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

Published on Jun 1, 2019in British Journal of Psychiatry7.85
· DOI :10.1192/BJP.2018.248
Minyoung Jung12
Estimated H-index: 12
(University of Fukui),
Yiheng Tu16
Estimated H-index: 16
(Harvard University)
+ 4 AuthorsJian Kong67
Estimated H-index: 67
(Harvard University)
Sources
Abstract
Background Both attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental disorders with a high prevalence. They are often comorbid and both exhibit abnormalities in sustained attention, yet common and distinct neural patterns of ASD and ADHD remain unidentified. Aims To investigate shared and distinct functional connectivity patterns in a relatively large sample of boys (7- to 15-year-olds) with ADHD, ASD and typical development matched by age, gender and IQ. Method We applied machine learning techniques to investigate patterns of surface-based brain resting-state connectivity in 86 boys with ASD, 83 boys with ADHD and 125 boys with typical development. Results We observed increased functional connectivity within the limbic and somatomotor networks in boys with ASD compared with boys with typical development. We also observed increased functional connectivity within the limbic, visual, default mode, somatomotor, dorsal attention, frontoparietal and ventral attention networks in boys with ADHD compared with boys with ASD. In addition, using a machine learning approach, we were able to discriminate typical development from ASD, typical development from ADHD and ASD from ADHD with accuracy rates of 76.3%, 84.1%, and 79.3%, respectively. Conclusions Our results may shed new light on the underlying mechanisms of ASD and ADHD and facilitate the development of new diagnostic methods for these disorders. Declaration of interest J.K. holds equity in a startup company, MNT.
📖 Papers frequently viewed together
20202.74PLOS ONE
12 Authors (D. Seernani, ..., Christoph Klein)
1 Citations
15 Citations
14 Citations
References40
Newest
#1Minyoung Jung (University of Fukui)H-Index: 12
#2Yiheng Tu (Harvard University)H-Index: 16
Last. Jian Kong (Harvard University)H-Index: 67
view all 8 authors...
Abstract Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by atypical social communication and repetitive behaviors. In this study, we applied a multimodal approach to investigate brain structural connectivity, resting state activity, and surface area, as well as their associations with the core symptoms of ASD. Data from forty boys with ASD (mean age, 11.5 years; age range, 5.5–19.5) and forty boys with typical development (TD) (mean age, 12.3; age range, ...
22 CitationsSource
#1Sunghyon Kyeong (Yonsei University)H-Index: 17
#2Jae Jin Kim (Yonsei University)H-Index: 54
Last. Eunjoo Kim (Yonsei University)H-Index: 11
view all 3 authors...
Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous condition and identification of clinically meaningful subgroups would open up a new window for personalized medicine. Thus, we aimed to identify new clinical phenotypes in children and adolescents with ADHD and to investigate whether neuroimaging findings validate the identified phenotypes. Neuroimaging and clinical data from 67 children with ADHD and 62 typically developing controls (TDCs) from the ADHD-200 database w...
9 CitationsSource
Sensory processing atypicalities are a common feature in Autism Spectrum Disorders (ASD) and have previously been linked to a range of behaviours in individuals with ASD and atypical neurological development. More recently research has demonstrated a relationship between autistic traits in the neurotypical (NT) population and increased levels of atypical sensory behaviours. The aim of the present study is to extend previous research by examining specific patterns across aspects of autistic trait...
28 CitationsSource
#1Bo-yong Park (SKKU: Sungkyunkwan University)H-Index: 13
#2Jisu Hong (SKKU: Sungkyunkwan University)H-Index: 6
Last. Hyunjin Park (SKKU: Sungkyunkwan University)H-Index: 27
view all 4 authors...
Attention deficit hyperactivity disorder (ADHD) is a pervasive neuropsychological disorder that affects both children and adolescents. Child and adolescent ADHD patients exhibit different behavioral symptoms such as hyperactivity and impulsivity, but not much connectivity research exists to help explain these differences. We analyzed openly accessible resting-state functional magnetic resonance imaging (rs-fMRI) data on 112 patients (28 child ADHD, 28 adolescent ADHD, 28 child normal control, an...
14 CitationsSource
#1Noriaki Yahata (UTokyo: University of Tokyo)H-Index: 28
#2Jun MorimotoH-Index: 35
Last. Mitsuo KawatoH-Index: 94
view all 19 authors...
Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficul...
175 CitationsSource
#1Rosa Rugani (UNIPD: University of Padua)H-Index: 21
#2Giorgio Vallortigara (University of Trento)H-Index: 87
Last. Lucia Regolin (UNIPD: University of Padua)H-Index: 40
view all 4 authors...
Newborn chicks do need number (magnitude) tricks, exactly like humans. Shaki and Fischer (2015) have argued that our results, according to which newborn chicks associate smaller numbers with the left space and larger numbers with the right space (Rugani et al., 2015), could be due to non-numerical cues such as area, perimeter, or density of the displayed dots. Regarding to our Experiment 3, they claimed “…chicks in all control conditions responded to both numerosity and at least one uncontrolled...
9 CitationsSource
#1Yiheng Tu (SWU: Southwest University)H-Index: 16
#2Zhiguo Zhang (SYSU: Sun Yat-sen University)H-Index: 53
Last. Li Hu (UCL: University College London)H-Index: 27
view all 8 authors...
Ongoing fluctuations of intrinsic cortical networks determine the dynamic state of the brain, and influence the perception of forthcoming sensory inputs. The functional state of these networks is defined by the amplitude and phase of ongoing oscillations of neuronal populations at different frequencies. The contribution of functionally different cortical networks has yet to be elucidated, and only a clear dependence of sensory perception on prestimulus alpha oscillations has been clearly identif...
70 CitationsSource
#1Winke Francx (Radboud University Nijmegen)H-Index: 4
#2Marianne Oldehinkel (Radboud University Nijmegen)H-Index: 10
Last. Maarten Mennes (Radboud University Nijmegen)H-Index: 48
view all 10 authors...
Background: One neurodevelopmental theory hypothesizes remission of attention-deficit/hyperactivity disorder (ADHD) to result from improved prefrontal top-down control, while ADHD, independent of the current diagnosis, is characterized by stable non-cortical deficits (Halperin & Schulz, 2006). We tested this theory using resting state functional MRI (fMRI) data in a large sample of adolescents with remitting ADHD, persistent ADHD, and healthy controls. Methods: Participants in this follow-up stu...
57 CitationsSource
#1Leonardo Cerliani (Netherlands Institute for Neuroscience)H-Index: 16
#2Maarten Mennes (Radboud University Nijmegen)H-Index: 48
Last. Christian Keysers (Netherlands Institute for Neuroscience)H-Index: 62
view all 6 authors...
Importance Individuals with autism spectrum disorder (ASD) exhibit severe difficulties in social interaction, motor coordination, behavioral flexibility, and atypical sensory processing, with considerable interindividual variability. This heterogeneous set of symptoms recently led to investigating the presence of abnormalities in the interaction across large-scale brain networks. To date, studies have focused either on constrained sets of brain regions or whole-brain analysis, rather than focusi...
179 CitationsSource
#1Terrie E. MoffittH-Index: 197
#2Renate HoutsH-Index: 64
Last. Avshalom CaspiH-Index: 182
view all 16 authors...
Objective:Despite a prevailing assumption that adult ADHD is a childhood-onset neurodevelopmental disorder, no prospective longitudinal study has described the childhoods of the adult ADHD population. The authors report follow-back analyses of ADHD cases diagnosed in adulthood, alongside follow-forward analyses of ADHD cases diagnosed in childhood, in one cohort.Method:Participants belonged to a representative birth cohort of 1,037 individuals born in Dunedin, New Zealand, in 1972 and 1973 and f...
288 CitationsSource
Cited By15
Newest
#1Ming Xu (CAS: Chinese Academy of Sciences)
#2Vince D. Calhoun (Georgia Institute of Technology)H-Index: 123
Last. Jing Sui (Georgia Institute of Technology)H-Index: 41
view all 5 authors...
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is comprised of a constellation of behavioral symptoms. Non-invasive brain imaging techniques, such as magnetic resonance imaging (MRI), provide a valuable objective measurement of the brain. Many efforts have been devoted to developing imaging-based diagnostic tools for ASD based on machine learning (ML) technologies. In this sur...
Source
#1von Polier Gg (Forschungszentrum Jülich)
Last. Langner D
view all 8 authors...
BackgroundIt is a key concern in psychiatric research to investigate objective measures to support and ultimately improve diagnostic processes. Current gold standard diagnostic procedures for attention deficit hyperactivity disorder (ADHD) are mainly subjective and prone to bias. Objective measures such as neuropsychological measures and EEG markers show limited specificity. Recent studies point to alterations of voice and speech production to reflect psychiatric symptoms also related to ADHD. H...
Source
OBJECTIVE Volumetric changes in the amygdaloid and hippocampal subfields have been observed in children with combined attention deficit hyperactivity disorder (ADHD-C). The purpose of this study was to investigate whether volumetric changes in the amygdaloid and hippocampal subfields could be used to predict disease severity in children with ADHD-C. APPROACH The data used in this study was from ADHD-200 datasets, a total of 76 ADHD-C patients were included in this study. T1 structural MRI data w...
Source
#1Binlong Zhang (Beijing University of Chinese Medicine)H-Index: 1
#2Jingling Chang (Beijing University of Chinese Medicine)H-Index: 5
Last. Jian Kong (Harvard University)H-Index: 67
view all 10 authors...
Abstract Aphasia, one of the most common cognitive impairments after stroke, is commonly considered to be a cortical deficit. However, many studies have reported cases of post subcortical stroke aphasia (PSSA). The pathology and recovery mechanism of PSSA remain unclear. This study aimed to investigate PSSA mechanism through a multimodal magnetic resonance imaging (MRI) approach and a two-session study design (baseline and one month after treatment). Thirty-six PSSA patients and twenty-four matc...
Source
Source
#1Chris McNorgan (UB: University at Buffalo)H-Index: 12
#2Cary Judson (UB: University at Buffalo)H-Index: 1
Last. John G. Holden (UC: University of Cincinnati)H-Index: 18
view all 4 authors...
A mixed literature implicates atypical connectivity involving attentional, reward and task inhibition networks in ADHD. The neural mechanisms underlying the utility of behavioral tasks in ADHD diagnosis are likewise underexplored. We hypothesized that a machine-learning classifier may use task-based functional connectivity to compute a joint probability function that identifies connectivity signatures that accurately predict ADHD diagnosis and performance on a clinically-relevant behavioral task...
3 CitationsSource
#1Eun Jung Choi (Mental Health Research Institute)H-Index: 1
#1Eun Jung Choi (Holland Bloorview Kids Rehabilitation Hospital)H-Index: 1
Last. Evdokia AnagnostouH-Index: 51
view all 12 authors...
Abstract Children with neurodevelopmental disorders (NDDs) share common behavioural manifestations despite distinct categorical diagnostic criteria. Here, we examined canonical resting-state network connectivity in three diagnostic groups (autism spectrum disorder, attention-deficit/hyperactivity disorder and paediatric obsessive–compulsive disorder) and typically developing controls (TD) in a large single-site sample (N = 407), applying diagnosis-based and dimensional approaches to understand u...
1 CitationsSource
#1Jae Won Song (Seoul National University Hospital)H-Index: 1
#1Jae-Won Song (Seoul National University Hospital)H-Index: 1
Last. Bung-Nyun Kim (Seoul National University Hospital)H-Index: 16
view all 5 authors...
Deep learning (DL) is a kind of machine learning technique that uses artificial intelligence to identify the characteristics of given data and efficiently analyze large amounts of information to perform tasks such as classification and prediction. In the field of neuroimaging of neurodevelopmental disorders, various biomarkers for diagnosis, classification, prognosis prediction, and treatment response prediction have been examined; however, they have not been efficiently combined to produce mean...
1 CitationsSource
#1Susan YoungH-Index: 46
#2Jack Hollingdale (South London and Maudsley NHS Foundation Trust)H-Index: 4
Last. Emma Woodhouse ('KCL': King's College London)H-Index: 13
view all 22 authors...
BACKGROUND: Individuals with co-occurring hyperactivity disorder/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) can have complex presentations that may complicate diagnosis and treatment. There are established guidelines with regard to the identification and treatment of ADHD and ASD as independent conditions. However, ADHD and ASD were not formally recognised diagnostically as co-occurring conditions until the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) was...
15 CitationsSource
#1Yiting Huang (Harvard University)H-Index: 4
#2Binlong Zhang (Harvard University)H-Index: 4
Last. Jian Kong (Harvard University)H-Index: 67
view all 7 authors...
Objectives: Non-invasive brain stimulation (NIBS) is an emerging tool for treating autism spectrum disorder (ASD). Exploring new stimulation targets may improve the efficacy of NIBS for ASD. Materials and Methods: We first conducted a meta-analysis on 170 functional magnetic resonance imaging studies to identify ASD-associated brain regions. We then performed resting-state functional connectivity analysis in 70 individuals with ASD to investigate brain surface regions correlated with these ASD-a...
5 CitationsSource