An approach for integrating the wealth of heterogeneous brain data — from gene expression and neurotransmitter receptor density to structure and function — allows neuroscientists to easily place their data within the broader neuroscientific context.
References
Markello, R. D. et al. Nat. Methods https://doi.org/10.1038/s41592-022-01625-w (2022).
Fornito, A., Arnatkevičiūtė, A. & Fulcher, B. D. Trends Cogn. Sci. 23, 34–50 (2019).
Kopell, N. J., Gritton, H. J., Whittington, M. A. & Kramer, M. A. Neuron 83, 1319–1328 (2014).
Jonas, E. & Kording, K. PLOS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1005268 (2017).
Churchland, P. S. & Sejnowski, T. J. Nat. Rev. Neurosci. 17, 667–668 (2016).
Halevy, A., Norvig, P. & Pereira, F. IEEE Intell. Syst. 24, 8–12 (2009).
Beam, E., Potts, C., Poldrack, R. A. & Etkin, A. Nat. Neurosci. https://doi.org/10.1038/s41593-021-00948-9 (2021).
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C. & Wager, T. D. Nat. Methods 8, 665–670 (2011).
Voytek, J. B. & Voytek, B. J. Neurosci. Methods 208, 92–100 (2012).
Voytek, B. PLOS Comput. Biol. 12, e1005037 (2016).
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B.V. is supported by National Institute of General Medical Sciences grant R01GM134363.
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Voytek, B. The data science future of neuroscience theory. Nat Methods 19, 1349–1350 (2022). https://doi.org/10.1038/s41592-022-01630-z
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DOI: https://doi.org/10.1038/s41592-022-01630-z
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