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Enregistrement W2077345454 · doi:10.1037/h0085813

The impact of the Hebbian learning rule on research in behavioural neuroscience.

2003· article· en· W2077345454 sur OpenAlexaboutno aff
Bryan Kolb

Notice bibliographique

RevueCanadian Psychology/Psychologie canadienne · 2003
Typearticle
Langueen
DomaineNeuroscience
ThématiqueMemory and Neural Mechanisms
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychologyCognitive scienceHebbian theoryNeuroscienceCognitive psychologyContext (archaeology)Cognitive neurosciencePerceptionPhysiological psychologyNeuropsychologyCognitionArtificial intelligenceArtificial neural network

Résumé

récupéré en direct d'OpenAlex

[HEADNOTE]AbstractHebb's principal theoretical propositions, the cell assembly and the nature of synaptic change, were generated at a time when the focus of work in behavioural neuroscience was directed at understanding issues such as the principles governing the behaviour of animals in neuropsychological studies of learning and memory and the role of drives in the control of behaviours like sex and feeding and drinking. It was not until attention shifted to understanding the neural underpinnings of learning and memory that Hebb's propositions had an impact on behavioural neuroscience as they provided a simple, and testable, mechanism for synaptic plasticity observed both in learning and in other forms of experience-dependent neural change. But much of the field remains interested in other issues such as sensation and perception, motivation, attention, and so on, and to date, Hebb's propositions have had little impact.An understanding of the role of Hebb's postulates in research on brain and behaviour must be seen in historical context. In 1949, the field that we now call behavioural neuroscience was usually described as physiological psychology, or as the subtitle of Hebb's book suggested, neuropsychology. The focus of research in physiological psychology was different than the interests of today with the emphasis being on motivational systems and the mechanisms of learning and memory. The ascending activating systems of the brainstem had just been discovered and there was keen interest in the role of the hypothalamus in controlling both regulatory and nonregulatory behaviours. Psychology had a long tradition of study in learning (e.g., Harlow, 1949) and Lashley had just spent 40 years looking for the location of memory in the brain (e.g., Lashley, 1956). When Scoville and Milner (1956) described case H.M. this added even more fuel to the general interest in wherein the brain learning and memory might reside. But this interest was largely phenomenological in the sense that correlations between behavioural events and brain injury were being described with little direct study of the mechanisms that might account for the formation of memories.Hebb's own interests were different, however, as he was thinking about the development of perceptual systems and the manner in which the external world comes to be represented in the brain. Hebb's principal theoretical propositions, namely, the cell assembly and the nature of synaptic change, were directed at these perceptual questions and thus not directly relevant to the research topics that were more popular at the time. Thus, it is safe to say that Hebb's propositions had rather little direct impact on the field in general in the first decades after the publication of his book. I note parenthetically that Hebb did have considerable impact upon the development of the field of behavioural neuroscience, especially in Canada, as the leaders of the '50s, '60s, and '70s, such as Brenda and Peter Milner, Doreen Kimura, Gordon Mogenson, Graham Goddard, Mort Mishkin, and Dalbir Bindra, to name only a few, were all students or colleagues of Hebb, and this group trained the next wave of investigators who, in turn, crafted the field that we now recognize as behavioural neuroscience, at least in Canada.By the 1980s, there had been a significant shift in the nature of neuropsychological investigations and the field expanded beyond its beginnings as phsyiological psychology. As behavioural neuroscience emerged as a multidisciplinary discipline, researchers were no longer satisfied with descriptions of behavioural phenomena, which is where it obviously had to begin, but had become more focused on understanding the nature of the mechanisms that were postulated to underlie the observed behavioural phenomena. Thus, whereas studies might previously have been interested in the general role of cerebral structures in learning and memory, the spotlight shifted to physiological studies looking at cellular changes that might underlie learning and memory. …

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)0,008
score de la tête « metaresearch » (Gemma)0,021
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,992
Score d'incertitude au seuil0,047

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,021
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0040,015
Communication savante0,0050,015
Science ouverte0,0020,002
Intégrité de la recherche0,0080,017
Charge utile insuffisante (le modèle a refusé de juger)0,0140,010

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 Opus0,362
Tête enseignante GPT0,452
Écart entre enseignants0,090 · 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.

Devis d'étudeThéorique ou conceptuel
DomaineMéthodes
GenreEmpirique

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

En bref

Citations13
Publié2003
Routes d'admission1
Résumé présentoui

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