Neural Habituation in Response to Emotional Faces and Houses in ASD

Background: Previous work has shown that abnormal amygdala habituation to faces is a robust indicator of ASD dysfunction and associated with individual differences in social impairments. However, the generalizability of the habituation effect to other classes of stimuli is unknown.

Objectives: To determine whether atypical neural habituation in ASD is a face-specific or a domain-general mechanism present across visually complex objects such as houses.

Methods: We performed a secondary analysis of previously published and unpublished fMRI data designed to follow-up and extend our previous work on habituation in ASD. Twenty-seven adults with an ASD and 25 age and IQ matched controls were included. Two identical block-design fMRI runs were collected (Time 1=T1, Time 2=T2). Masked fearful faces (“F”), masked houses (“H”), and scrambled images (“S”) were presented. Six, first-level analyses were conducted F_T1>S_T1;  F_T2>S_T2;  H_T1>S_T1;  H_T2>S_T2;  F_T1>H_T1; and H_T1>F_T1. Functional localizers for the Face (lateral fusiform) and House (medial fusiform) areas were created based on the entire study sample (N=54) for the contrasts F_T1>H_T1 and H_T1>F_T1. Anatomically-based right and left amygdala masks were also utilized. The average z-score within each mask was computed for each contrast. In addition, habituation was computed for each mask by subtracting T1-T2. Average z-scores and habituation scores were imported into Predictive Analytics SoftWare Statistics 18.0.0.

Results: We investigated the role of stimulus-type, brain region, and diagnosis on habituation rates. A 2x2x4 repeated measures ANOVA was conducted with diagnosis as the between-group variable and time (T₁ vs. T₂) and brain region (right/left amygdala, right lateral fusiform, right medial fusiform) as the within-subject variables. The dependent variable was average z-score, which was nested under the 16 variables. The three-way interaction was significant (F=3.808, p=.016). In addition, we found a diagnosis by time interaction (F=18.53, p=.000) and a brain region by time interaction (F = 3.027, p = .038) but no significant interaction between brain region and diagnosis (F=.399, p=.755). Follow-up tests reveal that the ASD group showed significantly less habituation to faces in the right amygdala (F=8.317, p=.006), left amygdala (F=30.521, p<.000) right lateral fusiform (F=4.612, p =.037). There was no group-by-time interaction effect for houses in the right medial fusiform (F=.733, p=.396). We evaluated the diagnostic discriminability of our habituation score for each brain region using Receiver Operating Characteristic curves. Left amygdala habituation to fearful faces had the strongest predictive value (AUC = .852, p<.000); a threshold of habituation score ≤ 0 (indicating no change in activation across time) detected 21/27 (78%) participants with ASD and correctly excluded 16/25 (64%) of controls. Habituation to houses had no predictive value (AUC = .573, p =.365).

Conclusions: These results suggest that reduced habituation in ASD is specific to emotional stimuli and especially pronounced in the amygdala. Fearful face activation in the amygdala shows a unique group-by-time interaction effect, characterized by a pattern of decreased activation in the TD group, and increased activation in the ASD group. We propose that amygdala habituation to emotional faces may be an effective biomarker for quantifying risk at the individual level in ASD.