The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
The BRAIN Initiative: developing technology to catalyse neuroscience discovery
Open accessAbstract
The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions.
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Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.
Kwong, K. K., Belliveau, J. W., Chesler, D. A., Goldberg, I. E., Weisskoff, R. M., Poncelet, B. P., Kennedy, D. N., Hoppel, B. E., Cohen, M. S., & Turner, R. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5675 · Cited by 4,212
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295
Self-citationStructural and molecular interrogation of intact biological systems
Chung, K., Wallace, J., Kim, S.-Y., Kalyanasundaram, S., Andalman, A. S., Davidson, T. J., Mirzabekov, J. J., Zalocusky, K. A., Mattis, J., Denisin, A. K., et al. (2013) · Nature · doi:10.1038/nature12107 · Cited by 2,008
Self-citationThe development and application of optogenetics
Fenno, L., Yizhar, O., & Deisseroth, K. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113817 · Cited by 1,822
Self-citationLong-term dynamics of CA1 hippocampal place codes
Ziv, Y., Burns, L. D., Cocker, E. D., Hamel, E. O., Ghosh, K. K., Kitch, L. J., Gamal, A. E., & Schnitzer, M. J. (2013) · Nature Neuroscience · doi:10.1038/nn.3329 · Cited by 1,155
Self-citationConnectomic reconstruction of the inner plexiform layer in the mouse retina
Helmstaedter, M., Briggman, K. L., Turaga, S. C., Jain, V., Seung, H. S., & Denk, W. (2013) · Nature · doi:10.1038/nature12346 · Cited by 997
Probing and regulating dysfunctional circuits using deep brain stimulation
Lozano, A. M., & Lipsman, N. (2013) · Neuron · doi:10.1016/j.neuron.2013.01.020 · Cited by 665
Multiple models to capture the variability in biological neurons and networks
Marder, E., & Taylor, A. L. (2011) · Nature Neuroscience · doi:10.1038/nn.2735 · Cited by 451
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Bassett, D. S., & Sporns, O. (2017) · Nature Neuroscience · doi:10.1038/nn.4502 · Cited by 2,398
Novel electrode technologies for neural recordings
Hong, G., & Lieber, C. M. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0140-6 · Cited by 695
Correlations and Neuronal Population Information
Kohn, A., Coen-Cagli, R., Kanitscheider, I., & Pouget, A. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013851 · Cited by 367
Improved tools to study astrocytes
Yu, X., Nagai, J., & Khakh, B. S. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0264-8 · Cited by 298
Multimodal analysis of cell types in a hypothalamic node controlling social behavior
Kim, D.-W., Yao, Z., Graybuck, L. T., Kim, T. K., Nguyen, T. N., Smith, K. A., Fong, O., Yi, L., Koulena, N., Pierson, N., et al. (2019) · Cell · doi:10.1016/j.cell.2019.09.020 · Cited by 259
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Metadata
- Authors
- Jorgenson, L. A., Newsome, W. T., Anderson, D. J., Bargmann, C. I., Brown, E. N., Deisseroth, K., Donoghue, J. P., Hudson, K. L., Ling, G. S. F., MacLeish, P. R., Marder, E., Normann, R. A., Sanes, J. R., Schnitzer, M. J., Sejnowski, T. J., Tank, D. W., Tsien, R. Y., Ugurbil, K., & Wingfield, J. C.
- Venue
- Philosophical Transactions of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2015-05-19
- Volume
- 370
- Issue
- 1668
- Pages
- 20140164
- ISSN
- 0962-8436 (ISSN-L)
- 1471-2970
- OpenAlex
- W2155063410
- Cited by
- 238
- References
- 13
- FWCI
- 12.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Jorgenson, L. A., Newsome, W. T., Anderson, D. J., Bargmann, C. I., Brown, E. N., Deisseroth, K., Donoghue, J. P., Hudson, K. L., Ling, G. S. F., MacLeish, P. R., Marder, E., Normann, R. A., Sanes, J. R., Schnitzer, M. J., Sejnowski, T. J., Tank, D. W., Tsien, R. Y., Ugurbil, K., & Wingfield, J. C. (2015). The BRAIN Initiative: developing technology to catalyse neuroscience discovery. Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rstb.2014.0164
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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