The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Self-organization of orientation sensitive cells in the striate cortex
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Simple memory: a theory for archicortex
Marr, D. (1971) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1971.0078 · Cited by 2,771
PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS
ROSENBLATT, F. (1961) · doi:10.21236/ad0256582 · Cited by 1,691
Development of the brain depends on the visual environment
BLAKEMORE, C., & COOPER, G. F. (1970) · Nature · doi:10.1038/228477a0 · Cited by 1,005
Cited by
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
Self-organized formation of topologically correct feature maps
Kohonen, T. (1982) · Biological Cybernetics · doi:10.1007/bf00337288 · Cited by 9,529
Kohonen, T. (1990) · Proceedings of the IEEE · doi:10.1109/5.58325 · Cited by 8,414
Bienenstock, E., Cooper, L., & Munro, P. (1982) · The Journal of Neuroscience · doi:10.1523/jneurosci.02-01-00032.1982 · Cited by 2,896
Homeostatic plasticity in the developing nervous system
Turrigiano, G. G., & Nelson, S. B. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1327 · Cited by 2,485
Simplified neuron model as a principal component analyzer
Oja, E. (1982) · Journal of Mathematical Biology · doi:10.1007/bf00275687 · Cited by 2,309
CORTICAL PLASTICITY: From Synapses to Maps
Buonomano, D. V., & Merzenich, M. M. (1998) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.21.1.149 · Cited by 2,083
Grossberg, S. (1976) · Biological Cybernetics · doi:10.1007/bf00344744 · Cited by 1,909
Barlow, H. B. (1989) · Neural Computation · doi:10.1162/neco.1989.1.3.295 · Cited by 1,650
Nonlinear neural networks: Principles, mechanisms, and architectures
Grossberg, S. (1988) · Neural Networks · doi:10.1016/0893-6080(88)90021-4 · Cited by 1,623
Competitive learning: From interactive activation to adaptive resonance
Grossberg, S. (1987) · Cognitive Science · doi:10.1111/j.1551-6708.1987.tb00862.x · Cited by 1,471
Changeux, J.-P., & Danchin, A. (1976) · Nature · doi:10.1038/264705a0 · Cited by 1,448
Toward a modern theory of adaptive networks: Expectation and prediction.
Sutton, R. S., & Barto, A. G. (1981) · Psychological Review · doi:10.1037/0033-295x.88.2.135 · Cited by 1,450
Connectionist learning procedures
Hinton, G. E. (1989) · Artificial Intelligence · doi:10.1016/0004-3702(89)90049-0 · Cited by 1,430
The ART of adaptive pattern recognition by a self-organizing neural network
Carpenter, G. A., & Grossberg, S. (1988) · Computer · doi:10.1109/2.33 · Cited by 1,287
Rate, Timing, and Cooperativity Jointly Determine Cortical Synaptic Plasticity
Sjöström, P. J., Turrigiano, G. G., & Nelson, S. B. (2001) · Neuron · doi:10.1016/s0896-6273(01)00542-6 · Cited by 1,174
The Spike-Timing Dependence of Plasticity
Feldman, D. E. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.001 · Cited by 1,071
The neural basis of temporal processing
Mauk, M. D., & Buonomano, D. V. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144247 · Cited by 976
Complementary roles of basal ganglia and cerebellum in learning and motor control
Doya, K. (2000) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(00)00153-7 · Cited by 964
Synaptic Plasticity Forms and Functions
Magee, J. C., & Grienberger, C. (2020) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-090919-022842 · Cited by 806
Cognitron: A self-organizing multilayered neural network
Fukushima, K. (1975) · Biological Cybernetics · doi:10.1007/bf00342633 · Cited by 757
Hebbian learning and spiking neurons
Kempter, R., Gerstner, W., & van Hemmen, J. L. (1999) · Physical Review E · doi:10.1103/physreve.59.4498 · Cited by 664
The development of features in object concepts
Schyns, P. G., Goldstone, R. L., & Thibaut, J.-P. (1998) · Behavioral and Brain Sciences · doi:10.1017/s0140525x98000107 · Cited by 593
Ultrastructural evidence for synaptic scaling across the wake/sleep cycle
de Vivo, L., Bellesi, M., Marshall, W., Bushong, E. A., Ellisman, M. H., Tononi, G., & Cirelli, C. (2017) · Science · doi:10.1126/science.aah5982 · Cited by 574
A symbolic-connectionist theory of relational inference and generalization.
Hummel, J. E., & Holyoak, K. J. (2003) · Psychological Review · doi:10.1037/0033-295x.110.2.220 · Cited by 567
Computational Neuroscience of Vision
Rolls, E., & Deco, G. (2001) · doi:10.1093/acprof:oso/9780198524885.001.0001 · Cited by 553
Requirement for Cholinergic Synaptic Transmission in the Propagation of Spontaneous Retinal Waves
Feller, M. B., Wellis, D. P., Stellwagen, D., Werblin, F. S., & Shatz, C. J. (1996) · Science · doi:10.1126/science.272.5265.1182 · Cited by 549
A Physiological Basis for a Theory of Synapse Modification
Bear, M. F., Cooper, L. N., & Ebner, F. F. (1987) · Science · doi:10.1126/science.3037696 · Cited by 530
Gasteiger, J., & Zupan, J. (1993) · Angewandte Chemie International Edition in English · doi:10.1002/anie.199305031 · Cited by 503
Bear, M., Kleinschmidt, A., Gu, Q., & Singer, W. (1990) · The Journal of Neuroscience · doi:10.1523/jneurosci.10-03-00909.1990 · Cited by 488
Plasticity of Cortical Excitatory-Inhibitory Balance
Froemke, R. C. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071714-034002 · Cited by 458
Hasselmo, M., & Schnell, E. (1994) · The Journal of Neuroscience · doi:10.1523/jneurosci.14-06-03898.1994 · Cited by 466
A history of spike-timing-dependent plasticity
Markram, H. (2011) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2011.00004 · Cited by 454
Rutherford, L. C., Nelson, S. B., & Turrigiano, G. G. (1998) · Neuron · doi:10.1016/s0896-6273(00)80563-2 · Cited by 451
The Role of Constraints in Hebbian Learning
Miller, K. D., & MacKay, D. J. C. (1994) · Neural Computation · doi:10.1162/neco.1994.6.1.100 · Cited by 448
3-D vision and figure-ground separation by visual cortex
Grossberg, S. (1994) · Perception & Psychophysics · doi:10.3758/bf03206880 · Cited by 440
Palm, G. (1980) · Biological Cybernetics · doi:10.1007/bf00337019 · Cited by 438
Neural representations and mechanisms for the performance of simple speech sequences
Bohland, J. W., Bullock, D., & Guenther, F. H. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21306 · Cited by 393
“Learning rules that conserve total synaptic strength have been proposed elsewhere (Grossberg, 1976; von der Malsburg, 1973), and similar conservational principles have been observed empirically (Markram & Tsodyks, 1996).”
The development of topography in the visual cortex: a review of models
Swindale, N. (1996) · Network: Computation in Neural Systems · doi:10.1088/0954-898x/7/2/002 · Cited by 398
The BCM theory of synapse modification at 30: interaction of theory with experiment
Cooper, L. N., & Bear, M. F. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3353 · Cited by 395
Four frames suffice: A provisional model of vision and space
Feldman, J. A. (1985) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00020707 · Cited by 395
The Hebbian paradigm reintegrated: local reverberations as internal representations
Amit, D. J. (1995) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00040164 · Cited by 388
Machine learning for large-scale crop yield forecasting
Paudel, D., Boogaard, H., de Wit, A., Janssen, S., Osinga, S., Pylianidis, C., & Athanasiadis, I. N. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2020.103016 · Cited by 357
Introduction to artificial neural networks
Grossi, E., & Buscema, M. (2007) · European Journal of Gastroenterology & Hepatology · doi:10.1097/meg.0b013e3282f198a0 · Cited by 342
Quantifying the neighborhood preservation of self-organizing feature maps
Bauer, H.-U., & Pawelzik, K. R. (1992) · IEEE Transactions on Neural Networks · doi:10.1109/72.143371 · Cited by 339
A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm
Bullock, D., Grossberg, S., & Guenther, F. H. (1993) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1993.5.4.408 · Cited by 313
Understanding Neural Networks as Statistical Tools
Warner, B., & Misra, M. (1996) · The American Statistician · doi:10.1080/00031305.1996.10473554 · Cited by 277
Self-organized computation with unreliable, memristive nanodevices
Snider, G. S. (2007) · Nanotechnology · doi:10.1088/0957-4484/18/36/365202 · Cited by 262
The temporal paradox of Hebbian learning and homeostatic plasticity
Zenke, F., Gerstner, W., & Ganguli, S. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.03.015 · Cited by 201
Sleep and synaptic down-selection
Tononi, G., & Cirelli, C. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14335 · Cited by 217
Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity
Turner, N. L., Macrina, T., Bae, J. A., Yang, R., Wilson, A. M., Schneider-Mizell, C., Lee, K., Lu, R., Wu, J., Bodor, A. L., et al. (2022) · Cell · doi:10.1016/j.cell.2022.01.023 · Cited by 206
Isolated and interrelated concepts
Goldstone, R. L. (1996) · Memory & Cognition · doi:10.3758/bf03201087 · Cited by 182
Comparison of computational models of familiarity discrimination in the perirhinal cortex
Bogacz, R., & Brown, M. W. (2003) · Hippocampus · doi:10.1002/hipo.10093 · Cited by 134
Modeling the Dynamic Interaction of Hebbian and Homeostatic Plasticity
Toyoizumi, T., Kaneko, M., Stryker, M. P., & Miller, K. D. (2014) · Neuron · doi:10.1016/j.neuron.2014.09.036 · Cited by 129
Carvalho, T. P., & Buonomano, D. V. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.013 · Cited by 100
Ohl, F. W., & Scheich, H. (1997) · Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology · doi:10.1007/s003590050150 · Cited by 85
Metastable dynamics of neural circuits and networks
Brinkman, B. A. W., Yan, H., Maffei, A., Park, I. M., Fontanini, A., Wang, J., & La Camera, G. (2022) · Applied Physics Reviews · doi:10.1063/5.0062603 · Cited by 64
Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation
Tetzlaff, C., Kolodziejski, C., Timme, M., Tsodyks, M., & Wörgötter, F. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003307 · Cited by 54
Metadata
- Authors
- von der Malsburg, C.
- Venue
- Kybernetik
- Published
- 1973-06
- Volume
- 14
- Issue
- 2
- Pages
- 85-100
- ISSN
- 0023-5946 (ISSN-L)
- OpenAlex
- W2887242076
- Cited by
- 1,461
- References
- 4
- FWCI
- 5.54
- 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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
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.