Accounting for motion in fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

The exclusion of high-motion participants can reduce the impact of motion in functional Magnetic Resonance Imaging (fMRI) data. However, the exclusion of high-motion participants may change the distribution of clinically relevant variables in the study sample, and the resulting sample may not be representative of the population. Our goals are two-fold: 1) to document the biases introduced by common motion exclusion practices in functional connectivity research and 2) to introduce a framework to address these biases by treating excluded scans as a missing data problem. We use a study of autism spectrum disorder to illustrate the problem and the potential solution. We aggregated data from 545 children (8-13 years old) who participated in resting-state fMRI studies at Kennedy Krieger Institute (173 autistic and 372 typically developing) between 2007 and 2020. We found that autistic children were more likely to be excluded than typically developing children, with 29.1% and 16.1% of autistic and typically developing children excluded, respectively, using a lenient criterion and 80.8% and 59.8% with a stricter criterion. The resulting sample of autistic children with usable data tended to be older, have milder social deficits, better motor control, and higher intellectual ability than the original sample. These measures were also related to functional connectivity strength among children with usable data. This suggests that the generalizability of previous studies reporting naïve analyses (i.e., based only on participants with usable data) may be limited by the selection of older children with less severe clinical profiles because these children are better able to remain still during an rs-fMRI scan. We adapt doubly robust targeted minimum loss based estimation with an ensemble of machine learning algorithms to address these data losses and the resulting biases. The proposed approach selects more edges that differ in functional connectivity between autistic and typically developing children than the naïve approach, supporting this as a promising solution to improve the study of heterogeneous populations in which motion is common.

Parent-Child Autonomic Synchrony During Vicarious Extinction Learning in Pediatric PTSD

Children must learn basic functional processes directly from their caregivers and child psychopathology may disrupt this transmission. This transmission may be seen through biological measures like peripheral nervous system outputs like skin conductance (SCR). Fear learning deficits have been seen in affective disorders like PTSD and are useful for studying parent-child learning transmission. Our study uses a vicarious fear extinction paradigm to study if biological synchrony (SCR and heart rate variability (HRV)) are potential mechanisms in which children learn safety cues from their parents. There were 16 dyads (PTSD n=11, TD n=5) undergoing a vicarious fear extinction paradigm. We used cross-recurrence quantification analysis (CRQA) to assess SCR and HRV synchrony between parent-child dyads. We then used a linear model looking at group differences between PTSD dyads and typically developing (TD) dyads. For SCR, we saw a significant group difference (p=.037) indicating that TD dyads had higher SCR synchrony compared to PTSD dyads. For HRV, there were no group differences between PTSD and TD dyads (p=.325). These results suggest that SCR synchrony, but not HRV, may be a potential mechanism that allows for fear and safety learning in youth. While this is preliminary, it may give the first insights on how therapies such as Trauma-Focused Cognitive Behavioral Therapy critically rely on parental coaching to model appropriate fear responses to help their child to recover from trauma.

Associations between early efficiency in language processing and learning outcomes in children born full term and preterm: Similarities and differences

Associations between children’s early language processing efficiency and later language, literacy, and non-verbal outcomes shed light on the extent to which early information processing skills support later learning across domains. Examining whether the strengths of associations are similar in typically developing and at risk populations provides an additional lens into the varying routes to learning that children take across development. We compared patterns of associations between early language processing efficiency (accuracy and reaction time) in the looking-while-listening (LWL) task and school-relevant skills in children born full-term (FT) and preterm (PT). Participants (n=94, 49 FT, 45 PT) were assessed in the LWL task at 18 months (corrected for degree of prematurity in PT group) and on standardized tests of expressive language, pre-literacy (print knowledge and phonological awareness), and non-verbal IQ at 4 ½ years. Early language processing efficiency was associated with later language and pre-literacy outcomes (r2 change ranged from 19.8 to 7.1, p < 0.01) to a similar extent in PT and FT children, controlling for age at test and SES, suggesting similar mechanisms of learning in these domains for PT and FT children. However, birth group moderated the association between reaction time and non-verbal IQ (r2 change 4.5, p < 0.05), such that an association was found in the PT but not the FT group. This finding suggests that information processing skills reflected in efficiency of real-time language processing may be recruited to support learning in a broader range of domains in the PT compared to the FT group.

Identification of Autism in Children Using Static Facial Features and Deep Neural Networks

Autism spectrum disorder (ASD) is a complicated neurological developmental disorder that manifests itself in a variety of ways. The child diagnosed with ASD and their parents’ daily lives can be dramatically improved with early diagnosis and appropriate medical intervention. The applicability of static features extracted from autistic children’s face photographs as a biomarker to distinguish them from typically developing children is investigated in this study paper. We used five pre-trained CNN models: MobileNet, Xception, EfficientNetB0, EfficientNetB1, and EfficientNetB2 as feature extractors and a DNN model as a binary classifier to identify autism in children accurately. We used a publicly available dataset to train the suggested models, which consisted of face pictures of children diagnosed with autism and controls classed as autistic and non-autistic. The Xception model outperformed the others, with an AUC of 96.63%, a sensitivity of 88.46%, and an NPV of 88%. EfficientNetB0 produced a consistent prediction score of 59% for autistic and non-autistic groups with a 95% confidence level.

Relation between exposure to different multimedia programs and presentation of attention deficit hyperactivity disorder

Background The current study aimed at constructing an Arabic-language questionnaire to investigate the association of the severity of ADHD with children’s degree of exposure to multimedia per day and the age of starting the engagement, and the effect of different multimedia programs on the attention, language, and socio-behavioral aspects in children presented with attention deficit hyperactivity disorder (ADHD). The present study was conducted on 69 children who attended the Phoniatric Unit at Mansoura University Hospitals and were divided into 2 groups: 30 normal typically developing children as a control group and 39 children with ADHD as the study group. The study group was subdivided into 3 subgroups according to ADHD severity; each subgroup consisted of 13 children. Results The time at which the child started to be exposed to multimedia showed no significant differences among ADHD subgroups as all of the cases started before the age of 2 years. Kids with mild ADHD had a significant increase in watching children’s programs, cartoons, rhymes, and commercials than the other two higher grades (moderate and severe) of ADHD. Conclusion The constructed Arabic questionnaire proved to be reliable and a valid tool that examined the relationship between multimedia usage and ADHD.

Inhibitory Control in Children with Tourette Syndrome Is Impaired in Everyday Life but Intact during a Stop Signal Task

Tourette Syndrome (TS) has previously been associated with deficits in inhibitory control (IC). However, studies on IC in individuals with TS have produced conflicting results. In the present study, we investigated IC, comparing the Stop Signal Reaction Time (SSRT) measure with parent and teacher ratings of daily life IC in 169 children aged 8–12 (60 with TS, 60 typically developing controls, 27 with attention-deficit/hyperactivity disorder (ADHD), and 22 with TS + ADHD). We further investigated associations of IC with TS and ADHD symptom severity. Children with TS showed intact SSRT performance, but impairments in daily life IC, as reported by parents and teachers. For the latter, we observed a staircase distribution of groups, with the healthy controls presenting with the best IC, followed by TS, TS + ADHD, and finally ADHD. Dimensional analyses indicated a strong association between ADHD severity and both measures of IC. Our results indicate that children with TS are not impaired in a laboratory-based measure of IC, although some difficulties were evident from measures of everyday behaviour, which may in part be due to parents and teachers interpreting tics as disinhibited behaviour. Comorbid ADHD or the severity of subthreshold ADHD symptomatology appeared to account for IC deficits.