Theoretical Neuroscience Rising

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 · see citing works

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 · see citing works

A neural substrate of prediction and reward

Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388 · see citing works

Emergence of simple-cell receptive field properties by learning a sparse code for natural images

Olshausen, B. A., & Field, D. J. (1996) · Nature · doi:10.1038/381607a0 · Cited by 5,694 · see citing works

Humans integrate visual and haptic information in a statistically optimal fashion

Ernst, M. O., & Banks, M. S. (2002) · Nature · doi:10.1038/415429a · Cited by 4,844 · see citing works

Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations

Maass, W., Natschläger, T., & Markram, H. (2002) · Neural Computation · doi:10.1162/089976602760407955 · Cited by 4,025 · see citing works

Relations between the statistics of natural images and the response properties of cortical cells

Field, D. J. (1987) · Journal of the Optical Society of America A · doi:10.1364/josaa.4.002379 · Cited by 3,241 · see citing works

Spikes: Exploring the Neural Code

Rieke, F. M., Warland, D., van Steveninck, R. R. D. R., & Bialek, W. (1996) · Medical Entomology and Zoology · Cited by 2,844 · see citing works

Normalization of cell responses in cat striate cortex

Heeger, D. J. (1992) · Visual Neuroscience · doi:10.1017/s0952523800009640 · Cited by 1,835 · see citing works

Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity

van Vreeswijk, C., & Sompolinsky, H. (1996) · Science · doi:10.1126/science.274.5293.1724 · Cited by 1,831 · see citing works

The “independent components” of natural scenes are edge filters

Bell, A. J., & Sejnowski, T. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00121-1 · Cited by 1,592 · see citing works

Bayesian inference with probabilistic population codes

Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A. (2006) · Nature Neuroscience · doi:10.1038/nn1790 · Cited by 1,457 · see citing works

Perception as Bayesian Inference

(1996) · doi:10.1017/cbo9780511984037 · Cited by 1,425 · see citing works

Correlated neuronal activity and the flow of neural information

Salinas, E., & Sejnowski, T. J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35086012 · Cited by 1,333 · see citing works

Synaptic theory of working memory

Mongillo, G., Barak, O., & Tsodyks, M. (2008) · Science · doi:10.1126/science.1150769 · Cited by 1,253 · see citing works

Probabilistic decision making by slow reverberation in cortical circuits

Wang, X.-J. (2002) · Neuron · doi:10.1016/s0896-6273(02)01092-9 · Cited by 1,242 · see citing works

Noise, neural codes and cortical organization

Shadlen, M. N., & Newsome, W. T. (1994) · Current Opinion in Neurobiology · doi:10.1016/0959-4388(94)90059-0 · Cited by 1,240 · see citing works

Spin-glass models of neural networks

Amit, D. J., Gutfreund, H., & Sompolinsky, H. (1985) · Physical Review A · doi:10.1103/physreva.32.1007 · Cited by 1,185 · see citing works

Synaptic Mechanisms and Network Dynamics Underlying Spatial Working Memory in a Cortical Network Model

Compte, A. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.9.910 · Cited by 1,143 · see citing works

A neuronal learning rule for sub-millisecond temporal coding

Gerstner, W., Kempter, R., van Hemmen, J. L., & Wagner, H. (1996) · Nature · doi:10.1038/383076a0 · Cited by 1,096 · see citing works

Gamma rhythms and beta rhythms have different synchronization properties

Kopell, N., Ermentrout, G. B., Whittington, M. A., & Traub, R. D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.4.1867 · Cited by 1,072 · see citing works

Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex

Amit, D. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.3.237 · Cited by 1,061 · see citing works

Statistics of natural images: Scaling in the woods

Ruderman, D., & Bialek, W. (1994) · Physical Review Letters · doi:10.1103/physrevlett.73.814 · Cited by 954 · see citing works

Bayesian decision theory in sensorimotor control

Kording, K. P., & Wolpert, D. M. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.003 · Cited by 866 · see citing works

An emergent model of orientation selectivity in cat visual cortical simple cells

Somers, D., Nelson, S., & Sur, M. (1995) · The Journal of Neuroscience · doi:10.1523/jneurosci.15-08-05448.1995 · Cited by 860 · see citing works

Pyramidal Neuron as Two-Layer Neural Network

Poirazi, P., Brannon, T., & Mel, B. W. (2003) · Neuron · doi:10.1016/s0896-6273(03)00149-1 · Cited by 792 · see citing works

Noise characteristics and prior expectations in human visual speed perception

Stocker, A. A., & Simoncelli, E. P. (2006) · Nature Neuroscience · doi:10.1038/nn1669 · Cited by 780 · see citing works

Spike Timing-Dependent Plasticity: From Synapse to Perception

Dan, Y., & Poo, M.-M. (2006) · Physiological Reviews · doi:10.1152/physrev.00030.2005 · Cited by 675 · see citing works

Efficient coding of natural sounds

Lewicki, M. S. (2002) · Nature Neuroscience · doi:10.1038/nn831 · Cited by 667 · see citing works

Solving the Distal Reward Problem through Linkage of STDP and Dopamine Signaling

Izhikevich, E. M. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl152 · Cited by 664 · see citing works

Redundancy reduction revisited

Barlow, H. B. (2001) · Network Computation in Neural Systems · doi:10.1080/net.12.3.241.253 · Cited by 608 · see citing works

Cascade Models of Synaptically Stored Memories

Fusi, S., Drew, P. J., & Abbott, L. F. (2005) · Neuron · doi:10.1016/j.neuron.2005.02.001 · Cited by 569 · see citing works

Parallel distributed processing: explorations in the microstructure of cognition. Volume 1. Foundations

Rumelhart, D. E., & McClelland, J. L. (1986) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · Cited by 553 · see citing works

Towards a Theory of Early Visual Processing

Atick, J. J., & Redlich, A. (1990) · Neural Computation · doi:10.1162/neco.1990.2.3.308 · Cited by 552 · see citing works

Flexible control of mutual inhibition: a neural model of two-interval discrimination

Machens, C. K., Romo, R., & Brody, C. D. (2005) · Science · doi:10.1126/science.1104171 · Cited by 535 · see citing works

Modelling the Power Spectra of Natural Images: Statistics and Information

van der Schaaf, A., & van Hateren, J. H. (1996) · Vision Research · doi:10.1016/0042-6989(96)00002-8 · Cited by 528 · see citing works

The role of neuronal synchronization in selective attention

Womelsdorf, T., & Fries, P. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.02.002 · Cited by 511 · see citing works

Amplitude spectra of natural images

Tolhurst, D. J., Tadmor, Y., & Chao, T. (1992) · Ophthalmic and Physiological Optics · doi:10.1111/j.1475-1313.1992.tb00296.x · Cited by 508 · see citing works

Cortical Development and Remapping through Spike Timing-Dependent Plasticity

Song, S., & Abbott, L. F. (2001) · Neuron · doi:10.1016/s0896-6273(01)00451-2 · Cited by 477 · see citing works

Probabilistic Models of the Brain : Perception and Neural Function

Rao, R. P. N., Olshausen, B. A., & Lewicki, M. S. (2002) · Cited by 385 · see citing works

Processing of expected and unexpected events during conditioning and attention: A psychophysiological theory.

Grossberg, S. (1982) · Psychological Review · doi:10.1037/0033-295x.89.5.529 · Cited by 373 · see citing works

Spike-Timing-Dependent Plasticity in Balanced Random Networks

Morrison, A., Aertsen, A., & Diesmann, M. (2007) · Neural Computation · doi:10.1162/neco.2007.19.6.1437 · Cited by 367 · see citing works

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 · see citing works

Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions

Sharpee, T. O., Rust, N. C., & Bialek, W. (2004) · Neural Computation · doi:10.1162/089976604322742010 · Cited by 307 · see citing works

Learning in Neural Networks with Material Synapses

Amit, D., & Fusi, S. (1994) · Neural Computation · doi:10.1162/neco.1994.6.5.957 · Cited by 299 · see citing works

New perspectives on the mechanisms for orientation selectivity

Sompolinsky, H., & Shapley, R. M. (1997) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(97)80031-1 · Cited by 297 · see citing works

Untangling Dendrites with Quantitative Models

Segev, I., & London, M. (2000) · Science · doi:10.1126/science.290.5492.744 · Cited by 287 · see citing works

Statistical models for neural encoding, decoding, and optimal stimulus design

Paninski, L., Pillow, J. W., & Lewi, J. (2007) · Progress in brain research · doi:10.1016/s0079-6123(06)65031-0 · Cited by 284 · see citing works

Fly photoreceptors demonstrate energy-information trade-offs in neural coding

Niven, J. E., Anderson, J. C., & Laughlin, S. B. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050116 · Cited by 272 · see citing works

Physiological Gain Leads to High ISI Variability in a Simple Model of a Cortical Regular Spiking Cell

Troyer, T. W., & Miller, K. D. (1997) · Neural Computation · doi:10.1162/neco.1997.9.5.971 · Cited by 246 · see citing works

A Model of V4 Shape Selectivity and Invariance

Cadieu, C. F., Kouh, M., Pasupathy, A., Connor, C. E., Riesenhuber, M., & Poggio, T. (2007) · Journal of Neurophysiology · doi:10.1152/jn.01265.2006 · Cited by 226 · see citing works

Generative models for discovering sparse distributed representations

Hinton, G. E., & Ghahramani, Z. (1997) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.1997.0101 · Cited by 225 · see citing works

Processing of natural time series of intensities by the visual system of the blowfly

van Hateren, J. H. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00105-3 · Cited by 216 · see citing works

A detailed model of the primary visual pathway in the cat: comparison of afferent excitatory and intracortical inhibitory connection schemes for orientation selectivity

Wörgötter, F., & Koch, C. (1991) · Journal of Neuroscience · doi:10.1523/jneurosci.11-07-01959.1991 · Cited by 204 · see citing works

Evolutionary expansion and anatomical specialization of synapse proteome complexity

Emes, R. D., Pocklington, A., Anderson, C. N. G., Bayés, À., Collins, M., Vickers, C., Croning, M., Malik, B., Choudhary, J., Armstrong, J., et al. (2008) · Nature Neuroscience · doi:10.1038/nn.2135 · Cited by 202 · see citing works

Complex cells as cortically amplified simple cells

Chance, F. S., Nelson, S. B., & Abbott, L. F. (1999) · Nature Neuroscience · doi:10.1038/6381 · Cited by 196 · see citing works

Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus

Dong, D. W., & Atick, J. J. (1995) · Network Computation in Neural Systems · doi:10.1088/0954-898x_6_2_003 · Cited by 183 · see citing works

Solving the distal reward problem through linkage of STDP and dopamine signaling

Izhikevich, E. M. (2007) · BMC Neuroscience · doi:10.1186/1471-2202-8-s2-s15 · Cited by 168 · see citing works

An egalitarian network model for the emergence of simple and complex cells in visual cortex

Tao, L., Shelley, M., McLaughlin, D. W., & Shapley, R. M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2036460100 · Cited by 142 · see citing works

Redundancy reduction revisited

Barlow, H. (2001) · Network Computation in Neural Systems · doi:10.1088/0954-898x/12/3/301 · Cited by 139 · see citing works

Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates

Fusi, S. (2002) · Biological Cybernetics · doi:10.1007/s00422-002-0356-8 · Cited by 131 · see citing works

A Cost–Benefit Analysis of Neuronal Morphology

Wen, Q., & Chklovskii, D. B. (2008) · Journal of Neurophysiology · doi:10.1152/jn.00280.2007 · Cited by 126 · see citing works

Enhancement of Synchronization in a Hybrid Neural Circuit by Spike-Timing Dependent Plasticity

Nowotny, T., Zhigulin, V. P., Selverston, A. I., Abarbanel, H. D. I., & Rabinovich, M. I. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-30-09776.2003 · Cited by 121 · see citing works

Cortical Cells Should Fire Regularly, But Do Not

Softky, W. R., & Koch, C. (1992) · Neural Computation · doi:10.1162/neco.1992.4.5.643 · Cited by 115 · see citing works

Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons

Brunel, N. (2000) · Journal of Physiology-Paris · doi:10.1016/s0928-4257(00)01084-6 · Cited by 108 · see citing works

Understanding Layer 4 of the Cortical Circuit: A Model Based on Cat V1

Miller, K. D. (2002) · Cerebral Cortex · doi:10.1093/cercor/13.1.73 · Cited by 75 · see citing works

Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus

Dong, D. W., & Atick, J. J. (1995) · Network Computation in Neural Systems · doi:10.1088/0954-898x/6/2/003 · Cited by 72 · see citing works

A Universal History of Infamy

Borges, J. L. (1935) · Medical Entomology and Zoology · Cited by 55 · see citing works

A Universal History of Infamy

Corvalán, O. (1974) · Hispanic American Historical Review · doi:10.1215/00182168-54.1.196 · Cited by 53 · see citing works

Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Simulation Results

Buchs, N. J., & Senn, W. (2002) · Journal of Computational Neuroscience · doi:10.1023/a:1020210230751 · Cited by 49 · see citing works

Structure of Spontaneous UP and DOWN Transitions Self-Organizing in a Cortical Network Model

Kang, S., Kitano, K., & Fukai, T. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000022 · Cited by 37 · see citing works

How tightly tuned are network parameters? Insight from computational and experimental studies in small rhythmic motor networks

Marder, E. E., Tobin, A.-E., & Grashow, R. G. (2007) · Progress in brain research · doi:10.1016/s0079-6123(06)65012-7 · Cited by 33 · see citing works

Cognitive computational neuroscience

Kriegeskorte, N., & Douglas, P. K. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0210-5 · Cited by 535 · see citing works

Connecting a Connectome to Behavior: An Ensemble of Neuroanatomical Models of C. elegans Klinotaxis

Izquierdo, E. J., & Beer, R. D. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002890 · Cited by 84 · see citing works

2022 roadmap on neuromorphic computing and engineering

Christensen, D. V., Dittmann, R., Linares-Barranco, B., Sebastian, A., Le Gallo, M., Redaelli, A., Slesazeck, S., Mikolajick, T., Spiga, S., Menzel, S., et al. (2022) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/ac4a83

Cognitive computational neuroscience

Kriegeskorte, N., & Douglas, P. K. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0210-5 · Cited by 535 · see citing works

Cognitive Neuroscience: The Biology of the Mind and Findings and Current Opinion in Cognitive Neuroscience

Milner, D. (1998) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(98)01226-1 · Cited by 14 · see citing works

Principles of Computational Modeling in Neuroscience * David Sterratt, Bruce Graham, Andrew Gillies and David Willshaw

Shen, L. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs003

The 8thannual computational and systems neuroscience (Cosyne) meeting

Histed, M. H., & Pillow, J. W. (2011) · Neural Systems & Circuits · doi:10.1186/2042-1001-1-8

Computational Neuroscience: From Biology to Cognition

O’Reilly, R. C., & Munakata, Y. (2005) · Encyclopedia of Cognitive Science · doi:10.1002/0470018860.s00051 · Cited by 1 · see citing works