Infant Cries Rattle Adult Cognition
Bibliographic record
Abstract
The attention-grabbing quality of the infant cry is well recognized, but how the emotional valence of infant vocal signals affects adult cognition and cortical activity has heretofore been unknown. We examined the effects of two contrasting infant vocalizations (cries vs. laughs) on adult performance on a Stroop task using a cross-modal distraction paradigm in which infant distractors were vocal and targets were visual. Infant vocalizations were presented before (Experiment 1) or during each Stroop trial (Experiment 2). To evaluate the influence of infant vocalizations on cognitive control, neural responses to the Stroop task were obtained by measuring electroencephalography (EEG) and event-related potentials (ERPs) in Experiment 1. Based on the previously demonstrated existence of negative arousal bias, we hypothesized that cry vocalizations would be more distracting and invoke greater conflict processing than laugh vocalizations. Similarly, we expected participants to have greater difficulty shifting attention from the vocal distractors to the target task after hearing cries vs. after hearing laughs. Behavioral results from both experiments showed a cry interference effect, in which task performance was slower with cry than with laugh distractors. Electrophysiology data further revealed that cries more than laughs reduced attention to the task (smaller P200) and increased conflict processing (larger N450), albeit differently for incongruent and congruent trials. Results from a correlation analysis showed that the amplitudes of P200 and N450 were inversely related, suggesting a reciprocal relationship between attention and conflict processing. The findings suggest that cognitive control processes contribute to an attention bias to infant signals, which is modulated in part by the valence of the infant vocalization and the demands of the cognitive task. The findings thus support the notion that infant cries elicit a negative arousal bias that is distracting; they also identify, for the first time, the neural dynamics underlying the unique influence that infant cries and laughs have on cognitive control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".