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Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex
Open accessAbstract
The development of stimulus selectivity in the primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in the efficacy of a given synapse depends not only on instantaneous pre- and postsynaptic activities but also on a slowly varying time-averaged value of the postsynaptic activity. Assuming an appropriate nonlinear form for this dependence, development of selectivity is obtained under quite general conditions on the sensory environment. One does not require nonlinearity of the neuron's integrative power nor does one need to assume any particular form for intracortical circuitry. This is first illustrated in simple cases, e.g., when the environment consists of only two different stimuli presented alternately in a random manner. The following formal statement then holds: the state of the system converges with probability 1 to points of maximum selectivity in the state space. We next consider the problem of early development of orientation selectivity and binocular interaction in primary visual cortex. Giving the environment an appropriate form, we obtain orientation tuning curves and ocular dominance comparable to what is observed in normally reared adult cats or monkeys. Simulations with binocular input and various types of normal or altered environments show good agreement with the relevant experimental data. Experiments are suggested that could test our theory further.
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“Consistent with original ideas (Bienenstock et al. 1982), modest depolarization can elicit LTD, whereas stronger depolarization leads to LTP.”
From NMDA receptor-dependent long-term potentiation and long-term depression (LTP/LTD). (2012) · cites this paper as Bienenstock et al. 1982
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“If this were the case, it has been argued that the system would be unstable and quickly saturate (366–371).”
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“The existence of LTD avoids the problem of saturation, which could be essential for a mnemonic device (366–371).”
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SINGLE-CELL RESPONSES IN STRIATE CORTEX OF KITTENS DEPRIVED OF VISION IN ONE EYE
Wiesel, T. N., & Hubel, D. H. (1963) · Journal of Neurophysiology · doi:10.1152/jn.1963.26.6.1003 · Cited by 2,628
Self-organization of orientation sensitive cells in the striate cortex
Malsburg, C. V. D. (1973) · Kybernetik · doi:10.1007/bf00288907 · Cited by 1,444
RECEPTIVE FIELDS OF CELLS IN STRIATE CORTEX OF VERY YOUNG, VISUALLY INEXPERIENCED KITTENS
Hubel, D. H., & Wiesel, T. N. (1963) · Journal of Neurophysiology · doi:10.1152/jn.1963.26.6.994 · Cited by 1,113
A Physiological Mechanism for Hebb's Postulate of Learning
Stent, G. S. (1973) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.70.4.997 · Cited by 710
EXTENT OF RECOVERY FROM THE EFFECTS OF VISUAL DEPRIVATION IN KITTENS
Wiesel, T. N., & Hubel, D. H. (1965) · Journal of Neurophysiology · doi:10.1152/jn.1965.28.6.1060 · Cited by 704
Storing covariance with nonlinearly interacting neurons
Sejnowski, T. J. (1977) · Journal of Mathematical Biology · doi:10.1007/bf00275079 · Cited by 546
Kasamatsu, T., & Pettigrew, J. D. (1976) · Science · doi:10.1126/science.959850 · Cited by 436
Kasamatsu, T., & Pettigrew, J. D. (1979) · The Journal of Comparative Neurology · doi:10.1002/cne.901850109 · Cited by 314
Imbert, M., & Buisseret, P. (1975) · Experimental Brain Research · doi:10.1007/bf00235409 · Cited by 303
Rauschecker, J. P., & Singer, W. (1981) · The Journal of Physiology · doi:10.1113/jphysiol.1981.sp013545 · Cited by 220
Research works printed but not linked: 7
- Anderson, J. A. (1970) Two models for memory organization Hebb, D. 0. (1949) Organization of Behavior, John Wiley and using interacting traces. Math. Biosci. 8: 137-160.
- selectivity. Doctoral thesis, Brown University, Providence, Hirsch, H. V. B., and D. N. Spinelli (1971) Modification of the RI. distribution of receptive field orientation in cats by selective
- Hubel, D. H., and T. N. Wiesel (1962) Receptive fields, binoc- Vol. 2, No. 1, Jan. 1982 ular interaction and functional architecture in the cat's visual cortex. J. Physiol. (Lond.) 160: 106-154.
- LeventhaI, A. G., and H. V. B. Hirsch (1977) Effects of early experience upon orientation selectivity and binocularity of neurons in visual cortex of cats. Proc. Natl. Acad. Sci. U. S. A. 74: 1272-1276.
- Pettigrew, J. D. (1978) The paradox of the critical period for striate cortex. In Neuronal Plasticity, C. W. Cotman, ed., pp. 311-330, Raven Press, New York.
- Singer, W. (1979) Central-core control of visual functions. In Neuroscience Fourth Study Program, F. Schmitt and F. Worden, eds., pp. 1093-1109, MIT Press, Cambridge.
- Trotter, Y., Y. Fregnac, P. Buisseret (1981) Gating control of developmental plasticity by extraocular proprioception in kitten area 17. In Fourth European Conference on Visual Perception, Gouzieux, France.
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Items 201–300 of 1,006
Mechanism for a sliding synaptic modification threshold.
Bear, M. (1995) · Neuron · doi:10.1016/0896-6273(95)90056-x · Cited by 247
Chapter 8 Synaptic plasticity in learning and memory: Stress effects in the hippocampus
Howland, J. G., & Wang, Y. T. (2008) · Progress in brain research · doi:10.1016/s0079-6123(07)00008-8 · Cited by 243
Model of Cortical-Basal Ganglionic Processing: Encoding the Serial Order of Sensory Events
Beiser, D. G., & Houk, J. C. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.6.3168 · Cited by 239
Graded bidirectional synaptic plasticity is composed of switch-like unitary events
O’Connor, D. H., Wittenberg, G. M., & Wang, S. S. ‐. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0502332102 · Cited by 232
SK2 channel plasticity contributes to LTP at Schaffer collateral–CA1 synapses
Lin, M. T., Luján, R., Watanabe, M., Adelman, J. P., & Maylie, J. (2008) · Nature Neuroscience · doi:10.1038/nn2041 · Cited by 244
Synaptic gain control and homeostasis
Burrone, J., & Murthy, V. N. (2003) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2003.09.007 · Cited by 236
Monocular deprivation induces homosynaptic long-term depression in visual cortex
Rittenhouse, C. D., Shouval, H. Z., Paradiso, M. A., & Bear, M. F. (1999) · Nature · doi:10.1038/16922 · Cited by 228
Debanne, D., Gähwiler, B. H., & Thompson, S. M. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.3.1148 · Cited by 233
Carpenter, G. A., & Grossberg, S. (1993) · Trends in Neurosciences · doi:10.1016/0166-2236(93)90118-6 · Cited by 229
A neural network model of retrieval-induced forgetting
Norman, K. A., Newman, E. L., & Detre, G. (2007) · Psychological Review · doi:10.1037/0033-295x.114.4.887 · Cited by 218
Mathematical foundations of neurocomputing
Амари, Ш.-И. (1990) · Proceedings of the IEEE · doi:10.1109/5.58324 · Cited by 226
Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation
Fusi, S., Annunziato, M., Badoni, D., Salamon, A., & Amit, D. J. (2000) · Neural Computation · doi:10.1162/089976600300014917 · Cited by 228
Spike timing dependent plasticity: a consequence of more fundamental learning rules
Shouval, H. Z. (2010) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2010.00019 · Cited by 238
Transcranial magnetic stimulation
Lefaucheur, J. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64032-1.00037-0 · Cited by 225
Karabanov, A. N., Ziemann, U., Hamada, M., George, M. S., Quartarone, A., Claßen, J., Massimini, M., Rothwell, J. C., & Siebner, H. R. (2015) · Brain stimulation · doi:10.1016/j.brs.2015.01.404 · Cited by 236
Nitsche, M. A., Roth, A., Kuo, M., Fischer, A., Liebetanz, D., Lang, N., Tergau, F., & Paulus, W. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.5348-06.2007 · Cited by 227
Hippocampal long-term depression mediates acute stress-induced spatial memory retrieval impairment
Wong, T. P., Howland, J. G., Robillard, J. M., Ge, Y., Yu, W. K., Titterness, A. K., Brebner, K., Liu, L., Weinberg, J., Christie, B. R., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0702308104 · Cited by 228
Senn, W., Markram, H., & Tsodyks, M. V. (2001) · Neural Computation · doi:10.1162/089976601300014628 · Cited by 213
Etkin, A., Alarcón, J. M., Weisberg, S. P., Touzani, K., Huang, Y. Y., Nordheim, A., & Kandel, E. R. (2006) · Neuron · doi:10.1016/j.neuron.2006.03.013 · Cited by 224
TMS Induced Plasticity in Human Cortex
Ziemann, U. (2004) · Reviews in the Neurosciences · doi:10.1515/revneuro.2004.15.4.253 · Cited by 222
Experience-dependent recovery of vision following chronic deprivation amblyopia
He, H., Ray, B., Dennis, K., & Quinlan, E. M. (2007) · Nature Neuroscience · doi:10.1038/nn1965 · Cited by 220
Synaptic plasticity and phosphorylation
Lee, H. (2006) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2006.06.003 · Cited by 222
A Review of Dimension Reduction Techniques
Carreira-Perpiñán, M. Á. (2009) · Cited by 216
Gjorgjieva, J., Clopath, C., Audet, J., & Pfister, J.-P. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1105933108 · Cited by 207
Altered plasticity of the human motor cortex in Parkinson's disease
Ueki, Y., Mima, T., Kotb, M. A., Sawada, H., Saiki, H., Ikeda, A., Begum, T., Reza, F., Nagamine, T., & Fukuyama, H. (2005) · Annals of Neurology · doi:10.1002/ana.20692 · Cited by 215
Neural Learning Rules for the Vestibulo-Ocular Reflex
Raymond, J. L., & Lisberger, S. G. (1998) · Journal of Neuroscience · doi:10.1523/jneurosci.18-21-09112.1998 · Cited by 213
RC3/neurogranin, a postsynaptic calpacitin for setting the response threshold to calcium influxes
Gerendasy, D. D., & Sutcliffe, J. G. (1997) · Molecular Neurobiology · doi:10.1007/bf02740632 · Cited by 206
Keck, T., Toyoizumi, T., Chen, L., Doiron, B., Feldman, D. E., Fox, K. D., Wulfram Gerstner, B., Haydon, P. G., Hübener, M., Lee, H., et al. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0158 · Cited by 217
Intrator, N., & Cooper, L. N. (1992) · Neural Networks · doi:10.1016/s0893-6080(05)80003-6 · Cited by 211
Self-citationInhibitory and Excitatory Spike-Timing-Dependent Plasticity in the Auditory Cortex
D’amour, J. A., & Froemke, R. C. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.014 · Cited by 210
Encoding Multielement Scenes: Statistical Learning of Visual Feature Hierarchies.
Fiser, J., & Aslin, R. Ν. (2005) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.134.4.521 · Cited by 223
GABA promotes the competitive selection of dendritic spines by controlling local Ca2+ signaling
Hayama, T., Noguchi, J., Watanabe, S., Takahashi, N., Hayashi-Takagi, A., Ellis-Davies, G. C. R., Matsuzaki, M., & Kasai, H. (2013) · Nature Neuroscience · doi:10.1038/nn.3496 · Cited by 193
Obligatory Role of NR2A for Metaplasticity in Visual Cortex
Philpot, B. D., Cho, K. K. A., & Bear, M. F. (2007) · Neuron · doi:10.1016/j.neuron.2007.01.027 · Cited by 207
Linking Hebb's coincidence-detection to memory formation
Tsien, J. Z. (2000) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(00)00070-2 · Cited by 209
Homeostatic-like plasticity of the primary motor hand area is impaired in focal hand dystonia
Quartarone, A., Rizzo, V., Bagnato, S., Morgante, F., SantʼAngelo, A., Romano, M. C., Crupi, D., Girlanda, P., Rothwell, J. C., & Siebner, H. R. (2005) · Brain · doi:10.1093/brain/awh527 · Cited by 207
Tatti, R., Haley, M. S., Swanson, O. K., Tselha, T., & Maffei, A. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.09.017 · Cited by 223
Optimal adaptive k-means algorithm with dynamic adjustment of learning rate
Chinrungrueng, C., & Séquin, C. H. (1995) · IEEE Transactions on Neural Networks · doi:10.1109/72.363440 · Cited by 206
Scharf, M. T., Woo, N. H., Lattal, K. M., Young, J. Z., Nguyen, P. V., & Abel, T. (2002) · Journal of Neurophysiology · doi:10.1152/jn.2002.87.6.2770 · Cited by 204
NMDA Receptors in the Central Nervous System
Hansen, K. B., Yi, F., Perszyk, R. E., Menniti, F. S., & Traynelis, S. F. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7321-7_1 · Cited by 216
Emerging roles of metaplasticity in behaviour and disease
Hulme, S. R., Jones, O. D., & Abraham, W. C. (2013) · Trends in Neurosciences · doi:10.1016/j.tins.2013.03.007 · Cited by 209
SWAT: A Spiking Neural Network Training Algorithm for Classification Problems
Wade, J. J., Mcdaid, L. J., Santos, J., & Sayers, H. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2074212 · Cited by 202
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
Calcineurin in memory and bidirectional plasticity
Mansuy, I. M. (2003) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2003.10.046 · Cited by 200
Hebbian learning and development
Munakata, Y., & Pfaffly, J. (2004) · Developmental Science · doi:10.1111/j.1467-7687.2004.00331.x · Cited by 206
The two sides of associative plasticity in writer's cramp
Weise, D. (2006) · Brain · doi:10.1093/brain/awl221 · Cited by 198
Modulation of spike timing by sensory deprivation during induction of cortical map plasticity
Celikel, T., Szostak, V. A., & Feldman, D. E. (2004) · Nature Neuroscience · doi:10.1038/nn1222 · Cited by 205
Ubiquitous Plasticity and Memory Storage
Kim, S. J., & Linden, D. J. (2007) · Neuron · doi:10.1016/j.neuron.2007.10.030 · Cited by 202
Synapse elimination accompanies functional plasticity in hippocampal neurons
Bastrikova, N., Gardner, G. A., Reece, J. M., Jeromin, A., & Dudek, S. M. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800027105 · Cited by 202
Short-term reverberant memory model of hippocampal field CA3
Wiebe, S. P., St�ubli, U. V., & Ambros-Ingerson, J. (1997) · Hippocampus · doi:10.1002/(sici)1098-1063(1997)7:6 · Cited by 33
Developmental plasticity of mouse visual acuity
Prusky, G. T., & Douglas, R. M. (2003) · European Journal of Neuroscience · doi:10.1046/j.1460-9568.2003.02420.x · Cited by 194
Tråvén, H. G. C. (1991) · IEEE Transactions on Neural Networks · doi:10.1109/72.97913 · Cited by 191
Homeostatic and Nonhomeostatic Modulation of Learning in Human Motor Cortex
Jung, P., & Ziemann, U. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.0222-09.2009 · Cited by 191
Hebbian plasticity requires compensatory processes on multiple timescales
Zenke, F., & Wulfram Gerstner, B. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0259 · Cited by 206
Towards artificial neurons and synapses: a materials point of view
Jeong, D. S., Kim, I., Ziegler, M., & Kohlstedt, H. (2012) · RSC Advances · doi:10.1039/c2ra22507g · Cited by 191
Ielmini, D., & Pedretti, G. (2025) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00845 · Cited by 201
Optimal Plasticity from Matrix Memories: What Goes Up Must Come Down
Willshaw, D. J., & Dayan, P. (1990) · Neural Computation · doi:10.1162/neco.1990.2.1.85 · Cited by 194
The role of metaplasticity mechanisms in regulating memory destabilization and reconsolidation
Finnie, P. S. B., & Nader, K. (2012) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.03.008 · Cited by 189
Arendt, T. (2003) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2003.09.007 · Cited by 189
Homeostatic plasticity and STDP: keeping a neuron's cool in a fluctuating world
Watt, A. J. (2010) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2010.00005 · Cited by 195
Krucoff, M. O., Rahimpour, S., Slutzky, M. W., Edgerton, V. R., & Turner, D. A. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00584 · Cited by 196
Calcium time course as a signal for spike-timing-dependent plasticity.
Rubin, J., Gerkin, R. C., Bi, G., & Chow, C. C. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00803.2004 · Cited by 203
Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron
Ramaswamy, S., & Markram, H. (2015) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2015.00233 · Cited by 204
Lansner, A. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2008.12.002 · Cited by 183
Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics
Mikhaylov, A. N., Pimashkin, A. S., Pigareva, Y., Gerasimova, S. A., Gryaznov, E. G., Shchanikov, S., Zuev, A. D., Talanov, M. O., Lavrov, I. A., Demin, V. A., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00358 · Cited by 189
The predictive brain: temporal coincidence and temporal order in synaptic learning mechanisms.Preprint
Montague, P. R., & B, T. J. S. A. (1994) · Learning & Memory · doi:10.1101/lm.1.1.1 · Cited by 187
Brain polarization enhances the formation and retention of motor memories.
Galea, J., & Celnik, P. (2009) · Journal of Neurophysiology · doi:10.1152/jn.00184.2009 · Cited by 202
Cerebral cortex : principles of operation
Rolls, E. T. (2016) · doi:10.82444/warw.33712699 · Cited by 187
Long-Term Depression at Thalamocortical Synapses in Developing Rat Somatosensory Cortex
Feldman, D. E., Nicoll, R. A., Malenka, R. C., & Isaac, J. T. R. (1998) · Neuron · doi:10.1016/s0896-6273(00)80544-9 · Cited by 186
Targeting Homeostatic Synaptic Plasticity for Treatment of Mood Disorders
Kavalali, E. T., & Monteggia, L. M. (2020) · Neuron · doi:10.1016/j.neuron.2020.05.015 · Cited by 179
Zhang, Y., Li, P., Jin, Y., & Choe, Y. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2388544 · Cited by 178
Bidirectional modification of CA1 synapses in the adult hippocampus in vivo
Heynen, A. J., Abraham, W. C., & Bear, M. F. (1996) · Nature · doi:10.1038/381163a0 · Cited by 178
Acute and chronic effects of ethanol on learning-related synaptic plasticity
Zorumski, C. F., Mennerick, S. J., & Izumi, Y. (2013) · Alcohol · doi:10.1016/j.alcohol.2013.09.045 · Cited by 177
Müller, J. F. M., Orekhov, Y., Liu, Y., & Ziemann, U. (2007) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2007.05603.x · Cited by 178
Bidirectional synaptic mechanisms of ocular dominance plasticity in visual cortex
Smith, G. B., Heynen, A. J., & Bear, M. F. (2008) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2008.0198 · Cited by 177
Hummel, F. C., & Cohen, L. G. (2005) · Current Opinion in Neurology · doi:10.1097/01.wco.0000189876.37475.42 · Cited by 173
A proportional but slower NMDA potentiation follows AMPA potentiation in LTP
Watt, A. J., Sjöström, P. J., Häusser, M., Nelson, S. B., & Turrigiano, G. G. (2004) · Nature Neuroscience · doi:10.1038/nn1220 · Cited by 178
Cho, K., Aggleton, J. P., Brown, M. W., & Bashir, Z. I. (2001) · The Journal of Physiology · doi:10.1111/j.1469-7793.2001.0459f.x · Cited by 170
Neuronal vector coding in spatial cognition
Bicanski, A., & Burgess, N. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-0336-9 · Cited by 172
Limited impact of homeostatic plasticity on motor learning in humans
Kuo, M., Unger, M., Liebetanz, D., Lang, N., Tergau, F., Paulus, W., & Nitsche, M. A. (2008) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2008.02.023 · Cited by 176
Raeis‐Hosseini, N., Park, Y., & Lee, J. (2018) · Advanced Functional Materials · doi:10.1002/adfm.201800553 · Cited by 172
Device and Circuit Architectures for In‐Memory Computing
Ielmini, D., & Pedretti, G. (2020) · Advanced Intelligent Systems · doi:10.1002/aisy.202000040 · Cited by 180
Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning
Kempter, R., Wulfram Gerstner, B., & van Hemmen, J. L. (2001) · Neural Computation · doi:10.1162/089976601317098501 · Cited by 173
Bidirectional synaptic plasticity rapidly modifies hippocampal representations
Milstein, A. D., Li, Y., Bittner, K. C., Grienberger, C., Soltesz, I., Magee, J. C., & Romani, S. (2021) · eLife · doi:10.7554/elife.73046 · Cited by 151
Modulation of cortical inhibition by rTMS – findings obtained from animal models
Funke, K., & Benali, A. (2011) · The Journal of Physiology · doi:10.1113/jphysiol.2011.206573 · Cited by 173
Heterosynaptic metaplasticity in the hippocampus in vivo : A BCM-like modifiable threshold for LTP
Abraham, W. C., Mason‐Parker, S. E., Bear, M. F., Webb, S. V., & Tate, W. P. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.181342098 · Cited by 170
Dumas, T. C. (2005) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2005.08.002 · Cited by 182
An innocuous bias in whisker use in adult rats modifies receptive fields of barrel cortex neurons
Armstrong‐James, M., Diamond, M. E., & Ebner, F. (1994) · Journal of Neuroscience · doi:10.1523/jneurosci.14-11-06978.1994 · Cited by 169
Albensi, B. C., Oliver, D. R., Toupin, J. D., & Odero, G. L. (2006) · Experimental Neurology · doi:10.1016/j.expneurol.2006.12.009 · Cited by 176
Kumar, A. (2011) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2011.00007 · Cited by 175
Oh, W. C., Hill, T. C., & Zito, K. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1214705110 · Cited by 175
Enhanced Just Noticeable Difference Model for Images With Pattern Complexity
Wu, J., Li, L., Dong, W., Shi, G., Lin, W., & Kuo, C. ‐. J. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2685682 · Cited by 168
A Role for cAMP in Long-Term Depression at Hippocampal Mossy Fiber Synapses
Tzounopoulos, T., Janz, R., Südhof, T. C., Nicoll, R. A., & Malenka, R. C. (1998) · Neuron · doi:10.1016/s0896-6273(00)80599-1 · Cited by 171
A test of Hebb's postulate at identified synapses which mediate classical conditioning in Aplysia
Carew, T., Hawkins, R. D., Abrams, T. W., & Kandel, E. R. (1984) · Journal of Neuroscience · doi:10.1523/jneurosci.04-05-01217.1984 · Cited by 166
Unsupervised learning by competing hidden units
Krotov, D., & Hopfield, J. J. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820458116 · Cited by 166
Homeostatic plasticity in the CNS: synaptic and intrinsic forms
Desai, N. S. (2003) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2004.01.005 · Cited by 168
Abnormal plasticity in dystonia: Disruption of synaptic homeostasis
Quartarone, A., & Pisani, A. (2010) · Neurobiology of Disease · doi:10.1016/j.nbd.2010.12.011 · Cited by 167
Crozier, R. A., Wang, Y., Liu, C.-H., & Bear, M. F. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609596104 · Cited by 163
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Metadata
- Authors
- Bienenstock, E., Cooper, L., & Munro, P.
- Affiliations
- Université Paris-Sud (FR)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 1982-01-01
- Volume
- 2
- Issue
- 1
- Pages
- 32-48
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6564292
- OpenAlex
- W1733248925
- Cited by
- 2,896
- References
- 19
- Citations by year
- 2026: 71 · 2025: 91 · 2024: 98 · 2023: 108 · 2022: 102 · 2021: 104 · 2020: 112 · 2019: 93 · 2018: 112 · 2017: 108 · 2016: 87 · 2015: 117 · 2014: 118 · 2013: 119 · 2012: 112
- FWCI
- 4.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ittleson Foundation
- Brown University
- Fondation de France
- Office of Naval Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- orientation selectivity, binocular interaction, primary visual cortex, ocular dominance, synaptic plasticity, orientation tuning curves, synaptic efficacy, cortical development
- MeSH terms
- Animals, Cats, Dominance, Cerebral, Mathematics, Models, Neurological, Neurons, Orientation, Retina, Sensory Deprivation, Synapses, Visual Cortex, Visual Pathways, Visual Perception
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