The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
From the neuron doctrine to neural networks
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Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
A logical calculus of the ideas immanent in nervous activity
McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
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
The perceptron: A probabilistic model for information storage and organization in the brain.
Rosenblatt, F. (1958) · Psychological Review · doi:10.1037/h0042519 · Cited by 12,280
On computable numbers, with an application to the entscheidungsproblem
Turing, A. M. (1937) · Proceedings of the London Mathematical Society · doi:10.1112/plms/s2-42.1.230 · Cited by 8,283
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483
Ultrasensitive fluorescent proteins for imaging neuronal activity
Chen, T.-W., Wardill, T. J., Sun, Y., Pulver, S. R., Renninger, S. L., Baohan, A., Schreiter, E. R., Kerr, R. A., Orger, M. B., Jayaraman, V., et al. (2013) · Nature · doi:10.1038/nature12354 · Cited by 6,474
Buzsáki, G. (2006) · doi:10.1093/acprof:oso/9780195301069.001.0001 · Cited by 4,873
Cited by
Neuroscience Needs Behavior: Correcting a Reductionist Bias
Krakauer, J. W., Ghazanfar, A. A., Gomez-Marin, A., MacIver, M. A., & Poeppel, D. (2017) · Neuron · doi:10.1016/j.neuron.2016.12.041 · Cited by 1,358
An Integrated Brain-Machine Interface Platform With Thousands of Channels
Musk, E., & Neuralink (2019) · Journal of Medical Internet Research · doi:10.2196/16194 · Cited by 1,206
Memory engrams: Recalling the past and imagining the future
Josselyn, S. A., & Tonegawa, S. (2020) · Science · doi:10.1126/science.aaw4325 · Cited by 1,087
Why neurons mix: high dimensionality for higher cognition
Fusi, S., Miller, E. K., & Rigotti, M. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.01.010 · Cited by 766
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
Metadata
- Authors
- Yuste, R.
- Venue
- Nature Reviews Neuroscience
- Published
- 2015-07-08
- Volume
- 16
- Issue
- 8
- Pages
- 487-497
- ISSN
- 1471-003X (ISSN-L)
- 1471-0048
- OpenAlex
- W1510964369
- Cited by
- 754
- References
- 39
- FWCI
- 5.58
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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- CoChat. (2026). Citation check: From the neuron doctrine to neural networks. https://app.cochat.ai/papers/10.1038/nrn3962
- The paper
- Yuste, R. (2015). From the neuron doctrine to neural networks. Nature Reviews Neuroscience. https://doi.org/10.1038/nrn3962
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
