We aimed to establish the feasibility of HD-DOT for investigating brain function in autistic and non-autistic school-aged children and adolescents. Our results support the hypothesis that HD-DOT is feasible for assessing brain function in children during passive viewing of biological motion point-light displays, including autistic children. HD-DOT demonstrated robust performance across a cohort of 112 participants, each of which completed a minimum of two tasks with good data quality (Fig. 2). While our final cohort sizes were smaller than planned due to data collection disruptions, the final sample size (ASD N = 21 and NAC N = 23) exceeds the median size (ASD N = 17, NAC N = 16) observed in extant fMRI-based studies on biological motion in ASD (18–20, 37–40, 45, 57). Second, our results for NAC implicate several regions previously reported to be associated with processing biological motion and social stimuli (19, 25, 37, 38, 57), including right STG, right PCG, right MOG, left IOG, and bilateral IFG (Fig. 3). Similarly, previous studies using fMRI in an NAC group reported corresponding patterns of brain activity in response to a similar task paradigm (20, 39, 45). Third, we observed the ASD group exhibited significant contrasts in the right MOG, right MFG, right MTG, and right PCG. While the ASD group findings in the right hemisphere align with existing literature (20), we did not observe similar results in the left hemisphere where effects have been previously reported (20). The disparity in the ASD activation patterns may be due to the heterogeneity of ASD presentation (31, 33).
Regarding group differences in brain contrast (NAC > ASD or ASD > NAC) to coherent vs. scrambled motion, we identified six distinct brain regions with greater contrast in the NAC group compared to the ASD group. First, we found that the bilateral IFG had greater contrast activity in the NAC group than the ASD group. Previous studies have also found less contrast activity in the IFG and overlapping/nearby regions, e.g., the ventrolateral prefrontal cortex, in response to biological motion in autistic children (18, 45, 58). Previous fNIRS studies have suggested that autistic children have lower IFG activity during imitation tasks when compared to NAC (59). Second, we found that the ASD cohort exhibited less contrast activity in the left lingual gyrus, left FFG, and right IOG compared to the NAC group. These regions are implicated in visual processing and object recognition, and studies of BMP have associated atypical activation in these regions to disruptions in processing socially relevant visual stimuli in autistic individuals (18–20). Third, the NAC participants had greater contrast than the ASD group in the left PCG. The PCG contains parts of the somatosensory system and is considered as part of the mirror-neuron system (MNS) (60, 61), which is involved in understanding, perceiving, and performing actions (60). These findings indicate that NAC children may use the MNS for BMP processing to a larger degree than autistic children – a finding consistent with fMRI studies indicating that MNS dysfunction is associated with disrupted facial and gesture imitation behaviors in autistic children (62–64). Fourth, we observed that the right STG had greater contrast in the NAC group. However, inconsistent with previous fMRI studies (18, 20), we did not observe a statistically significant diminished contrast within the superior temporal sulcus in the ASD group compared to the NAC group. This inconsistency may be due to the heterogeneity in neural responses in ASD (31, 33). Fifth, we did not observe any regions with statistically significant greater contrast activity in ASD than in NAC. Indeed, only two out of 11 fMRI studies have reported cortical areas exhibiting greater contrast activity in an ASD group compared to an NAC group in response to a similar task paradigm (31). To summarize, our study identified six distinct brain regions with greater contrast in NAC participants compared to the ASD group, and no regions with stronger contrast in the ASD group than the NAC group. Our findings, implicating specific cortical areas (i.e., bilateral IFG, left FFG, left PCG, and right IOG), strongly align with previous fMRI studies, thereby enhancing our overall understanding of the neural responses underlying BMP in ASD and NAC children.
Next, to investigate how the variability in brain function relates to variability in behavioral measures of autism traits, we correlated the brain contrast with SRS t-scores. Notably, positive correlations were observed in the right IFG, STG, MFG, MOG, and MTG across ASD participants. These results deviate from our hypothesis, as previous fMRI studies have reported negative correlations between SRS and brain contrast activity in regions linked to social processing (18, 20). Intriguingly, an fMRI study using the identical experimental paradigm as this study also did not find any negative correlations between brain contrast and social responsiveness in the NAC group or carriers of heightened genetic likelihood for developing ASD (39). In contrast, one fMRI study observed a similar positive correlation between a measure of autism trait severity (i.e., the Autism Quotient) and brain activity in ROI associated with BMP employing an identical experimental paradigm as the present study (45). As demonstrated in a meta-analysis of BMP studies, variations in experimental paradigms, analysis methods, sample size, age range, cognitive ability, and heterogeneity in autism traits such as adaptive functioning may contribute to disparate results regarding neural correlates (31). As an alternative secondary analysis, to provide an unbiased spatial sampling, we used the Gordon parcellation (56) to support a brain-wide exploratory analysis that implicated eight parcels (Figs. 4, 5). The left angular gyrus parcel exhibited a negative correlation between the contrast response and SRS t-scores, aligning with prior studies (20). The left angular gyrus plays a role in semantic processing, social cognition, and theory of mind (65, 66). This negative correlation suggests that alterations in left angular gyrus response may contribute to social interaction and communication challenges observed in some autistic individuals. Additionally, our results revealed that the parcels located in the dlPFC, STG, VAC, and MTG exhibit positive correlations between brain contrast and SRS t-scores. These regions are associated with higher-order cognitive, visual, and social functioning (67–69). Our results suggest that autistic children exhibiting stronger ASD symptoms display increased brain contrast activation in dlPFC, STG, VAC, and MTG. These findings align with recent studies showing that while non-autistic individuals depend on specialized perceptual mechanisms for BMP (70, 71), autistic individuals may lack these mechanisms, or if present, they might be less developed (29, 72). Consequently, autistic individuals may employ higher-order cognitive and visual skills during perceiving or responding to BMP, possibly in the brain regions we identified as having positive correlations with autistic traits.
We found with the hierarchical regression analyses that the SRS t-scores more strongly related to variability in brain function than variables reflecting demographic information (e.g., age) and cognitive ability (e.g., VIQ and NVIQ), which is consistent with the existing literature (31, 73). Age was a moderate predictor of variability in brain contrast in four ROI in addition to SRS t-scores. Similarly, an activation likelihood estimation analysis of biological motion studies reported a significant main effect of age and determined age to be a moderator of the variance between studies (31). Furthermore, previous studies found a relationship between IQ and biological motion perception in ASD (38, 73). Likewise, we found that IQ measures were moderately related to region-specific brain contrasts in multiple regions. Taken together, while demographic and cognitive variables contributed somewhat to the explained variance in brain contrast, the SRS t-scores far more strongly predicted variability in the brain contrast in autistic children.
Overall, these findings highlight the reliability and effectiveness of HD-DOT to capture reliable neurological data and affirms its feasibility as a valuable tool for investigating brain function in autistic and non-autistic children. Given that HD-DOT is sensitive to responses to socially relevant stimuli in this age group, future studies may take advantage of the minimally-constraining environment of HD-DOT for evaluating brain function during more naturalistic tasks, such as movie viewing (74, 75), gesture imitation (63, 76), and direct dyadic social interaction (77, 78), even during live dyadic eye-to-eye contact (79). Several fMRI, fNIRS, and HD-DOT studies indicate that, in contrast to strictly defined block design studies, naturalistic tasks more closely mimic real-life scenarios and interactions (80), leading to increased engagement, and greater ecological validity (74, 75, 80–84). Furthermore, while imaging awake toddlers and infants has proven challenging, several fNIRS groups have successfully used optical methods throughout this young age range (43, 82, 85, 86). Future work combining advanced optical imaging techniques, like HD-DOT, with naturalistic tasks will provide a unique opportunity to investigate neural mechanisms underlying development and social processing in ASD, including in infants and toddlers with a heightened likelihood for developing ASD (19).
Some limitations are important to consider. First, unlike fMRI, optical methods like fNIRS and HD-DOT cannot assess subcortical structures implicated in ASD-related differences, e.g., the amygdala and cerebellum (18, 31, 40, 58). However, the HD-DOT system field of view covers the frontal, visual, motor, and temporal cortical areas, which includes multiple brain regions previously implicated in both task-based and task-free studies on ASD (13). Importantly, HD-DOT technology is evolving rapidly, with multiple research and commercial systems providing full-head fields of view. Second, while the eye gaze patterns were not quantitatively assessed in this study, participant gaze was consistently monitored, and participants were instructed to maintain their attention on the screen. Eye tracking, previously used to assess visual patterns and gaze positions (9, 87), can be naturally combined with optical methods for cross-modal investigations of brain function and eye gaze. Third, while point-light displays of biological motion are well-validated stimuli, a more naturalistic and ecologically valid task paradigm that drives social and emotional processing and requires direct engagement may provide a more powerful assay of visual-social processing. A more naturalistic task that requires behavioral responses would potentially enhance participant engagement with the stimulus, such as observing or imitating dynamic movements in movie clips (64). Fourth, our study lacks enough female participants to assess sex-related differences or potential sex-by-diagnosis effects in BMP with meaningful statistical power. While the male-to-female ratio for ASD diagnosis is roughly 4:1 (88), recent investigations have suggested a more balanced sex ratio of the population having sub-clinical autism traits in light of under-diagnosis and exclusion of autistic females in research (89–91). These investigations underscore the importance of evaluating and correcting for measurement bias related to sex, as well as identifying patterns of symptom presentation specific to each sex (92). Larger studies with matched sex-ratios will be able to investigate the nuanced and complex effects of autosomal and sex-linked variability in brain function underlying behavioral autism traits (19, 88, 93). Last, our study lacked a sufficient sample size to include the pro-band siblings (PS) cohort in our primary analyses. As previous fMRI studies have shown compelling similarities and differences between PS compared to ASD and NAC participants, our future studies will target more PS participants to investigate genetic contributions to the broader autism phenotype more completely.
In conclusion, this study demonstrates the feasibility of HD-DOT for investigating brain activity in both autistic and non-autistic school-age children and establishes neural correlates with behavioral measures of social responsiveness. Our results show that both NAC and ASD groups tolerate HD-DOT scans well, exhibiting no differences in data quality or motion. Confirming results in fMRI studies, we found that NAC children exhibit greater brain contrasts in regions linked to visual, motor, and social processing as compared to autistic children. Additionally, we established brain-behavior correlations between the brain contrast and SRS t-scores through both cluster-based and brain-wide parcel-based analyses. Overall, this study highlights the effectiveness of HD-DOT as promising tool for studying brain function in autistic children throughout childhood development in a naturalistic setting.