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Record W2969354441 · doi:10.1002/bies.201900077

Habituation Is More Than Learning to Ignore: Multiple Mechanisms Serve to Facilitate Shifts in Behavioral Strategy

2019· review· en· W2969354441 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioEssays · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersCanadian Institutes of Health Research
KeywordsHabituationPsychologyCognitive psychologyNeuroscienceSelection (genetic algorithm)Cognitive scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Recent work indicates that there are distinct response habituation mechanisms that can be recruited by different stimulation rates and that can underlie different components (e.g., the duration or speed) of a single behavioral response. These findings raise the question: why is "the simplest form of learning" so complicated mechanistically? Beyond evolutionary selection for robustness of plasticity in learning to ignore, it is proposed in this article that multiple mechanisms of habituation have evolved to streamline shifts in ongoing behavioral strategy. Then, speculations are offered regarding the implications of this reconceptualization of habituation for approaching the analysis of mechanisms of more complex forms of learning and memory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.221
GPT teacher head0.358
Teacher spread0.137 · 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