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Record W2146123868 · doi:10.1162/jocn_a_00728

Contextual Alignment of Cognitive and Neural Dynamics

2014· article· en· W2146123868 on OpenAlexaff
Daniel L. Ames, Christopher J. Honey, Michael A. Chow, Alexander Todorov, Uri Hasson

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2014
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of Toronto
FundersDefense Advanced Research Projects AgencyNational Science Foundation
KeywordsPsychologyPosterior cingulateDefault mode networkCognitive psychologyPerspective (graphical)Context (archaeology)CognitionVignetteSimilarity (geometry)NeuroimagingNeuroscienceSocial psychologyComputer science

Abstract

fetched live from OpenAlex

Effective real-world communication requires the alignment of multiple individuals to a common perspective or mental framework. To study how this alignment occurs at the level of the brain, we measured BOLD response during fMRI while participants (n = 24) listened to a series of vignettes either in the presence or absence of a valid contextual cue. The valid contextual cue was necessary to understand the information in each vignette. We then examined where and to what extent the shared valid context led to greater intersubject similarity of neural processing. Regions of the default mode network including posterior cingulate cortex and medial pFC became more aligned when participants shared a valid contextual framework, whereas other regions, including primary sensory cortices, responded to the stimuli reliably regardless of contextual factors. Taken in conjunction with previous research, the present results suggest that default mode regions help the brain to organize incoming verbal information in the context of previous knowledge.

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)0.001
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.287
Teacher spread0.251 · 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 designBench or experimental
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

Citations82
Published2014
Admission routes1
Has abstractyes

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