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, 63 (3), 332-7

Cingulate-precuneus Interactions: A New Locus of Dysfunction in Adult Attention-Deficit/Hyperactivity Disorder

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Cingulate-precuneus Interactions: A New Locus of Dysfunction in Adult Attention-Deficit/Hyperactivity Disorder

F Xavier Castellanos et al. Biol Psychiatry.

Abstract

Background: Pathophysiologic models of attention-deficit/hyperactivity disorder (ADHD) have focused on frontal-striatal circuitry with alternative hypotheses relatively unexplored. On the basis of evidence that negative interactions between frontal foci involved in cognitive control and the non-goal-directed "default-mode" network prevent attentional lapses, we hypothesized abnormalities in functional connectivity of these circuits in ADHD.

Methods: Resting-state blood oxygen level-dependent functional magnetic resonance imaging (fMRI) scans were obtained at 3.0-Tesla in 20 adults with ADHD and 20 age- and sex-matched healthy volunteers.

Results: Examination of healthy control subjects verified presence of an antiphasic or negative relationship between activity in dorsal anterior cingulate cortex (centered at x = 8, y = 7, z = 38) and in default-mode network components. Group analyses revealed ADHD-related compromises in this relationship, with decreases in the functional connectivity between the anterior cingulate and precuneus/posterior cingulate cortex regions (p < .0004, corrected). Secondary analyses revealed an extensive pattern of ADHD-related decreases in connectivity between precuneus and other default-mode network components, including ventromedial prefrontal cortex (p < 3 x 10(-11), corrected) and portions of posterior cingulate (p < .02, corrected).

Conclusions: Together with prior unbiased anatomic evidence of posterior volumetric abnormalities, our findings suggest that the long-range connections linking dorsal anterior cingulate to posterior cingulate and precuneus should be considered as a candidate locus of dysfunction in ADHD.

Conflict of interest statement

Disclosure of Biomedical Financial Interests and Potential Conflicts of Interest:

Drs. Castellanos, Kelly, Uddin, Ghaffari, Kirsch, Di Martino, Biswal, Milham and Messrs. Margulies, Shaw, and Shehzad reported no biomedical financial interests or potential conflicts of interest.

Dr. Sonuga-Barke has potential conflicts of interest in relation to UCB Pharmaceuticals (consultancy, advisory board and speaker honoraria), Janssen Cilag (consultancy, research grant, speaker honoraria), Shire Pharmaceuticals (advisory board) and Medice (speaker honoraria).

Dr. Rotrosen reports consulting income from Axonyx, Inc., and United BioSource Corp.; research support from Alkermes, Inc., NIDA, and NIMH; equity interests in Alcon, American Oriental Bioengineering, Amgen, Atrion, Avon Products, Biogen Idec, Biosite, Colgate-Palmolive, Cooper Companies, Cyberoptics, Dentsply International, Dov Pharmaceutical, Dow Chemical, Elan, Genentech, Gillette, ICOS, Invitrogen, Ivax, Kinetic Concepts, Lyondell Chemical, Mikron Infrared, Mylan Labs, Polymedica, Procter and Gamble, PDL Biopharma Inc, Respironics, St. Jude Medical, and Tyco; and no potential conflicts of interest.

Dr. Adler receives grant/research support from Abbot Laboratories, Cortex Pharmaceuticals, Bristol-Myers Squibb, Merck & Co, Novartis Pharmaceuticals, Pfizer, Shire, Eli Lilly, Ortho McNeil/Johnson and Johnson, New River Pharmaceuticals, Cephalon, Neurosearch; he is a member of speakers bureaus for Eli Lilly and Shire; serves on the advisory boards and as a consultant for Abbot Laboratories, Cortex Pharmaceuticals, Novartis Pharmaceuticals, Pfizer, Shire, Eli Lilly, Ortho McNeil//Johnson and Johnson, New River Pharmaceuticals, Cephalon, Merck, and Neurosearch.

Figures

Figure 1
Figure 1
Data analytical path for preprocessing, extraction of region of interest and nuisance covariate timeseries, individual subject multiple regression analyses, and mixed effects analyses of group results.
Figure 2
Figure 2
Functional connectivity analyses were carried out using a spherical ROI located in ACC (diameter = 7mm, number of voxels = 123; x=8, y=9, z=35), based upon the findings of Weissman et al. (2006) (depicted in panel A). Voxels positively (red) and negatively (blue) predicted by the timeseries for the ACC ROI are depicted in panel B (sagittal slice: x=6; coronal slice: y=62). A robust negative or antiphasic relationship was noted between the ACC seed region and default-mode network components (i.e., an increase in ACC activity predicts a decrease in default-mode activity). ADHD-related decreases in functional connectivity were noted between ACC and precuneus.
Figure 3
Figure 3
Secondary functional connectivity analyses were carried out using the posterior cingulate/precuneus cluster identified in our primary analyses as the seed region (see panel A). For each group (ADHD, controls), voxels positively (red) and negatively (blue) predicted by the timeseries for the seed region are depicted in panel B. These analyses provided further support for ADHD-related decreases in precuneus/ACC connectivity. Furthermore, they identified areas of ADHD-related decreases in connectivity among precuneus and other default mode network components, including ventromedial prefrontal cortex and anterior portions of posterior cingulate cortex.
Figure 4
Figure 4
Decreased ACC-Precuneus Connectivity in ADHD. The scatter plot depicts the mean parameter estimates for dACC connectivity (seed region: x=8, y=7, z=38) in the precuneus/PCC region found to exhibit ADHD-related decrease in anti-relationship with anterior cingulate cortex. As depicted in the plot, while spontaneous activity in ACC negatively predicted activity in precuneus/PCC for controls, no such relationship is found in ACC (p < 9 × 10−6).

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