Center for Theoretical Neuroscience

Displaying 1 - 26 of 26CSV
Zanni, G., van Dijk, M. T., Cagliostro, M. C., Sepulveda, P., Pini, N., Rose, A. L., Kesin, A. L., Lugo-Candelas, C., Goncalves, P. D., MacKay, A. S., Iigaya, K., Kulkarni, P., Ferris, C. F., Weissman, M. M., Talati, A., Ansorge, M. S., & Gingrich, J. A. (2025). Perinatal SSRI exposure impacts innate fear circuit activation and behavior in mice and humans. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-58785-4
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Sepúlveda, P., Aitsahalia, I., Kumar, K., Atkin, T., & Iigaya, K. (2025). Addressing Altered Anticipation as a Transdiagnostic Target through Computational Psychiatry. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. https://doi.org/10.1016/j.bpsc.2025.02.014
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Perkins, S. M., Amematsro, E. A., Cunningham, J., Wang, Q., & Churchland, M. M. (2025). An emerging view of neural geometry in motor cortex supports high-performance decoding. ELife, 12. CLOCKSS. https://doi.org/10.7554/elife.89421
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Di Santo, S., Dipoppa, M., Keller, A., Roth, M., Scanziani, M., & Miller, K. D. (2025). Contextual modulation emerges by integrating feedforward and feedback processing in mouse visual cortex. Cell Reports, 44(1), 115088. https://doi.org/10.1016/j.celrep.2024.115088
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Xia, F., Fascianelli, V., Vishwakarma, N., Ghinger, F. G., Kwon, A., Gergues, M. M., Lalani, L. K., Fusi, S., & Kheirbek, M. A. (2024). Understanding the neural code of stress to control anhedonia. Nature. https://doi.org/10.1038/s41586-024-08241-y
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Iigaya, K., Larsen, T., Fong, T., & O’Doherty, J. P. (2024). Computational and neural evidence for altered fast and slow learning from losses in problem gambling. The Journal of Neuroscience, e0080242024. https://doi.org/10.1523/jneurosci.0080-24.2024
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Fascianelli, V., Battista, A., Stefanini, F., Tsujimoto, S., Genovesio, A., & Fusi, S. (2024). Neural representational geometries reflect behavioral differences in monkeys and recurrent neural networks. Nature Communications, 15(1). https://doi.org/10.1038/s41467-024-50503-w
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Lippl, S., Kay, K., Jensen, G., Ferrera, V. P., & Abbott, L. F. (2024). A mathematical theory of relational generalization in transitive inference. Proceedings of the National Academy of Sciences, 121(28). https://doi.org/10.1073/pnas.2314511121
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Holt, C. J., Miller, K. D., & Ahmadian, Y. (2024). The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. PLOS Computational Biology, 20(6), e1012190. https://doi.org/10.1371/journal.pcbi.1012190
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Kay, K., Biderman, N., Khajeh, R., Beiran, M., Cueva, C. J., Shohamy, D., Jensen, G., Wei, X.-X., Ferrera, V. P., & Abbott, L. (2024). Emergent neural dynamics and geometry for generalization in a transitive inference task. PLOS Computational Biology, 20(4), e1011954. https://doi.org/10.1371/journal.pcbi.1011954
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Goris, R. L. T., Coen-Cagli, R., Miller, K. D., Priebe, N. J., & Lengyel, M. (2024). Response sub-additivity and variability quenching in visual cortex. Nature Reviews Neuroscience, 25(4), 237–252. https://doi.org/10.1038/s41583-024-00795-0
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Sanzeni, A., Palmigiano, A., Nguyen, T. H., Luo, J., Nassi, J. J., Reynolds, J. H., Histed, M. H., Miller, K. D., & Brunel, N. (2023). Mechanisms underlying reshuffling of visual responses by optogenetic stimulation in mice and monkeys. Neuron, 111(24), 4102-4115.e9. https://doi.org/10.1016/j.neuron.2023.09.018
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Iigaya, K., Yi, S., Wahle, I. A., Tanwisuth, S., Cross, L., & O’Doherty, J. P. (2023). Neural mechanisms underlying the hierarchical construction of perceived aesthetic value. Nature Communications, 14(1). https://doi.org/10.1038/s41467-022-35654-y
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Marshall, N. J., Glaser, J. I., Trautmann, E. M., Amematsro, E. A., Perkins, S. M., Shadlen, M. N., Abbott, L. F., Cunningham, J. P., & Churchland, M. M. (2022). Flexible neural control of motor units. Nature Neuroscience, 25(11), 1492–1504. https://doi.org/10.1038/s41593-022-01165-8
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Abe, T., Kinsella, I., Saxena, S., Buchanan, E. K., Couto, J., Briggs, J., Kitt, S. L., Glassman, R., Zhou, J., Paninski, L., & Cunningham, J. P. (2022). Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis. Neuron, 110(17), 2771-2789.e7. https://doi.org/10.1016/j.neuron.2022.06.018
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Penner, C., Minxha, J., Chandravadia, N., Mamelak, A. N., & Rutishauser, U. (2022). Properties and hemispheric differences of theta oscillations in the human hippocampus. Hippocampus, 32(5), 335–341. Portico. https://doi.org/10.1002/hipo.23412
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Schmidt, E. R. E., Zhao, H. T., Park, J. M., Dipoppa, M., Monsalve-Mercado, M. M., Dahan, J. B., Rodgers, C. C., Lejeune, A., Hillman, E. M. C., Miller, K. D., Bruno, R. M., & Polleux, F. (2021). A human-specific modifier of cortical connectivity and circuit function. Nature, 599(7886), 640–644. https://doi.org/10.1038/s41586-021-04039-4
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Whiteway, M. R., Biderman, D., Friedman, Y., Dipoppa, M., Buchanan, E. K., Wu, A., Zhou, J., Bonacchi, N., Miska, N. J., Noel, J.-P., Rodriguez, E., Schartner, M., Socha, K., Urai, A. E., Salzman, C. D., Cunningham, J. P., & Paninski, L. (2021). Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. PLOS Computational Biology, 17(9), e1009439. https://doi.org/10.1371/journal.pcbi.1009439
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Tekieli, T., Yemini, E., Nejatbakhsh, A., Wang, C., Varol, E., Fernandez, R. W., Masoudi, N., Paninski, L., & Hobert, O. (2021). Visualizing the organization and differentiation of the male-specific nervous system of C. elegans. Development. https://doi.org/10.1242/dev.199687
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