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Record W4304731445 · doi:10.1093/cercor/bhac405

Creativity in verbal associations is linked to semantic control

2022· article· en· W4304731445 on OpenAlexaff
Katya Krieger‐Redwood, Anna Steward, Zhiyao Gao, Xiuyi Wang, Ajay D. Halai, Jonathan Smallwood, Elizabeth Jefferies

Bibliographic record

VenueCerebral Cortex · 2022
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsKingston Health Sciences CentreQueen's University
FundersEuropean Research CouncilMedical Research CouncilRosetrees Trust
KeywordsCreativityPsychologyControl (management)Cognitive psychologyLinguisticsCognitive scienceComputer scienceArtificial intelligenceSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

Although memory is known to play a key role in creativity, previous studies have not isolated the critical component processes and networks. We asked participants to generate links between words that ranged from strongly related to completely unrelated in long-term memory, delineating the neurocognitive processes that underpin more unusual versus stereotypical patterns of retrieval. More creative responses to strongly associated word-pairs were associated with greater engagement of episodic memory: in highly familiar situations, semantic, and episodic stores converge on the same information enabling participants to form a personal link between items. This pattern of retrieval was associated with greater engagement of core default mode network (DMN). In contrast, more creative responses to weakly associated word-pairs were associated with the controlled retrieval of less dominant semantic information and greater recruitment of the semantic control network, which overlaps with the dorsomedial subsystem of DMN. Although both controlled semantic and episodic patterns of retrieval are associated with activation within DMN, these processes show little overlap in activation. These findings demonstrate that controlled aspects of semantic cognition play an important role in verbal creativity.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.036
GPT teacher head0.350
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
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

Citations31
Published2022
Admission routes1
Has abstractyes

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