Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity

The Journey of the Default Mode Network: Development, Function, and Impact on Mental Health

The Default Mode Network has been extensively studied in recent decades due to its central role in higher cognitive processes and its relevance for understanding mental disorders. This neural network, characterized by synchronized and coherent activity at rest, is intrinsically linked to self-reflection, mental exploration, social interaction, and emotional processing. Our understanding of the DMN extends beyond humans to non-human animals, where it has been observed in various species, highlighting its evolutionary basis and adaptive significance throughout phylogenetic history. Additionally, the DMN plays a crucial role in brain development during childhood and adolescence, influencing fundamental cognitive and emotional processes. This literature review aims to provide a comprehensive overview of the DMN, addressing its structural, functional, and evolutionary aspects, as well as its impact from infancy to adulthood. By gaining a deeper understanding of the organization and function of the DMN, we can advance our knowledge of the neural mechanisms that underlie cognition, behavior, and mental health. This, in turn, can lead to more effective therapeutic strategies for a range of neuropsychiatric conditions.

Real-world goal-directed behavior reveals aberrant functional brain connectivity in children with ADHD

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

Multifractal dynamic changes of spontaneous brain activity in psychiatric disorders: Adult attention deficit-hyperactivity disorder, bipolar disorder, and schizophrenia

It is one of the strategies to study the complexity of spontaneous fluctuation of brain neurons based on resting-state functional magnetic resonance imaging (rs-fMRI), but the multifractal characteristics of spontaneous fluctuation of brain neurons in psychiatric diseases need to be studied. Therefore, this paper will study the multifractal spontaneous brain activity changes in psychiatric disorders using the multifractal detrended fluctuation analysis algorithm based on the UCLA datasets. Specifically: (1) multifractal characteristics in adult attention deficit-hyperactivity disorder (ADHD), bipolar disorder (BP), and schizophrenia (SCHZ); (2) the source of those multifractal characteristics. Results showed that for adult ADHD, BP, and SCHZ, all 6 functional brain regions exhibit multifractal characteristics, and the multifractal spectrum shows a reduction in bell-shaped asymmetry, unlike the intensity of healthy control (HC) asymmetry. Besides, compared with HC, the multifractal sources of all functional brain regions were fat-tail probability distribution and the long-range dependence correlation, but the intensity of fat-tail probability distribution was decreased and the long-range dependence correlation was increased. The results provide a reference for further understanding the complexity of spontaneous fluctuation of neurons in psychiatric disorders.

Task-based modulation of functional connectivity of dorsal attention network in adult-ADHD

Recent studies have prompted a shift in the understanding of attention deficit hyperactivity disorder (ADHD) from models positing dysfunction of individual brain areas to those that assume alterations in large-scale brain networks. Despite this shift, the underlying neural mechanism of ADHD in the adult population remains uncertain. With functional magnetic resonance imaging (fMRI), this study examined brain connectivity of dorsal and ventral attention networks. Adults with and without ADHD completed a Go/No-Go task inside the scanner and the functional connectivity of attention networks was analysed. The generalized psychophysiological interaction analysis indicated differences involving the dorsal attention network. For the ADHD group, an interaction effect revealed altered dorsal attention-default mode network connectivity modulation, particularly between the right frontal eye field and posterior cingulate gyrus. We conclude that dorsal attention network dysfunction may be involved in sustained attention deficits in adult-ADHD. This study sheds light into network-level alterations contributing to the understanding of adult-ADHD, which may be a potential avenue for future research and clinical interventions.

Default at fault? Exploring neural correlates of default mode network in children with ADHD, their unaffected siblings versus neurotypical controls: A quantitative EEG study

BACKGROUND

Sustained activation of default mode network has been implicated for momentary lapses of attention and higher errors during performance of cognitive tasks in attention deficit hyperactive disorder (ADHD) children. Despite emerging evidence indicating the genetic basis of ADHD, there is paucity of literature investigating the alteration of DMN in children with ADHD and their unaffected siblings.

AIM

To study the cortical sources of DMN in children with ADHD compared to their siblings and neurotypical controls.

METHODS

Eighty-six participants (35 ADHD (12.4(±2.7) years), 16 unaffected siblings (11.8(±4.3) years) and 35 matched neurotypical controls (12.6 (±3.6) years) participated in the study. 128 channel EEG data was acquired during rest and Stroop cognitive task and analyzed for cortical source estimation using LORETA software.

RESULTS

Higher activation of DMN and DMN associated areas were observed during encoding of the color-word stimuli in children with ADHD. Sustained activation of core DMN areas namely medial frontal gyrus, posterior cingulate gyrus, parahippocampal gyrus and inferior parietal lobule was observed across all groups. Among the three groups, distinct cortical source activation differences were identified solely in the DMN and its associated areas among children with ADHD during the task encoding phase compared to baseline. In contrast, both siblings and neurotypical controls displayed activation in fronto-parieto-temporal areas subserving executive function were also observed.

CONCLUSION

Sustained activity of DMN areas with minimal activity in executive network in ADHD children and unaffected siblings during encoding of stimulus implies potential endophenotypic marker in children with ADHD compared to neurotypical controls.

Gray matter volumetric changes in tinnitus: The impact of hearing loss and severity

Tinnitus is a phantom auditory sensation that commonly co-occurs with hearing loss. Both tinnitus and hearing loss can impact the quality of life, emotional well-being, and cognitive functioning of the affected individuals. While previous studies have highlighted structural alterations in hearing loss and/or tinnitus, the fundamental neural mechanisms underpinning tinnitus severity remain poorly understood. In this study, we conducted a voxel-based morphometry to investigate gray matter (GM) volume differences among groups of participants with varying tinnitus severity and hearing status, and controls within a large sample. We observed reduced GM volume in the left anterior insula and right planum polare in participants with hearing loss, regardless of their tinnitus status, compared to normal hearing controls. We noted decreased GM volume in the bilateral anterior and posterior insula for those with tinnitus and normal hearing compared to a normal hearing control group. Further, the tinnitus with hearing loss group showed decreased GM volume in the left planum polare, left inferior temporal gyrus, bilateral anterior temporal gyri, and right superior frontal gyrus compared to the normal hearing control group, suggesting a combined effect of hearing loss and tinnitus. While tinnitus severity did not show a significant overall effect, there was a significant positive correlation between tinnitus distress and GM volume in bilateral planum polare. Our findings enhance the understanding of structural brain changes related to hearing loss and tinnitus, and advance the overall knowledge of tinnitus pathophysiology, which can contribute to the development of more effective treatments for tinnitus.

Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia

Cognitive functioning is a crucial aspect in schizophrenia (SZ), and when altered it has devastating effects on patients' quality of life and treatment outcomes. Several studies suggested that they could result from altered communication between the cortex and cerebellum. However, the neural correlates underlying these impairments have not been identified. In this study, we investigated resting state functional connectivity (rsFC) in SZ patients, by considering the interactions between cortical networks supporting cognition and cerebellum. In addition, we investigated the relationship between SZ patients' rsFC and their symptoms. We used fMRI data from 74 SZ patients and 74 matched healthy controls (HC) downloaded from the publicly available database SchizConnect. We implemented a seed-based connectivity approach to identify altered functional connections between specific cortical networks and cerebellum. We considered ten commonly studied resting state networks, whose functioning encompasses specific cognitive functions, and the cerebellum, whose involvement in supporting cognition has been recently identified. We then explored the relationship between altered rsFC values and Positive and Negative Syndrome Scale (PANSS) scores. The SZ group showed increased connectivity values compared with HC group for cortical networks involved in attentive processes, which were also linked to PANSS items describing attention and language-related processing. We also showed decreased connectivity between cerebellar regions, and increased connectivity between them and attentive networks, suggesting the contribution of cerebellum to attentive and affective deficits. In conclusion, our findings highlighted the link between negative symptoms in SZ and altered connectivity within the cerebellum and between the same and cortical networks supporting cognition.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

Differences between subclinical attention-deficit/hyperactivity and autistic traits in default mode, salience, and frontoparietal network connectivities in young adult Japanese

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are associated with attentional impairments, with both commonalities and differences in the nature of their attention deficits. This study aimed to investigate the neural correlates of ADHD and ASD traits in healthy individuals, focusing on the functional connectivity (FC) of attention-related large-scale brain networks (LSBNs). The participants were 61 healthy individuals (30 men; age, 21.9 ± 1.9 years). The Adult ADHD Self-Report Scale (ASRS) and Autism Spectrum Quotient (AQ) were administered as indicators of ADHD and ASD traits, respectively. Performance in the continuous performance test (CPT) was used as a behavioural measure of sustained attentional function. Functional magnetic resonance imaging scans were performed during the resting state (Rest) and auditory oddball task (Odd). Considering the critical role in attention processing, we focused our analyses on the default mode (DMN), frontoparietal (FPN), and salience (SN) networks. Region of interest (ROI)-to-ROI analyses (false discovery rate < 0.05) were performed to determine relationships between psychological measures with within-network FC (DMN, FPN, and SN) as well as with between-network FC (DMN-FPN, DMN-SN, and FPN-SN). ASRS scores, but not AQ scores, were correlated with less frequent commission errors and shorter reaction times in the CPT. During Odd, significant positive correlations with ASRS were demonstrated in multiple FCs within DMN, while significant positive correlations with AQ were demonstrated in multiple FCs within FPN. AQs were negatively correlated with FPN-SN FCs. During Rest, AQs were negatively and positively correlated with one FC within the SN and multiple FCs between the DMN and SN, respectively. These findings of the ROI-to-ROI analysis were only partially replicated in a split-half replication analysis, a replication analysis with open-access data sets, and a replication analysis with a structure-based atlas. The better CPT performance by individuals with subclinical ADHD traits suggests positive effects of these traits on sustained attention. Differential associations between LSBN FCs and ASD/ADHD traits corroborate the notion of differences in sustained and selective attention between clinical ADHD and ASD.

Variability in Cognitive Task Performance in Early Adolescence Is Associated With Stronger Between-Network Anticorrelation and Future Attention Problems

Background

Intraindividual variability (IIV) during cognitive task performance is a key behavioral index of attention and a consistent marker of attention-deficit/hyperactivity disorder. In adults, lower IIV has been associated with anticorrelation between the default mode network (DMN) and dorsal attention network (DAN)-thought to underlie effective allocation of attention. However, whether these behavioral and neural markers of attention are 1) associated with each other and 2) can predict future attention-related deficits has not been examined in a developmental, population-based cohort.

Methods

We examined relationships at the baseline visit between IIV on 3 cognitive tasks, DMN-DAN anticorrelation, and parent-reported attention problems using data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,878 participants, ages 9 to 10 years, female = 47.8%). We also investigated whether behavioral and neural markers of attention at baseline predicted attention problems 1, 2, and 3 years later.

Results

At baseline, greater DMN-DAN anticorrelation was associated with lower IIV across all 3 cognitive tasks (B = 0.22 to 0.25). Older age at baseline was associated with stronger DMN-DAN anticorrelation and lower IIV (B = -0.005 to -0.0004). Weaker DMN-DAN anticorrelation and IIV were cross-sectionally associated with attention problems (B = 1.41 to 7.63). Longitudinally, lower IIV at baseline was associated with less severe attention problems 1 to 3 years later, after accounting for baseline attention problems (B = 0.288 to 0.77).

Conclusions

The results suggest that IIV in early adolescence is associated with worsening attention problems in a representative cohort of U.S. youth. Attention deficits in early adolescence may be important for understanding and predicting future cognitive and clinical outcomes.

Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance

Introduction

Attention-deficit/hyperactivity disorder (ADHD) and autism are multi-faceted neurodevelopmental conditions with limited biological markers. The clinical diagnoses of autism and ADHD are based on behavioural assessments and may not predict long-term outcomes or response to interventions and supports. To address this gap, data-driven methods can be used to discover groups of individuals with shared biological patterns.

Methods

In this study, we investigated measures derived from cortical/subcortical volume, surface area, cortical thickness, and structural covariance investigated of 565 participants with diagnoses of autism [n = 262, median(IQR) age = 12.2(5.9), 22% female], and ADHD [n = 171, median(IQR) age = 11.1(4.0), 21% female] as well neurotypical children [n = 132, median(IQR) age = 12.1(6.7), 43% female]. We integrated cortical thickness, surface area, and cortical/subcortical volume, with a measure of single-participant structural covariance using a graph neural network approach.

Results

Our findings suggest two large clusters, which differed in measures of adaptive functioning (χ 2 = 7.8, P = 0.004), inattention (χ 2 = 11.169, P < 0.001), hyperactivity (χ 2 = 18.44, P < 0.001), IQ (χ 2 = 9.24, P = 0.002), age (χ 2 = 70.87, P < 0.001), and sex (χ 2 = 105.6, P < 0.001).

Discussion

These clusters did not align with existing diagnostic labels, suggesting that brain structure is more likely to be associated with differences in adaptive functioning, IQ, and ADHD features.

Sex differences of the triple network model in children with autism: A resting-state fMRI investigation of effective connectivity

Autism spectrum disorder (ASD) has a pronounced male predominance, but the underlying neurobiological basis of this sex bias remains unclear. Gender incoherence (GI) theory suggests that ASD is more neurally androgynous than same-sex controls. Given its central role, altered structures and functions, and sex-dependent network differences in ASD, the triple network model, including the central executive network (CEN), default mode network (DMN), and salience network (SN), has emerged as a candidate for characterizing this sex difference. Here, we measured the sex-related effective connectivity (EC) differences within and between these three networks in 72 children with ASD (36 females, 8-14 years) and 72 typically developing controls (TCs) (36 females, 8-14 years) from 5 sites of the Autism Brain Imaging Data Exchange repositories using a 2 × 2 analysis of covariance factorial design. We also assessed brain-behavior relationships and the effects of age on EC. We found significant diagnosis-by-sex interactions on EC: females with ASD had significantly higher EC than their male counterparts within the DMN and between the SN and CEN. The interaction pattern supported the GI theory by showing that the higher EC observed in females with ASD reflected a shift towards the higher level of EC displayed in male TCs (neural masculinization), and the lower EC seen in males with ASD reflected a shift towards the lower level of EC displayed in female TCs (neural feminization). We also found significant brain-behavior correlations and significant effects of age on EC.

EEG Connectivity in ADHD Compared to a Normative Database: A Cohort Analysis of 120 Subjects from the ICAN Study

This study explores how EEG connectivity measures in children with ADHD ages 7-10 (n = 140) differ from an age-matched nonclinical database. We differentiated connectivity in networks, Brodmann area pairs, and frequencies. Subjects were in the International Collaborative ADHD Neurofeedback study, which explored neurofeedback for ADHD. Inclusion criteria were mainly rigorously diagnosed ADHD and a theta/beta power ratio (TBR) ≤ 4.5. Using statistical and machine learning algorithms, connectivity values were extracted in coherence, phase, and lag coherence at all Brodmann, subcortical, and cerebellar areas within the main networks in all EEG frequencies and then compared with a normative database. There is a higher rate of dysregulation (more than ± 1.97SD), in some cases as much as 75%, of the Brodmann pairs observed in coherence and phase between BAs 7, 10, and 11 with secondary connections from these areas to BAs 21, 30, 35, 37, 39, and 40 in the ADHD children as compared to the normative database. Left and right Brodmann areas 10 and 11 are highly disconnected to each other. The most dysregulated Brodmann Areas in ADHD are 7, 10, and 11, relevant to ADHD executive-function deficits and provide important considerations when developing interventions for ADHD children.

Characterizing different cognitive and neurobiological profiles in a community sample of children using a non-parametric approach: An fMRI study

Executive Functions (EF) is an umbrella term for a set of mental processes geared towards goal-directed behavior supporting academic skills such as reading abilities. One of the brain's functional networks implicated in EF is the Default Mode Network (DMN). The current study uses measures of inhibitory control, a main sub-function of EF, to create cognitive and neurobiological "inhibitory control profiles" and relate them to reading abilities in a large sample (N = 5055) of adolescents aged 9-10 from the Adolescent Brain Cognitive Development (ABCD) study. Using a Latent Profile Analysis (LPA) approach, data related to inhibitory control was divided into four inhibition classes. For each class, functional connectivity within the DMN was calculated from resting-state data, using a non-parametric algorithm for detecting group similarities. These inhibitory control profiles were then related to reading abilities. The four inhibitory control groups showed significantly different reading abilities, with neurobiologically different DMN segregation profiles for each class versus controls. The current study demonstrates that a community sample of children is not entirely homogeneous and is composed of different subgroups that can be differentiated both behaviorally/cognitively and neurobiologically, by focusing on inhibitory control and the DMN. Educational implications relating these results to reading abilities are noted.

Gender differences in dynamic functional network connectivity in pediatric and adult patients with attention deficit hyperactivity disorder

ADHD persistence into adulthood depends on gender, with 60% female and 35% male cases. This study sought to investigate gender differences in dynamic functional network connectivity (dFNC) using resting-state functional magnetic resonance imaging (rs-fMRI) data of pediatric ADHD patients (female: N=24; 11.02 ± 2.60 years, male: N=20;11.87 ± 2.62 years) and adult ADHD patients (female=19; 31.11 ± 10.40 years, males: N=20;32.05 ± 10.10 years). We identified nine and eight networks in pediatrics and adult data, respectively, using GICA. Each age group was clustered into four states using K-means. Significant gender differences in the pediatric group were only found in temporal profiles, particularly in "fraction of time" (FOT) and "mean dwell time" (MDT), but not in FNC. FOT spent by the female pediatric group in state 4 showed a negative relationship with hyperactivity severity. Compared to the adult male group, reduced connectivity was observed within the visual network, between the visual network and DMN, and FPN, as well as between the DMN and cerebellum networks in female adult ADHD patients. Significant FOT and MDT differences were observed between the two groups in state 3. Our results imply gender differences in ADHD, especially in the adult group. Furthermore, given the gender differences observed, our work provides insights into the pathophysiology of ADHD sub-served by gender.

Catecholaminergic and cholinergic neuromodulation in autism spectrum disorder: A comparison to attention-deficit hyperactivity disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by social impairments and restricted, repetitive behaviors. Treatment of ASD is notoriously difficult and might benefit from identification of underlying mechanisms that overlap with those disturbed in other developmental disorders, for which treatment options are more obvious. One example of the latter is attention-deficit hyperactivity disorder (ADHD), given the efficacy of especially stimulants in treatment of ADHD. Deficiencies in catecholaminergic systems [dopamine (DA), norepinephrine (NE)] in ADHD are obvious targets for stimulant treatment. Recent findings suggest that dysfunction in catecholaminergic systems may also be a factor in at least a subgroup of ASD. In this review we scrutinize the evidence for catecholaminergic mechanisms underlying ASD symptoms, and also include in this analysis a third classic ascending arousing system, the acetylcholinergic (ACh) network. We complement this with a comprehensive review of DA-, NE-, and ACh-targeted interventions in ASD, and an exploratory search for potential treatment-response predictors (biomarkers) in ASD, genetically or otherwise. Based on this review and analysis we propose that (1) stimulant treatment may be a viable option for an ASD subcategory, possibly defined by genetic subtyping; (2) cerebellar dysfunction is pronounced for a relatively small ADHD subgroup but much more common in ASD and in both cases may point toward NE- or ACh-directed intervention; (3) deficiency of the cortical salience network is sizable in subgroups of both disorders, and biomarkers such as eye blink rate and pupillometric data may predict the efficacy of targeting this underlying deficiency via DA, NE, or ACh in both ASD and ADHD.

The clinical, neuropsychological, and brain functional characteristics of the ADHD restrictive inattentive presentation

Objectives

There is an ongoing debate about the restrictive inattentive (RI) presentation of attention deficit hyperactivity disorder (ADHD). The current study aimed to systematically investigate the clinical, neuropsychological, and brain functional characteristics of children with ADHD restrictive inattentive presentation.

Methods

A clinical sample of 789 children with or without ADHD participated in the current study and finished clinical interviews, questionnaires, and neuropsychological tests. Those individuals with a diagnosis of ADHD were further divided into three subgroups according to the presentation of inattentive and/or hyperactive/impulsive symptoms, the ADHD-RI, the ADHD-I (inattentive), and the ADHD-C (combined) groups. Between-group comparisons were carried out on each clinical and neuropsychological measure using ANCOVA, with age and sex as covariates. Bonferroni corrections were applied to correct for multiple comparisons. Two hundred twenty-seven of the subjects also went through resting-state functional magnetic resonance imaging scans. Five ADHD-related brain functional networks, including the default mode network (DMN), the dorsal attention network (DAN), the ventral attention network, the executive control network, and the salience network, were built using predefined regions of interest (ROIs). Voxel-based group-wise comparisons were performed.

Results

Compared with healthy controls, all ADHD groups presented more clinical problems and weaker cognitive function. Among the ADHD groups, the ADHD-C group had the most clinical problems, especially delinquent and aggressive behaviors. Regarding cognitive function, the ADHD-RI group displayed the most impaired sustained attention, and the ADHD-C group had the worst response inhibition function. In terms of brain functional connectivity (FC), reduced FC in the DMN was identified in the ADHD-C and the ADHD-I groups but not the ADHD-RI group, compared to the healthy controls. Subjects with ADHD-I also presented decreased FC in the DAN in contrast to the control group. The ADHD-RI displayed marginally significantly lower FC in the salience network compared to the ADHD-I and the control groups.

Conclusion

The ADHD-RI group is distinguishable from the ADHD-I and the ADHD-C groups. It is characterized by fewer externalizing behaviors, worse sustained attention, and better response inhibition function. The absence of abnormally high hyperactive/impulsive symptoms in ADHD-RI might be related to less impaired brain function in DMN, but potentially more impairment in the salience network.

Evidence from "big data" for the default-mode hypothesis of ADHD: a mega-analysis of multiple large samples

We sought to identify resting-state characteristics related to attention deficit/hyperactivity disorder, both as a categorical diagnosis and as a trait feature, using large-scale samples which were processed according to a standardized pipeline. In categorical analyses, we considered 1301 subjects with diagnosed ADHD, contrasted against 1301 unaffected controls (total N = 2602; 1710 males (65.72%); mean age = 10.86 years, sd = 2.05). Cases and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables and drawn from multiple large cohorts. Associations between ADHD-traits and resting-state connectivity were also assessed in a large multi-cohort sample (N = 10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B = 0.009, t = 3.45, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.014), somatomotor (B = 0.008, t = 3.49, p-FDR = 0.004, d = 0.14, 95% CI = 0.004, 0.013), and dorsal attention networks (B = 0.01, t = 4.28, p-FDR < 0.001, d = 0.17, 95% CI = 0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits, with the largest effect size observed for connectivity between the default mode network and the dorsal attention network (B = 0.0006, t = 5.57, p-FDR < 0.001, partial-r = 0.06, 95% CI = 0.0004, 0.0008). We report significant ADHD-related differences in interactions between the default mode network and task-positive networks, in line with default mode interference models of ADHD. Effect sizes (Cohen's d and partial-r, estimated from the mega-analytic models) were small, indicating subtle group differences. The overlap between the affected brain networks in the clinical and general population samples supports the notion of brain phenotypes operating along an ADHD continuum.

Brain structural network to investigate the mechanism of cognitive impairment in patients with acoustic neuroma

Objective

Acoustic neuroma (AN) is a common benign tumor. Little is known of neuropsychological studies in patients with acoustic neuroma, especially cognitive neuropsychology, and the neuropsychological abnormalities of patients affect their life quality. The purpose of this study was to explore the changes in the cognitive function of patients with acoustic neuroma, and the possible mechanism of these changes by structural magnetic resonance imaging.

Materials and methods

We used a neuropsychological assessment battery to assess cognitive function in 69 patients with acoustic neuroma and 70 healthy controls. Then, we used diffusion tensor imaging data to construct the structural brain network and calculate topological properties based on graph theory, and we studied the relation between the structural brain network and cognitive function. Moreover, three different subnetworks (short-range subnetwork, middle-range subnetwork, and long-range subnetwork) were constructed by the length of nerve fibers obtained from deterministic tracking. We studied the global and local efficiency of various subnetworks and analyzed the correlation between network metrics and cognitive function. Furthermore, connectome edge analysis directly assessed whether there were differences in the number of fibers in the different brain regions. We analyzed the relation between the differences and cognitive function.

Results

Compared with the healthy controls, the general cognitive function, memory, executive function, attention, visual space executive ability, visual perception ability, movement speed, and information processing speed decreased significantly in patients with acoustic neuroma. A unilateral hearing loss due to a left acoustic neuroma had a greater impact on cognitive function. The results showed that changes in the global and local metrics, the efficiency of subnetworks, and cognitively-related fiber connections were associated with cognitive impairments in patients with acoustic neuroma.

Conclusion

Patients exhibit cognitive impairments caused by the decline of the structure and function in some brain regions, and they also develop partial compensation after cognitive decline. Cognitive problems are frequent in patients with acoustic neuroma. Including neuropsychological aspects in the routine clinical evaluation and appropriate treatments may enhance the clinical management and improve their life quality.

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.

Excessive Functional Coupling With Less Variability Between Salience and Default Mode Networks in Autism Spectrum Disorder

BACKGROUND

Atypical activity in the salience network (SN) and default mode network (DMN) has been previously reported in individuals with autism spectrum disorder (ASD). However, no study to date has investigated the nature and dynamics of the interaction between these two networks in ASD.

METHODS

Here, we aimed to characterize the functional connectivity between the SN and the DMN by using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange and comparing individuals with ASD (n = 325) to a typically developing group (n = 356). We examined static and dynamic levels of functional connectivity using the medial prefrontal cortex (mPFC) seed as a core region of the DMN.

RESULTS

We found that individuals with ASD have higher mPFC connectivity with the insula, a core region of the SN, when compared with the typical development group. Moreover, the mPFC-insula coupling showed less variability in ASD compared with the typical development group. A novel semblance-based network dynamic analysis further confirmed that the strong mPFC-insula coupling in the ASD group reduced spontaneous attentional shift for possible external elements of the environment. Indeed, we found that excessive mPFC-insula coupling was significantly associated with a tendency for reduced social responsiveness.

CONCLUSIONS

These findings suggest that the internally oriented cognition in individuals with ASD may be due to excessive coupling between the DMN and the SN.

Research on the Mechanism of Cognitive Decline in Patients With Acoustic Neuroma

Little is known about neuropsychological research on patients with acoustic neuroma (AN), especially cognitive neuropsychology. We aim to compare the cognitive function of patients with AN and healthy controls (HCs) and explore possible underlying mechanisms. Various neuropsychological assessments were performed on all participants. Tract-based spatial statistics (TBSS) was used to compare DTI metrics such as fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Correlation analysis was analyzed between DTI metrics and cognitive scales. Compared with the HC group, the AN group performed worse in the neuropsychological evaluations, and TBSS analysis showed widespread alteration of the FA, AD, RD, and MD, which correlated with the cognitive function. These white matter tracts include minor forceps, major forceps, anterior thalamic radiation, superior longitudinal fasciculus, corticospinal tract, and right inferior fronto-occipital fasciculus. Meanwhile, we found for the first time that cognitive decline was related to the decrease of FA in minor forceps, which can be used as a neurobiological marker of cognitive impairment in patients with AN. The occurrence of cognition impairment is common in patients with AN. Including neuropsychological evaluation in the routine clinical assessment and appropriate treatment may strengthen clinical management and improve the quality of life of patients.

Differential structure-function network coupling in the inattentive and combined types of attention deficit hyperactivity disorder

The heterogeneous presentation of inattentive and hyperactive-impulsive core symptoms in attention deficit hyperactivity disorder (ADHD) warrants further investigation into brain network connectivity as a basis for subtype divisions in this prevalent disorder. With diffusion and resting-state functional magnetic resonance imaging data from the Healthy Brain Network database, we analyzed both structural and functional network efficiency and structure-functional network (SC-FC) coupling at the default mode (DMN), executive control (ECN), and salience (SAN) intrinsic networks in 201 children diagnosed with the inattentive subtype (ADHD-I), the combined subtype (ADHD-C), and typically developing children (TDC) to characterize ADHD symptoms relative to TDC and to test differences between ADHD subtypes. Relative to TDC, children with ADHD had lower structural connectivity and network efficiency in the DMN, without significant group differences in functional networks. Children with ADHD-C had higher SC-FC coupling, a finding consistent with diminished cognitive flexibility, for all subnetworks compared to TDC. The ADHD-C group also demonstrated increased SC-FC coupling in the DMN compared to the ADHD-I group. The correlation between SC-FC coupling and hyperactivity scores was negative in the ADHD-I, but not in the ADHD-C group. The current study suggests that ADHD-C and ADHD-I may differ with respect to their underlying neuronal connectivity and that the added dimensionality of hyperactivity may not explain this distinction.

Empirical Bayes estimation of pairwise maximum entropy model for nonlinear brain state dynamics

The pairwise maximum entropy model (pMEM) has recently gained widespread attention to exploring the nonlinear characteristics of brain state dynamics observed in resting-state functional magnetic resonance imaging (rsfMRI). Despite its unique advantageous features, the practical application of pMEM for individuals is limited as it requires a much larger sample than conventional rsfMRI scans. Thus, this study proposes an empirical Bayes estimation of individual pMEM using the variational expectation-maximization algorithm (VEM-MEM). The performance of the VEM-MEM is evaluated for several simulation setups with various sample sizes and network sizes. Unlike conventional maximum likelihood estimation procedures, the VEM-MEM can reliably estimate the individual model parameters, even with small samples, by effectively incorporating the group information as the prior. As a test case, the individual rsfMRI of children with attention deficit hyperactivity disorder (ADHD) is analyzed compared to that of typically developed children using the default mode network, executive control network, and salient network, obtained from the Healthy Brain Network database. We found that the nonlinear dynamic properties uniquely established on the pMEM differ for each group. Furthermore, pMEM parameters are more sensitive to group differences and are better associated with the behavior scores of ADHD compared to the Pearson correlation-based functional connectivity. The simulation and experimental results suggest that the proposed method can reliably estimate the individual pMEM and characterize the dynamic properties of individuals by utilizing empirical information of the group brain state dynamics.

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.

Resting state functional connectivity in adolescent synthetic cannabinoid users with and without attention-deficit/hyperactivity disorder

OBJECTIVE

Synthetic cannabinoids (SCs) have become increasingly popular in recent years, especially among adolescents. The first aim of the current study was to examine resting-state functional connectivity (rsFC) in SC users compared to controls. Our second aim was to examine the influence of comorbid attention-deficit/hyperactivity disorder (ADHD) symptomatology on rsFC changes in SC users compared to controls.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) analysis included 25 SC users (14 without ADHD and 11 with ADHD combined type) and 12 control subjects.

RESULTS

We found (i) higher rsFC between the default mode network (DMN) and salience network, dorsal attention network and cingulo-opercular network, and (ii) lower rsFC within the DMN and between the DMN and visual network in SC users compared to controls. There were no significant differences between SC users with ADHD and controls, nor were there any significant differences between SC users with and without ADHD.

CONCLUSIONS

We found the first evidence of abnormalities within and between resting state networks in adolescent SC users without ADHD. In contrast, SC users with ADHD showed no differences compared to controls. These results suggest that comorbidity of ADHD and substance dependence may show different rsFC alterations than substance use alone.

Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study

Growing evidence indicates that disruptions in the brain's functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

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.

Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of disease identification, and improve treatment efficiency. ADHD is a common behavioral disorder in school-age children, and it is also one of the most common chronic health problems in this period. The internationally recognized prevalence of ADHD is 3%–9%. ADHD often brings adverse effects on children's life and studying and at the same time increases difficulties for their families. Therefore, this paper designs an intelligent management platform for public hospitals based on a deep learning algorithm, evaluates the current situation and influencing factors of ADHD children through the child adaptive behavior scale and the family function assessment scale, and designs its intelligent platform by using a new technology of fNIRS. According to the nonlinearity and unsteadiness of the fNIRS signal, this paper proposes a motion noise removal method based on EMD algorithm methods: to automatically identify children with ADHD and improve the cognitive function of children with ADHD by intervention technology. The data are from the outpatients of the Department of Child Psychology of the First People's Hospital of Tianshui City in Gansu Province in 2018. The results showed that there were significant differences in the adaptive behavior scale (CABS) and fad scores between the two groups. In the seven dimensions of family function, there were significant differences between the two groups (P < 0.01). fNIRS management platform can effectively identify ADHD patients with high recognition accuracy. The intelligent management platform can significantly reduce the number of physical examination personnel, prolong the diagnosis and treatment time, reduce a lot of repetitive work, and improve the efficiency of diagnosis and treatment. At the same time, this technology also provides great help for better research and improvement of ADHD patients and provides a reference for the information intelligent construction of modern hospitals.

Functional Connectivity Networks and Their Recruitment During Working Memory Tasks in Adult Survivors of Childhood Brain Tumors

Background: Assessments of functional connectivity of default mode network (DMN) and positive task-related networks (TRNs) using independent component analysis (ICA) may help describe long-term effects of childhood brain tumors and adjuvant treatments. Methods: Aiming to identify potential neuronal markers that may aid in prognosis and inform interventions to optimize outcomes, this study used ICA to evaluate the presence of functional connectivity networks and their recruitment during a letter n-back task in 23 adult survivors of childhood posterior fossa tumors (9 low grade, 14 high grade) at least 5 years past diagnosis compared with 40 age- and sex-matched healthy peers. Results: DMN components generally demonstrated increasing disengagement as task difficulty increased, and relationships between effective DMN disengagement and improved performance were observed in healthy controls (HCs). Low-grade brain tumor survivors (LGS) demonstrated unique patterns in DMN recruitment that suggested increased involvement of the medial prefrontal cortex in LGS during tasks. TRN components generally demonstrated increasing engagement, which was related to improved task performance in HCs for one executive control network (ECN) component. High-grade brain tumor survivors (HGS) demonstrated distinct challenges recruiting an ECN component at more difficult task levels and showed a relationship between recruitment of another ECN component and task performance, indicating a potential compensatory mechanism for some HGS. Conclusions: Findings suggest the importance of cognitive intervention in both survivor groups and the necessity to track LGS despite their cognitive abilities often resembling those of their healthy peers. Impact statement Distinct functional connectivity patterns were identified between both adult survivor of childhood brain tumor groups and peers during attention and working memory tasks, reflecting different damage and recovery from treatment. Survivors of low-grade tumors demonstrated unique patterns of recruitment of default mode network components in the context of similar cognitive abilities, whereas survivors of high-grade tumors demonstrated poorer cognitive abilities and may be utilizing compensatory executive control network components in the face of challenging tasks. Long-term clinical follow-up and cognitive remediation is warranted for both groups, including low grade cerebellar tumor patients who have traditionally not been monitored as closely.

No support for white matter connectivity differences in the combined and inattentive ADHD presentations

Evidence from functional neuroimaging studies support neural differences between the Attention Deficit Hyperactivity Disorder (ADHD) presentation types. It remains unclear if these neural deficits also manifest at the structural level. We have previously shown that the ADHD combined, and ADHD inattentive types demonstrate differences in graph properties of structural covariance suggesting an underlying difference in neuroanatomical organization. The goal of this study was to examine and validate white matter brain organization between the two subtypes using both scalar and connectivity measures of brain white matter. We used both tract-based spatial statistical (TBSS) and tractography analyses with network-based Statistics (NBS) and graph-theoretical analyses in a cohort of 35 ADHD participants (aged 8-17 years) defined using DSM-IV criteria as combined (ADHD-C) type (n = 19) or as predominantly inattentive (ADHD-I) type (n = 16), and 28 matched neurotypical controls. We performed TBSS analyses on scalar measures of fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivity to assess differences in WM between ADHD types and controls. NBS and graph theoretical analysis of whole brain inter-regional tractography examined connectomic differences and brain network organization, respectively. None of the scalar measures significantly differed between ADHD types or relative to controls. Similarly, there were no tractography connectivity differences between the two subtypes and relative to controls using NBS. Global and regional graph measures were also similar between the groups. A single significant finding was observed for nodal degree between the ADHD-C and controls, in the right insula (corrected p = .029). Our result of no white matter differences between the subtypes is consistent with most previous findings. These findings together might suggest that the white matter structural architecture is largely similar between the DSM-based ADHD presentations is similar to the extent of being undetectable with the current cohort size.

A Review of the Default Mode Network in Autism Spectrum Disorders and Attention Deficit Hyperactivity Disorder

Functional magnetic resonance imaging (fMRI) has been widely used to examine the relationships between brain function and phenotypic features in neurodevelopmental disorders. Techniques such as resting-state functional connectivity (FC) have enabled the identification of the primary networks of the brain. One fMRI network, in particular, the default mode network (DMN), has been implicated in social-cognitive deficits in autism spectrum disorders (ASD) and attentional deficits in attention deficit hyperactivity disorder (ADHD). Given the significant clinical and genetic overlap between ASD and ADHD, surprisingly, no reviews have compared the clinical, developmental, and genetic correlates of DMN in ASD and ADHD and here we address this knowledge gap. We find that, compared with matched controls, ASD studies show a mixed pattern of both stronger and weaker FC in the DMN and ADHD studies mostly show stronger FC. Factors such as age, intelligence quotient, medication status, and heredity affect DMN FC in both ASD and ADHD. We also note that most DMN studies make ASD versus ADHD group comparisons and fail to consider ASD+ADHD comorbidity. We conclude, by identifying areas for improvement and by discussing the importance of using transdiagnostic approaches such as the Research Domain Criteria (RDoC) to fully account for the phenotypic and genotypic heterogeneity and overlap of ASD and ADHD.

Accelerated maturation in functional connectivity following early life stress: Circuit specific or broadly distributed?

Psychosocial acceleration theory and other frameworks adapted from life history predict a link between early life stress and accelerated maturation in several physiological systems. Those findings led researchers to suggest that the emotion-regulatory brain circuits of previously-institutionalized (PI) youth are more mature than youth raised in their biological families (non-adopted, or NA, youth) during emotion tasks. Whether this accelerated maturation is evident during resting-state fMRI has not yet been established. Resting-state fMRI data from 83 early adolescents (Mage = 12.9 years, SD = 0.57 years) including 41 PI and 42 NA youth, were used to examine seed-based functional connectivity between the amygdala and ventromedial prefrontal cortex (vmPFC). Additional whole-brain analyses assessed group differences in functional connectivity and associations with cognitive performance and behavior. We found group differences in amygdala - vmPFC connectivity that may be consistent with accelerated maturation following early life stress. Further, whole-brain connectivity analyses revealed group differences associated with internalizing and externalizing symptoms. However, the majority of whole-brain results were not consistent with an accelerated maturation framework. Our results suggest early life stress in the form of institutional care is associated with circuit-specific alterations to a frontolimbic emotion-regulatory system, while revealing limited differences in more broadly distributed networks.

Attention-Deficit Hyperactivity Disorder and the Dysregulation of Emotion Generation and Emotional Expression

Individuals with attention-deficit/hyperactivity disorder (ADHD) frequently experience strong reactions to emotionally evocative situations. Difficulties modulating anger and other upsets have clinically significant behavioral consequences. Those with ADHD may have anomalies in emotion generation, emotion expression, or both that predispose to these problems. The association between ADHD and emotion dysregulation raises Important clinical and research issues, including possible heterogeneity in the mechanisms by which they are related. Although first-line treatments for ADHD often help to resolve emotional dysregulation symptoms as well, the evidence base for widespread practice of combination pharmacotherapy remains sparse. Psychosocial treatments that engage processes underlying emotional dysregulation are in development.

l-Cystine is associated with the dysconnectivity of the default-mode network and salience network in attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Distributed dysconnectivity within both the default-mode network (DMN) and the salience network (SN) has been observed in ADHD. L-cystine may serve as a neuroprotective molecule and signaling pathway, as well as a biomarker of ADHD. The purpose of this study was to explore whether differential brain network connectivity is associated with peripheral L-cystine levels in ADHD patients. We recruited a total of 31 drug-naïve patients with ADHD (mean age: 10.4 years) and 29 healthy controls (mean age: 10.3 years) that underwent resting state functional magnetic resonance imaging scans. Functional connectomes were generated for each subject, and we examined the cross-sectional group difference in functional connectivity (FC) within and between DMN and SN. L-cystine plasma levels were determined using high-performance chemical isotope labeling (CIL)-based liquid chromatography-mass spectrometry (LC-MS). Compared to the control group, the ADHD group showed decreased FC of dorsal DMN (p = 0.031), as well as decreased FC of precuneus-post SN (p = 0.006) and ventral DMN-post SN (p = 0.001). The plasma L-cystine levels of the ADHD group were significantly higher than in the control group (p = 0.002). Furthermore, L-cystine levels were negatively correlated with FC of precuneus-post SN (r = -0.404, p = 0.045) and ventral DMN-post SN (r = -0.540, p = 0.007). The findings suggest that decreased synergies of DMN and SN may serve as neurobiomarkers for ADHD, while L-cystine may be involved in the pathophysiology of network dysconnectivity. Future studies on the molecular mechanism of the cystine-glutamate system in brain network connectivity are warranted.

Functional Connectivity of Attention-Related Networks in Drug-Naïve Children With ADHD

Objective: This study aimed to explore alterations of seed-based functional connectivity (FC) in dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN) in ADHD children. Method: A voxel-based comparison of FC maps between 46 drug-naïve children with ADHD and 31 healthy controls (HCs) and correlation analysis between connectivity features and behavior were performed. Results: Compared with the HCs, children with ADHD were characterized by hyperconnectivity between DAN and regions of DMN and by hyperconnectivity between DMN and a set of regions involved in somatosensory, visual, and auditory cortices. No significant group different FC was found between VAN and the whole brain. Higher FC between DMN and somatosensory, visual, and auditory cortex was associated with better performance in attention and executive function. Conclusion: The dysregulation of networks in children with ADHD not only involves the DAN and DMN but also the somatosensory, motor, visual, and auditory networks.

Functional connectivity in frontostriatal networks differentiate offspring of parents with substance use disorders from other high-risk youth

BACKGROUND

Family history (FH) of substance use disorders (SUDs) is known to elevate SUD risk in offspring. However, the influence of FH SUDs has been confounded by the effect of externalizing psychopathologies in the addiction risk neuroimaging literature. Thus, the current study aimed to assess the association between parental SUDs and offspring functional connectivity in samples matched for psychopathology and demographics.

METHODS

Ninety 11-12-year-old participants with externalizing disorders were included in the study (48 FH+, 42 FH-). We conducted independent component analyses (ICA) and seed-based analyses (orbitofrontal cortex; OFC, nucleus accumbens (NAcc), dorsolateral prefrontal cortex) with resting state data.

RESULTS

FH+ adolescents showed stronger functional connectivity between the right lateral OFC seed and anterior cingulate cortex compared to FH- adolescents (p < 0.05, corrected). Compared to FH-, FH+ adolescents showed stronger negative functional connectivity between the left lateral OFC seed and right postcentral gyrus and between the left NAcc seed and right middle occipital gyrus (p < 0.05, corrected). Poorer emotion regulation was associated with more negative connectivity between right occipital/left NAcc among FH+ adolescents based on the seed-based analysis. FH- adolescents had stronger negative functional connectivity between ventral attention/salience networks and dorsal attention/visuospatial networks in the ICA.

CONCLUSIONS

Both analytic methods found group differences in functional connectivity between brain regions associated with executive functioning and regions associated with sensory input (e.g., postcentral gyrus, occipital regions). We speculate that families densely loaded for SUD may confer risk by altered neurocircuitry that is associated with emotion regulation and valuation of external stimuli beyond what would be explained by externalizing psychopathology alone.

Altered Functional Connectivity in a Triple-Network Model in Autism With Co-occurring Attention Deficit Hyperactivity Disorder

Purpose: This study aimed to explore alterations in functional connectivity (FC) within and between default mode network (DMN), central executive network, and salience network in autism spectrum disorder (ASD) with co-occurring attention deficit hyperactivity disorder (ADHD). Method: A total of 135 individuals' date of the Autism Brain Imaging Data Exchange II was used to compare the ASD+ADHD group with the ASD group in relation to the abnormal within-network and between-network connectivity of the ASD group relative to the TD group; consequently, the correlation analysis between abnormal FC and behavior was performed. Results: The ASD+ADHD group exhibited decreased within-network connectivity in the precuneus of the ventral DMN compared with the ASD group. Among the three groups, the ASD+ADHD group showed lower connectivity, whereas the ASD group had higher connectivity than the TD group, although the effect of the separate post hoc test was not significant. Meanwhile, the ASD+ADHD group showed increased between-network connectivity between the ventral DMN and dorsal DMN and between the ventral DMN and left executive control network, compared with the ASD and TD groups. Conclusion: Dysfunction of DMN in the "triple-network model" is the core evidence for ASD with co-occurring ADHD.

Brain Network Connectivity and Association with Catechol-O-Methyltransferase Gene Polymorphism in Korean Attention-Deficit Hyperactivity Disorder Children

OBJECTIVE

We sought to determine if the links between and within the default mode network (DMN) and dorsal attention network (DAT) exhibited different conditions according to catechol-O-methyltransferase (COMT) gene polymorphism in relationship to attention-deficit hyperactivity disorder (ADHD) symptoms.

METHODS

Fifty-seven children with ADHD and 48 healthy controls (HCs) were administered an intelligence test, the Children's Depression Inventory, the Korean ADHD rating scale, and continuous performance test. Resting-state brain functional MRI scans were obtained, and COMT genotyping was performed to distinguish valine carriers and methionine homozygotes.

RESULTS

Compared to controls, children with ADHD showed increased ADHD scale scores, increased visual commission errors, and increased functional connectivity (FC) within the DMN and DAT. Compared to all children with ADHD, children with the methionine homozygote and those who were valine carriers showed increased FC within the DMN and DAT and decreased FC between the DMN and DAT. FC within the DMN was also increased in HC valine carriers compared to HC children with the methionine homozygote, and in children with ADHD who were valine carriers compared to HC valine carriers.

CONCLUSION

We observed increased brain connectivity within the DMN and DAT and altered brain connectivity within and between the DMN and DAT associated with COMT polymorphism in children with ADHD.

Callous-unemotional traits and reduced default mode network connectivity within a community sample of children

Callous-unemotional (CU) traits characterize a subset of youth at risk for persistent and serious antisocial behavior. Differences in resting state connectivity in the default mode network (DMN) have been associated with CU traits in forensic and clinical samples of adolescents and with deficient interpersonal/affective traits (often operationalized as Factor 1 psychopathy traits) in adults. It is unclear whether these brain-behavior associations extend to community-based children. Using mixed model analyses, we tested the associations between CU traits and within-network resting-state connectivity of seven task-activated networks and the DMN using data from 9,636 9-11-year-olds in the Adolescent Brain Cognitive Development (ABCD) study. Even after accounting for comorbid externalizing problems, higher levels of CU traits were associated with reduced connectivity within the DMN. This finding is consistent with prior literature surrounding psychopathy and CU traits in clinically and forensically based populations, suggesting the correlation likely exists on a spectrum, can be detected in childhood, and is not restricted to children with significant antisocial behavior.

Healthy Subjects With Extreme Patterns of Performance Differ in Functional Network Topology and Benefits From Nicotine

Do subjects with atypical patterns in attentional and executive behaviour show different brain network topology and react differently towards nicotine administration? The efficacy of pro-cognitive drugs like nicotine considerably varies between subjects and previous theoretical and empirical evidence suggest stronger behavioural nicotine effects in subjects with low performance. One problem is, however, how to best define low performance, especially if several cognitive functions are assessed for subject characterisation. We here present a method that used a multivariate, robust outlier detection algorithm to identify subjects with suspicious patterns of performance in attentional and executive functioning. In contrast to univariate approaches, this method is sensitive towards extreme positions within the multidimensional space that do not have to be extreme values in the individual behavioural distributions. The method was applied to a dataset of healthy, non-smoking subjects (n = 34) who were behaviorally characterised by an attention and executive function test on which N = 12 volunteers were classified as outliers. All subjects then underwent a resting-state functional magnetic resonance imaging (fMRI) scan to characterise brain network topology and an experimental behavioural paradigm under placebo and nicotine (7 mg patch) that gauged aspects of attention and executive function. Our results indicate that subjects with an atypical multivariate pattern in attention and executive functioning showed significant differences in nodal brain network integration in visual association and pre-motor brain regions during resting state. These differences in brain network topology significantly predicted larger individual nicotine effects on attentional processing. In summary, the current approach successfully identified a subgroup of healthy volunteers with low behavioural performance who differ in brain network topology and attentional benefit from nicotine.

Impairments of large-scale functional networks in attention-deficit/hyperactivity disorder: a meta-analysis of resting-state functional connectivity

Altered resting-state functional connectivity (rsFC) has been noted in large-scale functional networks in attention-deficit/hyperactivity disorder (ADHD). However, identifying consistent abnormalities of functional networks is difficult due to varied methods and results across studies. To integrate rsFC alterations and search for coherent patterns of intrinsic functional network impairments in ADHD, this research conducts a coordinate-based meta-analysis of voxel-wise seed-based rsFC studies comparing rsFC between ADHD patients and healthy controls. A total of 25 datasets from 21 studies including 700 ADHD patients and 580 controls were analyzed. We extracted the coordinates of seeds and between-group effects. Each seed was then categorized into a seed-network by its location within priori 7-network parcellations. Then, pooled meta-analyses were conducted for the default mode network (DMN), frontoparietal network (FPN) and affective network (AN) separately, but not for the ventral attention network (VAN), dorsal attention network (DAN), somatosensory network (SSN) and visual network due to a lack of primary studies. The results showed that ADHD was characterized by hyperconnectivity between the FPN and regions of the DMN and AN as well as hypoconnectivity between the FPN and regions of the VAN and SSN. These findings not only support the triple-network model of pathophysiology associated with ADHD but also extend this model by highlighting the involvement of the SSN and AN in the mechanisms of network interactions that may account for motor hyperactivity and impulsive symptoms.

Decreased resting gamma activity in adult attention deficit/hyperactivity disorder

Objectives: To delineate task-free gamma activity in adult ADHD and healthy control subjects based on high-density EEG recordings. Relationship of gamma activity with symptom severity was also examined, since gamma activity is considered to be an index of network functions in the brain that underlie higher-order cognitive processes.Methods: Spontaneous EEG was recorded in adult ADHD subjects (N = 42; 25 methylphenidate-naïve and 17 on methylphenidate treatment) and controls (N = 59) with eyes open. EEG absolute power gamma was investigated in the gamma₁ (30.25-39 Hz) and gamma₂ (39.25-48 Hz) frequency bands.Results: Gamma₁ and gamma₂ activity was diminished in ADHD compared with healthy control subjects. The difference between ADHD and controls was the most pronounced in the right centroparietal region for both gamma₁ and gamma₂. Inverse associations were found between gamma₁ and gamma₂ activity and ADHD symptoms in centroparietal scalp regions.Conclusions: Gamma activity is reduced in adult ADHD, and the reduction has a predominantly right centroparietal distribution. Our findings are consistent with childhood ADHD literature with respect to diminished posterior gamma activity in patients, which may reflect altered dorsal attention network functions. Gamma abnormalities might provide a link between neurophysiological functioning and neuropsychological deficiencies, thereby offering an opportunity to investigate the neurobiological mechanisms that underlie the clinical symptoms of ADHD.

Altered social cognition and connectivity of default mode networks in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder

OBJECTIVE

As two common neurodevelopmental disorders, autistic spectrum disorder and attention deficit hyperactivity disorder frequently occur together. Until now, only a few studies have investigated the co-occurrence of attention deficit hyperactivity disorder and autistic spectrum disorder, this is due to restrictions associated with previous Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. Most previous research has focused on the developmental trajectories for autistic spectrum disorder and attention deficit hyperactivity disorder separately, while the neural mechanisms underpinning the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder remain largely unknown.

METHODS

We studied 162 autistic spectrum disorder individuals (including 79 co-attention deficit hyperactivity disorder and 83 non-attention deficit hyperactivity disorder patients) and 177 typical developing individuals using resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange II, an aggregated magnetic resonance imaging dataset from 19 centers. Independent component analysis was used to extract sub-networks from the classic resting-state networks. Functional connectivity values within (intra-iFC) and between (inter-iFC) these networks were then determined. Subsequently, we compared the ASD_coADHD group with the ASD_nonADHD group in relation to the abnormal intra-iFC and inter-iFC of autistic spectrum disorder group relative to the typical developing group.

RESULTS

The ASD_coADHD group showed more severe social impairment and decreased intra-iFC in the bilateral posterior cingulate cortex of the default mode network (independent component 17) and increased inter-iFC between the default mode network (independent component 8) and the somatomotor networks (independent component 2) compared to the ASD_nonADHD group. In addition, the strength of the intra-iFC in the default mode network was associated with the severity of autistic traits across the entire autistic spectrum disorder group and particularly the ASD_coADHD group.

CONCLUSION

Our results showed that dysfunction of the default mode network is a central feature in the co-occurrence of autistic spectrum disorder and attention deficit hyperactivity disorder, including connectivity within the default mode network as well as between the default mode network and the somatomotor networks, thus supporting the existence of a clinically combined phenotype (autistic spectrum disorder + attention deficit hyperactivity disorder).