The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Sparseness and Expansion in Sensory Representations
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Cites
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Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
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Relations between the statistics of natural images and the response properties of cortical cells
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A theory of cerebellar function
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The “independent components” of natural scenes are edge filters
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Visualizing an Olfactory Sensory Map
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Cited by
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
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
Synaptic diversity enables temporal coding of coincident multisensory inputs in single neurons
Chabrol, F. P., Arenz, A., Wiechert, M. T., Margrie, T. W., & DiGregorio, D. A. (2015) · Nature Neuroscience · doi:10.1038/nn.3974 · Cited by 230
Shared cortex-cerebellum dynamics in the execution and learning of a motor task
Wagner, M. J., Kim, T. H., Kadmon, J., Nguyen, N. D., Ganguli, S., Schnitzer, M. J., & Luo, L. (2019) · Cell · doi:10.1016/j.cell.2019.02.019 · Cited by 177
Neural representations of space in the hippocampus of a food-caching bird
Payne, H. L., Lynch, G. F., & Aronov, D. (2021) · Science · doi:10.1126/science.abg2009 · Cited by 163
Metadata
- Authors
- Babadi, B., & Sompolinsky, H.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 83
- Issue
- 5
- Pages
- 1213-1226
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W1993533483
- Cited by
- 253
- References
- 37
- FWCI
- 5.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Babadi, B., & Sompolinsky, H. (2014). Sparseness and Expansion in Sensory Representations. Neuron. https://doi.org/10.1016/j.neuron.2014.07.035
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.