N. Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition. Proceedings of the National Academy of Sciences 120, (2023).
Wang, C. et al. BrainBERT: Self-supervised representation learning for Intracranial Electrodes. International Conference on Learning Representations (2023). at <https://openreview.net/forum?id=xmcYx_reUn6>PDF icon 985_brainbert_self_supervised_repr.pdf (9.71 MB)
Wang, C. et al. BrainBERT: Self-supervised representation learning for Intracranial Electrodes. International Conference on Learning Representations (2023). at <https://openreview.net/forum?id=xmcYx_reUn6>PDF icon 985_brainbert_self_supervised_repr.pdf (9.71 MB)
Zador, A. et al. Catalyzing next-generation Artificial Intelligence through NeuroAIAbstract. Nature Communications 14, (2023).
Zador, A. et al. Catalyzing next-generation Artificial Intelligence through NeuroAIAbstract. Nature Communications 14, (2023).
Kanwisher, N., Gupta, P. & Dobs, K. CNNs reveal the computational implausibility of the expertise hypothesis. iScience 26, 105976 (2023).
Xiao, Y. et al. Cross-task specificity and within-task invariance of cognitive control processes. Cell Reports 42, 111919 (2023).PDF icon PIIS2211124722018174.pdf (3.97 MB)
Zhang, Y. et al. Decoding of human identity by computer vision and neuronal vision. Scientific Reports 13, (2023).PDF icon s41598-022-26946-w.pdf (1.88 MB)
Zhang, Y. et al. Decoding of human identity by computer vision and neuronal vision. Scientific Reports 13, (2023).PDF icon s41598-022-26946-w.pdf (1.88 MB)

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