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Record W4307423402 · doi:10.1016/j.isci.2022.105413

Face-to-face spatial orientation fine-tunes the brain for neurocognitive processing in conversation

2022· article· en· W4307423402 on OpenAlexfundno aff
Linda Drijvers, Judith Holler

Bibliographic record

VenueiScience · 2022
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
FundersH2020 European Research CouncilEuropean Research CouncilMax Planck Instituut voor PsycholinguïstiekMax-Planck-GesellschaftCANDU Owners Group
KeywordsConversationNeurocognitiveFace (sociological concept)Orientation (vector space)Cognitive scienceFace-to-facePsychologyNeuroscienceComputer scienceHuman–computer interactionCommunicationCognitionSociology

Abstract

fetched live from OpenAlex

We here demonstrate that face-to-face spatial orientation induces a special 'social mode' for neurocognitive processing during conversation, even in the absence of visibility. Participants conversed face to face, face to face but visually occluded, and back to back to tease apart effects caused by seeing visual communicative signals and by spatial orientation. Using dual EEG, we found that (1) listeners' brains engaged more strongly while conversing face to face than back to back, irrespective of the visibility of communicative signals, (2) listeners attended to speech more strongly in a back-to-back compared to a face-to-face spatial orientation without visibility; visual signals further reduced the attention needed; (3) the brains of interlocutors were more in sync in a face-to-face compared to a back-to-back spatial orientation, even when they could not see each other; visual signals further enhanced this pattern. Communicating in face-to-face spatial orientation is thus sufficient to induce a special 'social mode' which fine-tunes the brain for neurocognitive processing in conversation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.028
GPT teacher head0.325
Teacher spread0.298 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations11
Published2022
Admission routes1
Has abstractyes

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