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Cited by 33Functional Brain Connectivity StudiesAutism Spectrum Disorder ResearchAttention Deficit Hyperactivity Disorder

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders

Open access
Dajani, Dina R., Burrows, Catherine A., Odriozola, Paola, Baez, Adriana, Nebel, Mary Beth, Mostofsky, Stewart H., Uddin, Lucina Q.·2019·NeuroImage: Clinical
DOI 10.1016/j.nicl.2019.101678PMC PMC6356009

Published version of a preprint

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Abstract

BACKGROUND: Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a sample adequately powered to detect large effects. We also assess the neurobiological separability of a novel, potential alternative categorical scheme based on behavioral measures of executive function. METHOD: Five-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level. RESULTS: No significant group differences in within- or between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD + ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences. CONCLUSIONS: Using clinical diagnosis and behavioral measures of executive function, no differences in functional connectivity were observed among the categories examined. Despite our limited ability to detect small- to medium-sized differences between groups, this work contributes to a growing literature suggesting that traditional diagnostic categories do not define neurobiologically separable groups. Future work is necessary to ascertain the validity of the executive function-based nosology, but current results suggest that nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories.

AI snapshot

Written from the paper’s full text.

TL;DR

This study used resting-state fMRI and ICA dual regression to test whether traditional ASD/ADHD/TD categories or executive-function-based subgroups differ in within- and between-network connectivity of frontoparietal, salience, and default-mode networks. No significant group differences emerged across any categorical scheme, suggesting these categories are not neurobiologically separable by functional connectivity.

Key findings

  • No significant within- or between-network connectivity differences were found between TD, ADHD, and ASD groups (within-network FWE-corrected p’s > 0.26; between-network p’s > 0.37), and results remained null when controlling for EF subgroup (within p’s > 0.20; between p’s > 0.11).
  • When comorbidity was separated (TD, ADHD without ASD, ASD without ADHD, ASD + ADHD), no group differences emerged in within-network (FWE-corrected p’s > 0.30) or between-network connectivity (p’s > 0.14).
  • EF subgroups (“above average,” “average,” “impaired”) showed no significant within- or between-network connectivity differences (within p’s > 0.24; between p’s > 0.29), including after controlling for diagnostic status (within p’s > 0.25; between p’s > 0.47).
  • Motion decreased significantly after ICA-AROMA preprocessing, F(1, 332) = 25.36, p < .001 (raw mean FD = 0.22, SD = 0.14; preprocessed mean FD = 0.04, SD = 0.02).

Methods

  • Five-minute resting-state fMRI data were obtained from 168 children aged 8–13 years (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, or TD. Subsamples included a diagnostic group sample (N = 129, n = 43 per group), a comorbid diagnostic sample (N = 88, n = 22 per group), and an EF subgroup sample (N = 129, n = 43 per group).
  • Group ICA with FSL MELODIC identified five components of interest: right FPN, left FPN, SN, anterior DMN, and posterior DMN. Dual regression generated individual-level spatial and temporal maps; within-network differences were tested with FSL randomise (5000 permutations), and between-network differences with FSLNets F-tests, using threshold-free cluster enhancement at p < .05 FWE-corrected.
  • The diagnostic and EF subgroup samples were adequately powered to detect large effects (alpha = 0.05, f = 0.4, power = 99%) but underpowered for medium (71%) and small (16%) effects; the comorbid sample was powered at 88% for large effects, 46% for medium, and 10% for small effects.

Limitations

  • The paper states that the 5-minute resting-state scan length may not have been long enough to generate reliable functional connectivity indices, possibly contributing to null findings. It also notes that clinical samples had additional psychiatric comorbidities beyond ASD and ADHD (most commonly oppositional defiant disorder) that were not accounted for, and that another RDoC domain such as social communication may be better suited for an alternative nosology.
  • The paper states that EF subgrouping relied primarily on parent-report BRIEF measures, which may be many steps removed from underlying large-scale brain network integrity, and that the study was underpowered to detect medium or small effects. It also notes that the comorbid diagnostic sample could not be matched on FSIQ (p < .001), and EF subgroups differed on FSIQ (p < .001).
  • Evident from the text: the sample had relatively high FSIQ (diagnostic group means 107.5–112.4, ranges 90–145) and was predominantly male, so findings may not generalize to lower-functioning or more balanced-sex samples.

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Integrity signals

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Crossref · 10.1016/j.nicl.2019.101678

Cites

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Statistics

Claims the paper makes

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  • Findingown data

    Mean framewise displacement significantly decreased following preprocessing with ICA-AROMA, F(1,332)=25.36, p<.001 (raw: M=0.22 SD=0.14, preprocessed: M=0.04 SD=0.02).

    “The ANOVA demonstrated a significant decrease in mean FD following preprocessing, F(1, 332) = 25.36, p < .001 (raw: M = 0.22 SD = 0.14, preprocessed: M = 0.04 SD = 0.02, Fig. 1).”
    Quote in the paperSubstantial claim
  • Findingown data

    When comparing diagnostic groups and statistically controlling for the effects of EF subgroup, F-tests remained non-significant (within-network: FWE-corrected p's > 0.20, between-network: FWE-corrected p's > 0.11).

    “When comparing diagnostic groups and statistically controlling for the effects of EF subgroup, F-tests remained non-significant (within-network: FWE-corrected p's > 0.20, between-network: FWE-corrected p's > 0.11).”
    Quote in the paperSubstantial claim
  • Findingown data

    After controlling for diagnostic status, no differences in connectivity emerged between EF subgroups (within-network: FWE-corrected p's > 0.25, between-network: FWE-corrected p's > 0.47).

    “Likewise, after controlling for diagnostic status, no differences in connectivity emerged (within-network: FWE-corrected p's > 0.25, between-network: FWE-corrected p's > 0.47).”
    Quote in the paperSubstantial claim
  • Findingown data

    No within- or between-network connectivity differences were found when comparing diagnostic groups (TD, ADHD, ASD; within-network: FWE-corrected p's > 0.26, between-network: FWE-corrected p's > 0.37).

    “No within- or between-network connectivity differences were found when comparing diagnostic groups (TD, ADHD, ASD; within-network: FWE-corrected p's > 0.26, between-network: FWE-corrected p's > 0.37).”
    • Also stated in: § Discussion · plain
      “Comparisons between traditional diagnostic categories (i.e., ASD, ADHD, and TD), which are based on observable symptoms according to DSM criteria, showed no differences in within- or between-network functional connectivity of the FPN, SN or DMN.”
    Quote in the paperSubstantial claim
  • Findingown data

    The present study observed no differences in functional connectivity between EF subgroups.

    “Contrary to our hypotheses, we observed no differences in functional connectivity between these subgroups”
    • Also stated in: § Discussion · plain
      “we found that EF subgroups could not be distinguished based on within- or between-network connectivity metrics of major cognitive networks”
    Quote in the paperSubstantial claim
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    Findingown data

    When diagnostic groups were broken down according to comorbidity (TD, ADHD [without ASD], ASD [without ADHD], ASD + ADHD), F-tests revealed no group differences in within-network (FWE-corrected p's > 0.30) or between-network connectivity (FWE-corrected p's > 0.14).

    “When diagnostic groups were broken down according to comorbidity (TD, ADHD [without ASD], ASD [without ADHD], ASD + ADHD), F-tests revealed no group differences in within-network (FWE-corrected p's > 0.30) or between-network connectivity (FWE-corrected p's > 0.14).”
    Quote in the paperSubstantial claim

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    Findingown data

    F-tests revealed no significant differences between EF subgroups in within-network nor between-network connectivity (within-network: FWE-corrected p's > 0.24, between-network: FWE-corrected p's > 0.29).

    “F-tests revealed no significant differences between EF subgroups in within-network nor between-network connectivity (within-network: FWE-corrected p's > 0.24, between-network: FWE-corrected p's > 0.29).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Individual differences among children within a DSM diagnostic category are increasingly recognized across the biological psychiatry field, with recent calls to account for this variability in research studies.

    “Individual differences among children within a DSM diagnostic category are increasingly recognized across the biological psychiatry field, with recent calls to account for this variability in research studies (Ameis, 2017; Corbett et al., 2009).”
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    Premisecitation

    Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals.

    “Current diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals.”
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    • cites American Psychiatric Association, 2013

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    • cites Ameis, 2017 source

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    Premisecitation

    Lack of reproducible findings across studies may be the result of low sample sizes, inflated false-positive rates due to analytic choices, and heterogeneity inherent to groups of interest.

    “The neuroscience field is becoming increasingly aware of the lack of reproducible findings across studies, which may be the result of low sample sizes, inflated false-positive rates due to analytic choices, and heterogeneity inherent to groups of interest (Poldrack et al., 2017).”
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    Premisecitation

    ASD and ADHD exhibit shared deficits in executive function and associated functional brain alterations.

    “These disorders exhibit shared deficits in executive function (Leno et al., 2017) and associated functional brain alterations (Di Martino et al., 2013; Chantiluke et al., 2014)”
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    Premisecitation

    Few neuroimaging studies have directly compared functional network connectivity of children with ASD and ADHD, resulting in inconclusive findings of both common and distinct network alterations across case-control studies.

    “Few neuroimaging studies have directly compared functional network connectivity of children with ASD and ADHD, resulting in inconclusive findings of both common and distinct network alterations across case-control studies (Di Martino et al., 2013; Christakou et al., 2013).”
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    Premisecitation

    The field is calling for a focus on replication studies using adequately powered samples.

    “In response, the field is calling for a focus on replication studies using adequately powered samples (Fletcher and Grafton, 2013).”
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    Premisecitation

    Although ADHD has three DSM-defined subgroups (Inattentive, Hyperactive/Impulsive, and Combined), these are currently inadequate to capture the full range of symptoms or to predict treatment response.

    “Although ADHD has three DSM-defined subgroups (Inattentive, Hyperactive/Impulsive, and Combined), these are currently inadequate to capture the full range of symptoms (Lee et al., 2014) or to predict treatment response (Mueller et al., 2017).”
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    Premisecitation

    The NIH has proposed the RDoC framework, which advocates for revisions to diagnostic systems that define neurobiologically separable categories for mental health disorders.

    “The NIH has proposed the Research Domain Criteria (RDoC) framework, which instead advocates for revisions to diagnostic systems that define neurobiologically separable categories for mental health disorders (Insel et al., 2010).”
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    Premisecitation

    ASD and ADHD are behaviorally heterogeneous, prevalent neurodevelopmental disorders currently defined by a symptom-based classification.

    “Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are behaviorally heterogeneous, prevalent neurodevelopmental disorders that are currently defined by a symptom-based classification (American Psychiatric Association, 2013)”
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    Premisecitation

    Studies of children with ADHD appear to be more consistent than studies of ASD.

    “although studies of children with ADHD appear to be more consistent than studies of ASD (Castellanos and Aoki, 2016).”
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    Premisecitation

    Children with ASD and comorbid ADHD exhibit functional brain network abnormalities that resemble alterations in children with ASD (without ADHD) and ADHD (without ASD) plus unique abnormalities specific to comorbidity between ASD and ADHD.

    “These studies demonstrated that children with ASD and comorbid ADHD exhibit functional brain network abnormalities that resemble alterations in children with ASD (without ADHD) and ADHD (without ASD) plus unique abnormalities specific to comorbidity between ASD and ADHD (Di Martino et al., 2013; Chantiluke et al., 2014).”
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    Interpretationcitation

    Some brain network findings may be nonspecific across ASD and ADHD, and some may only hold for subgroups within a disorder (e.g., a comorbid group).

    “These prior results suggest that some brain network findings may be nonspecific across ASD and ADHD, and some may only hold for subgroups within a disorder (e.g., a comorbid group).”
    Quote in the paperSubstantial claim

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    Premisecitation

    Both hyperconnectivity and hypoconnectivity have been reported in children with ADHD and ASD.

    “Both hyperconnectivity (Uddin et al., 2013; de Celis et al., 2014) and hypoconnectivity (Bos et al., 2014; Yoo et al., 2017) have been reported in children with ADHD and ASD.”
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    • cites Uddin et al., 2013 source

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    • cites de Celis et al., 2014

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    Premisecitation

    There is considerable overlap in both phenotypic and biological alterations in ASD and ADHD, one of the most striking similarities being common difficulties in executive function.

    “In addition to high levels of within-group variability, there is considerable overlap in both phenotypic and biological alterations in ASD and ADHD, one of the most striking similarities being common difficulties in executive function (Corbett et al., 2009).”
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    Study design and conductreasoning

    In the diagnostic comorbid sample, groups did not differ in age, sex, handedness, or head motion, but were unable to match on FSIQ (p<.001).

    “Groups did not differ in age, sex, handedness, or head motion (Table S1). Due to sample size limitations, we were unable to match the diagnostic comorbid samples on FSIQ (p < .001).”
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    Interpretationcitation

    Defining subgroups solely within a single disorder is inadequate; subgroups should cut across disorders.

    “This finding highlights the inadequacy of defining subgroups solely within a single disorder, and instead calls for the definition of subgroups that may cut across disorders.”
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    Study design and conductown data

    The diagnostic comorbid sample (N=88, group size 22) was adequately powered to detect a large effect (alpha=0.05, f=0.4, power=88%), but not medium (46%) or small effects (10%).

    “Due to sample size limitations, group size for this analysis was limited to 22 (N = 88, ‘Diagnostic comorbid sample’), but this design was still adequately powered to detect a large effect (alpha = 0.05, f = 0.4, power = 88%). It was not adequately powered to detect medium (46%) or small effects (10%).”
    Quote in the paperSubstantial claim

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    Premisecitation

    Both hyperconnectivity and hypoconnectivity have been reported in ADHD for the FPN and the DMN.

    “For example, both hyperconnectivity (de Celis et al., 2014) and hypoconnectivity (Yoo et al., 2017) have been reported in ADHD for the FPN and the DMN.”
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    Study design and conductcitation

    ASD community diagnoses were confirmed with ADOS-G or ADOS-2 and ADI-R.

    “Community diagnoses of ASD were confirmed with the Autism Diagnostic Observation Schedule (ADOS-G, Lord et al., 2000, or ADOS-2, Lord et al., 2012, based on study enrollment date) and Autism Diagnostic Interview-Revised (ADI-R, Rutter et al., 2005).”
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    Interpretationown data

    Executive function subgroups displayed limited differences in functional connectivity of major cognitive networks, suggesting that a categorical nosology based solely on behavioral features may not map onto differences in functional connectivity.

    “Unpredictably, executive function subgroups displayed limited differences in functional connectivity of major cognitive networks, suggesting that a categorical nosology based solely on behavioral features may not map onto differences in functional connectivity.”
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    Study design and conductcitation

    Motion-related signals were removed using ICA-AROMA.

    “In addition, a state-of-the-art ICA-based denoising procedure (ICA-AROMA, Pruim et al., 2015) was used to remove motion-related artifacts in native space”
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    Study design and conductcitation

    Significance was determined using a threshold-free cluster enhancement of p < .05 (FWE-corrected) for both within- and between-network analyses.

    “Significance was determined using a threshold-free cluster enhancement of p < .05 (FWE-corrected) for both within- and between-network analyses, as in previous studies (Uddin et al., 2013; Nomi and Uddin, 2015).”
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    Premisecitation

    Three executive function subgroups emerged, with "above average," "average," and "impaired" executive functions, which crossed traditional diagnostic boundaries.

    “Three subgroups emerged, with “above average,” “average,” and “impaired” executive functions, which crossed traditional diagnostic boundaries.”
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    Study design and conductown data

    The diagnostic group sample design was adequately powered to detect a large effect for a one-way ANOVA (alpha=0.05, f=0.4, power=99%), but underpowered to detect medium (power=71%) and small effects (power=16%).

    “This design was adequately powered to detect a large effect for a one-way ANOVA (alpha = 0.05, f = 0.4, power = 99%). We were underpowered to detect medium (power = 71%) and small effects (power = 16%).”
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    Study design and conductcitation

    ADHD community diagnoses were confirmed with DICA-IV, CPRS, and ADHD Rating Scale IV.

    “The Diagnostic Interview for Children and Adolescents IV (Reich et al., 1997) was used to confirm community ADHD diagnoses, determine whether children with ASD had comorbid ADHD, and for exclusionary purposes. Community diagnoses of ADHD were also confirmed with the Conners' Parent Rating Scales (CPRS-R:L, Conners, 1997, or CPRS-3, Conners, 2008, based on study enrollment date) and the ADHD Rating”
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    Study design and conductown data

    Diagnostic groups did not differ in age, sex, handedness, FSIQ, or head motion.

    “Diagnostic groups did not differ in age, sex, handedness, FSIQ, or head motion (mean framewise displacement [FD (Power et al., 2012)], translational and rotational motion, Table 2).”
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    • cites Power et al., 2012 source

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    Study design and conductown data

    EF subgroups did not differ in age, sex, handedness or mean head motion, but did differ on FSIQ (p<.001) and reached a near-significant difference in mean FD for the raw data (p=.06); following preprocessing, there were no group differences in mean FD (p=.36).

    “EF subgroups did not differ in age, sex, handedness or mean head motion, but did differ on FSIQ (p < .001) and reached a near-significant difference in mean FD for the raw data (p = .06, Table S2). Following preprocessing, there were no group differences in mean FD (p = .36, Fig. 1).”
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    Study design and conductnone given

    The EF subgroup sample was representative of the Dajani et al. (2016) sample in EF scores, age, FSIQ and the distribution of diagnostic categories within each EF subgroup.

    “The ‘EF subgroup sample’ was representative of the Dajani et al. (2016) sample in EF scores, age, FSIQ and the distribution of diagnostic categories within each EF subgroup.”
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    Study design and conductnone given

    Participants with excessive in-scanner motion (>5 mm absolute maximum motion) were excluded.

    “Participants with excessive in-scanner motion (> 5 mm of absolute maximum motion) were excluded from the study.”
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    Interpretationreasoning

    Although results are not consistent across studies, they clearly demonstrate that positive results are possible when using ICA dual-regression to investigate network integrity in children with ASD and ADHD, ruling out the possibility that previously reported network connectivity differences in ASD and ADHD are method-specific.

    “Although results are not consistent across studies, they clearly demonstrate that positive results are possible when using ICA dual-regression to investigate network integrity in children with ASD and ADHD, ruling out the possibility that previously reported network connectivity differences in ASD and ADHD are method-specific.”
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    Interpretationreasoning

    These results do not preclude the existence of small- to medium-sized differences in functional connectivity between groups, but it is unclear whether such differences can contribute to the identification of sensitive and specific diagnostic biomarkers for ASD and ADHD.

    “These results do not preclude the existence of small- to medium-sized differences in functional connectivity between groups, but is unclear whether such differences can contribute to the identification of sensitive and specific diagnostic biomarkers for ASD and ADHD.”
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    Study design and conductcitation

    Executive functions used for latent profile analysis were measured primarily with parent-report BRIEF, plus NEPSY-II Statue and WISC-IV backward digit span.

    “Executive functions used for the latent profile analysis were measured primarily with a parent-report (eight subscales of the BRIEF, Gioia et al., 2000), in addition to two laboratory measures, the Statue subscale of the NEPSY-II (Korkman et al., 2007) and the backward digit span of the WISC-IV.”
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    Premisecitation

    Children with "pure" ASD and ADHD exhibited little to no disorder-specific functional alterations during a temporal discounting task, whereas the comorbid group exhibited pronounced functional differences compared with all other groups.

    “Importantly, Chantiluke et al. (2014) showed that children with “pure” ASD and ADHD exhibited little to no disorder-specific functional alterations during a temporal discounting task, whereas the comorbid group exhibited pronounced functional differences compared with all other groups (Chantiluke et al., 2014).”
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    Premisecitation

    Recent evidence has emerged for neurobiological subgroups of ADHD based on network connectivity of the reward system and other large-scale brain networks.

    “Recent evidence has also emerged for neurobiological subgroups of ADHD based on network connectivity of the reward system (Costa Dias et al., 2015) and other large-scale brain networks (Gates et al., 2014).”
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    Interpretationreasoning

    Two factors may be contributing to the limited separability of ASD and ADHD categories based on functional connectivity indices: high within-category heterogeneity and high between-category similarity.

    “Two factors may be contributing to the limited separability of ASD and ADHD categories based on functional connectivity indices: high within-category heterogeneity and high between-category similarity.”
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    Interpretationnone given

    The current study is one of the first functional neuroimaging studies to directly compare children with ASD, ADHD, comorbid ASD and ADHD, and TD children, and the first to do so using ICA dual regression combined with ICA-AROMA.

    “The current study is one of the first functional neuroimaging studies to directly compare children with ASD, ADHD, comorbid ASD and ADHD, and TD children, and the first to do so using ICA dual regression combined with ICA-AROMA.”
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    Premisecitation

    Varying types of functional network miswirings across development may manifest as a singular phenotype, suggesting that distinct brain abnormalities may appear behaviorally as the same neurodevelopmental disorder.

    “Varying types of functional network miswirings across development may manifest as a singular phenotype (Di Martino et al., 2014b), suggesting that distinct brain abnormalities may appear behaviorally as the same neurodevelopmental disorder.”
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    • cites Di Martino et al., 2014b

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    Premisecitation

    Similar trends are evident for understanding the impact of medication status on case-control neuroimaging studies.

    “Similar trends are evident for understanding the impact of medication status on case-control neuroimaging studies (Hull et al., 2016; Rubia, 2018; Rubia et al., 2014).”
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    Interpretationreasoning

    The choice to focus on a parent-report of behavior to characterize psychiatric disorders may be many steps removed from underlying large-scale brain network integrity.

    “the choice to focus on a parent-report of behavior to characterize psychiatric disorders may be many steps removed from underlying large-scale brain network integrity.”
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    Premisecitation

    A recent review of classification studies of ASD and ADHD using neuroimaging techniques suggested that heterogeneity within and between disorders may be limiting researchers' ability to distinguish disorders based on neurobiology.

    “Further, a recent review of classification studies of ASD and ADHD using neuroimaging techniques suggested that heterogeneity within and between disorders may be limiting researchers' (and machines') ability to distinguish disorders based on neurobiology (Uddin et al., 2017).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Uddin et al., 2017 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    This leads to inherent heterogeneity in clinical groups studied, likely leading to inconsistencies in findings across the neuroimaging literature.

    “This leads to inherent heterogeneity in clinical groups studied, likely leading to inconsistencies in findings across the neuroimaging literature.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Few neuroimaging studies consider the impact of comorbid ASD and ADHD on case-control findings, and instead rely on the primary diagnosis of children to classify patients.

  • May combine two claims.

    Interpretationcitation

    The present results and previous research comport with the idea that these traditional diagnostic categories are not neurobiologically separable, which contributes to their poor prediction of treatment response or prognosis.

    “The present results and previous research comport with the idea that these traditional diagnostic categories are not neurobiologically separable, which contributes to their poor prediction of treatment response or prognosis (Cuthbert, 2014).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Cuthbert, 2014 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationcitation

    Another possible explanation for the null EF subgroup result is that EF in children may be best assessed dimensionally rather than categorically.

    “Another possible explanation for this null result is that EF in children may be best assessed dimensionally rather than categorically (Barch, 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Barch, 2017 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    There is substantial overlap in ASD and ADHD categories in symptomatology, behavioral domains beyond symptoms, and genetic factors, in addition to high rates of comorbidity between ASD and ADHD.

    “In addition, there is substantial overlap in ASD and ADHD categories in symptomatology (e.g., social skills deficits), behavioral domains beyond symptoms (e.g., executive dysfunction), and genetic factors (Rommelse et al., 2010) in addition to high rates of comorbidity between ASD and ADHD.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Rommelse et al., 2010 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Recent studies have revealed the importance of testing whether categorical, dimensional, and hybrid categorical-dimensional models best describe psychiatric disorders.

    “In characterizing neurodevelopmental and psychiatric disorders, recent studies have revealed the importance of testing whether categorical, dimensional, and hybrid categorical-dimensional models best describe psychiatric disorders (Barch, 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Barch, 2017 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Research into the impact of IQ levels on neuroimaging results are only beginning to emerge for the ASD literature and are virtually absent in the ADHD literature.

    “Research into the impact of IQ levels on neuroimaging results are only beginning to emerge for the ASD literature (Reiter et al., 2019) and are virtually absent in the ADHD literature, where it is commonplace to forgo group matching on IQ (Choi et al., 2013).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Reiter et al., 2019

      Not checked in the free run.

    • cites Choi et al., 2013 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    It is commonplace to forgo group matching on IQ in the ADHD literature.

    “where it is commonplace to forgo group matching on IQ (Choi et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Choi et al., 2013 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    The null result for EF subgroups does not preclude the possibility that EF groups may be separable based on functional networks not examined here or structural neuroimaging metrics.

    “This null result does not preclude the possibility that EF groups may be separable based on functional networks not examined here (e.g., sensory or subcortical networks) or structural neuroimaging metrics.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In general, comorbidity tends to correlate with greater symptom severity and disability.

    “In general, comorbidity tends to correlate with greater symptom severity and disability (Lai et al., 2014).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Lai et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories, limiting their utility in predicting prognosis and efficacious treatments.

    “suggesting that nosologies reliant on behavioral data alone may not lead to discovery of neurobiologically distinct categories, limiting their utility in predicting prognosis and efficacious treatments.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductcitation

    The length of the timeseries of individuals' resting-state data (5 min) may not have been long enough to generate reliable indices of functional connectivity, possibly leading to null differences between groups.

    “Although our sample was adequately powered to detect large group differences in functional connectivity, it is possible that the length of the timeseries of individuals' resting-state data (5 min) was not long enough to generate reliable indices of functional connectivity (Birn et al., 2013), possibly leading to null differences between groups.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Birn et al., 2013 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    One alternative explanation for the finding of no group differences in functional network integrity between EF subgroups is that another RDoC domain, such as social communication, may be better suited for developing an alternative nosology for children with neurodevelopmental disorders.

    “One alternative explanation for our finding of no group differences in functional network integrity between EF subgroups is that another RDoC domain, such as social communication, may be better suited for developing an alternative nosology for children with neurodevelopmental disorders.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Premisecitation

    Applying principles of computational psychiatry to clinical research has the potential to transform the mental health field from the current trial-and-error choice of treatments towards precision medicine.

    “Applying principles of computational psychiatry to clinical research has the potential to transform the mental health field from the current trial-and-error choice of treatments towards precision medicine (Haker et al., 2016).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Haker et al., 2016 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Current psychiatric diagnostic systems rely on observable behaviors to classify disease, with unknown links to underlying neurobiology.

    “Current psychiatric diagnostic systems rely on observable behaviors to classify disease, with unknown links to underlying neurobiology (Huys et al., 2016).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Huys et al., 2016 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning

    Advances in mental health research necessarily rely on characterizing underlying neurobiological mechanisms of pathophysiology, and psychiatry may be fundamentally limited as long as assessments are limited to observable phenomena.

    “This suggests that advances in mental health research necessarily rely on characterizing underlying neurobiological mechanisms of pathophysiology, and that psychiatry may be fundamentally limited as long as assessments are limited to observable phenomena (Pine, 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Pine, 2017 source

      Not checked in the free run.

57 of 57

  • The paper relies on this without support.

    Low sample sizes contribute to reduced power to detect true results.

    “It is well established that low sample sizes contribute to reduced power to detect true results.”

  • The paper relies on this without support.

    Past results are inconsistent across studies.

    “in combination with the fact that past results are inconsistent across studies”

  • The paper relies on this without support.

    ICA-AROMA reduces the likelihood of group differences emerging solely due to differences in in-scanner motion.

    “ICA-AROMA is a denoising approach that reduces the likelihood of group differences emerging solely due to differences in in-scanner motion.”

  • The paper relies on this without support.

    Few neuroimaging studies consider the impact of comorbid ASD and ADHD on case-control findings, and instead rely on the primary diagnosis of children to classify patients.

    “Few neuroimaging studies consider the impact of comorbid ASD and ADHD on case-control findings, and instead rely on the primary diagnosis of children to classify patients.”
4 of 4

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • ConsistentF(1, 332) = 25.36reported p < .001 · recomputed p < .001

    “F(1, 332) = 25.36, p < .001”

1 of 1

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

  • Incorrect percentage for ADHD participants with a secondary diagnosis

    Minor

    The table lists 24 of 53 ADHD participants as having a secondary diagnosis, which is 45.3%, not 44.4%.

    Reported 44.4 · recomputed 45.283019

  • Incorrect percentage for TD participants with a secondary diagnosis

    Minor

    The table lists 2 of 59 TD participants as having a secondary diagnosis, which is 3.4%, not 3.2%.

    Reported 3.2 · recomputed 3.389831

2 of 2

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. DuPaul, 1998, vol. 25

Cited by

Sorted by citations

Related

Authors
Dajani, D. R., Burrows, C. A., Odriozola, P., Baez, A., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q.
Affiliations
  • University of Miami (US)
  • University of Minnesota (US)
  • Yale University (US)
  • Kennedy Krieger Institute (US)
Corresponding author
Dajani, Dina R.
ORCID
Venue
NeuroImage: Clinical
Publisher
Elsevier BV
Published
2019
Volume
21
Pages
101678
ISSN
2213-1582 (ISSN-L)
DOI
10.1016/j.nicl.2019.101678
PMC
PMC6356009
OpenAlex
W2952027690
Semantic Scholar
acd0a6811e75541f9e63dc8573e23a348fc1f24c
Cited by
33
References
88
Citations by year
2025: 2 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 8 · 2020: 9 · 2019: 2
FWCI
3.20
Type
journal article
Language
en
Open access
Licence
Locations
  • NeuroImage Clinical (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Institute of Mental Health (R01MH107549)
  • National Institutes of Health (R01 MH085328, R01NS048527, R01 MH078160)
  • Autism Speaks
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
Keywords
neurodevelopmental disorders, autism spectrum disorder, attention deficit hyperactivity disorder, functional connectivity, executive function, comorbidities, children, resting-state fMRI, independent component analysis, dual regression
MeSH terms
Autism Spectrum Disorder, Adolescent, Brain, Child, Female, Humans, Magnetic Resonance Imaging, Male, Neural Pathways, Executive Function, Neurodevelopmental Disorders

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

Statistics and arithmetic are recomputed, not judged.

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