The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index; 9 of the 25 sources its claims cite were checked for support.
Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD
Open accessAbstract
Research and clinical investigations in psychiatry largely rely on the de facto assumption that the diagnostic categories identified in the Diagnostic and Statistical Manual (DSM) represent homogeneous syndromes. However, the mechanistic heterogeneity that potentially underlies the existing classification scheme might limit discovery of etiology for most developmental psychiatric disorders. Another, perhaps less palpable, reality may also be interfering with progress-heterogeneity in typically developing populations. In this report we attempt to clarify neuropsychological heterogeneity in a large dataset of typically developing youth and youth with attention deficit/hyperactivity disorder (ADHD), using graph theory and community detection. We sought to determine whether data-driven neuropsychological subtypes could be discerned in children with and without the disorder. Because individual classification is the sine qua non for eventual clinical translation, we also apply support vector machine-based multivariate pattern analysis to identify how well ADHD status in individual children can be identified as defined by the community detection delineated subtypes. The analysis yielded several unique, but similar subtypes across both populations. Just as importantly, comparing typically developing children with ADHD children within each of these distinct subgroups increased diagnostic accuracy. Two important principles were identified that have the potential to advance our understanding of typical development and developmental neuropsychiatric disorders. The first tenet suggests that typically developing children can be classified into distinct neuropsychological subgroups with high precision. The second tenet proposes that some of the heterogeneity in individuals with ADHD might be "nested" in this normal variation.
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32 Own result · 12 Own interpretation · 6 No full text of the sources · 4 Partly supported · 4 Own method · 3 Supported · 2 Not checked yet · 1 Supported so far · 1 Sources not found · accuracy not yet measured
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In the paper
“Independently applying the community detection algorithm to the ADHD cohort shows similar findings to those in A.”
- Also stated in: § Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup · plain
“independently applying Newman's community detection algorithm (29) on the ADHD cohort replicated this finding, showing similar subgroup patterns (Fig. 4).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Partly supportedcites [29] 29. Newman ME (2006) Modularity and community structure in networks. Proc Natl Acad Sci USA 103:8577-8582. sourceExperimental — accuracy not yet measured
The method of optimal modularity (p. 2) describes the paper’s community-detection algorithm, supporting the methodological part of the sentence. The paper does not report an ADHD cohort or a comparison with typically developing subgroups, so it does not support the claimed replication of findings. (LLM, conf=0.84)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Also stated in: § Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup · plain
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In the paper
“Although common practice would expect this investigation to yield one unitary group, the analysis instead yielded four unique communities or subgroups (Fig. 4).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Importantly, despite these highly reliable differences, the SVM classifier was unable to make strong distinctions in individual cases with regard to ADHD status (65% accuracy, 86.3% sensitivity, and 38.5% specificity).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
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In the paper
“Independently testing the community structure in this sample revealed similar findings, albeit via six groups (Fig. 4).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
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In the paper
“The third group (18% of sample) had relatively inaccurate temporal information processing (subgroup 3).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
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In the paper
“The second group (20% of sample) had reduced working memory, memory span, inhibition, and output speed (subgroup 2).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
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In the paper
“One group (43% of sample) appeared to have a pattern consistent with more response variability relative to their peers (subgroup 1).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
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In the paper
“Fit was satisfactory and comparable for the best-fitting five-, six-, and seven-factor models as follows: five-factor χ 2 (63) = 103.4,CFI = 0.98, TLI = 0.97, RMSEA = 0.036; six-factor χ 2 (58) = 95.1,CFI = 0.98, TLI = 0.98, RMSEA = 0.035; and seven-factor χ 2 (52) = 89.9,CFI = 0.98, TLI = 0.97, RMSEA = 0.038.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
plain- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The last group (18% of sample) had relatively weak signal detection, suggesting suboptimal or altered arousal (subgroup 4).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Results for the feature reduction for the neuropsychological measures showed that a one-factor model fit inadequately [χ 2 (70) = 386.2,CFI = 0.87, TLI = 0.84, RMSEA = 0.09], justifying our effort to create a multiconstruct model.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
plain- Asserted: passes — The authors put it forward as true.
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- It may state two separate claims as one. 17
- Probably not a substantial claim. 13
Every source the paper cites for this claim was checked and supports it.
In the paper
“whereas the comparison of the full ADHD and TDC cohort replicated previous findings in this regard (41), the comparisons based on community structure yielded only a subset of profiles with working memory and temporal information processing deficits.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup
What the sources say
- Supportedcites [41] 41. Martinussen R, Hayden J, Hogg-Johnson S, Tannock R (2005) A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disor- der. J Am Acad Child Adolesc Psychiatry 44:377-384. sourceExperimental — accuracy not yet measured
Martinussen et al. (2005) is cited for the previous finding of working-memory impairment in children with ADHD, not for the citing study’s community-based comparisons. A Semantic Scholar snippet from “Fronto-parietal white matter microstructure associated with working memory performance in children with ADHD” explicitly cites Martinussen et al. among meta-analyses finding poorer working memory in ADHD than in controls (score 0.632). The cited paper has no available paper-scoped full-text snippets, so this supports the historical comparison but cannot independently verify the citing study’s subset-of-profiles result. (LLM, conf=0.77)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Supported
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In the paper
“Rapid and sizeable changes in environmental demands across time may have served as the driving force toward multiple "peaks" with regard to neurocognitive strategies or profiles in typical populations (21,36), as found here.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Partly supportedcites [21] 21. Goldman D, Oroszi G, Ducci F (2005) The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532. sourceExperimental — accuracy not yet measured
The Genes and neurobiologies and ANTAGONISTS passages describe a proposed balance between cognitive performance and stress resilience, with selection maintaining two COMT alleles in human populations. They do not say that rapid, sizeable changes in environmental demands produced multiple peaks in neurocognitive profiles in typical populations. Page numbers are unavailable in our copy. (LLM, conf=0.82)
- Not checked — no full text of the sourcecites [36] 36. Nettle D (2006) The evolution of personality variation in humans and other animals. Am Psychol 61:622-631. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“With respect to our findings it should be noted that at times heritable diversity might form along a continuous dimension (i.e., unimodal distribution), whereas at others times it may form as multiple discrete strategies (i.e., multimodal distributions) (21,(36)(37)(38).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Partly supportedcites [21] 21. Goldman D, Oroszi G, Ducci F (2005) The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532. sourceExperimental — accuracy not yet measured
The RESILIENCY section discusses two possible genetic architectures for addiction vulnerability: many variants acting together and different individual variants sufficing in different people. It does not establish that heritable diversity forms a continuous, unimodal dimension or multiple discrete, multimodal strategies; those distributional claims go beyond the passage. (LLM, conf=0.72)
- Not checked — no full text of the sourcecites [36] 36. Nettle D (2006) The evolution of personality variation in humans and other animals. Am Psychol 61:622-631. source
- Not checked — no full text of the sourcecites [37] 37. Mier D, Kirsch P, Meyer-Lindenberg A (2010) Neural substrates of pleiotropic action of genetic variation in COMT: A meta-analysis. Mol Psychiatry 15:918-927. source
hedged- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Similar arguments have been made with regard to COMT and working memory, with an evolutionary trade-off between efficient working memory updating (val) and robust working memory maintenance (met) (22).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Supportedcites [22] 22. Braver TS, Cole MW, Yarkoni T (2010) Vive les differences! Individual variation in neural mechanisms of executive control. Curr Opin Neurobiol 20:242-250. source
In “The origins of individual differences variation: Genetics, environment, and neural mechanisms,” the paper explicitly describes a COMT val158met trade-off between efficient working-memory updating (val) and robust maintenance (met). It proposes that differing environmental contexts may have favored one variant or the other, matching the claim’s evolutionary framing. (LLM, conf=0.94)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“In this proposal each allele is maintained in the population because each provides an environment-specific selective advantage-one for cognitive efficiency under typical conditions and the other for emotional resilience under stressful circumstances (21,37).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Supportedcites [21] 21. Goldman D, Oroszi G, Ducci F (2005) The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532. source
The Genes and neurobiologies passage identifies a trade-off between stress resilience (Val158) and cognitive function (Met158). The continuation labeled ANTAGONISTS says the warrior/worrier model invokes balancing selection to conserve both alleles, with Val158 improving stress resilience but modestly reducing executive cognitive performance under most conditions. (LLM, conf=0.93)
- Not checked — no full text of the sourcecites [37] 37. Mier D, Kirsch P, Meyer-Lindenberg A (2010) Neural substrates of pleiotropic action of genetic variation in COMT: A meta-analysis. Mol Psychiatry 15:918-927. source
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although consensus remains elusive on defining specific personality or cognitive "types" (18,19), substantial evidence has accrued that individual differences in successful adaptive psychological styles are central to human development, functioning, social cohesion, and health outcomes (20)(21)(22)(23).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > psychiatric disorders | research domain criteria | cognition | modularity |
What the sources say
- Not checked — no full text of the sourcecites [20] 20. Buss DM (1991) Evolutionary personality psychology. Annu Rev Psychol 42:459-491. source
- Partly supportedcites [21] 21. Goldman D, Oroszi G, Ducci F (2005) The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532. sourceExperimental — accuracy not yet measured
The “Progress through intermediate phenotypes” section says behavioural control supports long-term behaviour and that deficits in children are linked to problems including substance use. This supports a narrower point about development and addiction risk, but the paper does not establish that adaptive psychological styles broadly determine human functioning, social cohesion, and health outcomes. Page numbers were not available in our copy. (LLM, conf=0.82)
- Partly supportedcites [22] 22. Braver TS, Cole MW, Yarkoni T (2010) Vive les differences! Individual variation in neural mechanisms of executive control. Curr Opin Neurobiol 20:242-250. sourceExperimental — accuracy not yet measured
The Abstract links individual differences in personality, emotion processing, and cognitive ability to executive control, and the Emotion regulation section discusses differences in regulation success and depression. These passages support a narrower claim about cognitive and emotional functioning, but do not establish that adaptive psychological styles are central to human development, social cohesion, or health outcomes broadly. Page numbers are unavailable in our copy. (LLM, conf=0.83)
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Probably not a substantial claim.
Every source the paper cites for this claim was checked and supports it.
In the paper
“some have recently argued that the single-nucleotide polymorphism (val158met) of the catechol O-methyltransferase (COMT) gene, which codes for an enzyme that degrades dopamine in prefrontal cortex, may relate to evolutionary trade-offs between efficient executive functioning (met) and improved emotional regulation (val) (21,”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Supportedcites [21] 21. Goldman D, Oroszi G, Ducci F (2005) The genetics of addictions: Uncovering the genes. Nat Rev Genet 6:521-532. source
The Genes and neurobiologies passage links Val158 to stress resiliency and Met158 to cognitive function. The continuation under ANTAGONISTS describes the warrior/worrier model as balancing selection that maintains both alleles, with Val158 associated with better stress resiliency but modestly diminished executive performance. (LLM, conf=0.94)
hedgedconditional- Asserted: fails — The authors may not put it forward as true.
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Probably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These groups show minimal differences in intelligence quotient (IQ), age, or sex ratios (with one exception, see Tables S4 and S5).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
plainn = 4- Asserted: passes — The authors put it forward as true.
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In the paper
“Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.”
- Also stated in: § Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles. · plain
“Whereas the ANOVA in six of the seven factors showed a main effect of diagnosis, the post hoc comparisons showed that not all subgroups had the same atypical neuropsychological scores.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Also stated in: § Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles. · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Group 4A had the maximal improvement at 84.1% classification of ADHD vs. TCD youth (83.3% sensitivity and 84.6% specificity).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“The remaining groups were as follows: group 1, 68% total, 49.2% sensitivity, 80.4% specificity; group 2A, 68.5%, 83.7%, 51.2%; group 2B, 64.7%, 80.4%, 44.2%; group 3, 73.6%, 88.73%, 46.2%; group 4A, 84.1%, 83.3%, 84.6%; and group 4B, 61.9%, 37%, 76.9%.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“This procedure left us with four groups, which we label as follows: a variability group (subgroup 1), a low executive group (subgroup 2), a low temporal information processing group (subgroup 3), and a low arousal group (subgroup 4).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Among ADHD subgroups, atypical inhibitory control, speed, and working memory were each found in three groups.Atypical arousal and span were each identified in two groups.Atypical response variability and temporal information priming were each found in four groups.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Classification generally was quite respectable across the groups with 78% accuracy for the TDC population (subgroup 1, 93%; subgroup 2, 71%; subgroup 3, 71%; subgroup 4, 81.25%) and 77% accuracy for the ADHD population (subgroup 1, 78%; subgroup 2A, 75%; subgroup 2B, 66.25%; subgroup 3, 77%; subgroup 4A, 88%; note that subgroup 4B was unable to be examined as it was not reproduced in large enough”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > SVM-Based MVPA Highlights the Robustness of the Community
plain- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The difference between the two appears to be split in subgroup 2 and subgroup 4.”
- Also stated in: § Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup · plain
“The main deviation from the finding in TDC was the revelation of an additional low arousal group (subgroup 4B) and an additional low executive group (subgroup 2B).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Also stated in: § Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This analysis shows that despite traditional assumptions that nonclinical control populations are uniform entities, our results fit better with the alternative supposition that there are unique neuropsychological profiles even in typically developing, well-adjusted samples.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Results
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It may be that identifying a mechanism associated with a mental disorder requires comparing individuals to well-adjusted persons with the same cognitive style or profile.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > psychiatric disorders | research domain criteria | cognition | modularity |
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“The modeling literature related to adaptive complex social systems also provides significant evidence that suggests psychological heterogeneity is an important means by which to improve the robustness of the collective when faced with shifting environmental demands (35).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Not checked yetcites [35] 35. Miller JH, Page SE (2007) Complex Adaptive Systems: An Introduction to Computa- tional Models of Social Life (Princeton Univ Press, Princeton).
hedgeddirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the approach used here is not limited to the study of ADHD, but could be used to inform heterogeneity and perhaps etiology in other developmental or adult neuropsychiatric disorders, and thus has broad appeal.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Current Approach Can Be Extended Across Multiple Modalities for
hedgedconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“poor response inhibition has been suggested to be a critical component of ADHD (39) and has been well established at the group level (40).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Patterns in ADHD Are Specific to Subgroup
What the sources say
- Not checked — no full text of the sourcecites [39] 39. Barkley RA (1997) Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychol Bull 121:65-94. source
- Not checked — no full text of the sourcecites [40] 40. Willcutt EG, et al. (2010) Etiology and neuropsychology of comorbidity between RD and ADHD: The case for multiple-deficit models. Cortex 46(10):1345-1361. source
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In other words, whereas numerous unique neuropsychological measures have been proposed as related to ADHD, perhaps each of them applies to only a subset of those subjects with the disorder.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > psychiatric disorders | research domain criteria | cognition | modularity |
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“the robustness of the identified communities was tested in several ways (e.g., Figs.S2 and S3), indicating that the group assignments identified here are highly deviant from random.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Individual Classification Based on Neuropsychological Measures
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It might be reasoned that the discrete subgroups observed here (Figs. 3 and 4) are a small representation of similar forms of neuropsychological diversity.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“It is a key feature in the stability of complex social systems and thus has likely been an important attribute of our evolving species.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
What the sources say
- Not checked yetcites [35] 35. Miller JH, Page SE (2007) Complex Adaptive Systems: An Introduction to Computa- tional Models of Social Life (Princeton Univ Press, Princeton).
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The mechanistic heterogeneity that potentially underlies the existing classification scheme might be limiting our ability to clarify etiology and identify novel therapeutics for several psychiatric illnesses (3).”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > psychiatric disorders | research domain criteria | cognition | modularity |
What the sources say
- Not checked — no full text of the sourcecites [3] 3. Agid Y, et al. (2007) How can drug discovery for psychiatric disorders be improved? Nat Rev Drug Discov 6:189-201. source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper relies on this without support.
The 498 children in the dataset are representative of typically developing youth and youth with ADHD.
“For the current investigation we apply community detection to a well-characterized dataset of 498 children who include both typically developing control youth (TDC) (n = 213) and youth with ADHD (n = 285) (Table S1).”
The paper relies on this without support.
The 20 neuropsychological measures used are valid indicators of the cognitive functions they are intended to assess.
“From these youth, some 20 neuropsychological measures were obtained that were intended to cover a wide domain of cognitive functions variously theorized to be involved in ADHD (Table S2 and Fig. 2).”
The paper relies on this without support.
The typically developing and ADHD cohorts studied are representative of their respective populations, so that the observed subgroups reflect the broader population's neuropsychological variation.
“Children who completed a full research psychiatric evaluation aged 6-17 y participated in this study (TDC, n = 213; ADHD, n = 285) (SI Text).”
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Working memory impairments are reported in 30% to 37% (Coghill et al., 2014; Fair et al., 2012), and inhibitory control deficits are detected in 21%–46% of pediatric ADHD cases (Coghill et al., 2014; Nigg et al., 2005; Solanto et al., 2001; Sonuga-Barke et al., 2010).”
From Executive Functioning Heterogeneity in Pediatric ADHD (2019) · cites this paper as Fair et al., 2012
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“estimates for the proportion of pediatric ADHD cases who exhibit any form of executive dysfunction range from 21% to 60% across studies employing a wide range of tasks and impairment criteria (Biederman et al., 2004; Coghill et al., 2014; Fair, Bathula, Nikolas, & Nigg, 2012; Geurts, van der Oord, & Crone, 2006; Nigg et al., 2005; Solanto et al., 2001; Sonuga-Barke, Bitsalou, & Thompson, 2010).”
From Executive Functioning Heterogeneity in Pediatric ADHD (2019) · cites this paper as Fair, Bathula, Nikolas, & Nigg, 2012
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Applying the construct specificity concerns raised by Sonuga-Barke et al. (2008) and Snyder et al. (2015) to evaluate the tests used to evaluate neuropsychological heterogeneity in ADHD indicates that, to our knowledge, 100% of the available literature either omitted tests of working memory or measured working memory using at least one test with poor construct specificity (Biederman et al., 2004;”
From Executive Functioning Heterogeneity in Pediatric ADHD (2019) · cites this paper as Fair et al., 2012
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Four cognitive ADHD subtypes were revealed in a study based on a community of children with or without ADHD 70 ; however, whether these subtypes predict treatment response or course remains unclear.”
From Attention-deficit/hyperactivity disorder (2015) · cites this paper as [70]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“however, even within the same subtype, variations in clinical presentation are remarkable, and variations in etiology and pathophysiology are expected (Fair et al., 2012, Karalunas et al., 2015, Nigg et al., 2005).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The etiological heterogeneity in terms of the biological and environmental factors is likely reflected in variation in neural correlates (Nigg and Casey, 2005; Mackie et al., 2007; Fair et al., 2012; Costa Dias et al., 2013, 2015; Karalunas et al., 2014), and results in the diverse cognitive and behavioral profiles and developmental trajectories of the disorder (Halperin and Schulz, 2006; Rajendr”
From A Review of Heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD) (2019) · cites this paper as Fair et al., 2012
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Indeed, community detection of performance measures in ADHD did not yield subgroups separated by inhibition and working memory problems (Fair et al., 2012), as observed here.”
From Data‐driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders (2020) · cites this paper as Fair et al., 2012
The cited source says what the claim attributes to it.
In the citing paper
“Working memory impairments are reported in 30% to 37% (Coghill et al., 2014; Fair et al., 2012)”
From Executive Functioning Heterogeneity in Pediatric ADHD (2019) · cites this paper as Fair et al., 2012
The cited source says what the claim attributes to it.
In the citing paper
“Given that only a subset of children with ADHD meets criteria for an executive function deficit [16-23]”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“visuospatial WM deficits on group-level are probably carried by only a subset of children with ADHD [16].”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
The cited source says what the claim attributes to it.
In the citing paper
“recent findings suggest that ADHD is a neuropsychologically heterogeneous disorder that probably is not characterized by any single core dysfunction [16-19].”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
The cited source says what the claim attributes to it.
In the citing paper
“However, at the same time, these results support models and previous findings which suggest that ADHD is a neuropsychologically heterogeneous disorder that cannot be characterized by a single core dysfunction [16-22, 25].”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
The cited source says what the claim attributes to it.
In the citing paper
“This suggests that the neuropsychological heterogeneity in ADHD may be a derivative of normal variation”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
The cited source says what the claim attributes to it.
In the citing paper
“supports recent evidence suggesting separable neuropsychological subtypes in ADHD [e.g., 16, 19, 23]”
From Prevalence and diagnostic validity of motivational impairments and deficits in visuospatial short-term memory and working memory in ADHD subtypes (2015) · cites this paper as [16]
The cited source says what the claim attributes to it.
In the citing paper
“Other domains impaired in ADHD include temporal information processing and timing 67 ; speech and language 68 ; memory span, processing speed and response time variability 69 ; arousal and activation 70 ; and motor control 71 .”
From Attention-deficit/hyperactivity disorder (2015) · cites this paper as [70]
The cited source says what the claim attributes to it.
In the citing paper
“This particular finding is similar in theme to that of previous reports (Fair et al., 2012, Gates et al., 2014).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“While effects were relatively consistent across formulations of ADHD here, ADHD is likely to be heterogeneous with regard to mediating cognitive mechanisms64,65 as well as with regard to comorbidity, severity, clinical course, temporal variation, environmental exposures, and probably genetic variation.”
From Working Memory and Vigilance as Multivariate Endophenotypes Related to Common Genetic Risk for Attention-Deficit/Hyperactivity Disorder (2018) · cites this paper as [65]
In the citing paper
“Heterogeneity limits our ability to identify the underlying neurobiology of ADHD.”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“Findings from these studies suggest that identifying mechanistic subpopulations across ADHD and typically developing children may inform heterogeneity and the clinical course of a given child.”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“The study found that both groups (children with ADHD and typically developing children) could be classified into unique, but similar neuropsychological profiles. Furthermore, children with ADHD from each profile showed atypical scores in very specific neuropsychological measures.”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“Three recent reports from our team have highlighted the use of community detection as a way to characterize heterogeneity in ADHD (Fair et al., 2012, Gates et al., 2014, Karalunas et al., 2015).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“For example, in a recent work, we showed that variation across several neuropsychological measures does not always shape across a continuous dimension (i.e. unimodal distribution), but rather some behavioral features form multiple discrete subgroups (i.e. multimodal distribution) (Fair et al., 2012).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“These data highlight not only variation in ADHD, but in typically developing children as well (Fair et al., 2012, Gates et al., 2014).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“Similar methods have been used to assess behavioral and temperamental variation in ADHD and typically developing populations (Fair et al., 2012, Gates et al., 2014, Karalunas et al., 2015).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Fair et al., 2012
In the citing paper
“It is possible, if not likely [2], [3], that as with insomnia multiple mechanisms may lead to similar symptom clusters for a given mental disorder as defined by the Diagnostic and Statistical Manual of Mental Disorders (currently, DSM-5) or International Classification of Diseases (ICD).”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [2]
In the citing paper
“Most evidence for this phenomenon has been from neuropsychological data and behavior or symptom report (e.g., [2]), with recent evidence suggesting heterogeneity in the biological components as well [48].”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [2]
In the citing paper
“Prior work in fMRI using this modularity algorithm required that the researcher set an arbitrary threshold, or cutoff point, for what constitutes similarity between any two given individuals. Researchers would then arrive at thresholds by looking for consistency in community detection results at multiple thresholds (e.g., [2], [21], [22]).”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [2]
In the citing paper
“Data in the ADHD literature examining functional differences in the diagnostic subtypes (i.e. Combined type, and Inattentive type) lend support for this particular finding [2].”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [2]
In the citing paper
“This further supports the notion that many mechanisms exist by which children may meet criteria for ADHD [2].”
From Organizing Heterogeneous Samples Using Community Detection of GIMME-Derived Resting State Functional Networks (2014) · cites this paper as [2]
In the citing paper
“We identified seven functional domains implicated in ADHD (see Figure 1] that were described in the majority of several recent cognitive batteries [5,12,16,17]”
From Linking ADHD to the Neural Circuitry of Attention (2017) · cites this paper as [5]
In the citing paper
“However, evidence suggests that most children with ADHD show deficits on multiple EFs [24]”
In the citing paper
“However, there is now considerable justification suggesting that multiple developmental and pathophysiological pathways inform ADHD symptomatology (Fair et al., 2012; Nigg et al., 2004; Sonuga-Barke et al., 2003).”
From Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder (2013) · cites this paper as Fair et al., 2012
In the citing paper
“Some reports have suggested that disease variation may be nested within normal variation (7).”
From Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies (2016) · cites this paper as [7]
In the citing paper
“A key feature of our approach that differentiates it from other approaches to studying heterogeneity in clinical populations (7, 8) is the primary focus on mapping variation across the cohort.”
From Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies (2016) · cites this paper as [7]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Trait Variation in the Typically Developing Population Informs
“As illustrated by our single subject classification procedures, comparing typically developing children with ADHD children within each of these distinct subgroups increases diagnostic accuracy (i.e., ADHD vs. non-ADHD classification) on the basis of the neuropsychological measures.”
§ Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD > Atypical Neuropsychological Measures Are Unique on the Basis of Profile and ADHD Classification Improves Within Profiles.
“The remaining groups were as follows: group 1, 68% total, 49.2% sensitivity, 80.4% specificity; group 2A, 68.5%, 83.7%, 51.2%; group 2B, 64.7%, 80.4%, 44.2%; group 3, 73.6%, 88.73%, 46.2%; group 4A, 84.1%, 83.3%, 84.6%; and group 4B, 61.9%, 37%, 76.9%.”
Citations
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“The neuropsychological battery was designed to capture working memory (41), response inhibition (39, 45), response variability (8), temporal information processing (46), arousal and activation (47), interference control (48), and response speed (49).”
BackgroundMethodResult
Cited by
Sorted by citations
BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics
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Attention-deficit/hyperactivity disorder
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“Some reports have suggested that disease variation may be nested within normal variation (7).”
BackgroundAn open resource for transdiagnostic research in pediatric mental health and learning disorders
Alexander, L. M., Escalera, J., Ai, L., Andreotti, C., Febre, K., Mangone, A., Potler, N. V., Langer, N., Alexander, A., Kovacs, M., et al. (2017) · Scientific Data · doi:10.1038/sdata.2017.181 · Cited by 681
“Complete HBN Protocol Behavioral Measures Child Behavior Checklist (CBCL) (5-17) Youth Self Report (YSR) (11-18) Adult Self Report (ASR) (18+) Screen for Child Anxiety Related Disorders (SCARED) – Parent Report & Self Report (8-18) State Trait Anxiety Inventory (STAI) (18+) – Self Report Mood & Feelings Questionnaire…”
BackgroundCharacterizing a psychiatric symptom dimension related to deficits in goal-directed control
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“…has already been made by studies examining dissociable clusters of patients within groups diagnosed with the same disorder (Brodersen et al., 2014; Fair et al., 2012), the identification of robust, generalizable and specific markers that contribute to psychiatric co-morbidity has been curtailed…”
BackgroundThe Heterogeneity Problem: Approaches to Identify Psychiatric Subtypes
Feczko, E., Miranda-Dominguez, O., Marr, M., Graham, A. M., Nigg, J. T., & Fair, D. A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.03.009 · Cited by 443
“A community detection approach [80] uses a similar bottom up approach to identify novel executive function [80], temperament [81], and neural [82,83] subtypes in an ADHD population.”
MethodSelf-citationGrayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411
“…consistently implicated in Schizophrenia (Baker et al., 2014; Khadka et al., 2013; Satterthwaite et al., 2015), ADHD (Castellanos and Aoki, 2016; Fair et al., 2012b), and Autism (Kessler et al., 2016; Moseley et al., 2015; Supekar et al., 2013) – though a thorough examination of this literature…”
BackgroundResultInfluentialSelf-citationFair, D. A., Nigg, J. T., Iyer, S., Bathula, D., Mills, K. L., Dosenbach, N. U. F., Schlaggar, B. L., Mennes, M., Gutman, D., Bangaru, S., et al. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00080 · Cited by 463
“…datasets, with coordinated recruitment, deep phenotyping, multimodal data acquisition (e.g., rs-fcMRI, diffusion imaging, ASL), and likely improved homogeneity in our subgrouping (Fair et al., 2012) that a fair assessment of the predictive potential of MR-based approaches will be realized.”
BackgroundSelf-citationADHD: Current Concepts and Treatments in Children and Adolescents
Drechsler, R., Brem, S., Brandeis, D., Grünblatt, E., Berger, G. E., & Walitza, S. (2020) · Neuropediatrics · doi:10.1055/s-0040-1701658 · Cited by 521
A Review of Heterogeneity in Attention Deficit/Hyperactivity Disorder (ADHD)
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“The etiological heterogeneity in terms of the biological and environmental factors is likely reflected in variation in neural correlates (Nigg and Casey, 2005; Mackie et al., 2007; Fair et al., 2012; Costa Dias et al., 2013, 2015; Karalunas et al., 2014), and results in the diverse cognitive and behavioral profiles an…”
BackgroundUnraveling the Miswired Connectome: A Developmental Perspective
Martino, A. D., Fair, D. A., Kelly, C. A. M., Satterthwaite, T. D., Castellanos, F. X., Thomason, M. E., Craddock, R. C., Luna, B., LEVENTHAL, B. L., Zuo, X., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.08.050 · Cited by 357
“Indeed, the changes in shortand long-range connectivity appear to be most prominent in the first 2 years of life (e.g., Gao et al., 2011; Yap et al., 2011), with more modest changes occurring later in development (Fair et al., 2012b; Satterthwaite et al., 2012, 2013a).”
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Executive Functioning Heterogeneity in Pediatric ADHD
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“HYDRA is fundamentally different from previous clustering methods (Fair et al. , 2012; Arnedo et al. , 2015; Du et al. , 2015; Clementz et al. , 2016) because it specifically seeks to cluster illness effects by modelling differences from healthy controls rather than clustering patients directly.”
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“However, improvements on untrained EFs and behavior were mostly nonspecific.”
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“, 2012 (15) ADHD (285) and TDC (213) Neuropsychologic scores CD (33) 6 for ADHD (determined implicitly by the algorithm) Response time variability (1) None”
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“Further research on the behavioral effects of reward-sensitivity should therefore take into account individual differences and subgroups (e.g., Fair et al., 2012).”
BackgroundCoghill, D. R., Seth, S., & Matthews, K. (2014) · Psychological Medicine · doi:10.1017/s0033291713002547 · Cited by 242
“In a landmark study, Fair et al. (2012) demonstrated differences between children with ADHD and controls on a range of cognitive factors (inhibition, working memory, memory span, arousal/ activation, response variability, temporal information processing and processing speed).”
BackgroundInfluentialRauh, V., & Margolis, A. E. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12537 · Cited by 243
“…Fair, Bathula, Nikolas, and Nigg (2012) propose that (a) typically developing children can be classified into distinct neuropsychological subgroups with high precision, and (b) some of the heterogeneity in individuals with ADHD might be ‘nested’ in this normal variation (Fair et al., 2012).”
BackgroundInfluentialDissecting the Heterogeneous Cortical Anatomy of Autism Spectrum Disorder Using Normative Models
Zabihi, M., Oldehinkel, M., Wolfers, T., Frouin, V., Goyard, D., Loth, E., Charman, T., Tillmann, J., Banaschewski, T., Dumas, G., et al. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.11.013 · Cited by 204
The molecular genetic architecture of attention deficit hyperactivity disorder
Hawi, Z., Cummins, T. D. R., Tong, J., Johnson, B. P., Lau, R., Samarrai, W., & Bellgrove, M. A. (2015) · Molecular Psychiatry · doi:10.1038/mp.2014.183 · Cited by 226
Prediction complements explanation in understanding the developing brain
Rosenberg, M. D., Casey, B. J., & Holmes, A. J. (2018) · Nature Communications · doi:10.1038/s41467-018-02887-9 · Cited by 169
Connectotyping: Model Based Fingerprinting of the Functional Connectome
Miranda-Dominguez, O., Mills, B. D., Carpenter, S. D., Grant, K. A., Kroenke, C. D., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0111048 · Cited by 197
“Apinv~yx T xx {1 : ð6Þ While the pseudo-inverse method renders the solution with the lowest discrepancy between the predictions and measurements (in a least squares sense), its use often leads to over-fitting and its predictions are highly susceptible to noise on ill-posed systems [2].”
BackgroundSelf-citationExecutive function and developmental disorders: the flip side of the coin
Johnson, M. H. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.07.001 · Cited by 190
Model-Based Cognitive Neuroscience Approaches to Computational Psychiatry
Wiecki, T. V., Poland, J. S., & Frank, M. J. (2015) · Clinical Psychological Science · doi:10.1177/2167702614565359 · Cited by 207
“One potential way to deal with this problem is to use an unsupervised clustering algorithm to find a new grouping that is hopefully more sensitive to the neurocognitive deficits (Fair et al., 2012).”
BackgroundMethodCharting the landscape of priority problems in psychiatry, part 1: classification and diagnosis
Stephan, K. E., Bach, D. R., Fletcher, P. C., Flint, J., Frank, M. J., Friston, K. J., Heinz, A., Huys, Q. J. M., Owen, M. J., Binder, E. B., et al. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00361-2 · Cited by 180
Ostlund, B. D., Alperin, B. R., Drew, T., & Karalunas, S. L. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.100931 · Cited by 159
Costa Dias, T. G., Wilson, V. B., Bathula, D. R., Iyer, S. P., Mills, K. L., Thurlow, B. L., Stevens, C. A., Musser, E. D., Carpenter, S. D., Grayson, D. S., et al. (2013) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.10.015 · Cited by 180
“However, there is now considerable justification suggesting that multiple developmental and pathophysiological pathways inform ADHD symptomatology (Fair et al., 2012; Nigg et al., 2004; Sonuga-Barke et al., 2003).”
BackgroundSelf-citationTowards a brain‐based predictome of mental illness
Rashid, B., & Calhoun, V. D. (2020) · Human Brain Mapping · doi:10.1002/hbm.25013 · Cited by 166
Development of ADHD: Etiology, Heterogeneity, and Early Life Course
Nigg, J. T., Sibley, M. H., Thapar, A., & Karalunas, S. L. (2020) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-060320-093413 · Cited by 205
Self-citationInsomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping
Benjamins, J. S., Migliorati, F., Dekker, K., Wassing, R., Moens, S., Blanken, T. F., Lindert, B. H. W. T., Mook, J. S., & Someren, E. J. W. V. (2016) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2016.10.005 · Cited by 179
Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders
Jeste, S., Frohlich, J., & Loo, S. K. (2015) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000181 · Cited by 168
“Efforts to identify latent subgroups using neuropsychological measures [4], temperament dimensions [5 & ], and resting state connectivity [6], in both ADHD and typical development, suggest that a reconceptualization of classification efforts may be needed.”
BackgroundLinking ADHD to the Neural Circuitry of Attention
Mueller, A., Hong, D. S., Shepard, S., & Moore, T. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.03.009 · Cited by 158
A trans-diagnostic perspective on obsessive-compulsive disorder
Gillan, C. M., Fineberg, N. A., & Robbins, T. W. (2017) · Psychological Medicine · doi:10.1017/s0033291716002786 · Cited by 158
“This can be achieved in many different ways, just a few of which have been outlined here (see other good examples: Fair et al. 2012; Brodersen et al. 2014), and at many units of analysis.”
Nejati, V., Salehinejad, M. A., Nitsche, M. A., Najian, A., & Javadi, A.-H. (2020) · Journal of Attention Disorders · doi:10.1177/1087054717730611 · Cited by 163
“Instead, ADHD is quite a heterogeneous disorder in terms of impaired deficits and neuropsychological measures central to ADHD (Fair et al., 2012).”
BackgroundImaging Functional and Structural Brain Connectomics in Attention-Deficit/Hyperactivity Disorder
Cao, M., Shu, N., Cao, Q., Wang, Y., & Yong He, A. (2014) · Molecular Neurobiology · doi:10.1007/s12035-014-8685-x · Cited by 161
“Moreover, there could be mechanistic heterogeneity that potentially underlies the existing classification scheme [86].”
Backgroundvon Rhein, D. T., Mennes, M., van Ewijk, H., Groenman, A. P., Zwiers, M. P., Oosterlaan, J., Heslenfeld, D. J., Franke, B., Hoekstra, P. J., Faraone, S. V., et al. (2014) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-014-0573-4 · Cited by 150
“Using empirical modelling techniques like latent class analysis (LCA) and recent extensions of these techniques, one may identify groups of participants who have very similar patterning of scores on cognitive and brain measures reflecting biologically relevant, distinct etiological pathways towards disease [93, 94].”
MethodKaralunas, S. L., Hawkey, E., Gustafsson, H., Miller, M., Langhorst, M., Cordova, M., Fair, D., & Nigg, J. T. (2018) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-017-0394-2 · Cited by 148
“Although there is heterogeneity in the ADHD population (Fair et al. 2012; Nigg et al. 2005), at the group level relatively consistent impairments have been found in individuals with ADHD in each of these domains (Huang-Pollock et al. 2012; Kofler et al. 2013; Willcutt et al. 2005).”
Self-citationSarver, D. E., Rapport, M. D., Kofler, M. J., Raiker, J. S., & Friedman, L. M. (2015) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-015-0011-1 · Cited by 149
“Taken together, this finding is consistent with the well-documented neurocognitive and behavioral heterogeneity in ADHD and TD populations (Fair et al. 2012), and implies that gross motor movement may be more likely to facilitate than impair cognitive functioning for children with ADHD.”
BackgroundResultMultidimensional Neuroanatomical Subtyping of Autism Spectrum Disorder
Hong, S., Valk, S. L., Martino, A. D., Milham, M. P., & Bernhardt, B. C. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx229 · Cited by 136
Insights into multimodal imaging classification of ADHD
Colby, J. B., Rudie, J. D., Brown, J. A., Douglas, P. K., Cohen, M. S., & Shehzad, Z. (2012) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00059 · Cited by 144
Heritability of the human connectome: A connectotyping study
Miranda-Domínguez, Ó., Feczko, E., Grayson, D. S., Walum, H., Nigg, J. T., & Fair, D. A. (2017) · Network Neuroscience · doi:10.1162/netn_a_00029 · Cited by 124
Self-citationConsiderations for MRI study design and implementation in pediatric and clinical populations
Greene, D. J., BLACK, K. J., & Schlaggar, B. L. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.12.005 · Cited by 132
Mostert, J. C., Onnink, A. M. H., Klein, M., Dammers, J., Harneit, A., Schulten, T., van Hulzen, K. J. E., Kan, C. C., Slaats-Willemse, D., Buitelaar, J. K., et al. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.08.010 · Cited by 142
“The current findings provide a starting point to investigate individual differences in terms of impaired cognitive pathways, for instance by using clustering analyses on the neuropsychological data (Fair et al., 2012).”
MethodSalehinejad, M. A., Wischnewski, M., Nejati, V., Vicario, C. M., & Nitsche, M. A. (2019) · PLOS ONE · doi:10.1371/journal.pone.0215095 · Cited by 126
“A precise description of ADHD neuropathology is difficult to delineate due to its neuropsychological heterogeneity [12, 13], and substantial overlap between ADHD and typically developing children [14].”
BackgroundCharacterizing heterogeneity in children with and without ADHD based on reward system connectivity
Costa Dias, T. G., Iyer, S. P., Carpenter, S. D., Cary, R. P., Wilson, V. B., Mitchell, S. H., Nigg, J. T., & Fair, D. A. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.12.005 · Cited by 130
“Connectivity preprocessing followed prior methods, well described and widely used in the imaging literature (Fair et al., 2007, 2008, 2009; Fox et al., 2005).”
MethodSelf-citationKaralunas, S. L., Gustafsson, H., Fair, D. A., Musser, E. D., & Nigg, J. T. (2018) · Psychological Assessment · doi:10.1037/pas0000664 · Cited by 142
Self-citationGreen, B. C., Johnson, K. A., & Bretherton, L. (2013) · International Journal of Language & Communication Disorders · doi:10.1111/1460-6984.12056 · Cited by 154
“Recently there has been increasing recognition amongst researchers that behavioural and cognitive features associated with ADHD are distributed in the population as a whole, with the syndrome of ADHD representing the extreme end of a continuum (Fair et al. 2012, Shaw et al. 2011).”
Toward a revised nosology for attention-deficit/hyperactivity disorder heterogeneity
Nigg, J. T., Karalunas, S. L., Feczko, E., & Fair, D. A. (2020) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.02.005 · Cited by 132
Self-citationHeterogeneity of executive functions among comorbid neurodevelopmental disorders
Dajani, D. R., Llabre, M. M., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q. (2016) · Scientific Reports · doi:10.1038/srep36566 · Cited by 126
Vaidya, C. J., You, X., Mostofsky, S., Pereira, F., Berl, M. M., & Kenworthy, L. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13114 · Cited by 126
Salehinejad, M. A., Nejati, V., Mosayebi-Samani, M., Mohammadi, A., Wischnewski, M., Kuo, M.-F., Avenanti, A., Vicario, C. M., & Nitsche, M. A. (2020) · Neuroscience Bulletin · doi:10.1007/s12264-020-00501-x · Cited by 118
Are There Executive Dysfunction Subtypes Within ADHD?
Roberts, B. A., Martel, M. M., & Nigg, J. T. (2017) · Journal of Attention Disorders · doi:10.1177/1087054713510349 · Cited by 116
“Specific EF deficits have been shown to be dissociable such that subgroups of children with ADHD may be affected by problems in only one area of EF (Fair et al., 2012; Miller et al., 2010; Sonuga-Barke et al., 2010).”
BackgroundResultInfluentialSelf-citationEslami, T., Almuqhim, F., Raiker, J. S., & Saeed, F. (2021) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2020.575999 · Cited by 135
“…given the well-documented neurocognitive dysfunction and alterations in temperament characteristic of individuals with ADHD, graph theoretical and community detection algorithms have been applied to advance our understanding of these deficits in ADHD (Fair et al., 2012; Karalunas et al., 2014).”
MethodMetin, B., Roeyers, H., Wiersema, J. R., van der Meere, J., & Sonuga-Barke, E. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.08.023 · Cited by 121
Brain Subtyping Enhances The Neuroanatomical Discrimination of Schizophrenia
Dwyer, D., Cabral, C., Kambeitz‐Ilankovic, L., Sanfelici, R., Kambeitz, J. P., Calhoun, V. D., Falkai, P., Pantelis, C., Meisenzahl, E. M., & Koutsouleris, N. (2018) · Schizophrenia Bulletin · doi:10.1093/schbul/sby008 · Cited by 118
Finn, E. S., & Constable, R. T. (2016) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2016.18.3/efinn · Cited by 101
Classification and treatment of antisocial individuals: From behavior to biocognition
Brazil, I. A., van Dongen, J. D. M., Maes, J. H. R., Mars, R. B., & Baskin-sommers, A. R. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.10.010 · Cited by 135
What big data can do for treatment in psychiatry
Gillan, C. M., & Whelan, R. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.07.003 · Cited by 114
Remapping the cognitive and neural profiles of children who struggle at school
Astle, D. E., Bathelt, J., the CALM team, & Holmes, J. (2018) · Developmental Science · doi:10.1111/desc.12747 · Cited by 114
“Machine learning methods have rarely been applied to understanding developmental disorders (e.g. Fair et al., 2012).”
MethodOwens, M., Herbert, J., Jones, P. B., Sahakian, B. J., Wilkinson, P. O., Dunn, V. J., Croudace, T. J., & Goodyer, I. M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1318786111 · Cited by 118
“Etiological heterogeneity in another psychiatric disorder [attention deficit hyperactivity disorder (ADHD)] was recently revealed by recognizing subgroups nested within the normal population with distinctive cognitive profiles (34).”
BackgroundExecutive Functioning and Emotion Regulation in Children with and without ADHD
Groves, N. B., Wells, E. L., Soto, E. F., Marsh, C. L., Jaisle, E. M., Harvey, T. K., & Kofler, M. J. (2022) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-021-00883-0 · Cited by 110
“For example, working memory is impaired in 30% to 85% (Coghill et al., 2014; Fair et al., 2012; Fosco et al., 2019; Kofler et al., 2018; Karalunas et al., 2017), inhibitory control is impaired in 21% to 46% (Coghill et al.”
BackgroundKaralunas, S. L., Gustafsson, H. C., Dieckmann, N. F., Tipsord, J., Mitchell, S. H., & Nigg, J. T. (2017) · Journal of Abnormal Psychology · doi:10.1037/abn0000292 · Cited by 104
Self-citationAttention Deficit Hyperactivity Disorder
Matthews, M., Nigg, J. T., & Fair, D. A. (2013) · Current topics in behavioral neurosciences · doi:10.1007/978-3-662-45758-0_249 · Cited by 124
Self-citationKaralunas, S. L., Huang-Pollock, C. L., & Nigg, J. T. (2012) · Neuropsychology · doi:10.1037/a0029936 · Cited by 104
Self-citationGates, K. M., Molenaar, P. C. M., Iyer, S. P., Nigg, J. T., & Fair, D. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091322 · Cited by 107
“, [2]), with recent evidence suggesting heterogeneity in the biological components as well [48].”
BackgroundInfluentialSelf-citationWu, M., Mwangi, B., Bauer, I. E., Passos, I. C., Sanches, M., Zunta‐Soares, G. B., Meyer, T. D., Hasan, K. M., & Soares, J. C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.016 · Cited by 112
“Most recently, several studies have successfully identified unique neurocognitive subgroups using data-driven machine learning algorithms (Brodersen et al., 2014; Burdick et al., 2014; Fair et al., 2012; Heinrichs & Awad, 1993; LEE et al., 2014).”
BackgroundIntegrating Impairments in Reaction Time and Executive Function Using a Diffusion Model Framework
Karalunas, S. L., & Huang‐Pollock, C. L. (2013) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-013-9715-2 · Cited by 107
“Future studies that better characterize subgroups using methods such as latent class or graph theoretical approaches (Fair et al. 2012; Newman 2006) will be critical for understanding within-group heterogeneity.”
Francx, W., Oldehinkel, M., Oosterlaan, J., Heslenfeld, D., Hartman, C. A., Hoekstra, P. J., Franke, B., Beckmann, C. F., Buitelaar, J. K., & Mennes, M. (2015) · Cortex · doi:10.1016/j.cortex.2015.08.012 · Cited by 102
Blanken, T. F., Deserno, M. K., Dalege, J., Borsboom, D., Blanken, P., KERKHOF, G. A., & Cramer, A. O. J. (2018) · Scientific Reports · doi:10.1038/s41598-018-24224-2 · Cited by 103
Johnston, B. A., Mwangi, B., Matthews, K., Coghill, D., Konrad, K., & Steele, J. D. (2014) · Human Brain Mapping · doi:10.1002/hbm.22542 · Cited by 101
“Given the possible heterogeneity of the ADHD syndrome [Fair et al., 2012], the results are encouraging for the identification of consistent imaging biomarkers, that can inform future work into the aetiology, pathophysiology, and clinical management of ADHD.”
BackgroundNigg, J. T., Gustafsson, H. C., Karalunas, S. L., Ryabinin, P., McWeeney, S. K., Faraone, S. V., Mooney, M. A., Fair, D. A., & Wilmot, B. (2018) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2017.12.013 · Cited by 93
Self-citationComputer-based Cognitive Training for ADHD
Sonuga-Barke, E., Brandeis, D., Holtmann, M., & Cortese, S. (2014) · Child and Adolescent Psychiatric Clinics of North America · doi:10.1016/j.chc.2014.05.009 · Cited by 92
Heterogeneity in ADHD: Neurocognitive predictors of peer, family, and academic functioning
Kofler, M. J., Sarver, D. E., Spiegel, J. A., Day, T. N., Harmon, S. L., & Wells, E. L. (2017) · Child Neuropsychology · doi:10.1080/09297049.2016.1205010 · Cited by 94
“arousal (Fair et al., 2012), combinations of short-term memory, vigilance, set shifting, inhibition, and visual-motor integration (Biederman et al.”
BackgroundBrain connectivity in normally developing children and adolescents
Khundrakpam, B. S., Lewis, J. D., Zhao, L., Chouinard-Decorte, F., & Evans, A. C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.062 · Cited by 91
van Rooij, D., Hartman, C. A., Mennes, M., Oosterlaan, J., Franke, B., Rommelse, N., Heslenfeld, D., Faraone, S. V., Buitelaar, J. K., & Hoekstra, P. J. (2015) · NeuroImage: Clinical · doi:10.1016/j.nicl.2015.01.004 · Cited by 89
Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels
Dam, N. T. V., O’Connor, D. A., Marcelle, E. T., Ho, E. J., Craddock, R. C., Tobe, R. H., Gabbay, V., Hudziak, J. J., Castellanos, F. X., LEVENTHAL, B. L., et al. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.06.027 · Cited by 86
van Hulst, B. M., de Zeeuw, P., & Durston, S. (2015) · Psychological Medicine · doi:10.1017/s0033291714001792 · Cited by 87
“Building on a multiple-pathway hypothesis, recent studies have found several subgroups with varying neuropsychological profiles in ADHD (Sonuga-Barke et al. 2010; de Zeeuw et al. 2012; Fair et al. 2012).”
ResultBecker, S. P., & Willcutt, E. G. (2019) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-018-1136-x · Cited by 85
“1 3 difference between a target (signal) and a nontarget (noise) that is interpreted as an indicator of low (suboptimal) arousal [81].”
Rudolph, M. D., Miranda-Domínguez, Ó., Cohen, A. O., Breiner, K., Steinberg, L. D., Bonnie, R. J., Scott, E. S., Taylor‐Thompson, K., Chein, J. M., Fettich, K. C., et al. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.01.010 · Cited by 83
Self-citationAttention Deficit/Hyperactivity Disorder (ADHD) and Entrepreneurship
Antshel, K. M. (2017) · Academy of Management Perspectives · doi:10.5465/amp.2016.0144 · Cited by 97
Toward Precision Medicine in ADHD
Buitelaar, J. K., Bölte, S., Brandeis, D., Caye, A., Christmann, N., Cortese, S., Coghill, D., Faraone, S. V., Franke, B., Gleitz, M., et al. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.900981 · Cited by 83
“Several approaches to stratification of ADHD with the aim of producing more homogenous neurocognitive subgroups have been described ADHD (Fair et al., 2012; Coghill et al., 2014; van Hulst et al., 2015; Leikauf et al., 2017; Mostert et al., 2018).”
MethodThe Role of Speed in ADHD-Related Working Memory Deficits
Weigard, A. S., & Huang‐Pollock, C. L. (2016) · Clinical Psychological Science · doi:10.1177/2167702616668320 · Cited by 83
Alabdulakareem, E., & Jamjoom, M. M. (2020) · Entertainment Computing · doi:10.1016/j.entcom.2020.100341 · Cited by 75
Automated Selection of Robust Individual-Level Structural Equation Models for Time Series Data
Lane, S., & Gates, K. M. (2017) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2017.1309978 · Cited by 69
“Both theory (Lamiell, 1981; Molenaar, 2008) and emerging results (Anzman-Frasca et al., 2013; Fair, Bathula, Nikolas, & Nigg, 2012; Gates, Molenaar, Iyer, Nigg.”
Holmes, J., Bryant, A., the CALM Team, & Gathercole, S. E. (2019) · BMC Pediatrics · doi:10.1186/s12887-018-1385-3 · Cited by 67
Parsing heterogeneity in attention‐deficit hyperactivity disorder using EEG ‐based subgroups
Loo, S. K., McGough, J. J., McCracken, J. T., & Smalley, S. L. (2018) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12814 · Cited by 73
Rohr, C. S., Vinette, S. A., Parsons, K., Cho, I. Y. K., Dimond, D., Benischek, A., Lebel, C. A., Dewey, D., & Bray, S. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw236 · Cited by 67
Alaerts, K., Nayar, K., Kelly, C. A. M., Raithel, J., Milham, M. P., & Martino, A. D. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsv029 · Cited by 66
“As in prior work (Fair et al., 2012; Satterthwaite et al., 2013), these findings were robustly detectable across motion-correction approaches (i.”
BackgroundMethodResultInfluentialThe definition and measurement of heterogeneity
Nunes, A., Trappenberg, T. P., & Alda, M. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00986-0 · Cited by 81
Deficits in Cognitive Control, Timing and Reward Sensitivity Appear to be Dissociable in ADHD
de Zeeuw, P., Weusten, J., van Dijk, S., van Belle, J., & Durston, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051416 · Cited by 71
Heidbreder, R. (2015) · ADHD Attention Deficit and Hyperactivity Disorders · doi:10.1007/s12402-015-0171-4 · Cited by 81
Cordova, M., Antovich, D. M., Ryabinin, P., Neighbor, C., Mooney, M. A., Dieckmann, N. F., Miranda-Domínguez, Ó., Nagel, B. J., Fair, D. A., & Nigg, J. T. (2021) · PsyArXiv (OSF Preprints) · doi:10.1016/j.jaac.2022.03.030 · Cited by 69
Self-citationADHD and attentional control: Impaired segregation of task positive and task negative brain networks
Mills, B. D., Miranda-Domínguez, Ó., Mills, K. L., Earl, E., Cordova, M., Painter, J. G., Karalunas, S. L., Nigg, J. T., & Fair, D. A. (2017) · Network Neuroscience · doi:10.1162/netn_a_00034 · Cited by 61
Self-citationBaroni, A., & Castellanos, F. X. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.08.005 · Cited by 68
Metadata
- Authors
- Fair, D. A., Bathula, D., Nikolas, M. A., & Nigg, J. T.
- Affiliations
- Oregon Health & Science University (US)
- Indian Institute of Technology Ropar (IN)
- University of Iowa (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2012-04-02
- Volume
- 109
- Issue
- 17
- Pages
- 6769-6774
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3340031
- OpenAlex
- W2136530770
- Semantic Scholar
- adf36af1b47715f99d3f580f47ce0801a1338b8e
- Cited by
- 464
- References
- 54
- Citations by year
- 2026: 17 · 2025: 25 · 2024: 29 · 2023: 23 · 2022: 36 · 2021: 30 · 2020: 34 · 2019: 41 · 2018: 40 · 2017: 41 · 2016: 43 · 2015: 36 · 2014: 35 · 2013: 21 · 2012: 13
- FWCI
- 23.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UL1TR000128)
- Oregon Clinical and Translational Research Institute
- National Institute of Mental Health (R00MH091238, R01MH096773, R01MH059105, R01MH086654)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Developmental and Educational Neuropsychology
- Keywords
- attention deficit hyperactivity disorder, typically developing children, developmental heterogeneity, community detection, graph theory, multivariate pattern analysis, support vector machine, diagnostic classification
- MeSH terms
- Adolescent, Attention Deficit Disorder with Hyperactivity, Child, Cognition, Humans, Neuropsychological Tests, Cohort Studies
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.
A language model drew the claims from the paper on 2026-09-29, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-09-29 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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