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Autism Symptom Severity Predicts Accuracy of Facial Emotion Recognition Under Conditions of Low Theta-Power Early in Visual Processing
Objectives: We examine whether ASD SS predicted performance on a FER task and if this relation varied as a function of early theta-power during the P100 ERP window.
Methods: Fifty-three youth (Mage=11.60, SDage=2.96; 38 male) with IQ≥70 (MIQ=103.49, SDIQ=15.40) and ADOS-2-confirmed ASD diagnosis and SS. Electroencephalography (EEG) data were recorded during a FER task (DANVA-2; Nowicki, 2004). Natural log transformed theta power at the P100 ERP was calculated using wavelet analysis for central frequencies 4-7.5Hz using 20 logarithmic steps at 4 cycles. Moderated linear regression analyses were used to test the relation of ASD SS and accuracy for identifying adult and child emotional faces at varying levels of the theta frequency during the P100.
Results: No correlations between ADOS SS and FER performance, theta-power and FER performance, or theta-power and SS (p’s> 0.26) were found. However, a significant interaction was found between SS and P100 theta-power in predicting FER performance (B= 0.463 p = 0.026), such that at lower levels of theta-power and greater SS predicted better FER performance (Figure 1).
Conclusions: Our results suggest that greater SS predicts better FER performance, but only among those exhibiting lower occipital theta-power during the P100 ERP window. Heightened posterior theta is associated with holistic processing during FER tasks (Sauseng et al., 2009). These results suggest that, when such holistic processing is not engaged, individuals with greater symptoms of ASD may utilize alternate or compensatory strategies to decode faces, while those with fewer symptoms may rely on underdeveloped holistic processing abilities. Our results may help explain heterogeneity in relations between ASD SS and FER performance.
See more of: Brain Function (fMRI, fcMRI, MRS, EEG, ERP, MEG)