ABSTRACT
BACKGROUND AND PURPOSE: The present study utilized a multimodal approach encompassing connectome networks combined with brain volume analysis, and assessment of cortical excitability to provide novel insights into amyotrophic lateral sclerosis (ALS) pathogenesis. METHODS: Magnetic resonance images were acquired using a 3.0-Tesla Signa HDx scanner (GE Healthcare, Milwaukee, WI, USA), using an eight-channel head coil. Magnetic resonance images for the resting-state scan were acquired using an echo-planar imaging magnetic resonance sequence, acquiring 40 contiguous axial/oblique slices. Structural magnetic resonance imaging three-dimensional T1-weighted images were acquired in the sagittal plane using three-dimensional spoiled gradient echo sequences. For structural imaging, a T1-weighted high-resolution (3.0-Tesla) magnetic resonance imaging scan was used. Cortical excitability was assessed by using the threshold-tracking transcranial magnetic stimulation paradigm. Network-based statistics and whole-brain functional topology (using graph theoretical approaches) assessed functional connectivity. RESULTS: Using a global network-based statistical analysis approach, functional connectivity was increased in 12 network edges connecting 14 nodes (P < 0.05) within the frontal, temporal, parietal and subcortical regions. Analysis of local connectedness disclosed dichotomous effects with reduced connectivity in frontal regions and increased connectivity in occipital regions in ALS. Cortical hyperexcitability was evident in patients with ALS, negatively correlated with functional connectivity changes in the pre-central gyrus (P < 0.01). Connectivity changes in the frontal regions were negatively associated with functional disability (P < 0.05). CONCLUSIONS: Multimodal assessment of cortical function in patients with ALS identified deficits in functional connectivity associated with cortical hyperexcitability that correlated with patient disability. Novel integration of functional brain assessment further contributes to the understanding of disease pathogenesis in ALS.
Subject(s)
Amyotrophic Lateral Sclerosis/diagnostic imaging , Brain/drug effects , Adult , Aged , Amyotrophic Lateral Sclerosis/pathology , Brain/pathology , Connectome/methods , Female , Humans , Imaging, Three-Dimensional , Magnetic Resonance Imaging/methods , Male , Middle Aged , Severity of Illness IndexABSTRACT
Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome.