The DOI matches its Crossref record; 14 of the 15 references it cites were found in a registry or an index.
The perceptron: A probabilistic model for information storage and organization in the brain.
Abstract
If we are eventually to understand the capability of higher organisms for perceptual recognition, generalization, recall, and thinking, we must first have answers to three fundamental questions: 1. How is information about the physical world sensed, or detected, by the biological system? 2. In what form is information stored, or remembered? 3. How does information contained in storage, or in memory, influence recognition and behavior? The first of these questions is in the
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
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
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
Representation of Events in Nerve Nets and Finite Automata
Kleene, S. (1951) · Princeton University Press eBooks · doi:10.1515/9781400882618-002 · Cited by 1,927
Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components
von Neumann, J. (1956) · Cited by 1,652
(1952) · Medical Entomology and Zoology · Cited by 1,436
Kneale, M., & von Hayek, F. A. (1954) · The Philosophical Quarterly · doi:10.2307/2216396 · Cited by 494
Human Nature in the Light of Psychopathology
Goldstein, K. (1940) · Harvard University Press eBooks · doi:10.4159/harvard.9780674492103 · Cited by 286
Milner, P. M. (1957) · Psychological Review · doi:10.1037/h0042287 · Cited by 235
Human Nature in the Light of Psychopathology.
L., H. A., & Goldstein, K. (1941) · The Journal of Philosophy · doi:10.2307/2017294 · Cited by 126
McCulloch, W. S. (1950) · dialectica · doi:10.1111/j.1746-8361.1950.tb01019.x · Cited by 73
Cited by
Sorted by citations
Items 9,201–9,300 of 13,333
Parameter Inference for an Astrocyte Model using Machine Learning ApproachesPreprint
Fritschi, L., & Lenk, K. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.16.540982 · Cited by 1
InDL: A New Dataset and Benchmark for In-Diagram Logic Interpretation based on Visual IllusionPreprint
Yang, H., Wang, W., Cao, Z., Duan, Z., & Liu, X. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.17716 · Cited by 1
Golroudbari, A. A., & Sabour, M. H. (2023) · doi:10.22541/au.168727976.63672670/v1 · Cited by 1
de Souza, A. T. (2023) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.59.2023.tde-27072023-075811 · Cited by 1
Optimum Regularization Parameter C in Support Vector Machine (SVM) Binary Classification
Ahmed, I. (2023) · doi:10.32920/24050733 · Cited by 1
Deep learning and data warehousing techniques applied to real data in the medical domain
de Lima, D. M. (2023) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.55.2023.tde-01092023-164636 · Cited by 1
The Gap between Deep Learning and the Nervous SystemPreprint
Molina, E., & Rodriguez, X. (2023) · Preprints.org · doi:10.20944/preprints202309.0024.v1 · Cited by 1
A teoria computacional da mente e o dilema de Searle
Watanabe, C. H. A. (2021) · doi:10.47749/t/unicamp.2021.1235358 · Cited by 1
Multi-objective differentiable neural architecture search
Adamski, R. (2022) · doi:10.47749/t/unicamp.2022.1243400 · Cited by 1
Real-World Applications of Artificial Intelligence and Blockchain in HealthcarePreprint
Naraghi, A., Nourmohammadi, R., & Behravan, I. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4650201 · Cited by 1
Spatial forecasting of online food delivery demandPreprint
Bezerra, H. M., & Cancho, V. G. (2024) · Research Square · doi:10.21203/rs.3.rs-3903945/v1 · Cited by 1
Herlitzius, T., Noack, P., Späth, J., Barth, R., Wolfert, J., Bernardi, A., Traphöner, R., Martini, D., Kunisch, M., Trapp, M., et al. (2023) · Springer eBooks · doi:10.1007/978-3-662-67086-6_3 · Cited by 1
Ali, H. O. (2023) · theses.fr (ABES) · doi:10.70675/cd750917z1bb2z408bz88f4z339cba0c09bb · Cited by 1
Neural Networks for Structure-Informed Prediction of Formation Energy (employed in SIPFENN)
Krajewski, A. M., Siegel, J. W., Xu, J., & Liu, Z. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4006802 · Cited by 1
The Social Structure of Scientific Evaluation: AI, Benchmarking, and the Deep Learning MonoculturePreprint
Koch, B., & Peterson, D. (2024) · SocArXiv (OSF Preprints) · doi:10.31235/osf.io/s4qdy · Cited by 1
Ramzi, Z. (2022) · theses.fr (ABES) · doi:10.70675/17b99897zf4a1z45d6zb759zba72ce6bda41 · Cited by 1
Milbrath, J., Rivard, J., & Straub, J. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2404.11714 · Cited by 1
Population synthesis of Galactic pulsars with machine learningPreprint
Ronchi, M. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2404.15953 · Cited by 1
Alencar, J. P., Mendes, G. M. P., Mattos, C. L. C., Gomes, J. P. P., Babadopulos, L. F. D. A. L., Soares, J. B., & Veras, M. B. A. (2024) · Research Square · doi:10.21203/rs.3.rs-4437158/v1 · Cited by 1
Referenciais de Formação para o Curso de Bacharelado em Inteligência Artificial
(SBC), S. B. D. C. (2024) · Sociedade Brasileira de Computação · doi:10.5753/sbc.ref.2024.139 · Cited by 1
Exploring Methods of Explainable AI
Landt-Hayen, M. (2023) · doi:10.21941/kcss/2023/5 · Cited by 1
Surrogate models, physics-informed neural networks and climate change
Secci, D. (2024) · doi:10.4995/thesis/10251/205793 · Cited by 1
Machine Learning Methods in Radio Frequency and Microwave Domain
Shanthi, P., & Adish, K. (2024) · Wiley eBooks · doi:10.1002/9781119847717.ch5 · Cited by 1
Kitzelmann, E. (2024) · Ars digitalis · doi:10.1007/978-3-658-44248-4_5 · Cited by 1
Yoosoofsah, A. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2412.00105 · Cited by 1
Blood velocity reconstruction with contrast enhanced X-ray CT
Huang, S. (2024) · theses.fr (ABES) · doi:10.70675/4949be89z5a15z40abz85f3z1a596428c00b · Cited by 1
Machine Translation, Computational Linguistics and Natural Language Processing, History of-
Léon, J. (2025) · Elsevier eBooks · doi:10.1016/b978-0-323-95504-1.00754-7 · Cited by 1
Meftah, L. H., & Cherif, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5117781 · Cited by 1
Transhumanism and Artificial Personality
Mayer, J. D., & Leichtman, M. D. (2025) · Springer eBooks · doi:10.1007/978-3-031-38971-9_2032-2 · Cited by 1
Editorial: Biologically inspired Artificial Intelligent systems: state and perspectives
Borghi, F., & Vassanelli, S. (2025) · Frontiers in Materials · doi:10.3389/fmats.2025.1568640 · Cited by 1
Herath, S., Johannsson, J. G., Shrestha, Y. R., & von Krogh, G. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5153658 · Cited by 1
Delta Rule and Backpropagation
Vanneschi, L., & Castelli, M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00334-1 · Cited by 1
Forecasting credit risk using machine learning
Zhu, Y., Chen, Y., Gong, M., & Zhou, L. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-28993-4.00198-0 · Cited by 1
Prediction of movie box office revenue based on the XGBoost-FCNN modelPreprint
Wu, F., Sun, R., & Zhang, H. (2025) · Research Square · doi:10.21203/rs.3.rs-7169537/v1 · Cited by 1
Optimizing and benchmarking the computation of the permanent of general matricesPreprint
Masschelein, C., Richer, M., & Ayers, P. W. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5639920 · Cited by 1
Two views of the brain are reconciled by a unifying principle of maximal information processingPreprint
Fosque, L. J., Shew, W. L., Ching, S., & Hengen, K. B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.25.690580 · Cited by 1
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks TrainingPreprint
Colombo, L., Pittorino, F., Zambon, D., Baldassi, C., Roveri, M., & Alippi, C. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2512.04189 · Cited by 1
Knowledge-Guided Machine Learning Models to Upscale Evapotranspiration in the U.S. MidwestPreprint
Rozanov, A., Subedi, S., Sharma, V., & Runck, B. C. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2510.11505 · Cited by 1
da Fonseca, J. B. (2006) · Cited by 1
Automated Knowledge Discovery from Functional Magnetic Resonance Images using Spatial Coherence
Mitra, P. S. (2006) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 1
Feature-Oriented Hybrid Neural Adaptive Systems and Applications
Teodorescu, H.-N., & Bonciu, C. (2000) · International series in intelligent technologies · doi:10.1007/978-1-4615-4401-2_6 · Cited by 1
Observabilité et reconstitution d'état des réseaux de distribution du futur
Biserica, M. I. (2011) · theses.fr (ABES) · doi:10.70675/e1405ef1zf64cz4c0czb258z61816d15f48e · Cited by 1
Modelling human complex traits with regression and neural-network based methods
Kelemen, M. (2020) · Apollo (University of Cambridge) · doi:10.17863/cam.72055 · Cited by 1
Neuronale Netzwerke für transiente Vorgänge im Antriebsstrang
Cimniak, V. (2023) · OPUS Publication Server of the University of Stuttgart (University of Stuttgart) · doi:10.18419/opus-13530 · Cited by 1
Orsoni, M. (2024) · AMS Dottorato Institutional Doctoral Theses Repository (University of Bologna) · doi:10.48676/unibo/amsdottorato/11482 · Cited by 1
Assessment of computer vision methods in civil engineering
Neuhausen, M. (2022) · Dokumentenrepositorium der RUB (Ruhr University Bochum) · doi:10.13154/294-9268 · Cited by 1
N2O-Emissionsreduzierung durch KI-unterstützte Regelung der biologischen Abwasserreinigung
Freyschmidt, A. (2024) · Institutional Repository of Leibniz Universität Hannover (Leibniz Universität Hannover) · doi:10.15488/18126 · Cited by 1
Machine Learning for Zero Defect Manufacturing
Vásquez Lobos, J. M. (2022) · reposiTUm (TU Wien) · doi:10.34726/hss.2022.95242 · Cited by 1
Finck, J. S. (2020) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 1
Nocetti, N. (2019) · San Andres Digital Repository (University of San Andrés) · Cited by 1
Rural Fire Detection: A close-range approach for classification and localisation
Dias, F. D. C. P. M. (2024) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 1
Bhandari, S. K. (2021) · K-State Research Exchange (Kansas State University) · Cited by 1
Moradi, E. (2021) · eScholarship@McGill (McGill) · doi:10.82308/29121 · Cited by 1
Maralbashi-Zamini, S. (2007) · doi:10.1522/030012635 · Cited by 1
What Hinders Electric Vehicle Diffusion? Insights from a Neural Network ApproachPreprint
Bonacina, M., Demir, M., Sileo, A., & Zanoni, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5426897 · Cited by 1
Zhou, X., Ai, M., Adeli, E., Zhang, Y., Liu, Y. M., & Lin, F. V. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.30.697042 · Cited by 1
Dissipative Learning: A Framework for Viable Adaptive SystemsPreprint
Caraffa, L. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2601.17933 · Cited by 1
TinyTorch: Building Machine Learning Systems from First PrinciplesPreprint
Reddi, V. J. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2601.19107 · Cited by 1
STPredict: A Python package automating spatio-temporal predictions
Oriyad, A. M., Haratian, A., Naderi, M., Rafiei, N., Meghdadi, M., Maleki, Z., & Ramazi, P. (2026) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2026.106901 · Cited by 1
5 Years of BioMedInformatics: The Impact of Artificial Intelligence
de Brevern, A. G. (2026) · BioMedInformatics · doi:10.3390/biomedinformatics6020010 · Cited by 1
Billio, M., Hu, W., Maillet, B. B., Yuan, Z., & Zhang, X. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6409375 · Cited by 1
Kassab, R. (2009) · theses.fr (ABES) · doi:10.70675/2f1cb7e4ze268z452cz9823z6653510d180e · Cited by 1
Systèmes neuromorphiques : étude et implantation de fonctions d'apprentissage et de plasticité
Daouzli, A. (2009) · theses.fr (ABES) · doi:10.70675/5abd6241z059cz4af6zafa1zb29f9a3ceff3 · Cited by 1
Gardeux, V. (2011) · theses.fr (ABES) · doi:10.70675/699b756bzefacz471az85afzce72ad1fff5e · Cited by 1
Diagnostic de groupes électrogènes diesel par analyse de la vitesse de rotation du vilebrequin
Desbazeille, M. (2010) · theses.fr (ABES) · doi:10.70675/192c25c3z00fbz4764zafa0z7368d68e7d44 · Cited by 1
Estimation et sélection en classification semi-supervisée
Vandewalle, V. (2009) · theses.fr (ABES) · doi:10.70675/fda0e593zf7e2z4ed8zb3d1zdf08dcbcbd16 · Cited by 1
Boudoin, P. (2010) · theses.fr (ABES) · doi:10.70675/79cfa5d5z1a43z464dz8b9dzdfe714de037f · Cited by 1
Motivations intrinsèques et contraintes maturationnelles pour l'apprentissage sensorimoteur
Baranès, A. (2011) · theses.fr (ABES) · doi:10.70675/64c82975zca03z4f0ezaf60zbb6b7f1b5cb8 · Cited by 1
Videau, S. (2011) · theses.fr (ABES) · doi:10.70675/278a623fz7743z453cz9a66z46d3821673c5 · Cited by 1
Sakhi, O. B. (2012) · theses.fr (ABES) · doi:10.70675/4d7a3a50z55ffz479dz9f12zfcbb3d0b9aa8 · Cited by 1
Vayre, J.-S. (2016) · theses.fr (ABES) · doi:10.70675/79f4f1daz6849z4326za4f3z54d3b3ebde2c · Cited by 1
Droniou, A. (2015) · theses.fr (ABES) · doi:10.70675/396a49b1z7704z4ad3z83b9z2ad6ced4083c · Cited by 1
Cosso, A. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2603.26813 · Cited by 1
Spatially consistent nearest neighbor representations for fine-grained classification
Leveau, V. (2016) · theses.fr (ABES) · doi:10.70675/01951667zba6dz45c9z9de0z661188dd2584 · Cited by 1
Triangular similarity metric learning : A siamese architecture approach
Zheng, L. (2016) · theses.fr (ABES) · doi:10.70675/80580525z8dc6z4240za320z94b679a5476f · Cited by 1
Discontinuous constituency parsing of morphologically rich languages
Coavoux, M. (2017) · theses.fr (ABES) · doi:10.70675/8bb6891eza6f9z4466z8da9zfab12af43750 · Cited by 1
Simulation massive de monde virtuel par système multi-agent auto-adaptatif
Rantrua, A. (2017) · theses.fr (ABES) · doi:10.70675/7c45d1f4zd132z487cza479zda396a20e3c5 · Cited by 1
Deep learning for semantic description of visual human traits
Antipov, G. (2017) · theses.fr (ABES) · doi:10.70675/bc84743fzbc0ez4d0dz976az5c0e725e5cb4 · Cited by 1
Modélisation multi-échelles et calculs parallèles appliqués à la simulation de l'activité neuronale
Bedez, M. (2015) · theses.fr (ABES) · doi:10.70675/cff0bc3cz59a2z422dza0a7z3e2e007f4e97 · Cited by 1
Vers l’universalité des représentations visuelle et multimodales
Tamaazousti, Y. (2018) · theses.fr (ABES) · doi:10.70675/6a8e2fd3zb9a1z48cfzadeez002302237caf · Cited by 1
Automatic detection of screams and shouts in the metro
Laffitte, P. (2017) · theses.fr (ABES) · doi:10.70675/0be99ab9ze604z4efez919bzcaf30fb1578b · Cited by 1
Abadi, M. (2018) · theses.fr (ABES) · doi:10.70675/36b5fc05za3e8z4136za8f9z0ac5c8d95542 · Cited by 1
Advanced machine learning techniques based on DC programming and DCA
Ho, V. T. (2017) · theses.fr (ABES) · doi:10.70675/29714118zcf60z4e45za6bfzfe9403cbf302 · Cited by 1
Foveal autoregressive neural time-series modeling
Andreux, M. (2018) · theses.fr (ABES) · doi:10.70675/e3412787zcaffz424dz9afazd4fe6349545d · Cited by 1
Gruet, M. (2018) · theses.fr (ABES) · doi:10.70675/e0bda5e6z0f99z4334z998ezab2e85979989 · Cited by 1
Garzon, F. S. (2019) · theses.fr (ABES) · doi:10.70675/77dff9c9zde36z4f7dz8d53z9ed5c3fc83f2 · Cited by 1
Guigou, F. (2019) · theses.fr (ABES) · doi:10.70675/10249c83z779az4d37zb3d0z62fa7699b461 · Cited by 1
Steganalysis and steganography by deep learning
Yedroudj, M. (2019) · theses.fr (ABES) · doi:10.70675/cfdf2ac9ze3eaz44f6zb2d0z32eecd8da6b6 · Cited by 1
Kaoutoing, M. D. (2020) · theses.fr (ABES) · doi:10.70675/28bdcd99z4ba4z4cf3za8e7z9b6f9330fd0a · Cited by 1
3D-hyperspectral imaging and optical analysis of skin for the human face
Gevaux, L. (2019) · theses.fr (ABES) · doi:10.70675/d866f6c3z43e3z48f3zb8f0z00a533f16812 · Cited by 1
Imaging of the fish embryo model and applications to toxicology
Genest, D. (2019) · theses.fr (ABES) · doi:10.70675/aaaff214zcdb9z4820zbe38z5ecda94a48fa · Cited by 1
Reinforcement learning for dialogue systems optimization with user adaptation
Carrara, N. (2019) · theses.fr (ABES) · doi:10.70675/84c4f883z5773z48d6zba77z4c53329fb3e4 · Cited by 1
Deep learning for image compression
Dumas, T. (2019) · theses.fr (ABES) · doi:10.70675/fcaa9a7ez5918z4f67z8aabz728347754f35 · Cited by 1
Multi-lingual dependency parsing : word representation and joint training for syntactic analysis
Dehouck, M. (2019) · theses.fr (ABES) · doi:10.70675/1a37f05bzfd63z4cb1zbf35zae267ad7cda7 · Cited by 1
Nachar, S. (2019) · theses.fr (ABES) · doi:10.70675/adcb4757z64b8z4412z97b0z835d33b6a710 · Cited by 1
Robust Learning of a depth map for obstacle avoidance with a monocular stabilized flying camera
Pinard, C. (2019) · theses.fr (ABES) · doi:10.70675/14bf1a7dz78a9z4170zbfacz9b660a96e7db · Cited by 1
Metadata
- Authors
- Rosenblatt, F.
- Corresponding author
- Rosenblatt, F.
- Venue
- Psychological Review
- Published
- 1958
- Volume
- 65
- Issue
- 6
- Pages
- 386-408
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2040870580
- Semantic Scholar
- 5d11aad09f65431b5d3cb1d85328743c9e53ba96
- Cited by
- 12,280
- References
- 15
- Citations by year
- 2026: 659 · 2025: 1019 · 2024: 969 · 2023: 933 · 2022: 945 · 2021: 965 · 2020: 898 · 2019: 826 · 2018: 494 · 2017: 411 · 2016: 318 · 2015: 313 · 2014: 282 · 2013: 332 · 2012: 255
- FWCI
- 14.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- perceptron, probabilistic models, information storage, memory, perceptual identification, generalization, memory retrieval
- MeSH terms
- Brain, Humans, Perception, Models, Statistical, Information Storage and Retrieval, Neural Networks, Computer
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