Distinct topological properties of cue-evoked attention processing network in persisters and remitters of childhood ADHD

Distinct Topological Properties of the Reward Anticipation Network in Preadolescent Children With Binge Eating Disorder Symptoms

OBJECTIVE

Few studies have considered the neural underpinnings of binge eating disorder (BED) in children, despite clinical and subclinical symptom presentation occurring in this age group. Symptom presentation at this age is of clinical relevance, as early onset of binge eating is linked to negative health outcomes. Studies in adults have highlighted dysfunction in the frontostriatal reward system as a potential candidate for binge eating pathophysiology, although the exact nature of such dysfunction is currently unclear.

METHOD

Data from 83 children (mean age 9.9 years, SD = 0.60) with symptoms of BED (57% girls) and 123 control participants (mean age 10.0 years, SD = 0.60) (52% girls) were acquired from the 4.0 baseline release of the Adolescent Brain Cognitive Development Study. Task-based graph theoretic techniques were used to analyze data from anticipation trials of the monetary incentive delay task. Network and nodal properties were compared between groups.

RESULTS

The BED-S group showed alterations in topological properties associated with the frontostriatal subnetwork, such as reduced nodal efficiency in the superior frontal gyrus, nucleus accumbens, putamen, and in normal sex-difference patterns of these properties, such as diminished girls-greater-than-boys pattern of betweenness-centrality in nucleus accumbens observed in controls.

CONCLUSION

Distinct network properties and sex-difference patterns in preadolescent children with BED-S suggest dysregulation in the reward system compared to those of matched controls. For the first time, these results quantify this dysregulation in terms of systems-level properties during anticipation of monetary reward and significantly inform the early and sex-related brain markers of BED symptoms.

PLAIN LANGUAGE SUMMARY

Binge eating disorder is the most common eating disorder. One factor that may contribute to binge eating is dysregulation of the reward system in the brain. This study analyzed brain activity during anticipation of monetary rewards in 83 youth with and 123 children without binge eating disorder symptoms from the Adolescent Brain Cognitive Development Study. The authors found specific alterations in the frontostriatal system, responsible for reward processing, in children with binge eating disorder symptoms, compared to the control group, suggesting dysregulation of the reward system.

Functional reorganization of brain activity in children with attention-deficit/hyperactivity disorder: Evidence from the modulatory effect of cognitive demand during visuospatial attention task

Previous studies reported that the inferior parietal lobule (IPL) had lower activation during visuospatial attention in children with attention-deficit/hyperactivity disorder (ADHD), while the functional connectivity (FC) between the IPL and other brain regions and how cognitive demand might modulate IPL's FC remain unclear. We performed a functional magnetic resonance imaging experiment recruiting two task conditions with relatively low and high cognitive demand of visuospatial attention. Forty-four children with ADHD and 36 age- and sex-matched healthy controls were included. IPL's regional activation and FC intensities were compared between groups and correlated with clinical measurements. We found that the IPL had significantly reduced activation in children with ADHD compared to healthy controls and this abnormal activation was not modulated by the cognitive demand of visuospatial attention. Importantly, further analysis revealed that the functional connectivity between IPL and inferior frontal gyrus was modulated by the cognitive demand of visuospatial attention in children with ADHD. These results revealed a modulatory effect of cognitive demand of visuospatial attention on IPL's functional connectivity but not IPL's activation in children with ADHD. More generally, these results highlight the functional reorganization of the brain activity as a possible compensatory strategy in response to the symptoms of ADHD.

Task-Based Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Systematic Review

Altered neurocognitive functioning is a key feature of attention-deficit/hyperactivity disorder (ADHD), and increasing numbers of studies assess task-based functional connectivity in the disorder. We systematically reviewed and critically appraised functional magnetic resonance imaging (fMRI) task-based functional connectivity studies in ADHD. A systematic search conducted up to September 2020 found 34 studies, including 51 comparisons. Comparisons were divided into investigations of ADHD neuropathology (37 comparing ADHD and typical development, 2 comparing individuals with ADHD and their nonsymptomatic siblings, 2 comparing remitted and persistent ADHD, and 1 exploring ADHD symptom severity) and the effects of interventions (8 investigations of stimulant effects and 1 study of fMRI neurofeedback). Large heterogeneity in study methodologies prevented a meta-analysis; thus, the data were summarized as a narrative synthesis. Across cognitive domains, functional connectivity in the cingulo-opercular, sensorimotor, visual, subcortical, and executive control networks in ADHD consistently differed from neurotypical populations. Furthermore, literature comparing individuals with ADHD and their nonsymptomatic siblings as well as adults with ADHD and their remitted peers showed ADHD-related abnormalities in similar sensorimotor and subcortical (primarily striatal) networks. Interventions modulated those dysfunctional networks, with the most consistent action on functional connections with the striatum, anterior cingulate cortex, occipital regions, and midline default mode network structures. Although methodological issues limited many of the reviewed studies, the use of task-based functional connectivity approaches has the potential to broaden the understanding of the neural underpinnings of ADHD and the mechanisms of action of ADHD treatments.

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.

Training Executive, Attention, and Motor Skills (TEAMS): a Preliminary Randomized Clinical Trial of Preschool Youth with ADHD

This preliminary randomized controlled trial compared Training Executive, Attention and Motor Skills (TEAMS), a played-based intervention for preschool children with attention-deficit/hyperactivity disorder (ADHD), to an active comparison intervention consisting of parent education and support (ClinicalTrials.gov Identifier: NCT01462032). The primary aims were to gauge preliminary efficacy and assist in further development of TEAMS. Four- and 5-year-old children with ADHD were randomly assigned to receive TEAMS (N = 26) or the comparison intervention (N = 26) with blinded assessments by parents, teachers and clinicians ascertained pretreatment, post-treatment, and 1- and 3-months post-treatment. Changes in ADHD severity, impairment, parenting factors, and neuropsychological functioning over time as a function of treatment condition were assessed using the PROC MIXED procedure in SAS. Across most measures, significant main effects for Time emerged; both treatments were associated with reduced ADHD symptoms that persisted for three months post-treatment. There were no significant Treatment effects or Time x Treatment interactions on symptom and impairment measures, suggesting that the magnitude of improvement did not differ between the two interventions. However, significant correlations emerged between the magnitude of behavioral change, as assessed by parents and clinicians, and the amount of time families engaged in TEAMS-related activities during treatment. Across a wide array of parenting and neuropsychological measures, there were few significant group differences over time. TEAMS and other psychosocial interventions appear to provide similar levels of benefit. Play-based interventions like TEAMS represent a potentially viable alternative/addition to current ADHD treatments, particularly for young children, but more research and further development of techniques are necessary.

Altered modular segregation of brain networks during the cue-craving task contributes to the disrupted executive functions in internet gaming disorder

BACKGROUND

Previous studies have shown that gaming-related cues could induce gaming cravings and bring about changes in brain activities in subjects with Internet gaming disorder (IGD). However, little is known about the brain network organizations in IGD subjects during a cue-craving task and the relationship between this network organization and IGD severity.

METHODS

Sixty-one IGD subjects and 61 matched recreational game users (RGUs) were scanned while performing a cue-craving task. We calculated and compared the participation coefficient (PC) among brain network modules between IGD subjects and RGUs. Based on the results, further group comparison analyses were performed to explain the PC changes and to explore the relationship between PCs and IGD severity.

RESULTS

While performing a cue-craving task, compared with RGUs, IGD subjects showed significantly decreased PCs in the default-mode network (DMN) and the frontal-parietal network (FPN). Specifically, the number of connections between nodes in the ventromedial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex and other nodes in the DMN of IGD subjects was much larger than that in RGUs. Correlation results showed that the number of DMN intra-modular connections was positively correlated with addiction severity and craving degree.

CONCLUSIONS

These results provide neural evidence that can explain why cognitive control, emotion, attention and other functions are impaired in IGD subjects in the face of gaming cues, which leads to compulsive behavior toward games. These findings extend our understanding of the neural mechanism of IGD and have important implications for developing effective interventions to treat IGD subjects.

Brain Structural Network Compensation Is Associated With Cognitive Impairment and Alzheimer's Disease Pathology

BACKGROUND

Structural network alterations in Alzheimer's disease (AD) are related to worse cognitive impairment. The aim of this study was to quantify the alterations in gray matter associated with impaired cognition and their pathological biomarkers in AD-spectrum patients.

METHODS

We extracted gray matter networks from 3D-T1 magnetic resonance imaging scans, and a graph theory analysis was used to explore alterations in the network metrics in 34 healthy controls, 70 mild cognitive impairment (MCI) patients, and 40 AD patients. Spearman correlation analysis was computed to investigate the relationships among network properties, neuropsychological performance, and cerebrospinal fluid pathological biomarkers (i.e., Aβ, t-tau, and p-tau) in these subjects.

RESULTS

AD-spectrum individuals demonstrated higher nodal properties and edge properties associated with impaired memory function, and lower amyloid-β or higher tau levels than the controls. Furthermore, these compensations at the brain regional level in AD-spectrum patients were mainly in the medial temporal lobe; however, the compensation at the whole-brain network level gradually extended from the frontal lobe to become widely distributed throughout the cortex with the progression of AD.

CONCLUSION

The findings provide insight into the alterations in the gray matter network related to impaired cognition and pathological biomarkers in the progression of AD. The possibility of compensation was detected in the structural networks in AD-spectrum patients; the compensatory patterns at regional and whole-brain levels were different and the clinical significance was highlighted.

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.