Reduced hemispheric asymmetry of brain anatomical networks in attention deficit hyperactivity disorder

Clinical implications of brain asymmetries

No two human brains are alike, and with the rise of precision medicine in neurology, we are seeing an increased emphasis on understanding the individual variability in brain structure and function that renders every brain unique. Functional and structural brain asymmetries are a fundamental principle of brain organization, and recent research suggests substantial individual variability in these asymmetries that needs to be considered in clinical practice. In this Review, we provide an overview of brain asymmetries, variations in such asymmetries and their relevance in the clinical context. We review recent findings on brain asymmetries in neuropsychiatric and neurodevelopmental disorders, as well as in specific learning disabilities, with an emphasis on large-scale database studies and meta-analyses. We also highlight the relevance of asymmetries for disease symptom onset in neurodegenerative diseases and their implications for lateralized treatments, including brain stimulation. We conclude that alterations in brain asymmetry are not sufficiently specific to act as diagnostic biomarkers but can serve as meaningful symptom or treatment response biomarkers in certain contexts. On the basis of these insights, we provide several recommendations for neurological clinical practice.

Aberrant brain dynamics and spectral power in children with ADHD and its subtypes

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants (54 ADHD-Is and 53 ADHD-Cs and 54 healthy controls). Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (p = 1.46e-3), while the duration and contribution of frontal-parietal network (state D) were increased (p = 1.57e-3; p = 1.26e-4). Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I (p = 9.35e-5; p = 1.51e-8), suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

EEG frontal lobe asymmetry as a function of sex, depression severity, and depression subtype

To investigate possible contributors to the inconsistent association between frontal lobe asymmetry (FLA) and depression, EEG data were collected across five frontal sites, and examined for their associations with four subtypes of depression (Depressed mood, Anhedonia, Cognitive depression, Somatic depression). One hundred community volunteers (54 males, 46 females) aged at least 18 yr completed standardized scales for depression and anxiety, and gave EEG data under Eyes Open and Eyes Closed conditions. Results indicated that, although there was no significant correlation between the differences in EEG power across each of the five pairs of frontal sites and total depression scores, there were several meaningful correlations (accounting for at least 10% of the variance) between specific EEG site differences data and each of the four depression subtypes. There were also different patterns of association between FLA and the depression subtypes according to sex, and total depression severity. These findings help to explain the apparent inconsistency in previous FLA-depression results, and argue for a more nuanced approach to this hypothesis.

Disrupted structural connectivity and less efficient network system in patients with the treatment-naive adult attention-deficit/hyperactivity disorder

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder whose primary symptoms are hyperactivity, impulsivity, and inattention. Historically, ADHD was recognized as a disease of childhood and adolescence. However, many patients are known to have persistent symptoms into adulthood. Many researchers consider the neuropathology of ADHD to be based on abnormalities in multiple parallel and intersecting pathways rather than a single anatomical area, but such alterations remain to be clarified.

Methods

Using diffusion tensor imaging, we investigated differences in the global network metrics estimated by graph theory and the degree of connectivity between adjacent voxels within a white matter (WM) fascicle defined by the density of the diffusing spins (connectometry) between 19 drug-naive Japanese patients with adult ADHD and 19 matched healthy controls (HCs). In adult patients with ADHD, we examined the relationships between the symptomatology of ADHD and global network metrics and WM abnormalities.

Results

Compared with HCs, adult patients with ADHD showed a reduced rich-club coefficient and decreased connectivity in widely distributed WMs such as the corpus callosum, the forceps, and the cingulum bundle. Correlational analyses demonstrated that the general severity of ADHD symptoms was associated with several global network metrics, such as lower global efficiency, clustering coefficient, small worldness, and longer characteristic path length. The connectometry revealed that the severity of hyperactive/impulsive symptoms was associated with overconnectivity in the corticostriatal, corticospinal, and corticopontine tracts, the inferior fronto-occipital fasciculus, and the extreme capsule but dysconnectivity in the cerebellum. The severity of inattentive symptoms was associated with dysconnectivity in the intracerebellar circuit and some other fibers.

Conclusion

The results of the present study indicated that patients with treatment-naive adult ADHD showed disrupted structural connectivity, which contributes to less efficient information transfer in the ADHD brain and pathophysiology of ADHD.

Trial registration

UMIN Clinical Trials Registry (UMIN-CTR) UMIN000025183, Registered: 5 January 2017.

Altered higher-order coupling between brain structure and function with embedded vector representations of connectomes in schizophrenia

It has been shown that the functional dependency of the brain exists in both direct and indirect regional relationships. Therefore, it is necessary to map higher-order coupling in brain structure and function to understand brain dynamic. However, how to quantify connections between not directly regions remains unknown to schizophrenia. The word2vec is a common algorithm through create embeddings of words to solve these problems. We apply the node2vec embedding representation to characterize features on each node, their pairwise relationship can give rise to correspondence relationships between brain regions. Then we adopt pearson correlation to quantify the higher-order coupling between structure and function in normal controls and schizophrenia. In addition, we construct direct and indirect connections to quantify the coupling between their respective functional connections. The results showed that higher-order coupling is significantly higher in schizophrenia. Importantly, the anomalous cause of coupling mainly focus on indirect structural connections. The indirect structural connections play an essential role in functional connectivity–structural connectivity (SC–FC) coupling. The similarity between embedded representations capture more subtle network underlying information, our research provides new perspectives for understanding SC–FC coupling. A strong indication that the structural backbone of the brain has an intimate influence on the resting-state functional.

Reduced Modular Segregation of White Matter Brain Networks in Attention Deficit Hyperactivity Disorder

OBJECTIVE

Despite studies reporting alterations in the brain networks of patients with ADHD, alterations in the modularity of white matter (WM) networks are still unclear.

METHOD

Based on the results of module division by generalized Louvain algorithm, the modularity of ADHD was evaluated. The correlation between the modular changes of ADHD and its clinical characteristics was analyzed.

RESULTS

The participation coefficient and the connectivity between modules of ADHD increased, and the modularity coefficient decreased. Provincial hubs of ADHD did not change, and the number of connector hubs increased. All results showed that the modular segregation of WM networks of ADHD decreased. Modules with reduced modular segregation are mainly responsible for language and motor functions. Moreover, modularity showed evident correlation with the symptoms of ADHD.

CONCLUSION

The modularity changes in WM network provided a novel insight into the understanding of brain cognitive alterations in ADHD.

Handedness in ADHD: Meta-Analyses

Meta-analyses have shown that several neurodevelopmental and psychiatric disorders, such as autism spectrum disorder and schizophrenia, are associated with a higher prevalence of atypical (left-, non-right-, or mixed-) handedness. One neurodevelopmental disorder for which this association is unclear is attention deficit hyperactivity disorder (ADHD). Here, some empirical studies have found evidence for a higher prevalence of atypical handedness in individuals with ADHD compared to neurotypical individuals. However, other studies failed to establish such an association. Therefore, meta-analytic integration is critical to estimate whether or not there is an association between handedness and ADHD. We report the results of three meta-analyses (left-, mixed-, and non-right-handedness) comparing handedness in individuals with ADHD to controls (typically developing individuals). The results show evidence of a trend towards elevated levels of atypical handedness when it comes to differences in left- and mixed-handedness (p = 0.09 and p = 0.07, respectively), but do show clear evidence of elevated levels of non-right-handedness between individuals with ADHD and controls (p = 0.02). These findings are discussed in the context of the hypothesis that ADHD is a disorder in which mostly right-hemispheric brain networks are affected. Since right-handedness represents a dominance of the left motor cortex for fine motor behavior, such as writing, as well as a left-hemispheric dominance for language functions, and about 90% of individuals are right-handers, this hypothesis might explain why there is not stronger evidence for an association of left-handedness with ADHD. We suggest that the mechanisms involved in the pathogenesis of ADHD might show an overlap with the mechanisms involved in handedness strength, but not handedness direction.

The structural connectome in ADHD

Attention-deficit/hyperactivity disorder (ADHD) has been conceptualized as a brain dysconnectivity disorder. In the past decade, noninvasive diffusion magnetic resonance imaging (dMRI) studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome, and that these alterations are associated with core symptoms and cognitive deficits in patients. This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-, tractography-, and network-based perspectives. Voxel- and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts, the corpus callosum, the corticospinal tracts, and the cingulum bundle in patients with ADHD. Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes. The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification. These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation. However, given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations, these ADHD-related white matter alterations are still far from informing clinical practice. Future studies with larger and more homogeneous samples are needed to validate the consistency of current results; advanced dMRI techniques can help to generate much more precise estimation of white matter pathways and assure specific fiber configurations; and finally, dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

OBJECTIVE

Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

METHODS

We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

RESULTS

There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

CONCLUSION

Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Glutamate and functional connectivity - support for the excitatory-inhibitory imbalance hypothesis in autism spectrum disorders

It has been proposed that the Glutamate (Glu) system is implicated in autism spectrum disorders (ASD) via an imbalance between excitatory and inhibitory brain circuits, which impacts on brain function. Here, we investigated the excitatory-inhibitory imbalance theory by measuring Glu-concentrations and the relationship with resting-state function. Nineteen adult males with ASD and 19 age and sex-matched healthy controls (HC) (23 - 58 years) underwent Proton Magnetic Resonance Spectroscopy of the dorsal anterior cingulate cortex (dACC) and resting-state functional Magnetic Resonance Imaging (fMRI). Glu and Glx concentrations were compared between groups. Seed-based functional connectivity was analyzed with a priori seeds of the right and left dACC. Finally, metabolite concentrations were related to functional connectivity coefficients and compared between both groups. Individuals with ASD showed significantly negative associations between increased Glx concentrations and reduced functional connectivity between the dACC and insular, limbic and parietal regions. In contrast, HC displayed a positive relationship between the same metabolite and connectivity measures. We provided new evidence to support the excitatory-inhibitory imbalance theory, where excitatory Glx concentrations were related to functional dysconnectivity in ASD. Future research is needed to investigate large-scale functional networks in association with both excitatory and inhibitory metabolites in subpopulations of ASD.

Abnormal Rich Club Organization in Hemispheric White Matter Networks of ADHD

Objective: Brain network studies have revealed abnormal topology asymmetry of white matter (WM) in ADHD. Recently, rich club organization was proposed to be a key feature of brain network topology. However, abnormalities in the rich club organization of hemispheric WM networks in ADHD remain unclear. Method: Forty ADHD patients and 51 normal controls participated in this study. Structural networks were reconstructed based on diffusion tensor imaging (DTI) and analyzed with graph theory. Results: The two groups exhibited different patterns of asymmetry in connectivity measures of rich club connections. ADHD patients showed more feeder connections than normal controls. Reduced rightward asymmetry was observed in connectivity measures of local connections involving several peripheral regions of the ADHD patients. In addition, abnormal regional asymmetry scores were associated with ADHD symptoms. Conclusion: The topological changes in rich club organization provide a novel insight into the alteration of WM connections in ADHD.

Temporal Variability-Based Functional Brain Lateralization Study in ADHD

Objective: The aim of this work is to explore the relationship between temporal variability and brain lateralization in ADHD. Method: The temporal variabilities of 116 brain regions based on resting-state functional magnetic resonance imaging (rs-fMRI) data were calculated for analysis. Results: Between-group comparison revealed that in comparison with the controls, ADHD participants showed significantly higher temporal variability in the left superior frontal gyrus (medial), left rectus gyrus, left inferior parietal lobule and angular gyrus, and lower temporal variability in the amygdala, left caudate and putamen. Besides, ADHD patients exhibited significantly increased leftward lateralization in the orbitofrontal cortex (inferior), and decreased rightward lateralization in the orbitofrontal cortex (medial) and rectus gyrus, compared with controls. Lateralization indices were also found to be related with clinical characteristics of ADHD patients. Conclusion: Our results may help us deeper in understanding the pathology of ADHD.

Asymmetry in Cortical and Subcortical Structures of the Brain in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Human cognitive and emotional functions are asymmetrical between the left and right hemispheres. In neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) patients, the absence of aberrant asymmetry might serve as a neuroanatomical marker of ADHD. However, few studies have estimated abnormalities in cortical and subcortical asymmetry in children and adolescents of different ADHD subtypes.

METHODS

Data were from the results collected by the Peking University site in the "ADHD-200 sample" dataset, which comprised 31 eligible ADHD (20 inattentive ADHD (ADHD-I), 11 combined ADHD (ADHD-C)) and 31 matched typically developing (TD) individuals. The Asymmetry Indexes (AIs) in cortical thickness, cortical gray-matter volume and subcortical nucleus (SN) volume were calculated based on an automated surface-based approach. The differences in cortical thickness, cortical gray-matter volume, and SN volume AIs were evaluated among groups. We also analyzed the correlation between AIs and the severity of ADHD symptoms.

RESULTS

Compared with the TD group, SN asymmetry in ADHD group did not reveal significant differences. Altered cortical asymmetry of different subtypes in ADHD groups was located in the orbitofrontal and anterior cingulate circuits, including the medial orbitofrontal, paracentral, pars triangularis, caudal anterior cingulate, isthmus cingulate, and superior frontal regions. In the comparisons, cortical gray-matter volume AIs were significantly different in the caudal anterior cingulate, isthmus cingulate, and superior frontal regions between ADHD-I and ADHD-C groups. There were significant correlations between the severity of ADHD symptoms and asymmetric measurements in medial orbitofrontal, paracentral and isthmus cingulate regions.

CONCLUSION

These findings provide further evidence for the altered cortical morphological asymmetry in children and adolescents with ADHD, and these differences are associated (at least in part) with the severity of ADHD symptoms. Brain asymmetry could be an appropriate precursor of morphological alterations in neurodevelopmental disorders.

Electroencephalographic and Neuroimaging Asymmetry Correlation in Patients with Attention-Deficit Hyperactivity Disorder

The present study explores the correlation between electroencephalographic and neuroimaging asymmetry index from EEG-MRI functional connectome and EEG power analysis in inattention, motion, and mixed profile subgroups of ADHD. Sixty-two subjects from Healthy Brain Network Biobank of the Child Mind Institute dataset were selected basing on the quotient score. From both MRI and EEG asymmetry index, Pearson's correlation, ANOVA, and partial least square analysis were performed matching left and right brain parcels and channels. The asymmetry index significantly correlated across subjects between fMRI and power-EEG in the inattention group in frontal and temporal areas for theta and alpha bands, an anticorrelation in the same areas for delta band was found. Significant patterns of hemispheric asymmetry index have been reported, involving EEG bands that underlie cognitive impairments in ADHD. Alpha and theta bands were altered in the inattention group of patients, reflecting widespread deficiency of basic attentional processing.

Hemispheric Asymmetry of Functional Brain Networks under Different Emotions Using EEG Data

Despite many studies reporting hemispheric asymmetry in the representation and processing of emotions, the essence of the asymmetry remains controversial. Brain network analysis based on electroencephalography (EEG) is a useful biological method to study brain function. Here, EEG data were recorded while participants watched different emotional videos. According to the videos’ emotional categories, the data were divided into four categories: high arousal high valence (HAHV), low arousal high valence (LAHV), low arousal low valence (LALV) and high arousal low valence (HALV). The phase lag index as a connectivity index was calculated in theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz) and gamma (31–45 Hz) bands. Hemispheric networks were constructed for each trial, and graph theory was applied to quantify the hemispheric networks’ topological properties. Statistical analyses showed significant topological differences in the gamma band. The left hemispheric network showed significantly higher clustering coefficient (C_p), global efficiency (E_g) and local efficiency (E_loc) and lower characteristic path length (L_p) under HAHV emotion. The right hemispheric network showed significantly higher C_p and E_loc and lower L_p under HALV emotion. The results showed that the left hemisphere was dominant for HAHV emotion, while the right hemisphere was dominant for HALV emotion. The research revealed the relationship between emotion and hemispheric asymmetry from the perspective of brain networks.

Brain Network Measures for Groups of Nodes: Application to Normal Aging and Alzheimer's Disease

Background: The nodal brain network measures (e.g., centrality measures) are defined for a single node and the global network measures (e.g., global efficiency) are defined for the whole brain in the literature. But a meaningful group of nodes will be benefited from a formulation that applies to a group of nodes rather than a single node or the whole brain. The question such as "which brain lobe is more structurally central in the older-adult brain?" could be answered to some extent by the application of a centrality measure that applied to the group of nodes from each lobe. In the brain asymmetric studies, path-based global measures were applied to the left and right hemispherical networks separately, considering only intrahemispheric edges. However, for a valid comparison, such global measures should include the interhemispheric edges as well. This problem can be solved by considering both hemispherical nodes as two groups in one network. Methods: Novel definitions for group nodes network measures are presented in this study, to solve a number of such group-context problems in the brain networks analysis. We apply the group measures to the structural connectomes of older adults and Alzheimer's disease (AD) subjects based on the brain lobes and hemispherical groups to demonstrate the effectiveness of the proposed measures. Results: The temporal and parietal lobes are the most central lobes in older adults and AD, but the strength of these lobes has been heavily affected in AD. However, the rewiring of the AD brain preserves the paths for communication between other regions through these lobes. Leftward efficiency revealed in older adults and the asymmetry disappeared in the rewired AD. Conclusion: We prove that the concepts of group network measures have the potential to solve a number of such group-context problems in the brain networks analysis and the group network measures change the way of analyzing brain networks.

Abnormal Anatomical Rich-Club Organization and Structural-Functional Coupling in Mild Cognitive Impairment and Alzheimer's Disease

Emerging research indicates interruptions in the wiring organization of the brain network in Mild cognitive impairment (MCI) and Alzheimer's disease (AD). Due to the important role of rich-club organization in distinguishing abnormalities of AD patients and the close relationship between structural connectivity (SC) and functional connectivity (FC), our study examined whether changes in SC-FC coupling and the relationship with abnormal rich-club organizations during the development of diseases may contribute to the pathophysiology of AD. Structural diffusion-tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) were performed in 38 normal controls (NCs), 40 MCI patients and 19 AD patients. Measures of the rich-club structure and its role in global structural-functional coupling were administered. Our study found decreased levels of feeder and local connectivity in MCI and AD patients, which were the main contributing factors to the lower efficiency of the brain structural network. Another important finding was that we have more accurately characterized the changing pattern of functional brain dynamics. The enhanced coupling between SC and FC in MCI and AD patients might be due to disruptions in optimal structural organization. More interestingly, we also found increases in the SC-FC coupling for feeder and local connections in MCI and AD patients. SC-FC coupling also showed significant differences between MCI and AD patients, mainly between the abnormal feeder connections. The connection density and coupling strength were significantly correlated with clinical metrics in patients. The present findings enhanced our understanding of the neurophysiologic mechanisms associated with MCI and AD.

Altered brain white matter microstructural asymmetry in children with ADHD

OBJECTIVES

We aimed to examine brain white matter integrity in children with ADHD.

METHODS

In a cohort of children with ADHD (n = 83) and healthy controls (n = 122), we used tract-based spatial statistics on Diffusion Tensor Imaging (DTI) data to obtain the mean fractional anisotropy (FA) in 40 bilateral regions of interest (ROIs). Lateralization Index (LI) was calculated. The difference in LI between groups and correlations between the LI of each ROI and ADHD symptom scores as well as cognitive function were examined.

RESULTS

Children with ADHD had significantly greater LI at the posterior thalamic radiation (PTR) compared with healthy controls (mean LI in ADHD = 0.0096; in Control = 0.0044, p = 0.0143), and LI of the external capsule (EC) was significantly correlated with inattention symptoms in both groups (β = -0.00059, p = 0.0181). LI of the PTR was significantly correlated with inhibitory function in healthy controls (β = -0.0008510, p = 0.0248), but not in children with ADHD.

CONCLUSION

We found increased brain white matter asymmetry (leftward) in children with ADHD compared with healthy controls at the posterior thalamic radiation. Leftward lateralization of FA values at the external capsule was negatively correlated with ADHD symptoms in both children with ADHD and healthy controls.

Alterations of cerebral perfusion and functional brain connectivity in medication-naïve male adults with attention-deficit/hyperactivity disorder

Aims

Functional brain abnormalities, including altered cerebral perfusion and functional connectivities, have been illustrated in adults with attention‐deficit/hyperactivity disorder (aADHD). The present study attempted to explore the alterations of cerebral blood flow (CBF) and resting‐state functional connectivity (RSFC) simultaneously to understand the neural mechanisms for adults with ADHD comprehensively.

Methods

Resting‐state arterial spin labeling (ASL) and blood oxygenation level‐dependent (BOLD) magnetic resonance imaging (MRI) data were acquired for 69 male aADHD and 69 matched healthy controls (HCs). The altered CBFs associated with aADHD were explored based on both categorical (aADHD vs HCs) and dimensional (correlation with aADHD core symptoms) perspectives. Then, the seed‐based RSFC analyses were developed for the regions showing significant alterations of CBF.

Results

Significantly decreased CBF in the large‐scale resting‐state networks regions (eg, ventral attentional network, somatomotor network, limbic network) and subcortical regions was indicated in aADHD compared with HCs. The correlation analyses indicated that the hypoperfusion in left putamen/global pallidum and left amygdala/hippocampus was correlated with ADHD inattentive and total symptoms, respectively. Further, weaker negative functional connectivity between left amygdala and bilateral supplementary motor area, bilateral superior frontal gyrus, and left medial frontal gyrus was found in adults with ADHD.

Conclusion

The present findings suggested alterations of both cerebral perfusion and functional connectivity for the left amygdala in aADHD. The combination of CBF and RSFCs may help to interpret the neuropathogenesis of ADHD more comprehensively.