MétaCan
Menu
Back to cohort
Record W4283832032 · doi:10.3389/fnbeh.2022.920989

Spatiotemporal Dynamics of Covert vs. Overt Emotional Face Processing in Dysphoria

2022· article· en· W4283832032 on OpenAlexafffund
Fern Jaspers‐Fayer, Antonio Maffei, Jennifer Goertzen, Killian Kleffner, Ambra Coccaro, Paola Sessa, Mario Liotti

Bibliographic record

VenueFrontiers in Behavioral Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchSimon Fraser UniversityMichael Smith Health Research BC
KeywordsDysphoriaPsychologyCovertElectroencephalographyAudiologyDevelopmental psychologyCognitive psychologyAnxietyNeurosciencePsychiatryMedicine

Abstract

fetched live from OpenAlex

People at risk of developing clinical depression exhibit attentional biases for emotional faces. To clarify whether such effects occur at an early, automatic, or at a late, deliberate processing stage of emotional processing, the present study used high-density electroencephalography during both covert and overt processing of sad, fearful, happy, and neutral expressions in healthy participants with high dysphoria ( n = 16) and with low dysphoria ( n = 19). A state-of-the-art non-parametric permutation-based statistical approach was then used to explore the effects of emotion, attentional task demands, and group. Behaviorally, participants responded faster and more accurately when overtly categorizing happy faces and they were slower and less accurate when categorizing sad and fearful faces, independent of the dysphoria group. Electrophysiologically, in an early time-window (N170: 140–180 ms), there was a significant main effect for the dysphoria group, with greater negative voltage for the high vs. low dysphoria group over the left-sided temporo-occipital scalp. Furthermore, there was a significant group by emotional interaction, with the high dysphoria group displaying greater negative amplitude N170 for happy than fearful faces. Attentional task demands did not influence such early effects. In contrast, in an intermediate time-window (EPN: 200–400 ms) and in a late time-window (LPP: 500–750 ms) there were no significant main effects nor interactions involving the dysphoria Group. The LPP results paralleled the behavioral results, with greater LPP voltages for sad and fearful relative to happy faces only in the overt task, but similarly so in the two dysphoria groups. This study provides novel evidence that alterations in face processing in dysphoric individuals can be seen at the early stages of face perception, as indexed by the N170, although not in the form of a typical pattern of mood-congruent attentional bias. In contrast, intermediate (EPN) and late (LPP) stages of emotional face processing appear unaffected by dysphoria. Importantly, the early dysphoria effect appears to be independent of the top-down allocation of attention, further supporting the idea that dysphoria may influence a stage of automatic emotional appraisal. It is proposed that it may be a consequence of a shift from holistic to feature-based processing of facial expressions, or may be due to the influence of negative schemas acting as a negative context for emotional facial processing.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.045
GPT teacher head0.302
Teacher spread0.257 · 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 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

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Behavioral NeuroscienceSame topicFace Recognition and PerceptionFrench-language works237,207