BackgroundAutism spectrum traits are postulated to lie on a continuum that extends between individuals with autism and individuals with typical development (TD). Social cognition properties that are deeply associated with autism spectrum traits have been linked to functional connectivity between regions within the brain’s default mode network (DMN). Previous studies have shown that the resting-state functional connectivities (rs-FCs) of DMN are low and show negative correlation with the level of autism spectrum traits in individuals with autism spectrum disorder (ASD). However, it is unclear whether individual differences of autism spectrum traits are associated with the strength of rs-FCs of DMN in participants including the general population.MethodsUsing the seed-based approach, we investigated the rs-FCs of DMN, particularly including the following two core regions of DMN: the anterior medial prefrontal cortex (aMPFC) and posterior cingulate cortex (PCC) in 19 young male adults with high-functioning ASD (mean age = 25.3 ± 6.9 years; autism-spectrum quotient (AQ) = 33.4 ± 4.2; full scale IQ (F-IQ) = 109.7 ± 12.4) compared with 21 age- and IQ-matched young male adults from the TD group (mean age = 24.8 ± 4.3 years; AQ = 18.6 ± 5.7; F-IQ = 109.5 ± 8.7). We also analyzed the correlation between the strength of rs-FCs and autism spectrum traits measured using AQ score.ResultsThe strengths of rs-FCs from core regions of DMN were significantly lower in ASD participants than TD participants. Under multiple regression analysis, the strengths of rs-FCs in brain areas from aMPFC seed showed negative correlation with AQ scores in ASD participants and TD participants.ConclusionsOur findings suggest that the strength of rs-FCs in DMN is associated with autism spectrum traits in the TD population as well as patients with ASD, supporting the continuum view. The rs-FCs of DMN may be useful biomarkers for the objective identification of autism spectrum traits, regardless of ASD diagnosis.

BackgroundGaze abnormality is a diagnostic criterion for autism spectrum disorder (ASD). However, few easy-to-use clinical tools exist to evaluate the unique eye-gaze patterns of ASD. Recently, we developed Gazefinder, an all-in-one eye-tracking system for early detection of ASD in toddlers. Because abnormal gaze patterns have been documented in various ASD age groups, we predicted that Gazefinder might also detect gaze abnormality in adolescents and adults. In this study, we tested whether Gazefinder could identify unique gaze patterns in adolescents and adults with ASD.MethodsWe measured the percentage of eye fixation time allocated to particular objects depicted in movies (i.e., eyes and mouth in human face movies, upright and inverted biological motion in movies that presented these stimuli simultaneously, and people and geometry in movies that presented these stimuli simultaneously) by male adolescents and adults with ASD (N = 26) and age-matched males with typical development (TD; N = 35). We compared these percentages between the two groups (ASD and TD) and with scores on the social responsiveness scale (SRS). Further, we conducted discriminant analyses to determine if fixation times allocated to particular objects could be used to discriminate between individuals with and without ASD.ResultsCompared with the TD group, the ASD group showed significantly less fixation time at locations of salient social information (i.e., eyes in the movie of human faces without lip movement and people in the movie of people and geometry), while there were no significant groupwise differences in the responses to movies of human faces with lip movement or biological motion. In a within-group correlation analysis, a few of the fixation-time items correlated with SRS, although most of them did not. No items significantly correlated with SRS in both ASD and TD groups. The percentage fixation times to eyes and people, which exhibited large effect sizes for the group difference, could differentiate ASD and TD with a sensitivity of 81.0 % and a specificity of 80.0 %.ConclusionsThese findings suggest that Gazefinder is potentially a valuable and easy-to-use tool for objectively measuring unique gaze patterns and discriminating between ASD and TD in male adolescents and adults.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-016-0083-y) contains supplementary material, which is available to authorized users.

Recent studies have suggested that long-term oxytocin administration can alleviate the symptoms of autism spectrum disorder (ASD); however, factors influencing its efficacy are still unclear. We conducted a single-center phase 2, pilot, randomized, double-blind, placebo-controlled, parallel-group, clinical trial in young adults with high-functioning ASD, to determine whether oxytocin dosage and genetic background of the oxytocin receptor affects oxytocin efficacy. This trial consisted of double-blind (12 weeks), open-label (12 weeks) and follow-up phases (8 weeks). To examine dose dependency, 60 participants were randomly assigned to high-dose (32 IU per day) or low-dose intranasal oxytocin (16 IU per day), or placebo groups during the double-blind phase. Next, we measured single-nucleotide polymorphisms (SNPs) in the oxytocin receptor gene (OXTR). In the intention-to-treat population, no outcomes were improved after oxytocin administration. However, in male participants, Clinical Global Impression-Improvement (CGI-I) scores in the high-dose group, but not the low-dose group, were significantly higher than in the placebo group. Furthermore, we examined whether oxytocin efficacy, reflected in the CGI-I scores, is influenced by estimated daily dosage and OXTR polymorphisms in male participants. We found that >21 IU per day oxytocin was more effective than ⩽21 IU per day, and that a SNP in OXTR (rs6791619) predicted CGI-I scores for ⩽21 IU per day oxytocin treatment. No severe adverse events occurred. These results suggest that efficacy of long-term oxytocin administration in young men with high-functioning ASD depends on the oxytocin dosage and genetic background of the oxytocin receptor, which contributes to the effectiveness of oxytocin treatment of ASD.

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Accumulating evidence has shown that complicated brain systems are involved in the development and maintenance of chronic low back pain (cLBP), but its underlying mechanisms, particularly the association between brain functional changes and clinical outcomes, remain unclear. Here we used resting-state fMRI and multivariate pattern analysis (MVPA) to identify abnormal functional connectivity (FC) between the default mode, sensorimotor, salience and central executive brain networks in cLBP and tested whether abnormal FCs are related to pain and comorbid symptoms. Fifty cLBP patients and 44 matched healthy controls (HCs) underwent an fMRI scan, from which brain networks were identified by independent component analysis. MVPA, graph theory approaches, and correlation analyses were applied to find abnormal FCs that were associated with clinical symptoms. Findings were validated on a second cohort of 30 cLBP patients and 30 matched HCs. Results showed the medial prefrontal cortex (mPFC) had abnormal FCs with brain regions within the DMN and with other brain networks in cLBP patients. These altered FCs were also correlated with pain duration, pain severity, and pain interference. Lastly, we found restingstate FC could discriminate cLBP patients from HCs with 91% accuracy in the first cohort and 78% accuracy in the validation cohort. Our findings suggest the mPFC may be an important hub for linking the default mode network with the other three networks in cLBP patients. Elucidating the altered FCs and their association with clinical outcomes will enhance our understanding of the pathophysiology of cLBP and may facilitate the development of pain management approaches.

BackgroundBoth attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental disorders with a high prevalence. They are often comorbid and both exhibit abnormalities in sustained attention, yet common and distinct neural patterns of ASD and ADHD remain unidentified.AimsTo investigate shared and distinct functional connectivity patterns in a relatively large sample of boys (7- to 15-year-olds) with ADHD, ASD and typical development matched by age, gender and IQ.MethodWe applied machine learning techniques to investigate patterns of surface-based brain resting-state connectivity in 86 boys with ASD, 83 boys with ADHD and 125 boys with typical development.ResultsWe observed increased functional connectivity within the limbic and somatomotor networks in boys with ASD compared with boys with typical development. We also observed increased functional connectivity within the limbic, visual, default mode, somatomotor, dorsal attention, frontoparietal and ventral attention networks in boys with ADHD compared with boys with ASD. In addition, using a machine learning approach, we were able to discriminate typical development from ASD, typical development from ADHD and ASD from ADHD with accuracy rates of 76.3%, 84.1%, and 79.3%, respectively.ConclusionsOur results may shed new light on the underlying mechanisms of ASD and ADHD and facilitate the development of new diagnostic methods for these disorders.Declaration of interestJ.K. holds equity in a startup company, MNT.

Chronic low back pain (cLBP) is associated with widespread functional and structural changes in the brain. This study aims to investigate the resting state functional connectivity (rsFC) changes of visual networks in cLBP patients and the feasibility of distinguishing cLBP patients from healthy controls using machine learning methods. cLBP ( n = 90) and control individuals ( n = 74) were enrolled and underwent resting-state BOLD fMRI scans. Primary, dorsal, and ventral visual networks derived from independent component analysis were used as regions of interest to compare resting state functional connectivity changes between the cLBP patients and healthy controls. We then applied a support vector machine classifier to distinguish the cLBP patients and control individuals. These results were further verified in a new cohort of subjects. We found that the functional connectivity between the primary visual network and the somatosensory/motor areas were significantly enhanced in cLBP patients. The rsFC between the primary visual network and S1 was negatively associated with duration of cLBP. In addition, we found that the rsFC of the visual network could achieve a classification accuracy of 79.3% in distinguishing cLBP patients from HCs, and these results were further validated in an independent cohort of subjects (accuracy = 66.7%). Our results demonstrate significant changes in the rsFC of the visual networks in cLBP patients. We speculate these alterations may represent an adaptation/self-adjustment mechanism and cross-model interaction between the visual, somatosensory, motor, attention, and salient networks in response to cLBP. Elucidating the role of the visual networks in cLBP may shed light on the pathophysiology and development of the disorder.

Autism spectrum traits exist on a continuum and are more common in males than in females, but the basis for this sex difference is unclear. To this end, the present study draws on the extreme male brain theory, investigating the relationship between sex difference and the default mode network (DMN), both known to be associated with autism spectrum traits. Resting-state functional magnetic resonance imaging (MRI) was carried out in 42 females (mean age ± standard deviation, 22.4 ± 4.2 years) and 43 males (mean age ± standard deviation, 23.8 ± 3.9 years) with typical development. Using a combination of different analyses (viz., independent component analysis (ICA), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and seed-based analyses), we examined sex differences in the DMN and the relationship to autism spectrum traits as measured by autism-spectrum quotient (AQ) scores. We found significant differences between female and male subjects in DMN brain regions, with seed-based analysis revealing a significant negative correlation between default-mode resting state functional connectivity of the anterior medial prefrontal cortex seed (aMPFC) and AQ scores in males. However, there were no relationships between DMN sex differences and autism spectrum traits in females. Our findings may provide important insight into the skewed balance of functional connectivity in males compared to females that could serve as a potential biomarker of the degree of autism spectrum traits in line with the extreme male brain theory.