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BACKGROUND: Differences in responding to sensory stimuli, including sensory hyperreactivity (HYPER), hyporeactivity (HYPO), and sensory seeking (SEEK) have been observed in autistic individuals across sensory modalities, but few studies have examined the structure of these supra-modal traits in the autistic population. METHODS: Leveraging a combined sample of 3868 autistic youth drawn from 12 distinct data sources (ages 3-18 years and representing the full range of cognitive ability), the current study used modern psychometric and meta-analytic techniques to interrogate the latent structure and correlates of caregiver-reported HYPER, HYPO, and SEEK within and across sensory modalities. Bifactor statistical indices were used to both evaluate the strength of a general response pattern factor for each supra-modal construct and determine the added value of modality-specific response pattern scores (e.g., Visual HYPER). Bayesian random-effects integrative data analysis models were used to examine the clinical and demographic correlates of all interpretable HYPER, HYPO, and SEEK (sub)constructs. RESULTS: All modality-specific HYPER subconstructs could be reliably and validly measured, whereas certain modality-specific HYPO and SEEK subconstructs were psychometrically inadequate when measured using existing items. Bifactor analyses supported the validity of a supra-modal HYPER construct (ωH = .800) but not a supra-modal HYPO construct (ωH = .653), and supra-modal SEEK models suggested a more limited version of the construct that excluded some sensory modalities (ωH = .800; 4/7 modalities). Modality-specific subscales demonstrated significant added value for all response patterns. Meta-analytic correlations varied by construct, although sensory features tended to correlate most with other domains of core autism features and co-occurring psychiatric symptoms (with general HYPER and speech HYPO demonstrating the largest numbers of practically significant correlations). LIMITATIONS: Conclusions may not be generalizable beyond the specific pool of items used in the current study, which was limited to caregiver report of observable behaviors and excluded multisensory items that reflect many real-world sensory experiences. CONCLUSION: Of the three sensory response patterns, only HYPER demonstrated sufficient evidence for valid interpretation at the supra-modal level, whereas supra-modal HYPO/SEEK constructs demonstrated substantial psychometric limitations. For clinicians and researchers seeking to characterize sensory reactivity in autism, modality-specific response pattern scores may represent viable alternatives that overcome many of these limitations.

Depression and sensory reactivity are both common in autism. However, there is little understanding of the predictive relationship between these factors, or the nature of this relationship in autistic children who speak few to no words. This study set out to explore the longitudinal relationship between sensory reactivity and depressive symptoms in 33 young autistic children who speak few to no words. We found positive correlations between depressive symptoms and hyper-reactivity and sensory seeking at both timepoints, and across timepoints. We further found a bidirectional predictive relationship between depressive symptoms and sensory seeking. These results implicate sensory seeking in the development of depressive symptoms in young autistic children who use few to no words. Our findings have important implications for preventative mental health interventions, especially for those with a developmental language delay., Author(s): Timothy Rossow [sup.1] , Keren MacLennan [sup.1] , Teresa Tavassoli [sup.1] Author Affiliations: (1) grid.9435.b, 0000 0004 0457 9566, University of Reading, , Harry Pitt Building, Earley Gate, RG6 [...]

Background:Sensory processing difficulties are common across neurodevelopmental disorders. Thus, reliable measures are needed to understand the biological underpinnings of these differences. This study aimed to define a scoring methodology specific to auditory (AOR) and tactile (TOR) over-responsivity. Second, in a pilot cohort using MRI Diffusion Tensor Imaging, we performed a proof of concept study of whether children with AOR showed measurable differences in their white matter integrity. Methods:This study included children with AOR and TOR from a mixed neurodevelopmental disorder cohort including autism and sensory processing dysfunction (n = 176) as well as neurotypical children (n = 128). We established cohorts based on sensory over-responsivity using parent report (Short Sensory Profile (SSP)) and direct assessment (Sensory Processing-Three Dimensions: Assessment (SP-3D:A)) measures. With a subset of the children (n = 39), group comparisons, based on AOR phenotype, were conducted comparing the white matter fractional anisotropy in 23 regions of interest. Results:Using direct assessment, 31% of the children with neurodevelopmental disorders had AOR and 27% had TOR. The inter-test agreement between SSP and SP-3D:A for AOR was 65% and TOR was 50%. Children with AOR had three white matter tracts showing decreased fractional anisotropy relative to children without AOR. Conclusions:This study identified cut-off scores for AOR and TOR using the SSP parent report and SP-3D:A observation. A combination of questionnaire and direct observation measures should be used in clinical and research settings. The SSP parent report and SP-3D:A direct observation ratings overlapped moderately for sensory related behaviors. Based on these preliminary structural neuroimaging results, we suggest a putative neural network may contribute to AOR.

Sensory reactivity differences are a diagnostic criterion of autism. Sensory hyperreactivity has been linked to intolerance of uncertainty and anxiety in autistic children. However, research is yet to explore the mediating relationships or sensory hyporeactivity, seeking and anxiety subtypes in preschool-age autistic children. Therefore, we aimed to elucidate the relationships between sensory reactivity, intolerance of uncertainty and anxiety subtypes in a heterogeneous group of 54 preschool-age autistic children, age 3-5 years, using observation and parent-report assessments. Correlational analysis found sensory hyperreactivity, intolerance of uncertainty and total anxiety were significantly intercorrelated. In addition, sensory hyperreactivity was significantly correlated with separation anxiety when controlling for autism traits. Serial mediation analyses indicated significant full mediation between sensory hyperreactivity and anxiety through intolerance of uncertainty, and significant full mediation between sensory hyperreactivity and intolerance of uncertainty through anxiety. Our results suggest that sensory hyperreactivity is a key early factor in the development of anxiety, and supports that intolerance of uncertainty is an important interrelated construct in the development and maintenance of anxiety in autism. Our findings have important implications for the development of effective interventions. However, due to limitations with the measures, our research also highlights a pressing need for objective assessments of anxiety and intolerance of uncertainty that can be used with preschool-age autistic children.

Prior neuroimaging studies have reported white matter network underconnectivity as a potential mechanism for autism spectrum disorder (ASD). In this study, we examined the structural connectome of children with ASD using edge density imaging (EDI), and then applied machine-learning algorithms to identify children with ASD based on tract-based connectivity metrics. Boys aged 8-12 years were included: 14 with ASD and 33 typically developing children. The edge density (ED) maps were computed from probabilistic streamline tractography applied to high angular resolution diffusion imaging. Tract-based spatial statistics was used for voxel-wise comparison and coregistration of ED maps in addition to conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD). Tract-based average DTI/connectome metrics were calculated and used as input for different machine-learning models: naïve Bayes, random forest, support vector machines (SVMs), and neural networks. For these models, cross-validation was performed with stratified random sampling ( × 1,000 permutations). The average accuracy among validation samples was calculated. In voxel-wise analysis, the body and splenium of corpus callosum, bilateral superior and posterior corona radiata, and left superior longitudinal fasciculus showed significantly lower ED in children with ASD; whereas, we could not find significant difference in FA, MD, and RD maps between the two study groups. Overall, machine-learning models using tract-based ED metrics had better performance in identification of children with ASD compared with those using FA, MD, and RD. The EDI-based random forest models had greater average accuracy (75.3%), specificity (97.0%), and positive predictive value (81.5%), whereas EDI-based polynomial SVM had greater sensitivity (51.4%) and negative predictive values (77.7%). In conclusion, we found reduced density of connectome edges in the posterior white matter tracts of children with ASD, and demonstrated the feasibility of connectome-based machine-learning algorithms in identification of children with ASD.

Sensory over-responsivity (SOR) commonly involves auditory and/or tactile domains, and can affect children with or without additional neurodevelopmental challenges. In this study, we examined white matter microstructural and connectome correlates of auditory over-responsivity (AOR), analyzing prospectively collected data from 39 boys, aged 8-12 years. In addition to conventional diffusion tensor imaging (DTI) maps - including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD); we used DTI and high-resolution T1 scans to develop connectome Edge Density (ED) maps. The tract-based spatial statistics was used for voxel-wise comparison of diffusion and ED maps. Then, stepwise penalized logistic regression was applied to identify independent variable (s) predicting AOR, as potential imaging biomarker (s) for AOR. Finally, we compared different combinations of machine learning algorithms (i.e., naïve Bayes, random forest, and support vector machine (SVM) and tract-based DTI/connectome metrics for classification of children with AOR. In direct sensory phenotype assessment, 15 (out of 39) boys exhibited AOR (with or without neurodevelopmental concerns). Voxel-wise analysis demonstrates extensive impairment of white matter microstructural integrity in children with AOR on DTI maps - evidenced by lower FA and higher MD and RD; moreover, there was lower connectome ED in anterior-superior corona radiata, genu and body of corpus callosum. In stepwise logistic regression, the average FA of left superior longitudinal fasciculus (SLF) was the single independent variable distinguishing children with AOR (p = 0.007). Subsequently, the left SLF average FA yielded an area under the curve of 0.756 in receiver operating characteristic analysis for prediction of AOR (p = 0.008) as a region-of-interest (ROI)-based imaging biomarker. In comparative study of different combinations of machine-learning models and DTI/ED metrics, random forest algorithms using ED had higher accuracy for AOR classification. Our results demonstrate extensive white matter microstructural impairment in children with AOR, with specifically lower connectomic ED in anterior-superior tracts and associated commissural pathways. Also, average FA of left SLF can be applied as ROI-based imaging biomarker for prediction of SOR. Finally, machine-learning models can provide accurate and objective image-based classifiers for identification of children with AOR based on white matter tracts connectome ED.

The "sensory processing disorder" (SPD) refers to brain's inability to organize sensory input for appropriate use. In this study, we determined the diffusion tensor imaging (DTI) microstructural and connectivity correlates of SPD, and apply machine learning algorithms for identification of children with SPD based on DTI/tractography metrics. A total of 44 children with SPD and 41 typically developing children (TDC) were prospectively recruited and scanned. In addition to fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD), we applied probabilistic tractography to generate edge density (ED) and track density (TD) from DTI maps. For identification of children with SPD, accurate classification rates from a combination of DTI microstructural (FA, MD, AD, and RD), connectivity (TD) and connectomic (ED) metrics with different machine learning algorithms - including naïve Bayes, random forest, support vector machine, and neural networks - were determined. In voxel-wise analysis, children with SPD had lower FA, ED, and TD but higher MD and RD compared to TDC - predominantly in posterior white matter tracts including posterior corona radiata, posterior thalamic radiation, and posterior body and splenium of corpus callosum. In stepwise penalized logistic regression, the only independent variable distinguishing children with SPD from TDC was the average TD in the splenium (p

This pilot study estimates the effects of family structure on age of diagnosis, with the goal of identifying factors that may accelerate or delay diagnosis. We conducted an online survey with 477 parents of children with autism. In addition, we carried out novel, follow-up surveys of 196 "friends and family," who were referred by parents. Family structure and frequency of interactions with family members have significant effects on age of diagnosis (p < 0.05). In all, 25% of parents report that other individuals indicated that their child might have a serious condition before they themselves suspected it. Moreover, around 50% of friends and family report that they suspected that the child had a serious condition before they were aware that either parent was concerned, suggesting that the clues were there to see, especially for experienced viewers. While half of those individuals shared their concerns with the parents, the other half either did not raise any concern (23%) or just "hinted" at their concern (27%). Among children with siblings, children with an older sibling are diagnosed approximately 10 months earlier (p < 0.01) than those without, and children with no siblings were diagnosed 6-8 months earlier than children with siblings (p < 0.01). Interestingly, frequent interactions with grandparents, especially grandmothers, significantly lowered the age of diagnosis by as much as 5 months (p < 0.05). While this pilot study requires replication, the results identify potential causes for accelerated or delayed diagnosis, which if better understood, could ultimately improve age of diagnosis and treatment, and hence outcomes.

Abstract Background Vision in people with autism spectrum conditions (ASC) is reported to be different from people without ASC, but the neural level at which the differences begin to occur is not yet known. Here we examine two variants of a vernier acuity task to determine if differences are evident in early visual processing. Findings Abutting and separated vernier acuity was assessed in 16 people with ASC and 14 matched controls. In controls, abutting and separated thresholds were unrelated (r = 0.13, p = 0.65), suggesting thresholds are determined by two separate mechanisms. In contrast, the abutting and separated thresholds of ASC observers were strongly correlated (r = 0.88, p < 0.0001), with separated thresholds tending towards being superior to those of controls [t(28) = −2.46, p = 0.02]. Conclusions The findings suggest the mechanisms employed by ASC observers in separated vernier tasks are different to those of controls. This psychophysical evidence suggests that visual differences in ASC may begin at an early cortical stage of visual processing.

Sensory reactivity is a new DSM-5 criterion for autism spectrum disorder (ASD). The current study aims to validate a clinician-administered sensory observation in ASD, the Sensory Processing Scale Assessment (SPS). The SPS and the Short Sensory Profile (SSP) parent-report were used to measure sensory reactivity in children with ASD (n = 35) and typically developing children (n = 27). Sixty-five percent of children with ASD displayed sensory reactivity symptoms on the SPS and 81.1% on the SSP. SPS scores significantly predicted SSP scores. We next identified the five SPS tasks that best differentiated groups. Our results indicate that a combination of parent-report and at least the five most differentiating observational tasks may be most sensitive in identifying the presence of sensory reactivity issues.

Anecdotal reports and empirical evidence suggest that sensory processing issues are a key feature of autism spectrum conditions. This study set out to investigate whether adults with autism spectrum conditions report more sensory over-responsivity than adults without autism spectrum conditions. Another goal of the study was to identify whether autistic traits in adults with and without autism spectrum conditions were associated with sensory over-responsivity. Adults with (n = 221) and without (n = 181) autism spectrum conditions participated in an online survey. The Autism Spectrum Quotient, the Raven Matrices and the Sensory Processing Scale were used to characterize the sample. Adults with autism spectrum conditions reported more sensory over-responsivity than control participants across various sensory domains (visual, auditory, tactile, olfactory, gustatory and proprioceptive). Sensory over-responsivity correlated positively with autistic traits (Autism Spectrum Quotient) at a significant level across groups and within groups. Adults with autism spectrum conditions experience sensory over-responsivity to daily sensory stimuli to a high degree. A positive relationship exists between sensory over-responsivity and autistic traits. Understanding sensory over-responsivity and ways of measuring it in adults with autism spectrum conditions has implications for research and clinical settings.

People with autism and Asperger syndrome are anecdotally said to be hypersensitive to touch. In two experiments, we measured tactile thresholds and suprathreshold tactile sensitivity in a group of adults with Asperger syndrome. In the first experiment, tactile perceptual thresholds were measured. Two frequencies of vibrotactile stimulation were used: 30 and 200 Hz. The results demonstrated significantly lower tactile perceptual thresholds in the Asperger group at 200 Hz but not at 30 Hz, thus confirming tactile hypersensitivity but only for one class of stimulus. A second experiment investigated whether self-produced movement affected the perception of touch in a group of adults with Asperger syndrome. A suprathreshold tactile stimulus was produced either by the participant (self-produced condition) or by the experimenter (externally produced condition) and participants were asked to rate the perception of the tactile stimulation. The results demonstrated that, while both Asperger and control groups rated self-produced touch as less tickly than external touch, the Asperger group rated both types of tactile stimulus as significantly more tickly and intense than did the control group. This experiment confirms the finding of tactile hypersensitivity, but shows that the perceptual consequences of self-produced touch are attenuated in the normal way in people with Asperger syndrome. An abnormality in this process cannot therefore account for their tactile hypersensitivity.

Sensory reactivity differences are experienced by between 5% and 15% of the population, often taking the form of sensory over-responsivity (SOR), in which sensory stimuli are experienced as unusually intense and everyday function is affected. A potential mechanism underlying over-responsivity is an imbalance between neural excitation and inhibition in which inhibitory influences are relatively weakened. Therefore, interventions that boost neural inhibition or reduce neural excitation may reduce SOR; Vitamin-B6 is the coenzyme for the conversion of excitatory glutamate to inhibitory gamma-aminobutyric acid (GABA), and in animal models, it both increases the concentration of GABA and reduces glutamate.To discover whether taking a high dose of Vitamin-B6 reduces SOR and other aspects of sensory reactivity.We recruited 300 adults (249 females) from the general population who completed the Sensory Processing 3-Dimensions Scale (SP-3D) first at baseline, and again following randomisation to either 1 month’s supplementation with 100 mg Vitamin-B6, or one of two control conditions (1000 µg Vitamin-B12 or placebo). To focus on individuals who experience SOR, we analysed the effects of supplementation only on individuals with high baseline SOR scores (above the 87th percentile).In individuals with SOR at baseline, Vitamin-B6 selectively reduced SOR compared to both placebo and Vitamin-B12. We also found that Vitamin-B6 selectively reduced postural disorder in individuals with high scores on this subscale at baseline, but there were no effects on the four remaining SP-3D subscales.Clinical trials and mechanistic studies should now be conducted in autism, attention deficit hyperactivity disorder and other groups with SOR. [ABSTRACT FROM AUTHOR]

Abstract Background Autism spectrum conditions have a strong genetic component. Atypical sensory sensitivities are one of the core but neglected features of autism spectrum conditions. GABRB3 is a well-characterised candidate gene for autism spectrum conditions. In mice, heterozygous Gabrb3 deletion is associated with increased tactile sensitivity. However, no study has examined if tactile sensitivity is associated with GABRB3 genetic variation in humans. To test this, we conducted two pilot genetic association studies in the general population, analysing two phenotypic measures of tactile sensitivity (a parent-report and a behavioural measure) for association with 43 SNPs in GABRB3. Findings Across both tactile sensitivity measures, three SNPs (rs11636966, rs8023959 and rs2162241) were nominally associated with both phenotypes, providing a measure of internal validation. Parent-report scores were nominally associated with six SNPs (P Conclusions This is the first human study to show an association between GABRB3 variation and tactile sensitivity. This provides support for the evidence from animal models implicating the role of GABRB3 variation in the atypical sensory sensitivity in autism spectrum conditions. Future research is underway to directly test this association in cases of autism spectrum conditions.