Task-irrelevant affective prosody perception by typically developed children under attentional loads: electroencephalographic, behavioural data, and psychometric evaluation of autistic patterns in daily conducts.
Description
The relevance of affective information triggers attentional prioritisation, but when emotional stimuli act as distractors (task-irrelevant), attentional load dictates the balance between bottom-up processing and top-down executive control systems for attention allocation. In this dataset, electroencephalographic (EEG) signals related to implicit emotional speech perception under low, intermediate, and high attentional loads are provided. Demographic and behavioural data are also shared. Thirty-one typically developed children (mean age: 10-year-old, SD: 1, 20 girls) and their parents or legal guardians volunteered for data collection. As autistic traits may impair social-emotional reciprocity and verbal communication, assessments of autistic behaviours severity were conducted using the Autism Spectrum Rating Scales (ASRS, parent report). Sessions with children started with the completion of the Edinburgh Handedness Inventory followed by recording resting-state EEG activity for 2 minutes with eyes open. Those data are included in the dataset. Then, children answered three visual activities while listening to task-irrelevant affective prosodies (anger, disgust, fear, happiness, neutral and sadness). Particularly, low attentional load was induced by neutral image viewing; a one-target 4-disc Multiple Object Tracking (MOT) task triggered intermediate load; and high attentional load was conveyed by the one-target 8-disc MOT condition. Tracking capacity was computed from correct/incorrect answers during MOT tasks and are included in the dataset along with EEG data recorded during all three tasks. These data are relevant to investigate electrophysiological correlates of task-irrelevant affective speech integration under attentional load modulations and to assess their interaction with behavioural autistic patterns in a non-pathologic population. Besides, resting-state EEG data may be used to characterise inter-individual heterogeneity at rest and, in turn, associate it with attentional capacities during MOT and with autistic behavioural patterns. Finally, tracking capacity may be useful to explore dynamic and selective attentional mechanisms under emotional constraints. Keywords Emotion; Electroencephalography; Selective Attention; Dynamic Attention; Auditory stimuli; Multiple-Object Tracking; Prosody; Speech