All Publications

2019

C. R. Ponce, Xiao, W., Schade, P. F., Hartmann, T. S., Kreiman, G., and Livingstone, M. S., “Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences”, Cell , vol. 177, p. 1009, 2019.PDF icon Author's last draft (20.26 MB)
CBMM Funded

2018

S. Hu, Ciliberti, D., Grosmark, A. D., Michon, édéric, Ji, D., Penagos, H., áki, örgy, Wilson, M. A., Kloosterman, F., and Chen, Z., “Real-Time Readout of Large-Scale Unsorted Neural Ensemble Place Codes”, Cell Reports, vol. 25, no. 10, pp. 2635 - 2642.e5, 2018.
CBMM Funded
P. Misra, Marconi, A., Peterson, M. F., and Kreiman, G., “Minimal memory for details in real life events”, Scientific Reports, vol. 8, no. 1, 2018.
CBMM Funded
R. Madhavan, Bansal, A. K., Madsen, J., Golby, A. J., Tierney, T. S., Eskandar, E., Anderson, W. S., and Kreiman, G., “Neural Interactions Underlying Visuomotor Associations in the Human Brain”, Cerebral Cortex, vol. 1–17, 2018.
CBMM Funded
L. Isik, Singer, J., Kanwisher, N., ,, WS, A., and Kreiman, G., “What is changing when: decoding visual information in movies from human intracranial recordings”, NeuroImage, vol. 180, Part A, pp. 147-159, 2018.PDF icon Human neurophysiological responses during movies (2.78 MB)
CBMM Funded
M. Zhang, Feng, J., Ma, K. Teck, Lim, J. Hwee, Zhao, Q., and Kreiman, G., “Finding any Waldo with zero-shot invariant and efficient visual search”, Nature Communications, vol. 9, 2018.
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., “Comparing human and monkey neural circuits for processing social scenes”, Organization for Computational Neurosciences - CNS 2018. Seattle, WA, 2018.
CBMM Related
H. Tang, Schrimpf, M., Lotter, W., Moerman, C., Paredes, A., Caro, J. Ortega, Hardesty, W., Cox, D., and Kreiman, G., “Recurrent computations for visual pattern completion”, Proceedings of the National Academy of Sciences, 2018.PDF icon 1719397115.full_.pdf (1.1 MB)
CBMM Funded
CBMM Memo No.
096
M. Zhang, Feng, J., Lim, J. Hwee, Zhao, Q., and Kreiman, G., “What am I searching for?”. 2018.PDF icon CBMM-Memo-096.pdf (1.74 MB)
CBMM Funded
A. Palepu and Kreiman, G., “Development of automated interictal spike detector”, 40th International Conference of the IEEE Engineering in Medicine and Biology Society - EMBC 2018. Honolulu, HI, 2018.
CBMM Funded
W. Eric, Kevin, W., and Kreiman, G., “Learning scene gist with convolutional neural networks to improve object recognition”, 2018 52nd Annual Conference on Information Sciences and Systems (CISS). Princeton, NJ, 2018.PDF icon 08362305.pdf (3.17 MB)
CBMM Funded
W. Lotter, Kreiman, G., and Cox, D., “A neural network trained to predict future videoframes mimics critical properties of biologicalneuronal responses and perception”, arXiv | Cornell University, arXiv:1805.10734v2, 2018.PDF icon 1805.10734.pdf (9.59 MB)
CBMM Funded
J. Sliwa, Marvel, S. R., Ianni, G. A., and Freiwald, W. A., “Comparing human and monkey neural circuits for processing social scenes”, Social & Affective Neuroscience Society (SANS). Brooklyn, NY , 2018.
CBMM Related
I. Yildirim, Freiwald, W. A., and J., T., “Efficient inverse graphics in biological face processing”, bioRxiv. 2018.
CBMM Funded
K. Wu, Wu, E., and Kreiman, G., “Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition”, arXiv | Cornell University, vol. arXiv:1803.01967, 2018.
CBMM Funded
D. Muir, Fang, X., and Meyers, E., “Brain-Observatory-Toolbox”. 2018.
CBMM Funded
N. Dehghani and Wimmer, R., “A computational perspective of the role of Thalamus in cognition”, arxiv, 2018.PDF icon ThalamusComputationArxiv.pdf (5.12 MB)
CBMM Related
L. Isik, Tacchetti, A., and Poggio, T., “A fast, invariant representation for human action in the visual system”, Journal of Neurophysiology, 2018.
CBMM Funded
M. Schrimpf and Kubilius, J., “Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?”, bioRxiv preprint, 2018.PDF icon Brain-Score bioRxiv.pdf (789.83 KB)
CBMM Related

2017

M. L. Leavitt, Mendoza-Halliday, D., and J.C., M. - T., “Sustained Activity Encoding Working Memories: Not Fully Distributed”, Trends in Neurosciences , vol. 40 , no. 6, pp. 328-346, 2017.
CBMM Related
D. Mendoza-Halliday and Martinez-Trujillo, J., “Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex”, Nature Communications, vol. 8, 2017.
CBMM Related
N. Grossman, Bono, D., Dedic, N., Kodandaramaiah, S. B., Rudenko, ii, A., Suk, H. - J., Cassara, A., Neufeld, E., Kuster, N., Tsai, L. - H., Pascual-Leone, A., and Boyden, E. S., “Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields”, Cell, vol. 169, no. 6, pp. 1029 - 1041.e16, 2017.
CBMM Funded
M. Janner, Wu, J., Kulkarni, T., Yildirim, I., and Tenenbaum, J. B., “Self-supervised intrinsic image decomposition.”, in Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, 2017.PDF icon intrinsicImg_nips_2017.pdf (5.87 MB)
CBMM Funded
E. Meyers, Riley, M., Qi, X. - L., and Constantinidis, C., “Differences in dynamic and static coding within different subdivision of the prefrontal cortex”, Society for Neuroscience's Annual Meeting - SfN 2017. Washington, DC, 2017.
CBMM Funded
E. Meyers, Liang, A., Katsuki, F., and Constantinidis, C., “Differential Processing of Isolated Object and Multi-item Pop-Out Displays in LIP and PFC.”, Cerebral Cortex, 2017.
CBMM Funded

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