All Publications

2024

D. Mendoza-Halliday, Xu, H., Azevedo, F. A. C., and Desimone, R., “Dissociable neuronal substrates of visual feature attention and working memory”, Neuron, vol. 112, no. 5, pp. 850 - 863.e6, 2024.
CBMM Related
D. Mendoza-Halliday, Major, A. James, Lee, N., Lichtenfeld, M. J., Carlson, B., Mitchell, B., Meng, P. D., Xiong, Y., Westerberg, J. A., Jia, X., Johnston, K. D., Selvanayagam, J., Everling, S., Maier, A., Desimone, R., Miller, E. K., and Bastos, A. M., “A ubiquitous spectrolaminar motif of local field potential power across the primate cortexAbstract”, Nature Neuroscience, vol. 27, no. 3, pp. 547 - 560, 2024.
CBMM Related

2023

Z. M. Aghajan, Kreiman, G., and Fried, I., “Minute-scale periodicity of neuronal firing in the human entorhinal cortex”, Cell Reports, vol. 42, no. 11, p. 113271, 2023.PDF icon 1-s2.0-S2211124723012834-main.pdf (5.33 MB)
CBMM Funded
P. Singh, Li, Y., Sikarwar, A., Lei, S. Weixian, Gao, D., Talbot, M. B., Sun, Y., Shou, M. Zheng, Kreiman, G., and Zhang, M., “ Learning to Learn: How to Continuously Teach Humans and Machines ”, in International Conference on Computer Vision (ICCV), 2023, Paris, France, 2023.
CBMM Funded
E. J. Bigelow, McCoy, J. P., and Ullman, T. D., “Non-commitment in mental imagery”, Cognition, vol. 238, p. 105498, 2023.
CBMM Funded
P. A. Feliciano-Ramos, Galazo, M., Penagos, H., and Wilson, M., “Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices”, Learning & Memory, vol. 30, no. 9, pp. 221 - 236, 2023.
CBMM Related
T. Bricken, Schaeffer, R., Olshausen, B., and Kreiman, G., “Emergence of Sparse Representations from Noise”, ICML 2023. Honolulu, HI, 2023.
CBMM Funded
C. Consortium, Ferrante, O., Gorska-Klimowska, U., Henin, S., Hirschhorn, R., Khalaf, A., Lepauvre, A., Liu, L., Richter, D., Vidal, Y., Bonacchi, N., Brown, T., Sripad, P., Armendariz, M., Bendtz, K., Ghafari, T., Hetenyi, D., Jeschke, J., Kozma, C., Mazumder, D. R., Montenegro, S., Seedat, A., Sharafeldin, A., Yang, S., Baillet, S., Chalmers, D. J., Cichy, R. M., Fallon, F., Panagiotaropoulos, T. I., Blumenfeld, H., de Lange, F. P., Devore, S., Jensen, O., Kreiman, G., Luo, H., Boly, M., Dehaene, S., Koch, C., Tononi, G., Pitts, M., Mudrik, L., and Melloni, L., “An adversarial collaboration to critically evaluate theories of consciousness”, bioRxiv, 2023.
CBMM Related
T. Bricken, Davies, X., Singh, D., Krotov, D., and Kreiman, G., “Sparse distributed memory is a continual learner”, International Conference on Learning Representations. Kigali, Rwanda, Africa, 2023.PDF icon 6086_sparse_distributed_memory_is_a.pdf (13.3 MB)
CBMM Funded
M. S. Tomov, Tsividis, P. A., Pouncy, T., Tenenbaum, J. B., and Gershman, S. J., “The neural architecture of theory-based reinforcement learning”, Neuron, vol. 111, no. 8, pp. 1331 - 1344.e8, 2023.
CBMM Funded
H. Azami, Moguilner, S., Penagos, H., Sarkis, R. A., Arnold, S. E., Gomperts, S. N., and Lam, A. D., “EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer’s Disease”, Journal of Alzheimer's Disease, vol. 91, no. 4, pp. 1557 - 1572, 2023.
CBMM Related
G. Kreiman, “Neural coding: Stimulating cortex to alter visual perception”, Current Biology, vol. 33, no. 3, pp. R117 - R118, 2023.
CBMM Funded
L. Melloni, Mudrik, L., Pitts, M., Bendtz, K., Ferrante, O., Gorska, U., Hirschhorn, R., Khalaf, A., Kozma, C., Lepauvre, A., Liu, L., Mazumder, D., Richter, D., Zhou, H., Blumenfeld, H., Boly, M., Chalmers, D. J., Devore, S., Fallon, F., de Lange, F. P., Jensen, O., Kreiman, G., Luo, H., Panagiotaropoulos, T. I., Dehaene, S., Koch, C., and Tononi, G., “An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory”, PLOS ONE, vol. 18, no. 2, p. e0268577, 2023.PDF icon journal.pone_.0268577.pdf (1.99 MB)
CBMM Related
R. Francesco Srinivasan, Mignacco, F., Sorbaro, M., Refinetti, M., Kreiman, G., and Dellaferrera, G., “Forward learning with top-down feedback: empirical and analytical characterization”, arXiv, 2023.
CBMM Funded
C. Wang, Subramaniam, V., Yaari, A. Uri, Kreiman, G., Katz, B., Cases, I., and Barbu, A., “BrainBERT: Self-supervised representation learning for Intracranial Electrodes”, International Conference on Learning Representations. Kigali, Rwanda, Africa, 2023.PDF icon 985_brainbert_self_supervised_repr.pdf (9.71 MB)
CBMM Funded
W. Xiao, Sharma, S., Kreiman, G., and Livingstone, M. S., “Out of sight, out of mind: Responses in primate ventral visual cortex track individual fixations during natural vision”, bioRxiv, 2023.
CBMM Funded
Z. Sage Chen and Wilson, M. A., “How our understanding of memory replay evolves”, Journal of Neurophysiology, vol. 129, no. 3, pp. 552 - 580, 2023.
CBMM Related
Y. Xiao, Chou, C. - C., Cosgrove, G. Rees, Crone, N. E., Stone, S., Madsen, J. R., Reucroft, I., Shih, Y. - C., Weisholtz, D., Yu, H. - Y., Anderson, W. S., and Kreiman, G., “Cross-task specificity and within-task invariance of cognitive control processes”, Cell Reports, vol. 42, no. 1, p. 111919, 2023.PDF icon PIIS2211124722018174.pdf (3.97 MB)
CBMM Funded
Y. Zhang, Aghajan, Z. M., Ison, M., Lu, Q., Tang, H., Kalender, G., Monsoor, T., Zheng, J., Kreiman, G., Roychowdhury, V., and Fried, I., “Decoding of human identity by computer vision and neuronal vision”, Scientific Reports, vol. 13, no. 1, 2023.PDF icon s41598-022-26946-w.pdf (1.88 MB)
CBMM Funded
Y. Zhang, Aghajan, Z. M., Ison, M., Lu, Q., Tang, H., Kalender, G., Monsoor, T., Zheng, J., Kreiman, G., Roychowdhury, V., and Fried, I., “Decoding of human identity by computer vision and neuronal visionAbstract”, Scientific Reports, vol. 13, no. 1, 2023.
CBMM Funded

2022

H. S. Wirtshafter and Wilson, M. A., “Artificial intelligence insights into hippocampal processing”, Frontiers in Computational Neuroscience, vol. 16, 2022.
CBMM Related
M. Zhang, Armendariz, M., Xiao, W., Rose, O., Bendtz, K., Livingstone, M., Ponce, C., and Kreiman, G., “Look twice: A generalist computational model predicts return fixations across tasks and species”, PLOS Computational Biology, vol. 18, no. 11, p. e1010654, 2022.PDF icon journal.pcbi_.1010654.pdf (4.51 MB)
CBMM Funded
S. Casper, Nadeau, M., Hadfield-Menell, D., and Kreiman, G., “Robust Feature-Level Adversaries are Interpretability Tools”, NeurIPS. New Orleans, Louisiana, 2022.PDF icon 8789_robust_feature_level_adversari.pdf (3.79 MB)
CBMM Funded
G. Dellaferrera and Kreiman, G., “Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass”, Proceedings of the 39th International Conference on Machine Learning, PMLR, vol. 162. pp. 4937-4955, 2022.PDF icon dellaferrera22a.pdf (909.91 KB)
CBMM Funded
N. Shaham, Chandra, J., Kreiman, G., and Sompolinsky, H., “Stochastic consolidation of lifelong memoryAbstract”, Scientific Reports, vol. 12, no. 1, 2022.PDF icon s41598-022-16407-9.pdf (2.54 MB)
CBMM Funded

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