A Multi-Methodological MR Resting State Network Analysis to Assess the Changes in Brain Physiology of Children with ADHD

Abstract

The purpose of this work was to highlight the neurological differences between the MR resting state networks of a group of children with ADHD (pre-treatment) and an age-matched healthy group. Results were obtained using different image analysis techniques. A sample of n = 46 children with ages between 6 and 12 years were included in this study (23 per cohort). Resting state image analysis was performed using ReHo, ALFF and ICA techniques. ReHo and ICA represent connectivity analyses calculated with different mathematical approaches. ALFF represents an indirect measurement of brain activity. The ReHo and ICA analyses suggested differences between the two groups, while the ALFF analysis did not. The ReHo and ALFF analyses presented differences with respect to the results previously reported in the literature. ICA analysis showed that the same resting state networks that appear in healthy volunteers of adult age were obtained for both groups. In contrast, these networks were not identical when comparing the healthy and ADHD groups. These differences affected areas for all the networks except the Right Memory Function network. All techniques employed in this study were used to monitor different cerebral regions which participate in the phenomenological characterization of ADHD patients when compared to healthy controls. Results from our three analyses indicated that the cerebellum and mid-frontal lobe bilaterally for ReHo, the executive function regions in ICA, and the precuneus, cuneus and the clacarine fissure for ALFF, were the “hubs” in which the main inter-group differences were found. These results do not just help to explain the physiology underlying the disorder but open the door to future uses of these methodologies to monitor and evaluate patients with ADHD.

The Relationship Between Motor Skills, Social Problems, and ADHD Symptomatology: Does It Vary According to Parent and Teacher Report?

“…Specifically, better motor performance was related to fewer social problems, as rated by parents (Ayaz, Ayaz, Yazgan, & Akin, 2013). Further research is needed, particularly since social competence has been highlighted as a significant predictor for optimal developmental outcomes in both the short term and the long term (Alonso Bde et al, 2014). For example, childhood peer rejection has been shown to be one of the strongest predictors of current and future adjustment problems (Bagwell, Newcomb, & Bukowski, 1998 (Pedersen, Vitaro, Barker, & Borge, 2007).…”

Subject-adaptive Integration of Multiple SICE Brain Networks with Different Sparsity

“…Especially, as indicated in Figure 8, the most strongest connections include connections within frontal gyrus, e.g. Superior frontal gyrus dorsolateral-Middle frontal gyrus (4,8), Middle frontal gyrus orbital part-Inferior frontal gyrus opercular part (9, 11) and connections between Hippocampus (37∼40), Amygdala (41∼42) and Calcarine (43∼44). An interesting thing this figure presented is that the same parts in left and right brain are often closely functionally connected.…”

“…This is expected since the ROIs in the same lobe have higher chances to be anatomically and functionally connected. Also, most of the functional abnormalities identified in the literature [45,8] are within lobes. Especially, as indicated in Figure 8, the most strongest connections include connections within frontal gyrus, e.g.…”

“…For example, Attention Deficit Hyperactivity Disorder (ADHD) affects at least 5-10% of school-age children and, unfortunately, there does not exist well-known biological diagnosis. Recent studies have found increased connectivities between the right pulvinar and bilateral occipital regions and reduced connectivities between bilateral pulvinar and right prefrontal regions for ADHD patients in comparison with healthy controls [6,7,8]. Another example is Alzheimer's disease (AD).…”

Functional MR imaging (BOLD and resting States). Clinical and research applications

“…Therefore it is of great interest if possible to find a diagnostic technique which can answer with great precision if a child has it or not and furthermore, which of the three subtypes it is. In our study 6 we aimed at using RS to address the question if there was a biomarker in a Mexican population that could be used to diagnose individual subjects. Several RS studies (Fig 3.…”