The executive control network and symptomatic improvement in attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder in pregnancy and the postpartum period

Attention-deficit/hyperactivity disorder is a childhood-onset neurodevelopmental disorder that frequently persists into adulthood with 3% of adult women having a diagnosis of attention-deficit/hyperactivity disorder. Many women are diagnosed and treated during their reproductive years, which leads to management implications during pregnancy and the postpartum period. We know from clinical practice that attention-deficit/hyperactivity disorder symptoms frequently become challenging to manage during the perinatal period and require additional support and attention. There is often uncertainty among healthcare providers about the management of attention-deficit/hyperactivity disorder in the perinatal period, particularly the safety of pharmacotherapy for the developing fetus. This guideline is focused on best practices in managing attention-deficit/hyperactivity disorder in the perinatal period. We recommend (1) mitigating the risks associated with attention-deficit/hyperactivity disorder that worsen during the perinatal period via individualized treatment planning; (2) providing psychoeducation, self-management strategies or coaching, and psychotherapies; and, for those with moderate or severe attention-deficit/hyperactivity disorder, (3) considering pharmacotherapy for attention-deficit/hyperactivity disorder, which largely has reassuring safety data. Specifically, providers should work collaboratively with patients and their support networks to balance the risks of perinatal attention-deficit/hyperactivity disorder medication with the risks of inadequately treated attention-deficit/hyperactivity disorder during pregnancy. The risks and impacts of attention-deficit/hyperactivity disorder in pregnancy can be successfully managed through preconception counselling and appropriate perinatal planning, management, and support.

Microstate dynamics and spectral components as markers of persistent and remittent attention-deficit/hyperactivity disorder

OBJECTIVE

We leveraged microstate characteristics and power features to examine temporal and spectral deviations underlying persistent and remittent attention-deficit/hyperactivity disorder (ADHD).

METHODS

50 young adults with childhood ADHD (28 persisters, 22 remitters) and 28 demographically similar healthy controls (HC) were compared on microstates features and frequency principal components (f-PCs) of eye-closed resting state. Support vector machine model with sequential forward selection (SVM-SFS) was utilized to discriminate three groups.

RESULTS

Four microstates and four comparable f-PCs were identified. Compared to HC, ADHD persisters showed prolonged duration in microstate C, elevated power of the delta component (D), and compromised amplitude of the two alpha components (A1 and A2). Remitters showed increased duration and coverage of microstate C, together with decreased activity of D, relatively intact amplitude of A1, and amplitude reduction in A2. The SVM-SFS algorithm achieved an accuracy of 93.59% in classifying persisters, remitters and controls. The most discriminative features selected were those exhibiting group differences.

CONCLUSIONS

We found widespread anomalies in ADHD persisters in brain dynamics and intrinsic EEG components. Meanwhile, the neural features in remitters exhibited multiple patterns.

SIGNIFICANCE

This study underlines the use of microstate dynamics and spectral components as potential markers of persistent and remittent ADHD.

Executive functioning, ADHD symptoms and resting state functional connectivity in children with perinatal stroke

Perinatal stroke describes a group of focal, vascular brain injuries that occur early in development, often resulting in lifelong disability. Two types of perinatal stroke predominate, arterial ischemic stroke (AIS) and periventricular venous infarction (PVI). Though perinatal stroke is typically considered a motor disorder, other comorbidities commonly exist including attention-deficit hyperactivity disorder (ADHD) and deficits in executive function. Rates of ADHD symptoms are higher in children with perinatal stroke and deficits in executive function may also occur but underlying mechanisms are not known. We measured resting state functional connectivity in children with perinatal stroke using previously established dorsal attention, frontoparietal, and default mode network seeds. Associations with parental ratings of executive function and ADHD symptoms were examined. A total of 120 participants aged 6-19 years [AIS N = 31; PVI N = 30; Controls N = 59] were recruited. In comparison to typically developing peers, both the AIS and PVI groups showed lower intra- and inter-hemispheric functional connectivity values in the networks investigated. Group differences in between-network connectivity were also demonstrated, showing weaker anticorrelations between task-positive (frontoparietal and dorsal attention) and task-negative (default mode) networks in stroke groups compared to controls. Both within-network and between-network functional connectivity values were highly associated with parental reports of executive function and ADHD symptoms. These results suggest that differences in functional connectivity exist both within and between networks after perinatal stroke, the degree of which is associated with ADHD symptoms and executive function.

Extraction of brain function pattern with visual-capture-task fMRI using dynamic time-window method in ADHD children

Attention deficit/Hyperactivity disorder (ADHD) has a great impact on children's development. This paper uses a novel adaptive brain state extraction algorithm to construct a dynamic time-window brain network, which captures the brain function pattern characteristics of ADHD children with higher temporal resolution. The test data were acquired by functional magnetic resonance imaging (fMRI) obtained from 23 children with ADHD during the visual-capture-task [age: (8.27 ± 2.77)]. A spatial standard deviation method is used after the initial data processing, to extract the brain activity pattern state; An improved clustering algorithm is constructed to verify the changes made to the dynamic time-window brain network model. There can be seen clear differences between each state within 0.05 s after the test. The results show that our improved new framework can effectively obtain the characteristics of dynamic brain functional connection strength changes during the task. In addition, the new algorithm is able to capture the dynamic changes of the brain network, with an 80 % improvement compared to traditional methods for the average modularity value Q. This work demonstrates a novel approach to find out the pattern changes between dynamic brain function connections, which can be of great significance for the adjuvant treatment of children with ADHD.

Down-regulation of theta amplitude through neurofeedback improves executive control network efficiency in healthy children

Despite extensive clinical research on neurofeedback (NF) in attention-deficit/hyperactivity disorder (ADHD), few studies targeted the optimization of attention performance in healthy children. As a crucial component of attention networks, the executive control network, involved in resolving response conflicts and allocating cognitive resources, is closely linked to theta activity. Here, we aimed to answer whether theta down-regulating NF can enhance healthy children's attention performance, especially the executive control network. Sixty children aged 6-12 years were randomly assigned to the NF and waitlist control groups. The NF group received theta down-regulation NF training for five days (a total of 100 mins), and the attention performance of both groups was measured by the attention network test (ANT) in the pre, post-NF, and 7-day follow-up. The electroencephalographic (EEG) results demonstrated a significant decrease in resting-state theta amplitude within sessions. For the behavioral results, the NF group exhibited significant improvements in overall attention performance and the efficiency of the executive control network relative to the control group in the post-NF and follow-up assessment, whereas the alerting and orienting networks remained unchanged. These findings proved the feasibility of theta down-regulating NF and its positive effect on attention in the healthy children population. In particular, the facilitation of the efficiency of the executive control network and the unaltered performance of the other two attention networks in the NF group may support the causality between theta rhythm and the executive control network.

Longitudinal Changes of Resting-State Networks in Children With Attention-Deficit/Hyperactivity Disorder and Typically Developing Children

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent childhood neurodevelopmental disorder. Given the profound brain changes that occur across childhood and adolescence, it is important to identify functional networks that exhibit differential developmental patterns in children with ADHD. This study sought to examine whether children with ADHD exhibit differential developmental trajectories in functional connectivity compared with typically developing children using a network-based approach.

METHODS

This longitudinal neuroimaging study included 175 participants (91 children with ADHD and 84 control children without ADHD) between ages 9 and 14 and up to 3 waves (173 total resting-state scans in children with ADHD and 197 scans in control children). We adopted network-based statistics to identify connected components with trajectories of development that differed between groups.

RESULTS

Children with ADHD exhibited differential developmental trajectories compared with typically developing control children in networks connecting cortical and limbic regions as well as between visual and higher-order cognitive regions. A pattern of reduction in functional connectivity between corticolimbic networks was seen across development in the control group that was not present in the ADHD group. Conversely, the ADHD group showed a significant decrease in connectivity between predominantly visual and higher-order cognitive networks that was not displayed in the control group.

CONCLUSIONS

Our findings show that the developmental trajectories in children with ADHD are characterized by a subnetwork involving different trajectories predominantly between corticolimbic regions and between visual and higher-order cognitive network connections. These findings highlight the importance of examining the longitudinal maturational course to understand the development of functional connectivity networks in children with ADHD.

The brain network underlying attentional blink predicts symptoms of attention deficit hyperactivity disorder in children

Attention deficit hyperactivity disorder (ADHD) is a chronic neuropsychiatric disease that can markedly impair educational, social, and occupational function throughout life. Behavioral deficits may provide clues to the underlying neurological impairments. Children with ADHD exhibit a larger attentional blink (AB) deficit in rapid serial visual presentation (RSVP) tasks than typically developing children, so we examined whether brain connectivity in the neural network associated with AB can predict ADHD symptoms and thus serve as potential biomarkers of the underlying neuropathology. We first employed a connectome-based predictive model analysis of adult resting-state functional magnetic resonance imaging data to identify a distributed brain network for AB. The summed functional connectivity (FC) strength within the AB network reliably predicted individual differences in AB magnitude measured by a classical dual-target RSVP task. Furthermore, the summed FC strength within the AB network predicted individual differences in ADHD Rating Scale scores from an independent dataset of pediatric patients. Our findings suggest that the individual AB network could serve as an applicable neuroimaging-based biomarker of AB deficit and ADHD symptoms.

Functional connectivity directionality between large-scale resting-state networks across typical and non-typical trajectories in children and adolescence

Mental disorders often emerge during adolescence and have been associated with age-related differences in connection strengths of brain networks (static functional connectivity), manifesting in non-typical trajectories of brain development. However, little is known about the direction of information flow (directed functional connectivity) in this period of functional brain progression. We employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 1143 participants, aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on estimates of direction flow. Across participants, we show a pattern of reciprocal information flow between visual-medial and visual-lateral connections, in line with findings in adults. Investigating directed connectivity patterns between networks, we observed a positive association for age and direction flow from the cerebellar to the auditory network, and for the auditory to the sensorimotor network. Further, higher cognitive abilities were linked to lower information flow from the visual occipital to the default mode network. Additionally, examining the degree networks overall send and receive information to each other, we identified age-related effects implicating the right frontoparietal and sensorimotor network. However, we did not find any associations with psychopathology. Our results suggest that the directed functional connectivity of large-scale resting-state brain networks is sensitive to age and cognition during adolescence, warranting further studies that may explore directed relationships at rest and trajectories in more fine-grained network parcellations and in different populations.

The Effects of White Noise on Attentional Performance and On-Task Behaviors in Preschoolers with ADHD

Several models have tentatively associated improving attention-deficit/hyperactivity disorder (ADHD) symptoms with arousal and external environmental stimulation. In order to further clarify the relationships between ADHD symptoms, arousal, and external stimulation, this study focused on exploring the "simultaneous" effects of white noise on intrinsic attentional performance and extrinsic on-task behaviors in preschoolers with and without ADHD. By using the computerized task (K-CPT 2), 104 preschoolers, including 52 ADHD children and 52 typically developing (TD) children, were tested and analyzed for their intrinsic attention (such as detectability, omission errors, commission errors, and reaction time). Simultaneously, these preschoolers' external on-task behaviors were recorded for analysis through systematic observation. This study showed that white noise could effectively improve attention performance, including enhancing the ability to differentiate non-targets from targets and decreasing omission errors. It could also reduce the extrinsic hyperactive behaviors of preschoolers with ADHD. The findings of this study highlighted that white noise stimulation is a beneficial non-pharmacological treatment for preschoolers with ADHD. In contrast, for TD preschoolers, the results of this study showed that the external white noise stimuli were not only unhelpful but also a burden.

Effects of a single-dose methylphenidate challenge on resting-state functional connectivity in stimulant-treatment naive children and adults with ADHD

Prior studies suggest that methylphenidate, the primary pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD), alters functional brain connectivity. As the neurotransmitter systems targeted by methylphenidate undergo significant alterations throughout development, the effects of methylphenidate on functional connectivity may also be modulated by age. Therefore, we assessed the effects of a single methylphenidate challenge on brain network connectivity in stimulant-treatment naïve children and adults with ADHD. We obtained resting-state functional MRI from 50 boys (10-12 years of age) and 49 men (23-40 years of age) with ADHD (DSM IV, all subtypes), before and after an oral challenge with 0.5 mg/kg methylphenidate; and from 11 boys and 12 men as typically developing controls. Connectivity strength (CS), eigenvector centrality (EC), and betweenness centrality (BC) were calculated for the striatum, thalamus, dorsal anterior cingulate cortex (dACC), and prefrontal cortex (PFC). In line with our hypotheses, we found that methylphenidate decreased measures of connectivity and centrality in the striatum and thalamus in children with ADHD, but increased the same metrics in adults with ADHD. Surprisingly, we found no major effects of methylphenidate in the dACC and PFC in either children or adults. Interestingly, pre-methylphenidate, participants with ADHD showed aberrant connectivity and centrality compared to controls predominantly in frontal regions. Our findings demonstrate that methylphenidate's effects on connectivity of subcortical regions are age-dependent in stimulant-treatment naïve participants with ADHD, likely due to ongoing maturation of dopamine and noradrenaline systems. These findings highlight the importance for future studies to take a developmental perspective when studying the effects of methylphenidate treatment.

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.

White Matter Microstructure in Attention-Deficit/Hyperactivity Disorder: A Systematic Tractography Study in 654 Individuals

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity. ADHD has been related to differences in white matter (WM) microstructure. However, much remains unclear regarding the nature of these WM differences and which clinical aspects of ADHD they reflect. We systematically investigated whether fractional anisotropy (FA) is associated with current and/or lifetime categorical diagnosis, impairment in daily life, and continuous ADHD symptom measures.

METHODS

Diffusion-weighted imaging data were obtained from 654 participants (322 unaffected, 258 affected, 74 subthreshold; 7-29 years of age). We applied automated global probabilistic tractography on 18 major WM pathways. Linear mixed-effects regression models were used to examine associations of clinical measures with overall brain and tract-specific FA.

RESULTS

There were significant interactions of tract with all ADHD variables on FA. There were no significant associations of FA with current or lifetime diagnosis, nor with impairment. Lower FA in the right cingulum angular bundle was associated with higher hyperactivity-impulsivity symptom severity (p_{familywise error} = .045). There were no significant effects for other tracts.

CONCLUSIONS

This is the first time global probabilistic tractography has been applied to an ADHD dataset of this size. We found no evidence for altered FA in association with ADHD diagnosis. Our findings indicate that associations of FA with ADHD are not uniformly distributed across WM tracts. Continuous symptom measures of ADHD may be more sensitive to FA than diagnostic categories. The right cingulum angular bundle in particular may play a role in symptoms of hyperactivity and impulsivity.

Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms

Alpha rhythms in the human electroencephalogram (EEG), oscillating at 8-13 Hz, are located in parieto-occipital cortex and are strongest when awake people close their eyes. It has been suggested that alpha rhythms were related to attention-related functions and mental disorders (e.g., Attention-deficit/hyperactivity disorder (ADHD)). However, many studies have shown inconsistent results on the difference in alpha oscillation between ADHD and control groups. Hence it is essential to verify this difference. In this study, a dataset of EEG recording (128 channel EGI) from 87 healthy controls (HC) and 162 ADHD (141 persisters and 21 remitters) adults in a resting state with their eyes closed was used to address this question and a three-gauss model (summation of baseline and alpha components) was conducted to fit the data. To our surprise, the power of alpha components was not a significant difference among the three groups. Instead, the baseline power of remission and HC group in the alpha band is significantly stronger than that of persister groups. Our results suggest that ADHD recovery may have compensatory mechanisms and many abnormalities in EEG may be due to the influence of behavior rather than the difference in brain signals.

Investigation of white matter functional networks underlying different behavioral profiles in attention-deficit/hyperactivity disorder

Background

Cortical functional network alterations have been widely accepted as the neural basis of attention-deficit/hyperactivity disorder (ADHD). Recently, white matter has also been recognized as a novel neuroimaging marker of psychopathology and has been used as a complement to cortical functional networks to investigate brain-behavior relationships. However, disorder-specific features of white matter functional networks (WMFNs) are less well understood than those of gray matter functional networks. In the current study, we constructed WMFNs using a new strategy to characterize behavior-related network features in ADHD.

Methods

We recruited 46 drug-naïve boys with ADHD and 46 typically developing (TD) boys, and used clustering analysis on resting-state functional magnetic resonance imaging data to generate WMFNs in each group. Intrinsic activity within each network was extracted, and the associations between network activity and behavior measures were assessed using correlation analysis.

Results

Nine WMFNs were identified for both ADHD and TD participants. However, boys with ADHD showed a splitting of the inferior corticospinal-cerebellar network and lacked a cognitive control network. In addition, boys with ADHD showed increased activity in the dorsal attention network and somatomotor network, which correlated positively with attention problems and hyperactivity symptom scores, respectively, while they presented decreased activity in the frontoparietal network and frontostriatal network in association with poorer performance in response inhibition, working memory, and verbal fluency.

Conclusions

We discovered a dual pattern of white matter network activity in drug-naïve ADHD boys, with hyperactive symptom-related networks and hypoactive cognitive networks. These findings characterize two distinct types of WMFN in ADHD psychopathology.

Goal management training improves executive control in adults with ADHD: an open trial employing attention network theory to examine effects on attention

Background

Adults with Attention-Deficit/Hyperactivity Disorder (ADHD) typically experience poorer attentional control. According to the attention network theory, attentional control relies on three interacting networks of alerting, orienting, and executive control. In ADHD, it is mainly the alerting and executive control networks that are suggested and found to be compromised.

Methods

In the current study, we investigated if a group-based metacognitive remediation program (Goal Management Training [GMT]) in adults with ADHD would enhance attentional control using an experimental measure of the attention network theory. We expected that GMT would specifically enhance the executive control and alerting networks.

Results

Data from post- and follow up-assessments of 21 adults (age: 39.05 [11.93]) with ADHD who had completed GMT were included. Linear mixed-effects modeling revealed significant improvements in the functioning of the executive control network for the majority of the participants, although a small subset of participants showed a negative development following the intervention. Results also showed an improvement in the orienting network at follow up, but no change in the alerting network.

Conclusion

The results may indicate that improvements in the functioning of the executive control network are central to the positive effects of GMT reported in disorders characterized by impaired attentional control.

Trial registration: The study was retrospectively registered in the ISRCTN (Identifier: ISRCTN91988877) on the 18/01/2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-022-00902-9.

Shared intrinsic functional connectivity alterations as a familial risk marker for ADHD: a resting-state functional magnetic resonance imaging study with sibling design

BACKGROUND

Although aberrant intrinsic functional connectivity has been reported in attention-deficit/hyperactivity disorder (ADHD), we have a limited understanding of whether connectivity alterations are related to the familial risk of ADHD.

METHODS

Fifty-three probands with ADHD, their unaffected siblings (n = 53) and typically developing controls (n = 53) underwent resting-state functional magnetic resonance imaging scans. A seed-based approach with the bilateral precuneus/posterior cingulate cortex (PCC) was used to derive a whole-brain functional connectivity map in each subject. The differences in functional connectivity among the three groups were tested with one-way ANOVA using randomized permutation. Comparisons between two groups were also performed to examine the increase or decrease in connectivity. The severity of ADHD symptoms was used to identify brain regions where symptom severity is correlated to the strength of intrinsic functional connectivity.

RESULTS

When compared to controls, both probands and unaffected siblings showed increased functional connectivity in the left insula and left inferior frontal gyrus. The connectivity in these regions was linked to better performance in response inhibition in the control group but absent in other groups. Higher ADHD symptom severity was correlated with increased functional connectivity in bilateral fronto-parietal-temporal regions only noted in probands with ADHD.

CONCLUSIONS

Alterations in resting-state functional connectivities with the precuneus/PCC, hubs of default-mode network, account for the underlying familial risks of ADHD. Since the left insula and left inferior frontal gyri are key regions of the salience and frontoparietal network, respectively, future studies focusing on alterations of cross-network functional connectivity as the familial risk of ADHD are suggested.

Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types

Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8–17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type (n = 15) or combined (ADHD-C) type (n = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.

ADHD co-morbidities: A review of implication of gene × environment effects with dopamine-related genes

ADHD is a major burden in adulthood, where co-morbid conditions such as depression, substance use disorder and obesity often dominate the clinical picture. ADHD has substantial shared heritability with other mental disorders, contributing to comorbidity. However, environmental risk factors exist but their interaction with genetic makeup, especially in relation to comorbid disorders, remains elusive. This review for the first time summarizes present knowledge on gene x environment (GxE) interactions regarding the dopamine system. Hitherto, mainly candidate (GxE) studies were performed, focusing on the genes DRD4, DAT1 and MAOA. Some evidence suggest that the variable number tandem repeats in DRD4 and MAOA may mediate GxE interactions in ADHD generally, and comorbid conditions specifically. Nevertheless, even for these genes, common variants are bound to suggest risk only in the context of gender and specific environments. For other polymorphisms, evidence is contradictory and less convincing. Particularly lacking are longitudinal studies testing the interaction of well-defined environmental with polygenic risk scores reflecting the dopamine system in its entirety.

Lifespan associations of resting-state brain functional networks with ADHD symptoms

Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition approach to study resting-state brain networks of ADHD patients (n = 97) and healthy controls (HCs, n = 97) across the lifespan (7–50 years). Compared to the linear lifespan associations of brain segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole-brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD and provide potential shared neural bases of distinct ADHD symptoms in children and adults.

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ADHD patients have a quadratic association with age in brain functional networks

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Limbic system better predicts hyperactivity across the lifespan

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Salient attention system better predicts the inattention across the lifespan

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The predictions on symptom scores are shared in ADHD children and adults

Segregation and integration of the functional connectome in neurodevelopmentally 'at risk' children

Functional connectivity within and between Intrinsic Connectivity Networks (ICNs) transforms over development and is thought to support high order cognitive functions. But how variable is this process, and does it diverge with altered cognitive development? We investigated age-related changes in integration and segregation within and between ICNs in neurodevelopmentally 'at-risk' children, identified by practitioners as experiencing cognitive difficulties in attention, learning, language, or memory. In our analysis we used performance on a battery of 10 cognitive tasks alongside resting-state functional magnetic resonance imaging in 175 at-risk children and 62 comparison children aged 5-16. We observed significant age-by-group interactions in functional connectivity between two network pairs. Integration between the ventral attention and visual networks and segregation of the limbic and fronto-parietal networks increased with age in our comparison sample, relative to at-risk children. Furthermore, functional connectivity between the ventral attention and visual networks in comparison children significantly mediated age-related improvements in executive function, compared to at-risk children. We conclude that integration between ICNs show divergent neurodevelopmental trends in the broad population of children experiencing cognitive difficulties, and that these differences in functional brain organisation may partly explain the pervasive cognitive difficulties within this group over childhood and adolescence.

How general anesthetics work: from the perspective of reorganized connections within the brain

General anesthesia is critical for various procedures and surgeries. Despite the widespread use of anesthetics, their precise mechanisms remain poorly understood. Anesthetics inevitably act on the brain, primarily through the modulation of target receptors. Even if the action is specific to an individual neuron, however, long-range effects can occur due to the tremendous interconnectedness of neuronal activity. The strength of this connectivity can be understood using mathematical models that allow for the study of neuronal connectivity dynamics. These models also allow researchers to develop hypotheses on the candidate mechanisms of action of different types of anesthesia. This review highlights the theoretical background associated with the study of the mechanisms of action of anesthetics. We propose a candidate framework that describes how anesthetics act on the brain and consciousness in general.

Emotion dysregulation and integration of emotion-related brain networks affect intraindividual change in ADHD severity throughout late adolescence

The course of attention deficit hyperactivity disorder (ADHD) from adolescence into adulthood shows large variations between individuals; nonetheless determinants of interindividual differences in the course are not well understood. A frequent problem in ADHD, associated with worse outcomes, is emotion dysregulation. We investigated whether emotion dysregulation and integration of emotion-related functional brain networks affect interindividual differences in ADHD severity change. ADHD severity and resting state neuroimaging data were measured in ADHD and unaffected individuals at two points during adolescence and young adulthood. Bivariate latent change score models were applied to investigate whether emotion dysregulation and network integration affect ADHD severity changes. Emotion dysregulation was gauged from questionnaire subscales for conduct problems, emotional problems and emotional lability. Better emotion regulation was associated with a better course of ADHD (104 participants, 44 females, age range: 12-27). Using graph analysis, we determined network integration of emotion-related functional brain networks. Network integration was measured by nodal efficiency, i.e., the average inverse path distance from one node to all other nodes. A pattern of low nodal efficiency of cortical regions associated with emotion processing and high nodal efficiency in subcortical areas and cortical areas involved in implicit emotion regulation predicted a better ADHD course. Larger nodal efficiency of the right orbitofrontal cortex was related to a better course of ADHD (99 participants, 42 females, age range: 10-29). We demonstrated that neural and behavioral covariates associated with emotion regulation affect the course of ADHD severity throughout adolescence and early adulthood beyond baseline effects of ADHD severity.

A transdiagnostic data-driven study of children's behaviour and the functional connectome

Behavioural difficulties are seen as hallmarks of many neurodevelopmental conditions. Differences in functional brain organisation have been observed in these conditions, but little is known about how they are related to a child's profile of behavioural difficulties. We investigated whether behavioural difficulties are associated with how the brain is functionally organised in an intentionally heterogeneous and transdiagnostic sample of 957 children aged 5-15. We used consensus community detection to derive data-driven profiles of behavioural difficulties and constructed functional connectomes from a subset of 238 children with resting-state functional Magnetic Resonance Imaging (fMRI) data. We identified three distinct profiles of behaviour that were characterised by principal difficulties with hot executive function, cool executive function, and learning. Global organisation of the functional connectome did not differ between the groups, but multivariate patterns of connectivity at the level of Intrinsic Connectivity Networks (ICNs), nodes, and hubs significantly predicted group membership in held-out data. Fronto-parietal connector hubs were under-connected in all groups relative to a comparison sample and children with hot vs cool executive function difficulties were distinguished by connectivity in ICNs associated with cognitive control, emotion processing, and social cognition. This demonstrates both general and specific neurodevelopmental risk factors in the functional connectome.

Associations between attention‐deficit hyperactivity disorder (ADHD) symptom remission and white matter microstructure: A longitudinal analysis

Background:

Attention-deficit hyperactivity disorder (ADHD) is associated with white matter (WM) microstructure. Our objective was to investigate how WM microstructure is longitudinally related to symptom remission in adolescents and young adults with ADHD.

Methods:

We obtained diffusion-weighted imaging (DWI) data from 99 participants at two timepoints (mean age baseline: 16.91 years, mean age follow-up: 20.57 years). We used voxel-wise Tract-Based Spatial Statistics (TBSS) with permutation-based inference to investigate associations of inattention (IA) and hyperactivity-impulsivity (HI) symptom change with fractional anisotropy (FA) at baseline, follow-up, and change between time-points.

Results:

Remission of combined HI and IA symptoms was significantly associated with reduced FA at follow-up in the left superior longitudinal fasciculus and the left corticospinal tract (CST; P_FWE = 0.038 and P_FWE = 0.044, respectively), mainly driven by an association between HI remission and follow-up CST FA (P_FWE = 0.049). There was no significant association of combined symptom decrease with FA at baseline or with changes in FA between the two assessments.

Conclusions:

In this longitudinal DWI study of ADHD using dimensional symptom scores, we show that greater symptom decrease is associated with lower follow-up FA in specific WM tracts. Altered FA thus may appear to follow, rather than precede, changes in symptom remission. Our findings indicate divergent WM developmental trajectories between individuals with persistent and remittent ADHD, and support the role of prefrontal and sensorimotor tracts in the remission of ADHD.

Evaluating the Neuroimaging-Genetic Prediction of Symptom Changes in Individuals with ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that could persist into adulthood with known abnormalities in brain structure. Genetics also play an important role in the etiology of the disorder and could affect the disorder trajectory. In this study, we investigated the prediction power of brain image and genomic features for symptom change in 77 individuals with ADHD as part of NeuroIMAGE cohort. Gray matter components and working memory assessments at baseline, as well as gene scores of interest, were used to predict the changes in the two symptom domains: inattentive and hyperactive/impulsive, an average of 4 years. A linear regression model coupled with various feature selection approaches, including leave-one-out-cross-validation (LOOCV), stability selection with resampling, and permutation tests, was implemented to mitigate the overtraining potential caused by small sample sizes. Results showed that traditional LOOCV overestimated the prediction power. We proposed a novel stability selection with the threshold set by permutation tests, which provided more objective assessment. Using our proposed procedure, we identified a statistical promising prediction model for inattention symptom change; the consistent correlation between predicted values and measured values during model training, validating and hold out testing (r=0.64, 0.53, 0.46, respectively), but the p value is not significant in the holdout test. The selected features include age, gray matter in the insula, genes OSBPL1A, CTNNB1, PRPSAP2, ACADM, and polygenic risk score of education attainment, which have been previously reported to be associated with ADHD. We speculate that significant associations may be observed with a large sample size.

White matter abnormalities associated with ADHD outcomes in adulthood

It remains unclear if previously reported structural abnormalities in children with ADHD are present in adulthood regardless of clinical outcome. In this study, we examined the extent to which focal-rather than diffuse-abnormalities in fiber collinearity of 18 major white matter tracts could distinguish 126 adults with rigorously diagnosed childhood ADHD (ADHD; mean age [SD] = 34.3 [3.6] years; F/M = 12/114) from 58 adults without ADHD histories (non-ADHD; mean age [SD] = 33.9 [4.1] years; F/M = 5/53) and if any of these abnormalities were greater for those with persisting ADHD symptomatology. To this end, a tract profile approach was used. After accounting for age, sex, handedness, and comorbidities, a MANCOVA revealed a main effect of group (ADHD < non-ADHD; F_[18,155] = 2.1; p = 0.007) on fractional anisotropy (FA, a measure of fiber collinearity and/or integrity), in focal portions of white matter tracts involved in visuospatial processing and memory (i.e., anterior portion of the left inferior longitudinal fasciculus, and middle portion of the left and right cingulum angular bundle). Only abnormalities in the anterior portion of the left inferior longitudinal fasciculus distinguished probands with persisting versus desisting ADHD symptomatology, suggesting that abnormalities in the cingulum angular bundle might reflect "scarring" effects of childhood ADHD. To our knowledge, this is the first study using a tract profile approach to identify focal or widespread structural abnormalities in adults with ADHD rigorously diagnosed in childhood.

Differences in Disrupted Dynamic Functional Network Connectivity Among Children, Adolescents, and Adults With Attention Deficit/Hyperactivity Disorder: A Resting-State fMRI Study

Attention deficit hyperactivity disorder (ADHD) is one of the most widespread mental disorders and often persists from childhood to adulthood, and its symptoms vary with age. In this study, we aim to determine the disrupted dynamic functional network connectivity differences in adult, adolescent, and child ADHD using resting-state functional magnetic resonance imaging (rs-fMRI) data consisting of 35 children (8.64 ± 0.81 years), 40 adolescents (14.11 ± 1.83 years), and 39 adults (31.59 ± 10.13 years). We hypothesized that functional connectivity is time-varying and that there are within- and between-network connectivity differences among the three age groups. Nine functional networks were identified using group ICA, and three FC-states were recognized based on their dynamic functional network connectivity (dFNC) pattern. Fraction of time, mean dwell time, transition probability, degree-in, and degree-out were calculated to measure the state dynamics. Higher-order networks including the DMN, SN, and FPN, and lower-order networks comprising the SMN, VN, SC, and AUD were frequently distributed across all states and were found to show connectivity differences among the three age groups. Our findings imply abnormal dynamic interactions and dysconnectivity associated with different ADHD, and these abnormalities differ between the three ADHD age groups. Given the dFNC differences between the three groups in the current study, our work further provides new insights into the mechanism subserved by age difference in the pathophysiology of ADHD and may set the grounds for future case-control studies in the individual age groups, as well as serving as a guide in the development of treatment strategies to target these specific networks in each age group.

Atypical resting-state gamma band trajectory in adult attention deficit/hyperactivity disorder

Decreased gamma activity has been reported both in children and adults with attention deficit/hyperactivity disorder (ADHD). However, while ADHD is a lifelong neurodevelopmental disorder, our insight into the associations of spontaneous gamma band activity with age is limited, especially in adults. Therefore, we conducted an explorative study to investigate trajectories of resting gamma activity in adult ADHD patients (N = 42) versus matched healthy controls (N = 59). We investigated the relationship of resting gamma activity (30–48 Hz) with age in four right hemispheric electrode clusters where diminished gamma power in ADHD had previously been demonstrated by our group. We found significant non-linear association between resting gamma power and age in the lower frequency gamma₁ range (30–39 Hz) in ADHD as compared to controls in all investigated locations. Resting gamma₁ increased with age and was significantly lower in ADHD than in control subjects from early adulthood. We found no significant association between gamma activity and age in the gamma₂ range (39–48 Hz). Alterations of gamma band activity might reflect altered cortical network functioning in adult ADHD relative to controls. Our results reveal that abnormal gamma power is present at all ages, highlighting the lifelong nature of ADHD. Nonetheless, longitudinal studies are needed to confirm our results.

Adolescent Attention-Deficit/Hyperactivity Disorder: Understanding Teenage Symptom Trajectories

Symptoms of attention-deficit/hyperactivity disorder (ADHD) run a variable course through adolescence. While most affected individuals show some improvement, particularly of hyperactivity-impulsivity, symptoms of inattention are more persistent, and some individuals may meet diagnostic criteria for the first time during adolescence. Genetic factors affect adolescent symptom trajectories; those showing persistence likely carry a greater burden of common risk alleles. Rare structural genomic variants, such as copy number variants and point mutations, might also play a role. Although psychostimulant medication is associated with better functional outcomes, an impact on underlying adolescent symptom trajectories has been hard to demonstrate. At a neural level, several studies report that adolescents whose childhood ADHD symptoms have remitted are indistinguishable from neurotypical individuals. This finding could reflect the "carrying forward" of relatively typical childhood neural features among those destined for adolescent remission or the correction of early childhood anomalies with a convergence toward typical dimensions. Other studies have noted unique, possibly compensatory patterns of neural activity among adolescents whose ADHD has improved. Finally, different neural processes might occur in different brain regions. Thus, some functional imaging studies find that subcortical anomalies reflect the onset of ADHD and remain throughout life regardless of symptom change, whereas the variable clinical course of adolescent ADHD is determined by plasticity of the cerebral cortex. Integrating an understanding of the neural processes with genomic risk could elucidate the mechanisms underlying the complex course of adolescent ADHD.

The Co-occurrence of Pediatric Obesity and ADHD: an Understanding of Shared Pathophysiology and Implications for Collaborative Management

PURPOSE OF REVIEW

To describe what is known about the association between obesity and attention-deficit hyperactivity disorder (ADHD) in children along with the co-occurring conditions of sleep dysfunction, loss of control/binge eating disorder (LOC-ED/BED), and anxiety.

RECENT FINDINGS

Obesity and ADHD share common brain pathways (hypothalamic, executive, and reward centers) with pathophysiology in these areas manifesting in partial or complete expression of these diseases. Sleep dysfunction, LOC-ED/BED, and anxiety share similar pathways and are associated with this disease dyad. The association of obesity and ADHD with sleep dysfunction, LOC-ED/BED, and anxiety is discussed. An algorithm outlining decision pathways for patients with obesity and with and without ADHD is presented. Future research exploring the complex pathophysiology of both obesity and ADHD as well as co-occurring conditions is needed to develop clinical guidelines and ultimately assist in providing the best evidence-based care.

Neuropsychopharmacological effects of midazolam on the human brain

As a commonly used anesthetic agent, midazolam has the properties of water-soluble, rapid onset, and short duration of action. With the rapid development in the field of neuroimaging, numerous studies have investigated how midazolam acts on the human brain to induce the alteration of consciousness. However, the neural bases of midazolam-induced sedation or anesthesia remain beginning to be understood in detail. In this review, we summarize findings from neuroimaging studies that have used midazolam to study altered consciousness at different levels and content. We also compare the results to those of neuroimaging studies using diverse anesthetic agents and describe the common neural correlates of anesthetic-induced alteration of consciousness.

Peripheral Hypoarousal but Not Preparation-Vigilance Impairment Endures in ADHD Remission

Objective: This study investigates whether impairments associated with persistent ADHD-impaired attention allocation (P3 amplitude), peripheral hypoarousal (skin conductance level [SCL]), and adjustment in preparatory state (contingent negative variation [CNV])-reflect enduring deficits unrelated to ADHD outcome or are markers of ADHD remission. Method: Young people with childhood ADHD (73 persisters and 18 remitters) and 144 controls were compared on neurophysiological measures during two conditions (baseline and fast-incentive) of a four-choice reaction time task. Results: ADHD remitters differed from persisters, and were indistinguishable from controls, on baseline P3 amplitude and fast-incentive CNV amplitude (p ≤ .05). ADHD remitters differed from controls (p ≤ .01), and were indistinguishable from persisters (p > .05), on baseline SCL. Conclusion: Preparation-vigilance measures were markers of ADHD remission, confirming previous findings with other measures. Yet, SCL-measured peripheral hypoarousal emerges as an enduring deficit unrelated to ADHD improvement. Future studies should explore potential compensatory mechanisms that enable efficient preparation-vigilance processes in ADHD remitters.

Resting-state network dysconnectivity in ADHD: A system-neuroscience-based meta-analysis

OBJECTIVES

Neuroimaging studies report altered resting-state functional connectivity in attention deficit/hyperactivity disorder (ADHD) across multiple brain systems. However, there is inconsistency among individual studies.

METHODS

We meta-analyzed seed-based resting state studies of ADHD connectivity within and between four established resting state brain networks (default mode, cognitive control, salience, affective/motivational) using Multilevel Kernel Density Analysis method.

RESULTS

Twenty studies with 944 ADHD patients and 1121 controls were included in the analysis. Compared to controls, ADHD was associated with disrupted within-default mode network (DMN) connectivity - reduced in the core (i.e. posterior cingulate cortex seed) but elevated in the dorsal medial prefrontal cortex sub-system (i.e. temporal pole-inferior frontal gyrus). Connectivity was elevated between nodes in the cognitive control system. When the analysis was restricted to children and adolescents, additional reduced connectivity was detected between DMN and cognitive control and affective/motivational and salience networks.

CONCLUSIONS

Our data are consistent with the hypothesis that paediatric ADHD is a DMN-dysconnectivity disorder with reduced connectivity both within the core DMN sub-system and between that system and a broad set of nodes in systems involved in cognition and motivation.

In Quest of Pathognomonic/Endophenotypic Markers of Attention Deficit Hyperactivity Disorder (ADHD): Potential of EEG-Based Frequency Analysis and ERPs to Better Detect, Prevent and Manage ADHD

Attention deficit hyperactivity disorder (ADHD) is a chronic heritable developmental delay psychiatric disorder requiring chronic management, characterized by inattention, hyperactivity, hyperkinectivity and impulsivity. Subjective clinical evaluation still remains crucial in its diagnosis. Discussed are two key aspects in the “characterizing ADHD” and on the quest for objective “pathognomonic/endophenotypic diagnostic markers of ADHD”. The first aspect briefly revolves around issues related to identification of pathognomonic/endophenotypic diagnostic markers in ADHD. Issues discussed include changes in ADHD definition, remission/persistence and overlapping-symptoms cum shared-heritability with its co-morbid cross-border mental disorders. The second aspect discussed is neurobiological and EEG-based studies on ADHD. Given the neurobiological and temporal aspects of ADHD symptoms the electroencephalograph (EEG) like NeuralScan by Medeia appears as an appropriate tool. The EEGs appropriateness is further enhanced when coupled with suitable behavior/cognitive/motor/psychological tasks/paradigms yielding EEG-based markers like event-related-potential (ERPs like P3 amplitudes and latency), reaction time variability (RTV), Theta:Beta ratio (TBR) and sensorimotor rhythm (SMR). At present, these markers could potentially help in the neurobiological characterization of ADHD and either help in identifying or lay the groundwork for identifying pathognomonic and/or endophenotypic EEG-based markers enabling its diagnosis, treatment and management.

Transcranial Direct Current Stimulation in ADHD: A Systematic Review of Efficacy, Safety, and Protocol-induced Electrical Field Modeling Results

Transcranial direct current stimulation (tDCS) is a promising method for altering cortical excitability with clinical implications. It has been increasingly used in neurodevelopmental disorders, especially attention-deficit hyperactivity disorder (ADHD), but its efficacy (based on effect size calculations), safety, and stimulation parameters have not been systematically examined. In this systematic review, we aimed to (1) explore the effectiveness of tDCS on the clinical symptoms and neuropsychological deficits of ADHD patients, (2) evaluate the safety of tDCS application, especially in children with ADHD, (3) model the electrical field intensity in the target regions based on the commonly-applied and effective versus less-effective protocols, and (4) discuss and propose advanced tDCS parameters. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach, a literature search identified 14 empirical experiments investigating tDCS effects in ADHD. Partial improving effects of tDCS on cognitive deficits (response inhibition, working memory, attention, and cognitive flexibility) or clinical symptoms (e.g., impulsivity and inattention) are reported in 10 studies. No serious adverse effects are reported in 747 sessions of tDCS. The left and right dorsolateral prefrontal cortex are the regions most often targeted, and anodal tDCS the protocol most often applied. An intensity of 2 mA induced stronger electrical fields than 1 mA in adults with ADHD and was associated with significant behavioral changes. In ADHD children, however, the electrical field induced by 1 mA, which is likely larger than the electrical field induced by 1 mA in adults due to the smaller head size of children, was sufficient to result in significant behavioral change. Overall, tDCS seems to be a promising method for improving ADHD deficits. However, the clinical utility of tDCS in ADHD cannot yet be concluded and requires further systematic investigation in larger sample sizes. Cortical regions involved in ADHD pathophysiology, stimulation parameters (e.g. intensity, duration, polarity, and electrode size), and types of symptom/deficit are potential determinants of tDCS efficacy in ADHD. Developmental aspects of tDCS in childhood ADHD should be considered as well.

Estimating individual scores of inattention and impulsivity based on dynamic features of intrinsic connectivity network

Inattention and impulsivity are the two most important indices for evaluations of ADHD. Currently, inattention and impulsivity were evaluated by clinical scales. The intelligent evaluation of the two indices using machine learning remains largely unexplored. This paper aimed to build regression modes for inattention and impulsivity based on resting state fMRI and additional measures, and discover the associating features for the two indices. To achieve these goals, a cohort of 95 children with ADHD as well as 105 healthy controls were selected from the ADHD-200 database. The raw features were consisted of univariate dynamic estimators of intrinsic connectivity network (ICNs), head motion, and additional measures. The regression models were solved using support vector regression (SVR). The performance of the regression models was evaluated by cross-validations. The performance of regression models based on ICNs outperformed that based on regional measures. The estimated clinical scores were significantly correlated to inattention (r = 0.4 ± 0.02, p < 0.01) and impulsivity (r = 0.31 ± 0.02, p < 0.01). The most associating ICNs are sensorimotor network (SMN) for inattention and executive control network (ECN) for impulsivity. The results suggested that inattention and impulsivity could be estimated using machine learning, and the intra-ICN dynamics could be supplementary features for regression models of clinical scores of ADHD.

Anatomical substrates of symptom remission and persistence in young adults with childhood attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder that emerges in childhood and persists into adulthood in a sizeable portion of afflicted individuals. The persistence of ADHD symptoms elevates the risk of adverse outcomes that result in substantial individual and societal burden. The objective of this study was to delineate neuroanatomical substrates associated with the diversity of adult outcomes of childhood ADHD, which may have considerable value for development of novel interventions that target mechanisms associated with recovery. Structural MRI and diffusion tensor imaging data from 32 young adults who were diagnosed with ADHD combined-type during childhood and 35 group-matched controls were analyzed. Adults with childhood ADHD were divided into 16 remitters and 16 persisters based on DSM-IV criteria. Compared to the controls, ADHD probands showed significantly reduced gray matter (GM) volume in right putamen and white matter (WM) volume in left parieto-insular fiber tracts. Within the ADHD probands, the remitters, as compared to persisters, showed significantly greater volume of right hippocampo-frontal and right parieto-insular WM fiber tracts, and those connecting caudate with the frontal, parietal, occipital, temporal, and insular cortices. Among ADHD probands, increased fractional anisotropy value of left caudate-parietal tract was significantly correlated with reduced hyperactive/impulsive symptoms. These findings suggest that optimal structural development in the WM tracts that connect caudate with cortical areas, especially in the caudate-parietal path, may play an important role in symptom remission in young adults with childhood ADHD.

Multimodal neuroimaging-based prediction of adult outcomes in childhood-onset ADHD using ensemble learning techniques

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelopmental disorder, which is diagnosed using subjective symptom reports. Machine learning classifiers have been utilized to assist in the development of neuroimaging-based biomarkers for objective diagnosis of ADHD. However, existing basic model-based studies in ADHD report suboptimal classification performances and inconclusive results, mainly due to the limited flexibility for each type of basic classifier to appropriately handle multi-dimensional source features with varying properties. This study applied ensemble learning techniques (ELTs), a meta-algorithm that combine several basic machine learning models into one predictive model in order to decrease variance, bias, or improve predictions, in multimodal neuroimaging data collected from 72 young adults, including 36 probands (18 remitters and 18 persisters of childhood ADHD) and 36 group-matched controls. All currently available optimization strategies for ELTs (i.e., voting, bagging, boosting and stacking techniques) were tested in a pool of semifinal classification results generated by seven basic classifiers. The high-dimensional neuroimaging features for classification included regional cortical gray matter (GM) thickness and surface area, GM volume of subcortical structures, volume and fractional anisotropy of major white matter fiber tracts, pair-wise regional connectivity and global/nodal topological properties of the functional brain network for cue-evoked attention process. As a result, the bagging-based ELT with the base model of support vector machine achieved the best results, with significant improvement of the area under the receiver of operating characteristic curve (0.89 for ADHD vs. controls and 0.9 for ADHD persisters vs. remitters). Features of nodal efficiency in right inferior frontal gyrus, right middle frontal (MFG)-inferior parietal (IPL) functional connectivity, and right amygdala volume significantly contributed to accurate discrimination between ADHD probands and controls; higher nodal efficiency of right MFG greatly contributed to inattentive and hyperactive/impulsive symptom remission, while higher right MFG-IPL functional connectivity strongly linked to symptom persistence in adults with childhood ADHD. Considering their improved robustness than the commonly implemented basic classifiers, findings suggest that ELTs may have the potential to identify more reliable neurobiological markers for neurodevelopmental disorders.

Deriving and validating biomarkers associated with autism spectrum disorders from a large-scale resting-state database

Resting-state functional magnetic resonance imaging (MRI) has been used to investigate the brain activity related to autism spectrum disorder (ASD). In this study, we applied information from a large-scale dataset, the Autism Brain Imaging Data Exchange (ABIDE), to clinical applications. We recruited 21 patients with ASD and 23 individuals with neurotypical development (TD). We applied ASD biomarkers derived from ABIDE datasets and subsequently investigated the relationship between the MRI biomarkers and indicators from clinical screening questionnaires, the social responsiveness scale (SRS), and the Swanson, Nolan, and Pelham Questionnaire IV. The results indicated that the biomarkers generated from the default mode and executive control networks significantly differed between the participants with ASD and TD. In particular, the biomarkers derived from the default mode network were negatively correlated with the raw scores and model factors of the SRS. In summary, this study transferred the efforts of the global autism research community to clinical applications and identified connectivity-based biomarkers in ASD.

Surface-based shared and distinct resting functional connectivity in attention-deficit hyperactivity disorder and autism spectrum disorder

BACKGROUND

Both 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.

METHOD

We 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.

RESULTS

We 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.

CONCLUSIONS

Our 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.

Behavioral and Cognitive Impacts of Mindfulness-Based Interventions on Adults with Attention-Deficit Hyperactivity Disorder: A Systematic Review

Mindfulness-based interventions (MBIs) are becoming increasingly popular as treatments for physical and psychological problems. Recently, several studies have suggested that MBIs may also be effective in reducing symptoms of attention-deficit hyperactivity disorder (ADHD). Most studies have examined the effectiveness in children, but there are now a sufficient number of individual treatment trials to consider a systematic review in adults. Majority of existing systematic reviews and meta-analyses only consider ADHD symptoms as an outcome, and most of them do not fully report potential biases of included studies, thus limiting considerably their conclusions. This is an important facet because some studies could be found ineligible to be included in future analysis due to their low quality. In this systematic review, we followed the PRISMA/PICO criteria and we thoroughly assessed the risks of bias for each of the selected studies according to Cochrane guidelines. We searched the available literature concerning MBIs in adult participants with ADHD using PsycINFO, PubMed, Scopus, and ERIC databases. In total, 13 studies conducted with 753 adults (mean age of 35.1 years) were identified as eligible. Potential moderators such as participants' age, ADHD subtypes, medication status, comorbidity, intervention length, mindfulness techniques, homework amount, and training of therapists were carefully described. Aside from measuring the symptoms of ADHD, outcome measures were categorized into executive/cognitive functioning, emotional disturbances, quality of life, mindfulness, and grade point average at school. According to presented descriptive results, all the studies (100%) showed improvement of ADHD symptoms. In addition, mindfulness meditation training improves some aspects of executive function and emotion dysregulation. Although these are promising findings to support treatment efficacy of MBIs for ADHD, various biases such as absence of randomization and lack of a control group may affect the actual clinical value and implications of the studies. Moreover, the relatively low quality of selection and performance criteria in several studies, as well as relatively high attrition bias across studies, call for caution before considering conducting further analysis.

Interhemispheric functional connectivity for Alzheimer's disease and amnestic mild cognitive impairment based on the triple network model

The purpose of this study was to explore the differences in interhemispheric functional connectivity in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) based on a triple network model consisting of the default mode network (DMN), salience network (SN), and executive control network (ECN). The technique of voxel-mirrored homotopic connectivity (VMHC) analysis was applied to explore the aberrant connectivity of all patients. The results showed that: (1) the statistically significant connections of interhemispheric brain regions included DMN-related brain regions (i.e. precuneus, calcarine, fusiform, cuneus, lingual gyrus, temporal inferior gyrus, and hippocampus), SN-related brain regions (i.e. frontoinsular cortex), and ECN-related brain regions (i.e. frontal middle gyrus and frontal inferior); (2) the precuneus and frontal middle gyrus in the AD group exhibited lower VMHC values than those in the aMCI and healthy control (HC) groups, but no significant difference was observed between the aMCI and HC groups; and (3) significant correlations were found between peak VMHC results from the precuneus and Mini Mental State Examination (MMSE) and Montreal Cognitive Scale (MOCA) scores and their factor scores in the AD, aMCI, and AD plus aMCI groups, and between the results from the frontal middle gyrus and MOCA factor scores in the aMCI group. These findings indicated that impaired interhemispheric functional connectivity was observed in AD and could be a sensitive neuroimaging biomarker for AD. More specifically, the DMN was inhibited, while the SN and ECN were excited. VMHC results were correlated with MMSE and MOCA scores, highlighting that VMHC could be a sensitive neuroimaging biomarker for AD and the progression from aMCI to AD.

A Review of Heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD)

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects approximately 8%–12% of children worldwide. Throughout an individual’s lifetime, ADHD can significantly increase risk for other psychiatric disorders, educational and occupational failure, accidents, criminality, social disability and addictions. No single risk factor is necessary or sufficient to cause ADHD. The multifactorial causation of ADHD is reflected in the heterogeneity of this disorder, as indicated by its diversity of psychiatric comorbidities, varied clinical profiles, patterns of neurocognitive impairment and developmental trajectories, and the wide range of structural and functional brain anomalies. Although evidence-based treatments can reduce ADHD symptoms in a substantial portion of affected individuals, there is yet no curative treatment for ADHD. A number of theoretical models of the emergence and developmental trajectories of ADHD have been proposed, aimed at providing systematic guides for clinical research and practice. We conducted a comprehensive review of the current status of research in understanding the heterogeneity of ADHD in terms of etiology, clinical profiles and trajectories, and neurobiological mechanisms. We suggest that further research focus on investigating the impact of the etiological risk factors and their interactions with developmental neural mechanisms and clinical profiles in ADHD. Such research would have heuristic value for identifying biologically homogeneous subgroups and could facilitate the development of novel and more tailored interventions that target underlying neural anomalies characteristic of more homogeneous subgroups.

Neurometabolic and functional connectivity basis of prosocial behavior in early adolescence

Human prosocial behavior (PB) emerges in childhood and matures during adolescence. Previous task-related functional magnetic resonance imaging (fMRI) studies have reported involvement of the medial prefrontal cortex including the anterior cingulate cortex (ACC) in social cognition in adolescence. However, neurometabolic and functional connectivity (FC) basis of PB in early adolescence remains unclear. Here, we measured GABA levels in the ACC and FC in a subsample (aged 10.5–13.4 years) of a large-scale population-based cohort with MR spectroscopy (MEGA-PRESS) and resting-state fMRI. PB was negatively correlated with GABA levels in the ACC (N = 221), and positively correlated with right ACC-seeded FC with the right precentral gyrus and the bilateral middle and posterior cingulate gyrus (N = 187). Furthermore, GABA concentrations and this FC were negatively correlated, and the FC mediated the association between GABA levels and PB (N = 171). Our results from a minimally biased, large-scale sample provide new insights into the neurometabolic and neurofunctional correlates of prosocial development during early adolescence.