The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Neural networks as spatio-temporal pattern-forming systems
Abstract
Models of neural networks are developed from a biological point of view. Small networks are analysed using techniques from dynamical systems. The behaviour of spatially and temporally organized neural fields is then discussed from the point of view of pattern formation. Bifurcation methods, analytic solutions and perturbation methods are applied to these models.
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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
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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
Hopfield, J. J. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.10.3088 · Cited by 6,918
The Geometry of Biological Time
Winfree, A. T. (1980) · doi:10.1007/978-3-662-22492-2 · Cited by 3,613
Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex
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Hansel, D., Mato, G., & Meunier, C. (1995) · Neural Computation · doi:10.1162/neco.1995.7.2.307 · Cited by 587
How the brain keeps the eyes still
Seung, H. S. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.23.13339 · Cited by 534
A coupled attractor model of the rodent head direction system
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Cited by
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition
Wang, X.-J. (2010) · Physiological Reviews · doi:10.1152/physrev.00035.2008 · Cited by 1,939
Compte, A. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.9.910 · Cited by 1,143
The dynamic brain: from spiking neurons to neural masses and cortical fields
Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000092 · Cited by 1,084
Mathematical framework for large-scale brain network modeling in The Virtual Brain
Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.002 · Cited by 356
Stability of the memory of eye position in a recurrent network of conductance-based model neurons
Seung, H. S., Lee, D. D., Reis, B. Y., & Tank, D. W. (2000) · Neuron · doi:10.1016/s0896-6273(00)81155-1 · Cited by 339
Metadata
- Authors
- Ermentrout, B.
- Venue
- Reports on Progress in Physics
- Publisher
- IOP Publishing
- Published
- 1998-04-01
- Volume
- 61
- Issue
- 4
- Pages
- 353-430
- ISSN
- 0034-4885 (ISSN-L)
- 1361-6633
- OpenAlex
- W2129207384
- Cited by
- 679
- References
- 10
- FWCI
- 12.31
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ermentrout, B. (1998). Neural networks as spatio-temporal pattern-forming systems. Reports on Progress in Physics. https://doi.org/10.1088/0034-4885/61/4/002
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.
