Article

Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI

National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Brain and Development (Impact Factor: 1.54). 04/2007; 29(2):83-91. DOI: 10.1016/j.braindev.2006.07.002
Source: PubMed

ABSTRACT In children with attention deficit hyperactivity disorder (ADHD), functional neuroimaging studies have revealed abnormalities in various brain regions, including prefrontal-striatal circuit, cerebellum, and brainstem. In the current study, we used a new marker of functional magnetic resonance imaging (fMRI), amplitude of low-frequency (0.01-0.08Hz) fluctuation (ALFF) to investigate the baseline brain function of this disorder. Thirteen boys with ADHD (13.0+/-1.4 years) were examined by resting-state fMRI and compared with age-matched controls. As a result, we found that patients with ADHD had decreased ALFF in the right inferior frontal cortex, [corrected] and bilateral cerebellum and the vermis as well as increased ALFF in the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem. This resting-state fMRI study suggests that the changed spontaneous neuronal activity of these regions may be implicated in the underlying pathophysiology in children with ADHD.

1 Bookmark
 · 
332 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Aiming at abundant scientific and engineering data with not only high dimensionality but also complex structure, we study the regression problem with a multidimensional array (tensor) response and a vector predictor. Applications include, among others, comparing tensor images across groups after adjusting for additional covariates, which is of central interest in neuroimaging analysis. We propose parsimonious tensor response regression adopting a generalized sparsity principle. It models all voxels of the tensor response jointly, while accounting for the inherent structural information among the voxels. It effectively reduces the number of free parameters, leading to feasible computation and improved interpretation. We achieve model estimation through a nascent technique called the envelope method, which identifies the immaterial information and focuses the estimation based upon the material information in the tensor response. We demonstrate that the resulting estimator is asymptotically efficient, and it enjoys a competitive finite sample performance. We also illustrate the new method on two real neuroimaging studies.
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper analyzes the resting state fMRI signal of 21 ADHD subjects and 27 healthy volunteers, and proposes a novel method for extracting an effective feature in frequency domain. Utilizing this feature, the ADHD subjects and the control persons are classified with an accuracy of 95.83% by support vector machine (SVM). Furthermore, using this method, some specific brain regions such as the right amygdaloid nucleus, the left thalamus, cerebellum and vermis, with high classification accuracies, are relative to the pathological mechanism of ADHD which are consistent with the previous research results.
    2013 IEEE Third International Conference on Information Science and Technology (ICIST); 12/2013
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: There is evidence that attention-deficit/hyperactivity disorder (ADHD) is associated with linguistic difficulties. However, the pathophysiology underlying these difficulties is yet to be determined. This study investigates functional abnormalities in Broca's area, which is associated with speech production and processing, in adolescents with ADHD by means of resting-state fMRI. Data for the study was taken from the ADHD-200 project and included 267 ADHD patients (109 with combined inattentive/hyperactive subtype and 158 with inattentive subtype) and 478 typically-developing control (TDC) subjects. An analysis of fractional amplitude of low-frequency fluctuations (fALFF), which reflects spontaneous neural activity, in Broca's area (Brodmann Areas 44/45) was performed on the data and the results were compared statistically across the participant groups. fALFF was found to be significantly lower in the ADHD inattentive group as compared to TDC in BA 44, and in the ADHD combined group as compared to TDC in BA 45. The results suggest that there are functional abnormalities in Broca's area with people suffering from ADHD, and that the localization of these abnormalities might be connected to particular language deficits associated with ADHD subtypes, which we discuss in the article. The findings might help explore the underlying causes of specific language difficulties in ADHD. Pikusa, M. and R. Jończyk. In press. " Functional abnormalities in Broca's area in adolescents with ADHD: resting-state fMRI ". PSiCL
    Poznan Studies in Contemporary Linguistics 01/2015;

Full-text (2 Sources)

Download
3,725 Downloads
Available from
Jun 5, 2014