Search

Although previous studies have suggested the involvement of dopamine (DA) and noradrenaline (NA) neurotransmissions in the autism spectrum disorder (ASD) pathophysiology, few studies have examined these neurotransmissions in individuals with ASD in vivo. Here, we investigated DA D1 receptor (D1R) and noradrenaline transporter (NAT) binding in adults with ASD (n = 18) and neurotypical controls (n = 20) by utilizing two different PET radioligands, [11C]SCH23390 and (S,S)-[18F]FMeNER-D2, respectively. We found no significant group differences in DA D1R (striatum, anterior cingulate cortex, and temporal cortex) or NAT (thalamus and pons) binding. However, in the ASD group, there were significant negative correlations between DA D1R binding (striatum, anterior cingulate cortex and temporal cortex) and the "attention to detail" subscale score of the Autism Spectrum Quotient. Further, there was a significant positive correlation between DA D1R binding (temporal cortex) and emotion perception ability assessed by the neurocognitive battery. Associations of NAT binding with empathic abilities and executive function were found in controls, but were absent in the ASD group. Although a lack of significant group differences in binding might be partly due to the heterogeneity of ASD, our results indicate that central DA and NA function might play certain roles in the clinical characteristics of ASD., (© The Author(s) 2020. Published by Oxford University Press.)

Background: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are biologically heterogeneous and often co-occur. As within-diagnosis heterogeneity and overlapping diagnoses are challenging for researchers and clinicians, identifying biologically homogenous subgroups, independent of diagnosis, is an urgent need., Methods: MRI data from 148 adult males with developmental disorders (99 primary ASD, mean age = 31.7 ± 8.0, 49 primary ADHD; mean age = 31.7 ± 9.6) and 105 neurotypical controls (NTC; mean age = 30.6 ± 6.8) were analyzed. We extracted mean cortical thickness (CT) and surface area (SA) values using a functional atlas. Then, we conducted HeterogeneitY through DiscRiminant Analysis (HYDRA) to transdiagnostically cluster and classify individuals. Differences in diagnostic likelihood and clinical symptoms between subtypes were tested. Sensitivity analyses tested the stability of the number of subtypes and their membership by excluding 13 participants diagnosed with both ASD and ADHD and by using a different atlas., Results: In relation to both CT and SA, HYDRA identified two subtypes. The likelihood of ASD or ADHD was not significantly different from the chance of belonging to any of these two subtypes. Clinical characteristics did not differ between subtypes in either CT or SA based analyses. The high consistency in membership was replicated when utilizing a different atlas or excluding people with dual diagnoses in CT (dice coefficients > 0.94) and in SA (>0.88)., Conclusion: Although the brain-derived subtypes do not match diagnostic groups, individuals with developmental disorders were successfully and stably subtyped using either CT or SA., Competing Interests: Declaration of interest SC: honoraria for talks on ADHD from: Association form Child and Adolescent Mental Health (CADDRA), British Association of Psychopharmacology (BAP), Canadian ADHD Alliance Resource (CADDRA), and Healthcare Convention. All the other authors declare no conflict of interest., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Endophenotype refers to a measurable and heritable component between genetics and diagnosis, and the same endophenotype is present in both individuals with a diagnosis and their unaffected siblings. Determination of the neural correlates of an endophenotype and diagnosis is important in autism spectrum disorder (ASD). However, prior studies enrolling individuals with ASD and their unaffected siblings have generally included only one group of typically developing (TD) subjects; they have not accounted for differences between TD siblings. Thus, they could not differentiate the neural correlates for endophenotype from the clinical diagnosis. In this context, we enrolled pairs of siblings with an ASD endophenotype (individuals with ASD and their unaffected siblings) and pairs of siblings without this endophenotype (pairs of TD siblings). Using resting-state functional MRI, we first aimed to identify an endophenotype pattern consisting of multiple functional connections (FCs) then examined the neural correlates of FCs for ASD diagnosis, controlling for differences between TD siblings. Sparse logistic regression successfully classified subjects as to the endophenotype (area under the curve = 0.78, classification accuracy = 75%). Then, a bootstrapping approach controlling for differences between TD siblings revealed that an FC between the right middle temporal gyrus and right anterior cingulate cortex was substantially different between individuals with ASD and their unaffected siblings, suggesting that this FC may be a neural correlate for the diagnosis, while the other FCs represent the endophenotype. The current findings suggest that an ASD endophenotype pattern exists in FCs, and a neural correlate for ASD diagnosis is dissociable from this endophenotype. (250 words).

In interactive social situations, it is often crucial to be able to take another person's perspective when evaluating one's own or another person's specific trait; individuals with autism spectrum disorder (ASD) critically lack this social skill. To examine how perspective-dependent self- and other-evaluation processes modulate functional connectivity in ASD, we conducted a functional magnetic resonance imaging study in which 26 high-functioning adults with ASD and 24 typically developed (TD) controls were asked to decide whether an adjective describing a personality trait correctly described the participant himself/herself ("self") or the participant's mother ("other") by taking either the first (1P) or third person (3P) perspective. We observed that functional connectivity between the left sensorimotor cortex and the left middle cingulate cortex was enhanced in TD control individuals taking the 3P perspective, this enhancement was significantly reduced in ASD, and the degree of reduction was significantly correlated with the severity of autistic traits. Furthermore, the self-reference effect on functional connectivity between the left inferior frontal cortex and frontopolar cortices was significantly enhanced in TD control individuals taking the 3P perspective, whereas such effect was reversed in ASD. These findings indicate altered effects of perspective on the functional connectivity, which may underlie the deficits in social interaction and communication observed in individuals with ASD.

Therapeutic applications of repetitive transcranial magnetic stimulation (rTMS) have long been awaited for not only neurological but also psychiatric disorders as a low-invasive transcranial brain stimulation. In 2008, the Food and Drug Administration (FDA) of the United States finally approved repetitive transcranial magnetic stimulation (rTMS) for medication-resistant patients with major depression. More recently, at the beginning of 2013, a deep TMS device with the H-coil received FDA approval as the second TMS device for major depression. In Japan, it is estimated that more than 200,000 patients with medication-resistant major depression could be candidates for rTMS treatment. To promote the clinical introduction of rTMS for major depression, joint discussion has been ongoing including the Japanese Society of Psychiatry and Neurology (JSPN), the Japanese Ministry of Health, Labour, and Welfare (MHLW), and the Pharmaceutical and Medical Devices Agency (PMDA). On the other hand, some corporate efforts have begun to get MHLW/PMDA approval for a few types of rTMS device. In 2013, the JSPN established a new committee in order to discuss the introduction of neuromodulation methods such as rTMS in Japan. The committee has been discussing how rTMS should be introduced appropriately with expedition, considering the MHLW regulations for the expedited introduction or provisional use of advanced medical technology. Also, the MHLW has required related psychiatric societies to formulate clinical guidelines of rTMS for major depression in order to avoid any potential overuse or misuse. A number of controversies are ongoing, such as standards for the appropriate clinical application of rTMS, a suitable position of rTMS within the comprehensive treatment algorithm of major depression, and bioethical standards for brain stimulation (neuroethics). Moreover, there are some pragmatic issues. For instance, the Japanese Society of Clinical Neurophysiology (JSCN) has restricted repetitive TMS administration to medical doctors due to safety concerns. In order to disseminate rTMS in Japan, it should be discussed how to reduce the work-load of psychiatrists who administer rTMS on a daily basis. For this purpose, standards should be established by the JSCN to qualify non-MD rTMS operators under the supervision of psychiatrists. In this paper, recent progress in the clinical introduction of rTMS for major depression in Japan is reported, in order to facilitate future discussion about how rTMS should be introduced for patients with major depression in Japan.

Growing evidence suggests that a broad range of behavioral anomalies in people with autism spectrum disorder (ASD) can be linked with morphological and functional alterations in the brain. However, the neuroanatomical underpinnings of ASD have been investigated using either structural magnetic resonance imaging (MRI) or diffusion tensor imaging (DTI), and the relationships between abnormalities revealed by these two modalities remain unclear. This study applied a multimodal data-fusion method, known as linked independent component analysis (ICA), to a set of structural MRI and DTI data acquired from 46 adult males with ASD and 46 matched controls in order to elucidate associations between different aspects of atypical neuroanatomy of ASD. Linked ICA identified two composite components that showed significant between-group differences, one of which was significantly correlated with age. In the other component, participants with ASD showed decreased gray matter (GM) volumes in multiple regions, including the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral pre- and post-central gyri. These GM changes were linked with a pattern of decreased fractional anisotropy (FA) in several white matter tracts, such as the bilateral inferior longitudinal fasciculi, bilateral inferior fronto-occipital fasciculi, and bilateral corticospinal tracts. Furthermore, unimodal analysis for DTI data revealed significant reductions of FA along with increased mean diffusivity in those tracts for ASD, providing further evidence of disrupted anatomical connectivity. Taken together, our findings suggest that, in ASD, alterations in different aspects of brain morphology may co-occur in specific brain networks, providing a comprehensive view for understanding the neuroanatomy of this disorder.

Recent functional magnetic resonance imaging (fMRI) studies on autism spectrum condition (ASC) have identified dysfunctions in specific brain networks involved in social and non-social cognition that persist into adulthood. Although increasing numbers of fMRI studies have revealed atypical functional connectivity in the adult ASC brain, such functional alterations at the network level have not yet been fully characterized within the recently developed graph-theoretical framework. Here, we applied a graph-theoretical analysis to resting-state fMRI data acquired from 46 adults with ASC and 46 age- and gender-matched controls, to investigate the topological properties and organization of autistic brain network. Analyses of global metrics revealed that, relative to the controls, participants with ASC exhibited significant decreases in clustering coefficient and characteristic path length, indicating a shift towards randomized organization. Furthermore, analyses of local metrics revealed a significantly altered organization of the hub nodes in ASC, as shown by analyses of hub disruption indices using multiple local metrics and by a loss of "hubness" in several nodes (e.g., the bilateral superior temporal sulcus, right dorsolateral prefrontal cortex, and precuneus) that are critical for social and non-social cognitive functions. In particular, local metrics of the anterior cingulate cortex consistently showed significant negative correlations with the Autism-Spectrum Quotient score. Our results demonstrate altered patterns of global and local topological properties that may underlie impaired social and non-social cognition in ASC.

We examined variability in performance on widely-used neuropsychological Wechsler tests of intelligence and memory in a large sample of persons with chronic schizophrenia, a subset of whom had also undergone prior studies of magnetic resonance imaging (MRI) of the orbital frontal cortex (OFC) gray matter and diffusion tensor imaging (DTI) of the cingulum bundle (CB) and the uncinate fasiculus (UF) white matter. In comparison to controls, persons with schizophrenia showed lower scores across neuropsychological tests, with most pronounced drops in processing speed and immediate memory, in relation to oral reading. For patients, greater declines in intelligence and memory each correlated with reduced CB white matter fractional anisotropy and reduced OFC gray matter, respectively. However, only memory decline correlated with severity of negative symptoms. Taken together, these data raise the intriguing question as to whether communication and motivational deficits expressed in negative symptoms may contribute to the relationship of auditory memory decline and OFC volume observed in this patient sample.

While clinical features of panic disorder show significant sexual dimorphism, previous structural MRI studies have not sufficiently controlled for sex when looking at regional brain abnormalities in panic disorder. Using optimized voxel-based morphometry (VBM), regional gray matter volume was compared between 24 patients (male/female: 9/15) with panic disorder and 24 healthy subjects matched for age and sex. Significant gray matter volume reductions were found in the bilateral dorsomedial and right ventromedial prefrontal cortices, right amygdala, anterior cingulate cortex, bilateral insular cortex, occipitotemporal gyrus and left cerebellar vermis in the patients compared with the controls. Among these regions, the VBM revealed significant sexual dimorphism: volume reduction in the right amygdala and the bilateral insular cortex was significantly greater in the males, while reduction in the right superior temporal gyrus was greater in females. Furthermore, a significant reduction in the dorsolateral and ventrolateral prefrontal cortices, thalamus, and parietal cortex was specific to the female patients. The present study demonstrated the morphological changes in extensive brain regions of patients with panic disorder compared with the sex-matched controls. The current results further suggested that the sexually dimorphic clinical phenotypes of panic disorder might have a neurobiological background even at the structural level of the brain.

We introduce an algorithm for segmenting brain magnetic resonance (MR) images into anatomical compartments such as the major tissue classes and neuro-anatomical structures of the gray matter. The algorithm is guided by prior information represented within a tree structure. The tree mirrors the hierarchy of anatomical structures and the subtrees correspond to limited segmentation problems. The solution to each problem is estimated via a conventional classifier. Our algorithm can be adapted to a wide range of segmentation problems by modifying the tree structure or replacing the classifier. We evaluate the performance of our new segmentation approach by revisiting a previously published statistical group comparison between first-episode schizophrenia patients, first-episode affective psychosis patients, and comparison subjects. The original study is based on 50 MR volumes in which an expert identified the brain tissue classes as well as the superior temporal gyrus, amygdala, and hippocampus. We generate analogous segmentations using our new method and repeat the statistical group comparison. The results of our analysis are similar to the original findings, except for one structure (the left superior temporal gyrus) in which a trend-level statistical significance (p = 0.07) was observed instead of statistical significance.

Abstract: In this paper, we present a set of techniques for the evaluation of brain tissue classifiers on a large data set of MR images of the head. Due to the difficulty of establishing a gold standard for this type of data, we focus our attention on methods which do not require a ground truth, but instead rely on a common agreement principle. Three different techniques are presented: the Williams’ index, a measure of common agreement; STAPLE, an Expectation Maximization algorithm which simultaneously estimates performance parameters and constructs an estimated reference standard; and Multidimensional Scaling, a visualization technique to explore similarity data. We apply these different evaluation methodologies to a set of eleven different segmentation algorithms on forty MR images. We then validate our evaluation pipeline by building a ground truth based on human expert tracings. The evaluations with and without a ground truth are compared. Our findings show that comparing classifiers without a gold standard can provide a lot of interesting information. In particular, outliers can be easily detected, strongly consistent or highly variable techniques can be readily discriminated, and the overall similarity between different techniques can be assessed. On the other hand, we also find that some information present in the expert segmentations is not captured by the automatic classifiers, suggesting that common agreement alone may not be sufficient for a precise performance evaluation of brain tissue classifiers. [Copyright &y& Elsevier]