All Publications

2022

CBMM Memo No.
137
A. Rangamani and Xie, Y., “Understanding the Role of Recurrent Connections in Assembly Calculus”. 2022.PDF icon CBMM-Memo-137.pdf (1.49 MB)
CBMM Funded
CBMM Memo No.
136
Y. Han, Poggio, T., and Cheung, B., “System identification of neural systems: If we got it right, would we know?”. 2022.PDF icon CBMM-Memo-136.pdf (1.75 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
K. Kar, “A computational probe into the behavioral and neural markers of atypical facial emotion processing in autism”, The Journal of Neuroscience, pp. JN-RM-2229-21, 2022.
CBMM Related
P. Nilchian, Wilson, M. A., and Sanders, H., “Animal-to-Animal Variability in Partial Hippocampal Remapping in Repeated Environments”, The Journal of Neuroscience, vol. 42, no. 26, pp. 5268 - 5280, 2022.PDF icon 5268.full_.pdf (2.97 MB)
CBMM Funded
A. Banburski and Rangamani, A., “Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay”, in IEEE International Conference on Acoustics, Speech and Signal Processing, Singapore, 2022.
CBMM Funded
K. Dobs, Martinez-Trujillo, J., Kell, A. J. E., and Kanwisher, N., “Brain-like functional specialization emerges spontaneously in deep neural networks”, Science Advances, vol. 8, no. 11, 2022.
CBMM Funded
CBMM Memo No.
134
T. Galanti and Poggio, T., “SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks”. 2022.PDF icon Implicit Rank Regularization.pdf (1.42 MB)
CBMM Funded
T. Galanti and Galanti, L., “On the Implicit Bias Towards Minimal Depth of Deep Neural Networks”, arXiv, 2022.PDF icon 2202.09028.pdf (2 MB)
CBMM Funded
F. S. Kamps, Richardson, H., N. Murty, A. Ratan, Kanwisher, N., and Saxe, R., “Using child‐friendly movie stimuli to study the development of face, place, and object regions from age 3 to 12 years”, Human Brain Mapping, 2022.
CBMM Related
Y. Li, Wang, Y. Q., Boger, T., Smith, K. A., Gershman, S. J., and Ullman, T., “An approximate representation of objects underlies physical reasoning”, psyArXiv, 2022.
CBMM Related
J. Zheng, Schjetnan, A. G. P., Yebra, M., Gomes, B. A., Mosher, C. P., Kalia, S. K., Valiante, T. A., Mamelak, A. N., Kreiman, G., and Rutishauser, U., “Neurons detect cognitive boundaries to structure episodic memories in humans”, Nature Neuroscience, vol. 25, no. 3, pp. 358 - 368, 2022.
CBMM Funded
CBMM Memo No.
121
M. Yamada, D'Amario, V., Takemoto, K., Boix, X., and Sasaki, T., “Transformer Module Networks for Systematic Generalization in Visual Question Answering”. 2022.PDF icon CBMM-Memo-121.pdf (1.06 MB)
CBMM Funded
M. Armendariz, Xiao, W., Vinken, K., and Kreiman, G., “Do computational models of vision need shape-based representations? Evidence from an individual with intriguing visual perceptions”, Cognitive Neuropsychology, pp. 1 - 3, 2022.
CBMM Funded
A. Bardon, Xiao, W., Ponce, C. R., Livingstone, M. S., and Kreiman, G., “Face neurons encode nonsemantic features”, Proceedings of the National Academy of Sciences, vol. 119, no. 16, 2022.
CBMM Funded
S. Madan, Henry, T., Dozier, J., Ho, H., Bhandari, N., Sasaki, T., Durand, F., Pfister, H., and Boix, X., “When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations”, Nature Machine Intelligence, vol. 4, no. 2, pp. 146 - 153, 2022.
CBMM Funded
S. V. Norman-Haignere, Feather, J., Boebinger, D., Brunner, P., Ritaccio, A., McDermott, J. H., Schalk, G., and Kanwisher, N., “A neural population selective for song in human auditory cortex”, Current Biology, 2022.PDF icon mmc2.pdf (9.52 MB)
CBMM Funded
CBMM Memo No.
119
A. Sakai, Sunagawa, T., Madan, S., Suzuki, K., Katoh, T., Kobashi, H., Pfister, H., Sinha, P., Boix, X., and Sasaki, T., “Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations”. 2022.PDF icon CBMM-Memo-119.pdf (31.08 MB)
CBMM Funded
L. A. Becker, Penagos, H., Flores, F. J., Manoach, D. S., Wilson, M. A., and Varela, C., “Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple DensityDataSheet1.docx”, Frontiers in Pharmacology, vol. 12, 2022.
CBMM Funded
S. Casper, Nadeau, M., and Kreiman, G., “One thing to fool them all: generating interpretable, universal, and physically-realizable adversarial features”, arXiv, 2022.PDF icon 2110.03605.pdf (6.7 MB)
CBMM Funded
A. Francl and McDermott, J. H., “Deep neural network models of sound localization reveal how perception is adapted to real-world environments”, Nature Human Behavior, vol. 6, pp. 111–133 , 2022.PDF icon s41562-021-01244-z.pdf (7.22 MB)
CBMM Funded
M. J. McPherson, Grace, R. C., and McDermott, J. H., “Harmonicity aids hearing in noise”, Attention, Perception, & Psychophysics, 2022.
CBMM Related
A. Sikarwar and Kreiman, G., “On the Efficacy of Co-Attention Transformer Layers in Visual Question Answering”, arXiv, 2022.PDF icon On_the_Efficacy_of_Co-Attention_Transformer_Layers.pdf (35.54 MB)
CBMM Funded
A. J. Thomas, Woo, B., Nettle, D., Spelke, E. S., and Saxe, R., “Early concepts of intimacy: Young humans use saliva sharing to infer close relationships”, Science, vol. 375, no. 6578, pp. 311 - 315, 2022.
CBMM Funded

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