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Enregistrement W2061107048 · doi:10.1037/h0085817

A brief history of the Hebbian learning rule.

2003· article· en· W2061107048 sur OpenAlexaffabout
Peter Milner

Notice bibliographique

RevueCanadian Psychology/Psychologie canadienne · 2003
Typearticle
Langueen
DomaineNeuroscience
ThématiqueNeurology and Historical Studies
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésHebbian theoryPsychologyLeabraCognitive scienceCognitive psychologyArtificial intelligenceUnsupervised learningArtificial neural networkComputer science

Résumé

récupéré en direct d'OpenAlex

Abstract Hebb included a version of his neural postulate of learning in his MA thesis (1932). It seems to be a translation of Pavlovian conditioning into neural terms. The version that appears in his book, The Organization of Behavior (1949), speaks of synapses rather than routes, but the idea of simultaneous firing of afferent and efferent elements is common to both versions. The postulate was adopted by groups interested in programming computers to learn and think. It was also one of the hypotheses tested by neurophysiologists in their search for the synaptic mechanism of learning. So far the neurophysiologists have had more success than the logicians; the NMDA synapse appears to explain the main features of Hebb's postulate. In his monograph, The Organization of Behavior, Hebb (1949) presented a theory concerning the way stimuli might be represented in the brain. It was the first such attempt to be widely accepted by psychologists and it has had a strong influence on subsequent theories. Commonsense decrees that brain representations must be learned, at least in the case of representations of the shapes of human artefacts such as the letters of the alphabet, tools, and buildings. The radical empiricism of early 20th century psychology led Hebb to go the whole hog and base his model on the assumption that the neurons of the newborn visual cortex are randomly interconnected. In order to proceed, Hebb then had to specify the conditions under which visual input might organize these connections. In 1932, when Hebb was a part-time graduate student at McGill, he submitted an MA thesis entitled Conditioned and Unconditioned Reflexes and Inhibition. The gist of the thesis is that spinal reflexes are the result of prenatal Pavlovian conditioning; in his more mature years Hebb referred to it as nonsense (Hebb, 1980). The McGill library had, in the meantime, lost its copy of the thesis, so Hebb's evaluation could not readily be verified. Recently, however, Professor Richard Brown of Dalhousie University, in connection with a presentation he made to the Society of Neuroscience, tracked down another copy of the thesis. The part of it dealing with the ontogeny of spinal reflexes may well be nonsense, as Hebb maintained, but Brown (2001, 2002) made the interesting discovery that the thesis includes an analysis of the neural learning mechanism underlying Pavlovian conditioning that foreshadows the one he later presented to explain the learning of visual representations. Based on the observations of Pavlov and others that a stimulus occurring repeatedly at about the same time as a response, acquires a connection to that response, Hebb concluded that: An excited neuron tends to decrease its discharge to inactive neurons, and to increase this discharge to any active neuron, and therefore to form a route to it, whether there are intervening neurons between the two or not. With repetition this tendency is prepotent in the formation of neural routes. (Hebb, 1932, p. 8) An accompanying diagram makes it clear that this postulate was indeed a transposition of Pavlov's conditioning paradigm to the neural level. When, some dozen or so years later, Hebb needed to specify the neural learning mechanism responsible for the acquisition of shape representations in the brain, it seems that he consciously or unconsciously returned to the formulation in his thesis. The neurological postulate was presented in The Organization of Behavior as follows: Let us assume then that the persistence or repetition of a reverberatory activity (or trace) tends to induce lasting cellular changes that add to its stability. The assumption can be precisely stated as follows: When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes a part in in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,045

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0040,004
Études des sciences et des technologies0,0010,004
Communication savante0,0030,005
Science ouverte0,0010,001
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0140,013

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,063
Tête enseignante GPT0,260
Écart entre enseignants0,197 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations30
Publié2003
Routes d'admission2
Résumé présentoui

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