Functional and structural brain network development in children with attention deficit hyperactivity disorder.

Attention deficit hyperactivity disorder (ADHD) is a prevalent childhood neurodevelopmental disorder. Given the profound brain changes that occur during childhood and adolescence, it is important to examine longitudinal changes of both functional and structural brain connectivity across development in ADHD. This study aimed to examine the development of functional and structural connectivity in children with ADHD compared to controls using graph metrics. One hundred and seventy five individuals (91 children with ADHD and 84 non-ADHD controls) participated in a longitudinal neuroimaging study with up to three waves. Graph metrics were derived from 370 resting state fMRI (197 Control, 173 ADHD) and 297 diffusion weighted imaging data (152 Control, 145 ADHD) acquired between the ages of 9 and 14. For functional connectivity, children with ADHD (compared to typically developing children) showed lower degree, local efficiency and betweenness centrality predominantly in parietal, temporal and visual cortices and higher degree, local efficiency and betweenness centrality in frontal, parietal, and temporal cortices. For structural connectivity, children with ADHD had lower local efficiency in parietal and temporal cortices and, higher degree and betweenness centrality in frontal, parietal and temporal cortices. Further, differential developmental trajectories of functional and structural connectivity for graph measures were observed in higher-order cognitive and sensory regions. Our findings show that topology of functional and structural connectomes matures differently between typically developing controls and children with ADHD during childhood and adolescence. Specifically, functional and structural neural circuits associated with sensory and various higher order cognitive functions are altered in children with ADHD.

Semi-Supervised Nonnegative Matrix Factorization of Wide-Field Fluorescence Microscopic Images for Tissue Diagnosis.

This study tests the use of a constrained nonnegative matrix factorization (NMF) algorithm to explore the comparatively new field of chemometric microscopy to support tissue diagnosis. The algorithm can extract the spectral signature and the absolute concentration map of endogenous fluorophores from wide-field microscopic images. The resultant data distinguished normal and fibrous calvarial tissues, based on the changes in their spectral signatures. The absolute concentration map of endogenous fluorophores, nicotinamide adenine dinucleotide (NADH), flavin adenine dinucleotide (FAD), and lipofuscin were derived from microscopic images and compared with the fluorescence from pure fluorophores. While the absolute concentration of NADH increased, the same of FAD and lipofuscin decreased from a normal to fibrous calvarial condition. An increase in the optical redox ratio, possibly due to the metabolic changes during the development of fibrosis, was observed. Differentiating tissue types using the absolute concentration map was found to be considerably more precise than that achievable with relative concentration. The quantification of fluorophores with reference to the absolute concentration map can eliminate uncertainties due to system responses or measurement details, thereby generating more biologically apposite data. Wide-field microscopy augmented with a constrained NMF algorithm could emerge as an advanced diagnostic tool, potentially heralding the emergence of chemometric microscopy.

Longitudinal Changes of Resting-State Networks in Children With Attention-Deficit/Hyperactivity Disorder and Typically Developing Children.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent childhood neurodevelopmental disorder. Given the profound brain changes that occur across childhood and adolescence, it is important to identify functional networks that exhibit differential developmental patterns in children with ADHD. This study sought to examine whether children with ADHD exhibit differential developmental trajectories in functional connectivity compared with typically developing children using a network-based approach. METHODS: This longitudinal neuroimaging study included 175 participants (91 children with ADHD and 84 control children without ADHD) between ages 9 and 14 and up to 3 waves (173 total resting-state scans in children with ADHD and 197 scans in control children). We adopted network-based statistics to identify connected components with trajectories of development that differed between groups. RESULTS: Children with ADHD exhibited differential developmental trajectories compared with typically developing control children in networks connecting cortical and limbic regions as well as between visual and higher-order cognitive regions. A pattern of reduction in functional connectivity between corticolimbic networks was seen across development in the control group that was not present in the ADHD group. Conversely, the ADHD group showed a significant decrease in connectivity between predominantly visual and higher-order cognitive networks that was not displayed in the control group. CONCLUSIONS: Our findings show that the developmental trajectories in children with ADHD are characterized by a subnetwork involving different trajectories predominantly between corticolimbic regions and between visual and higher-order cognitive network connections. These findings highlight the importance of examining the longitudinal maturational course to understand the development of functional connectivity networks in children with ADHD.

Cortical structural and functional coupling during development and implications for attention deficit hyperactivity disorder.

Functional connectivity is scaffolded by the structural connections of the brain. Disruptions of either structural or functional connectivity can lead to deficits in cognitive functions and increase the risk for neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). To date, very little research has examined the association between structural and functional connectivity in typical development, while no studies have attempted to understand the development of structure-function coupling in children with ADHD. 175 individuals (84 typically developing children and 91 children with ADHD) participated in a longitudinal neuroimaging study with up to three waves. In total, we collected 278 observations between the ages 9 and 14 (139 each in typically developing controls and ADHD). Regional measures of structure-function coupling were calculated at each timepoint using Spearman's rank correlation and mixed effect models were used to determine group differences and longitudinal changes in coupling over time. In typically developing children, we observed increases in structure-function coupling strength across multiple higher-order cognitive and sensory regions. Overall, weaker coupling was observed in children with ADHD, mainly in the prefrontal cortex, superior temporal gyrus, and inferior parietal cortex. Further, children with ADHD showed an increased rate of coupling strength predominantly in the inferior frontal gyrus, superior parietal cortex, precuneus, mid-cingulate, and visual cortex, compared to no corresponding change over time in typically developing controls. This study provides evidence of the joint maturation of structural and functional brain connections in typical development across late childhood to mid-adolescence, particularly in regions that support cognitive maturation. Findings also suggest that children with ADHD exhibit different patterns of structure-function coupling, suggesting atypical patterns of coordinated white matter and functional connectivity development predominantly in the regions overlapping with the default mode network, salience network, and dorsal attention network during late childhood to mid-adolescence.

Relationship between Cerebral Perfusion on Arterial Spin Labeling (ASL) MRI with Brain Volumetry and Cognitive Performance in Mild Cognitive Impairment and Dementia due to Alzheimer's Disease.

CONTEXT: Cerebral blood flow (CBF) measurement using arterial spin labelling (ASL) MRI sequences has recently emerged as a prominent tool in dementia research. AIMS: To establish association between quantified regional cerebral perfusion and gray matter (GM) volumes with cognitive measures in mild cognitive impairment (MCI) and early Alzheimer's Dementia (AD), using three dimensional fast spin echo pseudo-continuous ASL MRI sequences. SETTINGS AND DESIGN: Hospital-based cross-sectional study. METHODS AND MATERIAL: Three age-matched groups, i.e., 21 cognitively normal healthy controls (HC), 20 MCI and 19 early AD patients diagnosed using neuropsychological tests and who consented for multimodality 3T MRI were recruited for the study. STATISTICAL ANALYSIS USED: Statistical parametric mapping and regions of interest (ROI) multivariate analysis of variance was used to ascertain differences between patients and controls on MRI-volumetry and ASL. Linear regression was used to assess relationship between CBF with GM atrophy and neuropsychological test measures. RESULTS: Compared to HC, patients with MCI and AD had significantly lower quantified perfusion in posterior cingulate and lingual gyri, over hippocampus in MCI, with no differences noted between MCI and AD. Atrophy over the middle temporal gyrus and hippocampus differentiated AD from MCI. No significant positive correlations were noted between perfusion and GM volumes in ROI with the exception of temporal neocortex. Significantly positive coefficient b-value (p < 0.01) were apparent between global cognition with CBF in precuneus, temporal neocortex and precuneus volume, with negative b-values noted between medial temporal CBF for global cognition and recall scores. CONCLUSIONS: ROI-based CBF measurements differentiated MCI and AD from HC; volumetry of medial and neocortical temporal GM separates AD from MCI. Correlations between CBF and neuropsychology are variable and require further longitudinal studies to gauge its predictive utility on cognitive trajectory in MCI.

Does resting state functional connectivity differ between mild cognitive impairment and early Alzheimer's dementia?

PURPOSE: This study aimed to investigate differences in functional connectivity (FC) among different resting state networks (RSN) in clinically non-progressive mild cognitive impairment (MCI) and Alzheimer's disease (AD). METHODS: Using 3T MRI acquired resting-state functional MRI (rs-fMRI), we attempted identification of different RSN using independent component analysis (ICA) in amnestic-MCI, convertors to early AD and age-matched cognitively normal healthy controls. Regions of interest (ROI) that showed significant differences in connectivity on group ICA were selected as seeds for seed-voxel analysis. Group differences in FC for each network-connectivity map were entered into a general linear model with age, gender and total intra-cranial volume (TIV) as covariates. RESULTS: In this cross-sectional design 31 HC, 30 MCI and 30 MCI-convertors to early AD were evaluated. Seed-based analysis between AD and controls revealed reduced posterior connectivity within the default mode (DMN), dorsal attention (DAN) and antero-posterior connectivity with sensori-motor (SMN) networks. Reduced cerebellar connectivity of DMN and posterior connectivity within the frontal parietal network (FPN) separated AD from MCI. MCI-control comparisons revealed differences only on ICA. Positive correlation was observed between FC in DMN network clusters with verbal list-learning (r = 0.50) and recall scores (r = 0.51) in AD, the latter additionally demonstrating correlation with SMN clusters (r = 0.50). CONCLUSIONS: Widespread network hypo-connectivity is apparent in AD as opposed to MCI non-convertors in comparison to controls, along with positive correlation with memory scores. Reduced connectivity involving DMN and FPN helps to differentiate between AD and MCI-nonconvertors to dementia. Longitudinal studies are required into utility of these measures.