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Articles, Behavioral/Systems/Cognitive

Altered Functional Brain Connectivity in a Non-Clinical Sample of Young Adults with Attention-Deficit/Hyperactivity Disorder

Luca Cocchi, Ivanei E. Bramati, Andrew Zalesky, Emi Furukawa, Leonardo F. Fontenelle, Jorge Moll, Gail Tripp and Paulo Mattos
Journal of Neuroscience 5 December 2012, 32 (49) 17753-17761; DOI: https://doi.org/10.1523/JNEUROSCI.3272-12.2012
Luca Cocchi
1Queensland Brain Institute, The University of Queensland, St Lucia, Queensland 4072, Australia,
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Ivanei E. Bramati
2D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil CEP 22281-100,
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Andrew Zalesky
3Melbourne Neuropsychiatry Centre, The University of Melbourne, Carlton South, Victoria 3053, Australia,
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Emi Furukawa
4Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan 904-0495, and
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Leonardo F. Fontenelle
2D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil CEP 22281-100,
5Anxiety and Depression Research Program, Institute of Psychiatry of the Federal University of Rio de Janeiro, Rio de Janeiro, Brazil CEP 22290-140
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Jorge Moll
2D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil CEP 22281-100,
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Gail Tripp
4Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan 904-0495, and
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Paulo Mattos
2D'Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil CEP 22281-100,
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  • Figure 1.
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    Figure 1.

    Flowchart of methods pipeline: overview of data processing and analysis pipeline. Resting-state fMRI data were acquired in 16 individuals meeting DSM-IV criteria for ADHD and a group of 15 matched healthy controls. Data were corrected for a temporal shift in acquisition (slice timing), realigned to the middle slice, normalized to an EPI template, smoothed using a full width at half maximum kernel of 6 mm, detrended, and bandpass filtered (0.01–0.08 Hz). The six head-motion parameters (matched between the two groups), as well as the white matter and cerebrospinal fluid signals, were regressed out from each voxel's time course. Time courses were extracted for the 90 cerebral regions comprising the AAL template and the extent of dependency between every pair of regions was represented at the subject level with a 90 × 90 connectivity matrix. The resulting connectivity matrices were then investigated for between-group differences in connectivity using the network-based statistic as well as differences in key network measures. Intra-regional connectivity was also assessed from the EPI images (voxel wise) and the AAL regions of interest.

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    Figure 2.

    Measures of global topological attributes of brain connectivity. Multivariate measures describing topological attributes of brain connectivity were quantified in a drug-naive, non-clinical sample of young adults with ADHD and matched healthy controls. No significant differences were found between the two groups for the five measures and six densities considered. A, Characteristic path length and normalized characteristic path length. B, Average clustering coefficient and normalized average clustering coefficient. C, Small worldness.

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    Figure 3.

    Group differences in inter-regional functional connectivity. Two abnormal networks in ADHD identified with the NBS. In both panels, red lines indicate reduced inter-regional functional connectivity in the ADHD group compared with controls. In contrast, blue lines designate enhanced inter-regional functional connectivity in individuals with ADHD compared with healthy controls. A, Network 1: 1, superior frontal cortex; 2, mid-orbitofrontal cortex; 3, precentral gyrus; 4, amygdala; 5, lingual gyrus. B, Network 2: A, superior occipital cortex; B, fusiform gyrus; C, superior temporal gyrus; D, temporal pole; E, inferior part of the orbitofrontal cortex; F, medial orbitofrontal cortex.

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    Figure 4.

    Associations between values of intrinsic functional connectivity and symptoms of ADHD. A–C, Correlations between ADHD individuals' functional connectivity values in the left medial orbitofrontal-superior temporal connection (network 2) and the following: current symptoms of hyperactivity/impulsivity (A); total number of current symptoms (hyperactivity/impulsivity and inattention) (B); and number of past symptoms of hyperactivity/impulsivity (C). D, Representation of the correlation between the number of past symptoms of inattention and connectivity values in the left amygdala-right precentral gyrus connection (network 1).

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    Table 1.

    Sample characteristics

    CharacteristicsControls (N = 15)ADHD (N = 16)
    Sex M/F, no7/89/7
    Age female, average (SD)23.3 (±1.0)23.8 (±1.0)
    Age males, average (SD)22.4 (±0.9)23.0 (±1.8)
    Handedness, Right/left, no15/016/0
    Formal education, years1616
    Intelligence-Full scale (WASI)114.7 (±8.7)116.5 (±7.9)
    ADHD symptoms (average, SD)
    K-SADS Inattention (current)*0.8 (±1.2)6.8 (±1.0)
    K-SADS Hyperactivity/impulsivity (current)*1.0 (±1.0)5.4 (±2.4)
    K-SADS global (current)*1.8 (±1.9)12.3 (±2.6)
    K-SADS Inattention (past)*0.8 (±1.4)5.5 (±1.7)
    K-SADS Hyperactivity/impulsivity (past) *0.8 (±1.5)5.2 (±2.4)
    K-SADS global (past)*1.7 (±2.4)10.7 (±2.4)
    • ↵*Between group difference (independent sample t test, p < 0.001). SD, Standard deviation.

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    Table 2.

    Complex networks measures of functional segregation and integration

    Network connection densityRegions showing a significant between-group difference in nodal clustering (1/N correction)Regions showing significant between-group difference in nodal path length (1/N correction)
    10%Left inferior orbitofrontal cortex (p = 0.008), ⇑
    15%Right medial frontal cortex (p = 0.009), ⇓
    20%Right superior temporal cortex (p = 0.007), ⇑Right superior occipital cortex (p = 0.008), ⇓
    25%Right superior temporal cortex (p = 0.009), ⇑
    30%Left superior occipital cortex (p = 0.010), ⇓
    • Note. ⇑ ADHD > healthy controls; ⇓ ADHD < healthy controls.

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    Table 3.

    Inter-regional changes in functional connectivity (network-based statistic)

    Anatomyap value
    xyz
    Network 1
        Superior frontal cortex−203143
        Lateral orbitofrontal cortex−3252−11p = 0.020
        Precentral gyrus40−650
        Amygdala−260−18
        Lingual gyrus16−68−5
    Network 2
        Medial orbitofrontal cortex−751−8
        Inferior orbitofrontal cortex−4032−12
        Temporal pole−4714−17p = 0.005
        Superior temporal gyrus−57−226
        Superior occipital cortex−23−8130
        Fusiform gyrus33−41−21
    • ↵aCoordinates (x, y, z) are given in Montreal Neurological Institute (MNI) atlas space and refer to the centroid of each AAL region. P values are all familywise error corrected for multiple comparisons.

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    Table 4.

    Average values of functional connectivity in the pairwise connections of interest (network-based statistic)

    ControlsADHD
    Network 1
        Amygdala–Precentral gyrus−0.10 (±0.03)0.07 (±0.03)
        Lateral orbitofrontal cortex–Superior frontal cortex−0.07 (±0.04)0.14 (±0.04)
        Lateral orbitofrontal cortex–Amygdala0.10 (±0.05)−0.08 (±0.02)
        Lateral orbitofrontal cortex–Lingual gyrus−0.06 (±0.03)0.08 (±0.02)
    Network 2
        Superior temporal gyrus–Inferior orbitofrontal cortex0.08 (±0.03)−0.13 (±0.04)
        Superior temporal gyrus–Medial orbitofrontal cortex0.10 (±0.03)−0.05 (±0.03)
        Temporal pole–Superior occipital cortex−0.10 (±0.03)0.11 (±0.04)
        Superior temporal gyrus–Fusiform gyrus−0.07 (±0.03)0.13 (±0.04)
        Superior temporal gyrus–Temporal pole0.04 (±0.04)0.24 (±0.03)
    • Standard error of the mean values are reported between brackets.

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The Journal of Neuroscience: 32 (49)
Journal of Neuroscience
Vol. 32, Issue 49
5 Dec 2012
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Altered Functional Brain Connectivity in a Non-Clinical Sample of Young Adults with Attention-Deficit/Hyperactivity Disorder
Luca Cocchi, Ivanei E. Bramati, Andrew Zalesky, Emi Furukawa, Leonardo F. Fontenelle, Jorge Moll, Gail Tripp, Paulo Mattos
Journal of Neuroscience 5 December 2012, 32 (49) 17753-17761; DOI: 10.1523/JNEUROSCI.3272-12.2012

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Altered Functional Brain Connectivity in a Non-Clinical Sample of Young Adults with Attention-Deficit/Hyperactivity Disorder
Luca Cocchi, Ivanei E. Bramati, Andrew Zalesky, Emi Furukawa, Leonardo F. Fontenelle, Jorge Moll, Gail Tripp, Paulo Mattos
Journal of Neuroscience 5 December 2012, 32 (49) 17753-17761; DOI: 10.1523/JNEUROSCI.3272-12.2012
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