Self-Organization and Associative Memory

Deep learning in neural networks: an overview

Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works

Nonlinear Dimensionality Reduction by Locally Linear Embedding

Roweis, S. T., & Saul, L. K. (2000) · Science · doi:10.1126/science.290.5500.2323 · Cited by 14,965 · see citing works

The self-organizing map

Kohonen, T. (1990) · Proceedings of the IEEE · doi:10.1109/5.58325 · Cited by 8,414 · see citing works

Whatever next? Predictive brains, situated agents, and the future of cognitive science

Clark, A. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x12000477 · Cited by 5,924 · see citing works

An efficient k-means clustering algorithm: analysis and implementation

Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, A. Y. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017616 · Cited by 5,660 · see citing works

Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory

McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995) · Psychological Review · doi:10.1037/0033-295x.102.3.419 · Cited by 5,256 · see citing works

Introduction to multi-layer feed-forward neural networks

Svozil, D., Kvasnicka, V., & Pospichal, J. (1997) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(97)00061-0 · Cited by 1,600 · see citing works

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 · 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

A ROWS is a ROSE: Spelling, sound, and reading

van Orden, G. C. (1987) · Memory & Cognition · doi:10.3758/bf03197716 · Cited by 867 · see citing works

Perspectives on system identification

Ljung, L. (2010) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2009.12.001 · Cited by 707 · see citing works

Schizophrenia, sensory gating, and nicotinic receptors

Adler, L. E., Olincy, A., Waldo, M., Harris, J. G., Griffith, J., Stevens, K., Flach, K., Nagamoto, H., Bickford, P., Leonard, S., et al. (1998) · Schizophrenia Bulletin · doi:10.1093/oxfordjournals.schbul.a033320 · Cited by 690 · see citing works

The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming

Revonsuo, A. (2000) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00004015 · Cited by 676 · see citing works

Introduction to neural networks

Cross, S. S., Harrison, R. F., & Kennedy, R. L. (1995) · The Lancet · doi:10.1016/s0140-6736(95)91746-2 · Cited by 615 · see citing works

The role of visual experience in the development of columns in cat visual cortex

Crair, M. C., Gillespie, D. C., & Stryker, M. P. (1998) · Science · doi:10.1126/science.279.5350.566 · Cited by 578 · see citing works

Cortex and memory: emergence of a new paradigm

Fuster, J. M. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21280 · Cited by 559 · see citing works

The mechanisms for pattern completion and pattern separation in the hippocampus

Rolls, E. T. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2013.00074 · Cited by 545 · see citing works

Impaired processing of rapid stimulus sequences in dyslexia

Hari, R., & Renvall, H. (2001) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01801-5 · Cited by 527 · see citing works

Laminar selectivity of the cholinergic suppression of synaptic transmission in rat hippocampal region CA1: computational modeling and brain slice physiology

Hasselmo, M., & Schnell, E. (1994) · The Journal of Neuroscience · doi:10.1523/jneurosci.14-06-03898.1994 · Cited by 466 · see citing works

A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives

Haynes, J.-D. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.025 · Cited by 402 · see citing works

The Hebbian paradigm reintegrated: local reverberations as internal representations

Amit, D. J. (1995) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00040164 · Cited by 388 · see citing works

Novelty or Surprise?

Barto, A., Mirolli, M., & Baldassarre, G. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00907 · Cited by 397 · see citing works

Data mining and machine learning in astronomy

BALL, N. M., & BRUNNER, R. J. (2010) · International Journal of Modern Physics D · doi:10.1142/s0218271810017160 · Cited by 383 · see citing works

Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods

Alzahrani, S. M., Salim, N., & Abraham, A. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2134847 · Cited by 299 · see citing works

Deep reinforcement learning and its neuroscientific implications

Botvinick, M., Wang, J. X., Dabney, W., Miller, K. J., & Kurth-Nelson, Z. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.014 · Cited by 269 · see citing works

Pattern separation, completion, and categorisation in the hippocampus and neocortex

Rolls, E. T. (2016) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2015.07.008 · Cited by 234 · see citing works

An analysis of customer retention and insurance claim patterns using data mining: a case study

Smith, K. A., Willis, R. J., & Brooks, M. (2000) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2600941 · Cited by 137 · see citing works

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 · see citing works

Multiple perspectives on word production

Levelt, W. J. M., Roelofs, A., & Meyer, A. S. (1999) · Behavioral and Brain Sciences · doi:10.1017/s0140525x99451775 · Cited by 107 · see citing works

Learning-induced dynamic receptive field changes in primary auditory cortex of the unanaesthetized Mongolian gerbil

Ohl, F. W., & Scheich, H. (1997) · Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology · doi:10.1007/s003590050150 · Cited by 85 · see citing works

Nonlinear dimensionality reduction and mapping of compound libraries for drug discovery

Reutlinger, M., & Schneider, G. (2012) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2011.12.006 · Cited by 72 · see citing works

Bayesian spiking neurons II: learning

Deneve, S. (2008) · Neural Computation · doi:10.1162/neco.2008.20.1.118 · Cited by 71 · see citing works

Identification of ischemic heart disease via machine learning analysis on magnetocardiograms

Tantimongcolwat, T., Naenna, T., Isarankura-Na-Ayudhya, C., Embrechts, M. J., & Prachayasittikul, V. (2008) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2008.04.009 · Cited by 57 · see citing works

Mapping Selective Logging in Mixed Deciduous Forest

Lippitt, C. D., Rogan, J., Li, Z., Eastman, J. R., & Jones, T. G. (2008) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.74.10.1201 · Cited by 56 · see citing works

Web process inspection using neural classification of scattering light

Olsson, L. J., & Gruber, S. (1993) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.222644 · Cited by 40 · see citing works

Sky Surveys

Djorgovski, S. G., Mahabal, A., Drake, A., Graham, M., & Donalek, C. (2013) · Planets, Stars and Stellar Systems · doi:10.1007/978-94-007-5618-2_5 · Cited by 37 · see citing works

Noninvasive monitoring of blood glucose using color-coded photoplethysmographic images of the illuminated fingertip within the visible and near-infrared range: opportunities and questions

Vahlsing, T., Delbeck, S., Leonhardt, S., & Heise, H. M. (2018) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818798347 · Cited by 28 · see citing works

On the analysis of the inverse problem of metabolic pathways using artificial neural networks

Mendes, P., & Kell, D. B. (1996) · Biosystems · doi:10.1016/0303-2647(95)01565-5 · Cited by 24 · see citing works

Differential protein expression profiles between Plasmodium falciparum parasites isolated from subjects presenting with pregnancy-associated malaria and uncomplicated malaria in Benin

Bertin, G. I., Sabbagh, A., Guillonneau, F., Jafari-Guemouri, S., Ezinmegnon, S., Federici, C., Hounkpatin, B., Fievet, N., & Deloron, P. (2013) · The Journal of Infectious Diseases · doi:10.1093/infdis/jit377 · Cited by 21 · see citing works

Modeling chemical reactions for drug design

Gasteiger, J. (2007) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-006-9097-4 · Cited by 19 · see citing works

LSISOM — A Latent Semantic Indexing Approach to Self-Organizing Maps of Document Collections

Ampazis, N., & Perantonis, S. J. (2004) · Neural Processing Letters · doi:10.1023/b:nepl.0000023449.95030.8f · Cited by 18 · see citing works