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Record W2077345454 · doi:10.1037/h0085813

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

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

Bibliographic record

VenueCanadian Psychology/Psychologie canadienne · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCognitive scienceHebbian theoryNeuroscienceCognitive psychologyContext (archaeology)Cognitive neurosciencePerceptionPhysiological psychologyNeuropsychologyCognitionArtificial intelligenceArtificial neural network

Abstract

fetched live from 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. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.015
Scholarly communication0.0050.015
Open science0.0020.002
Research integrity0.0080.017
Insufficient payload (model declined to judge)0.0140.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.362
GPT teacher head0.452
Teacher spread0.090 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2003
Admission routes1
Has abstractyes

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