Discussion: McCulloch-Pitts and related neural nets from 1943 to 1989

Optimization by Simulated Annealing

Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134 · see citing works

Learning representations by back-propagating errors

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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 logical calculus of the ideas immanent in nervous activity

McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566 · see citing works

Learning Internal Representations by Error Propagation

Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1985) · doi:10.21236/ada164453 · Cited by 16,501 · see citing works

Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations

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The perceptron: A probabilistic model for information storage and organization in the brain.

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The Organization of Behavior

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On computable numbers, with an application to the entscheidungsproblem

Turing, A. M. (1937) · Proceedings of the London Mathematical Society · doi:10.1112/plms/s2-42.1.230 · Cited by 8,283 · see citing works

“Neural” computation of decisions in optimization problems

Hopfield, J. J., & Tank, D. W. (1985) · Biological Cybernetics · doi:10.1007/bf00339943 · Cited by 6,035 · see citing works

Adaptive switching circuits

WIDROW, B., & HOFF, M. E. (1960) · doi:10.21236/ad0241531 · Cited by 4,009 · see citing works

An Effective Heuristic Algorithm for the Traveling-Salesman Problem

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Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons

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Solvable Model of a Spin-Glass

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Perceptrons: An Introduction to Computational Geometry

Minsky, M., & Papert, S. A. (1969) · Cited by 3,273 · see citing works

A theory of cerebellar cortex

Marr, D. (1969) · The Journal of Physiology · doi:10.1113/jphysiol.1969.sp008820 · Cited by 3,253 · see citing works

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 · see citing works

The nature of explanation

Craik, K. J. W. (1943) · Cited by 1,845 · see citing works

A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue

Wilson, H. R., & Cowan, J. D. (1973) · Kybernetik · doi:10.1007/bf00288786 · Cited by 1,823 · see citing works

Single Units and Sensation: A Neuron Doctrine for Perceptual Psychology?

Barlow, H. B. (1972) · Perception · doi:10.1068/p010371 · Cited by 1,714 · see citing works

Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components

von Neumann, J. (1956) · Cited by 1,665 · see citing works

Behavior, Purpose and Teleology

Rosenblueth, A., Wiener, N., & Bigelow, J. (1943) · Philosophy of Science · doi:10.1086/286788 · Cited by 1,579 · see citing works

Storing Infinite Numbers of Patterns in a Spin-Glass Model of Neural Networks

Amit, D. J., Gutfreund, H., & Sompolinsky, H. (1985) · Physical Review Letters · doi:10.1103/physrevlett.55.1530 · Cited by 1,063 · see citing works

Organization of Behavior.

Kaplan, S. J. (1950) · PubMed Central · Cited by 1,054 · see citing works

Non-Holographic Associative Memory

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The capacity of the Hopfield associative memory

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How patterned neural connections can be set up by self-organization

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An analogue approach to the travelling salesman problem using an elastic net method

Durbin, R. M., & Willshaw, D. J. (1987) · Nature · doi:10.1038/326689a0 · Cited by 810 · see citing works

The General and Logical Theory of Automata

von Neumann, J. (2017) · doi:10.4324/9781315130569-15 · Cited by 728 · see citing works

Stability by Liapunov's Direct Method with Applications

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Stability by Liapunov's Direct Method With Applications

Salle, J. L., Lefschetz, S., & Alverson, R. C. (1962) · Physics Today · doi:10.1063/1.3057800 · Cited by 704 · see citing works

NETtalk: a parallel network that learns to read aloud

Sejnowski, T. J., & Rosenberg, C. (1988) · Cited by 671 · see citing works

On Computable Numbers, with an Application to the Entscheidungsproblem. A Correction

Turing, A. M. (1938) · Proceedings of the London Mathematical Society · doi:10.1112/plms/s2-43.6.544 · Cited by 606 · see citing works

A mathematical theory of visual hallucination patterns

Ermentrout, G. B., & Cowan, J. D. (1979) · Biological Cybernetics · doi:10.1007/bf00336965 · Cited by 600 · see citing works

Outline of a theory of thought-processes and thinking machines

Caianiello, E. R. (1961) · Journal of Theoretical Biology · doi:10.1016/0022-5193(61)90046-7 · Cited by 500 · see citing works

Associative Memory

Kohonen, T. (1977) · Communication and cybernetics · doi:10.1007/978-3-642-96384-1 · Cited by 465 · see citing works

Androgens Prevent Normally Occurring Cell Death in a Sexually Dimorphic Spinal Nucleus

Nordeen, E. J., Nordeen, K. W., Sengelaub, D. R., & Arnold, A. P. (1985) · Science · doi:10.1126/science.4023706 · Cited by 464 · see citing works

Associative memory. A system-theoretical approach

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The physiology of nerve cells

Paul, D. H. (1975) · Cited by 396 · see citing works

Properties of a mass of cells capable of regenerating pulses

Beurle, R. L. (1956) · Philosophical transactions of the Royal Society of London. Series B, Biological sciences · doi:10.1098/rstb.1956.0012 · Cited by 386 · see citing works

The Physiology of Nerve Cells

Case, J. F., & Eccles, J. C. (1957) · AIBS Bulletin · doi:10.2307/1292338 · Cited by 376 · see citing works

Die Lernmatrix

Steinbuch, K. (1961) · Kybernetik · doi:10.1007/bf00293853 · Cited by 344 · see citing works

Cerebral mechanisms in behavior: The Hixon symposium

Krendel, E. S. (1952) · Journal of the Franklin Institute · doi:10.1016/0016-0032(52)90728-x · Cited by 317 · see citing works

A Set of Five Independent Postulates for Boolean Algebras, with Application to Logical Constants

Sheffer, H. M. (1913) · Transactions of the American Mathematical Society · doi:10.1090/s0002-9947-1913-1500960-1 · Cited by 299 · see citing works

A marker induction mechanism for the establishment of ordered neural mappings: its application to the retinotectal problem

Willshaw, D. J., & von der Malsburg, C. (1979) · Philosophical transactions of the Royal Society of London. Series B, Biological sciences · doi:10.1098/rstb.1979.0056 · Cited by 270 · see citing works

Reliable Computation in the Presence of Noise

Hamming, R. W., Winograd, S., & Cowan, J. D. (1964) · Mathematics of Computation · doi:10.2307/2003803 · Cited by 256 · see citing works

Associative Holographic Memories

Габор, Д. (1969) · IBM Journal of Research and Development · doi:10.1147/rd.132.0156 · Cited by 182 · see citing works

A statistical theory of short and long term memory

Little, W. A., & Shaw, G. L. (1975) · Behavioral Biology · doi:10.1016/s0091-6773(75)90122-4 · Cited by 154 · see citing works

Temporal oscillations in neuronal nets

Ermentrout, G. B., & Cowan, J. D. (1979) · Journal of Mathematical Biology · doi:10.1007/bf00275728 · Cited by 130 · see citing works

Internal representations for associative memory

Baum, E. B., Moody, J. E., & Wilczek, F. A. (1988) · Biological Cybernetics · doi:10.1007/bf00332910 · Cited by 129 · see citing works

The organisation of neurones: A co-operative analogy

Cragg, B. G., & Temperley, H. N. V. (1954) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(54)90008-5 · Cited by 86 · see citing works

A memory storage model utilizing spatial correlation functions

Anderson, J. (1968) · Kybernetik · doi:10.1007/bf00288902 · Cited by 74 · see citing works

The classification of modifiable synapses and their use in models for conditioning

Brindley, G. S. (1967) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1967.0070 · Cited by 58 · see citing works

Statistical Mechanics of Nervous Nets

Cowan, J. D. (1968) · Springer eBooks · doi:10.1007/978-3-642-87596-0_17 · Cited by 46 · see citing works

A comparison of algorithms for neuron-like cells

Parker, D. B. (1986) · AIP conference proceedings · doi:10.1063/1.36233 · Cited by 44 · see citing works

MEMORY: THE ANALOGY WITH FERROMAGNETIC HYSTERESIS

Cragg, B. G., & Temperley, H. N. V. (1955) · Brain · doi:10.1093/brain/78.2.304 · Cited by 39 · see citing works

A STATISTICAL MECHANICS OF NERVOUS ACTIVITY.

Cowan, J. D. (1969) · Cited by 35 · see citing works

The stability of a randomly assembled nerve-network

Ashby, W. R. (1950) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(50)90085-x · Cited by 24 · see citing works

The Problem of Organismic Reliability

Cowan, J. D. (1965) · Progress in brain research · doi:10.1016/s0079-6123(08)60154-5 · Cited by 17 · see citing works

The origin and evolution of a strange attractor in the system of coupled oscillators

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Application of machine learning in intelligent fish aquaculture: A review

Zhao, S., Zhang, S., Liu, J., Wang, H., Jia, Z., Li, D., & Zhao, R. (2021) · Aquaculture · doi:10.1016/j.aquaculture.2021.736724 · Cited by 324 · see citing works

The First Computational Theory of Mind and Brain: A Close Look at Mcculloch and Pitts's “Logical Calculus of Ideas Immanent in Nervous Activity”

Piccinini, G. (2004) · Synthese · doi:10.1023/b:synt.0000043018.52445.3e · Cited by 215 · see citing works

Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset

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Applications MLP and Other Methods in Artificial Intelligence of Fruit and Vegetable in Convective and Spray Drying

Przybył, K., & Koszela, K. (2023) · Applied Sciences · doi:10.3390/app13052965 · Cited by 41 · see citing works

Computational evaluation of different numerical tools for the prediction of proximal femur loads from bone morphology

Garijo, N., Martínez, J. M., García‐Aznar, J. M., & Pérez, M. Á. (2013) · Computer Methods in Applied Mechanics and Engineering · doi:10.1016/j.cma.2013.10.005 · Cited by 37 · see citing works

Design Guidelines for Mammogram-Based Computer-Aided Systems Using Deep Learning Techniques

Azour, F., & Boukerche, A. (2022) · IEEE Access · doi:10.1109/access.2022.3151830 · Cited by 35 · see citing works

Fundamental constraints to the logic of living systems

Solé, R., Kempes, C. P., Corominas-Murtra, B., De Domenico, M., Kolchinsky, A., Lachmann, M., Libby, E., Saavedra, S., Smith, E., & Wolpert, D. (2024) · Interface Focus · doi:10.1098/rsfs.2024.0010 · Cited by 34 · see citing works

Some neural networks compute, others don’t

Piccinini, G. (2007) · Neural Networks · doi:10.1016/j.neunet.2007.12.010 · Cited by 31 · see citing works

Intelligent Algorithms Enable Photocatalyst Design and Performance Prediction

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Subject-specific musculoskeletal loading of the tibia: Computational load estimation

Garijo, N., Verdonschot, N. J. J., Engelborghs, K., García‐Aznar, J. M., & Pérez, M. Á. (2016) · Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · doi:10.1016/j.jmbbm.2016.08.026 · Cited by 27 · see citing works

Appraisal of Cu( ii ) adsorption by graphene oxide and its modelling via artificial neural network

Zhang, Y., Dai, M., Liu, K., Peng, C., Du, Y., Chang, Q., Ali, I., Naz, I., & Saroj, D. P. (2019) · RSC Advances · doi:10.1039/c9ra06079k · Cited by 22 · see citing works

Synapse Models for Neural Networks: From Ion Channel Kinetics to Multiplicative Coefficient wij

Chapeau‐Blondeau, F., & Chambet, N. (1995) · Neural Computation · doi:10.1162/neco.1995.7.4.713 · Cited by 22 · see citing works

Safety Risk Assessment Using a BP Neural Network of High Cutting Slope Construction in High-Speed Railway

Huang, J., Zeng, X., Fu, J. W., Yang, H., & Chen, H. (2022) · Buildings · doi:10.3390/buildings12050598 · Cited by 18 · see citing works

Neural networks: New tools for modelling and data analysis in science

Clark, J. W. (2007) · Springer eBooks · doi:10.1007/bfb0104277 · Cited by 7 · see citing works

Architecting for Artificial Intelligence with Emerging Nanotechnology

Kulkarni, S., Bhat, S., & Moritz, C. A. (2021) · ACM Journal on Emerging Technologies in Computing Systems · doi:10.1145/3445977 · Cited by 6 · see citing works

A neural network approach for determining spatial and geometry dependent Green's functions for thermal stress approximation in power plant header components

Rouse, J. P., Hyde, C. J., & Morris, A. (2018) · International Journal of Pressure Vessels and Piping · doi:10.1016/j.ijpvp.2018.10.020 · Cited by 6 · see citing works

Stochastic formulation for a partial neural circuit of C. elegans

Iwasaki, Y. (2003) · Bulletin of Mathematical Biology · doi:10.1016/j.bulm.2003.10.007 · Cited by 5 · see citing works

Two-dimensional spectral image calibration based on feed-forward neural network

Li, M., Haerken, H., Guo, P., Duan, F., Yin, Q., & Zheng, X. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7966386 · Cited by 2 · see citing works

Hypnosis modelling in neural networks

Kuzin, I. A. (1995) · Bulletin of Mathematical Biology · doi:10.1007/bf02458314 · Cited by 2 · see citing works

From Mushroom-Peaches to Disease Prediction: Deep Learning Approaches

Loukil, Z., & Mirza, Q. K. A. (2022) · International Conference on Future Internet of Things and Cloud (FiCloud) · doi:10.1109/ficloud57274.2022.00024

Neuro-Inspired Energy-Efficient Computing Platforms

Causo, M. (2017) · theses.fr (ABES) · doi:10.70675/0368b25fz8da5z44e2za6b7zadd451c023e2

Comparing hedonic and machine learning models in residential property valuation: evidence from sub-market analysis in Italy

Maselli, G., Gabrielli, L., & Nestıcò, A. (2026) · International Journal of Housing Markets and Analysis · doi:10.1108/ijhma-03-2026-0065

The McCulloch–Pitts neural net

Rowe, G. (1994) · doi:10.1093/oso/9780198596882.003.0017

Warren McCulloch and Walter Pitts: A Logical Calculus of the Ideas Immanent in Nervous Activity

Palm, G. (1986) · Springer eBooks · doi:10.1007/978-3-642-70911-1_14 · Cited by 23 · see citing works

70th Anniversary of Publication: Warren McCulloch & Walter Pitts - A Logical Calculus of the Ideas Immanent in Nervous Activity

Pospı́chal, J., & Kvasnička, V. (2014) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-10783-7_1 · Cited by 11 · see citing works

From McCulloch–Pitts Neurons Toward Biology

Graben, P. B., & Wright, J. (2011) · Bulletin of Mathematical Biology · doi:10.1007/s11538-011-9629-5 · Cited by 7 · see citing works

Mc C ulloch– P itts Neurons

Anderson, J. A. (2005) · Encyclopedia of Cognitive Science · doi:10.1002/0470018860.s00353 · Cited by 7 · see citing works