Altered structural connectivity is related to attention deficit/hyperactivity subtypes: A DTI study

Ercan, Eyüp Sabri; Süren, Serkan; Bacanlı, Ali; Yazıcı, Kemal Utku; Çallı, Cem; Ardıç, Ülkü Akyol; Aygüneş, Duygu; Kosova, Buket; Özyurt, Onur; Aydın, Cahide; Rohde, Luís Augusto

doi:10.1016/j.pscychresns.2016.04.002

Cited by 29 publications

(37 citation statements)

References 55 publications

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“…Additionally, a number of differences were observed specific to subtype when compared to controls, with increased FA in the right cingulum in ADHD-C, and increased FA in ADHD-I involving regions linked to fronto–striatal–thalamic circuits and the cingulum bundle, which forms connections between the frontal, parietal and temporal lobes (Svatkova et al, 2016 ). The second study, by Ercan et al ( 2016a ) compared 24 ADHD-C and 24 ADHD-I children and adolescents with 24 controls and found increased RD bilaterally and increased AD in brain regions mostly on the left side linked to fronto–striato–cerebellar regions in ADHD-C than ADHD-I. The third study that used voxel-based analyses measured FA, RD, and AD values in children, aged 7–13 years old, and found significant differences in ADHD-C ( n = 28), relative to ADHD-I ( n = 28), involving the motor circuit, with increased FA and RD in the right thalamus, increased AD in the left postcentral gyrus and right caudate, and increased RD in the left postcentral gyrus and supplementary motor area (Lei et al, 2014 ).…”

Section: Resultsmentioning

confidence: 99%

“…Of the four DTI studies available to review examining the microstructural properties of WM tracts between ADHD subtypes, three studies used whole brain voxel-wise analysis whereby two of these studies employed tract-based spatial statistical (TBSS) analyses of FA, RD, AD (Ercan et al, 2016a ; Svatkova et al, 2016 ), and MD (Svatkova et al, 2016 ) diffusion properties, and one study analyzed FA, RD, and AD values using a voxel-based analysis (Lei et al, 2014 ). The fourth study utilized a whole brain connectome approach to map interregional brain connections using tractography and applied network-based statistic (NBS) analysis of FA values of these connections and also examined correlations of tract-averaged FA values and neuropsychological attention measures as a subsequent analysis (Hong et al, 2014 ).…”

Section: Resultsmentioning

confidence: 99%

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A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

Saad

Griffiths

Korgaonkar

2020

Front. Integr. Neurosci.

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Insights to underlying neural mechanisms in attention deficit hyperactivity disorder (ADHD) have emerged from neuroimaging research; however, the neural mechanisms that distinguish ADHD subtypes remain inconclusive. Method: We reviewed 19 studies integrating magnetic resonance imaging [MRI; structural (sMRI), diffusion, functional MRI (fMRI)] findings into a framework exploring pathophysiological mechanisms underlying the combined (ADHD-C) and predominantly inattentive (ADHD-I) ADHD subtypes. Results: Despite equivocal structural MRI results, findings from fMRI and DTI imaging modalities consistently implicate disrupted connectivity in regions and tracts involving frontal striatal thalamic in ADHD-C and frontoparietal neural networks in ADHD-I. Alterations of the default mode, cerebellum, and motor networks in ADHD-C and cingulo-frontoparietal attention and visual networks in ADHD-I highlight network organization differences between subtypes. Conclusion: Growing evidence from neuroimaging studies highlight neurobiological differences between ADHD clinical subtypes, particularly from a network perspective. Understanding brain network organization and connectivity may help us to better conceptualize the ADHD types and their symptom variability.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

Saad

Griffiths

Korgaonkar

2020

Front. Integr. Neurosci.

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“…Encouragingly, the results from those studies overlap with ours in finding widespread regions, including decreased FA with or without increased RD in overlapping regions. In contrast, other studies failed to identify any regional alteration, in either children or adults with ADHD compared with healthy controls, even with comparable sample sizes (Ercan et al, 2016;Yoncheva et al, 2016). Inconsistency might result from differences in scanning, data processing, and quality assurance protocols, differences in demographic characteristics of the participants, eg, age (Roalf et al, 2016), sex (Jacobson et al, 2015), medication history (de Luis-Garcia et al, 2015), as well as the heterogeneous nature of the disorder (Thapar and Cooper, 2015).…”

Section: Discussionmentioning

confidence: 95%

White Matter Microstructural Alterations in Children with ADHD: Categorical and Dimensional Perspectives

Bralten

Cao

et al. 2016

Neuropsychopharmacol

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Studies of brain alterations in children with attention-deficit/hyperactivity disorder (ADHD) have shown heterogeneous results. The aims of the current study were to investigate white matter microstructure in children using both categorical and dimensional definitions of ADHD and to determine the functional consequences of observed alterations. In a large single-site sample of children (aged 8-15 years) with ADHD (n = 83) and healthy controls (n = 122), we used tract-based spatial statistics on diffusion tensor imaging data to investigate whole-skeleton differences of fractional anisotropy (FA), mean, axial, and radial diffusivity (MD, AD, RD), and mode of anisotropy related to ADHD status (categorical) and symptom severity (dimensional). For categorical differences observed, we analyzed their association with cognitive functioning in working memory and inhibition. Compared with healthy controls, children with ADHD showed decreased FA and increased RD in widespread, overlapping brain regions, mainly in corpus callosum (CC) and major tracts in the left hemisphere. Decreased FA was associated with inhibition performance in the participants with ADHD. Using dimensional definitions, greater hyperactivity/ impulsivity symptom severity was associated with higher FA also in widespread regions, mainly in CC and major tracts in the right hemisphere. Our study showed white matter alterations to be related to ADHD status and symptom severity in patients. The coexistence of decreased FA and increased RD in the absence of alterations in MD or AD might indicate altered myelination as a pathophysiological factor in ADHD.

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“…Growing evidence from both functional and structural connectivity studies highlight brain connectivity differences in ADHD and between subtypes, which extends support for specific key networks that may underlie the combined and inattentive types (Carmona et al, 2015, Park et al, 2016, Iannaccone et al, 2015, Wang and Li, 2015). Correspondingly, diffusion tensor imaging (DTI) studies provide further support for distinct structural and white matter connectivity disturbances between the ADHD-C and ADHD-I subtype (Hong et al, 2014, Lei et al, 2014a, Svatkova et al, 2016, Ercan et al, 2016). A novel connectivity approach which complements both DTI and functional connectivity is connectivity mapping using the covariance of brain regional volumes (Singh et al, 2013, Griffiths et al, 2016).…”

Section: Introductionmentioning

confidence: 97%

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder

Saad

Griffiths

Kohn

et al. 2017

NeuroImage: Clinical

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Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization.We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I (n = 16) or as ADHD-C (n = 18) and 28 matched typically developing controls, aged 8–17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry.Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in “nodal degree”). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization.Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be reflected in distinct aberrations in underlying brain organization.

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Altered structural connectivity is related to attention deficit/hyperactivity subtypes: A DTI study

Cited by 29 publications

References 55 publications

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

White Matter Microstructural Alterations in Children with ADHD: Categorical and Dimensional Perspectives

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder

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