Altered Cortico-Striatal–Thalamic Connectivity in Relation to Spatial Working Memory Capacity in Children with ADHD

Introduction: Attention deficit hyperactivity disorder (ADHD) captures a heterogeneous group of children, who are characterized by a range of cognitive and behavioral symptoms. Previous resting-state functional connectivity MRI (rs-fcMRI) studies have sought to understand the neural correlates of ADHD by comparing connectivity measurements between those with and without the disorder, focusing primarily on cortical–striatal circuits mediated by the thalamus. To integrate the multiple phenotypic features associated with ADHD and help resolve its heterogeneity, it is helpful to determine how specific circuits relate to unique cognitive domains of the ADHD syndrome. Spatial working memory has been proposed as a key mechanism in the pathophysiology of ADHD. Methods: We correlated the rs-fcMRI of five thalamic regions of interest (ROIs) with spatial span working memory scores in a sample of 67 children aged 7–11 years [ADHD and typically developing children (TDC)]. In an independent dataset, we then examined group differences in thalamo-striatal functional connectivity between 70 ADHD and 89 TDC (7–11 years) from the ADHD-200 dataset. Thalamic ROIs were created based on previous methods that utilize known thalamo-cortical loops and rs-fcMRI to identify functional boundaries in the thalamus. Results/Conclusion: Using these thalamic regions, we found atypical rs-fcMRI between specific thalamic groupings with the basal ganglia. To identify the thalamic connections that relate to spatial working memory in ADHD, only connections identified in both the correlational and comparative analyses were considered. Multiple connections between the thalamus and basal ganglia, particularly between medial and anterior dorsal thalamus and the putamen, were related to spatial working memory and also altered in ADHD. These thalamo-striatal disruptions may be one of multiple atypical neural and cognitive mechanisms that relate to the ADHD clinical phenotype

Maturing Thalamocortical Functional Connectivity Across Development

Recent years have witnessed a surge of investigations examining functional brain organization using resting-state functional connectivity MRI (rs-fcMRI). To date, this method has been used to examine systems organization in typical and atypical developing populations. While the majority of these investigations have focused on cortical–cortical interactions, cortical–subcortical interactions also mature into adulthood. Innovative work by Zhang et al. (2008) in adults have identified methods that utilize rs-fcMRI and known thalamo-cortical topographic segregation to identify functional boundaries in the thalamus that are remarkably similar to known thalamic nuclear grouping. However, despite thalamic nuclei being well formed early in development, the developmental trajectory of functional thalamo-cortical relations remains unexplored. Thalamic maps generated by rs-fcMRI are based on functional relationships, and should modify with the dynamic thalamo-cortical changes that occur throughout maturation. To examine this possibility, we employed a strategy as previously described by Zhang et al. to a sample of healthy children, adolescents, and adults. We found strengthening functional connectivity of the cortex with dorsal/anterior subdivisions of the thalamus, with greater connectivity observed in adults versus children. Temporal lobe connectivity with ventral/midline/posterior subdivisions of the thalamus weakened with age. Changes in sensory and motor thalamo-cortical interactions were also identified but were limited. These findings are consistent with known anatomical and physiological cortical–subcortical changes over development. The methods and developmental context provided here will be important for understanding how cortical–subcortical interactions relate to models of typically developing behavior and developmental neuropsychiatric disorders

Developments and challenges in the diagnosis and treatment of ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder, often associated with other psychiatric comorbidities, functional impairments, and poor long-term outcomes. The objective of this selected review is to describe current advances and challenges in the diagnosis and treatment of ADHD. The disorder is associated with neurobiological underpinnings and is highly heterogeneous in various aspects, such as symptom profiles, cognitive impairments, and neurobiological and genetic features. The efficacy and safety of short-term pharmacological treatments across the life cycle is well studied, but further research investigating long-term treatment, impact of treatment in preschoolers, and non-pharmacological interventions is needed. Future research is also needed to better characterize the neurodevelopmental pathways of the disorder, linking clinical and neurobiological information, less investigated populations, and new interventions

Characterizing heterogeneity in children with and without ADHD based on reward system connectivity

One potential obstacle limiting our ability to clarify ADHD etiology is the heterogeneity within the disorder, as well as in typical samples. In this study, we utilized a community detection approach on 106 children with and without ADHD (aged 7–12 years), in order to identify potential subgroups of participants based on the connectivity of the reward system. Children with ADHD were compared to typically developing children within each identified community, aiming to find the community-specific ADHD characteristics. Furthermore, to assess how the organization in subgroups relates to behavior, we evaluated delay-discounting gradient and impulsivity-related temperament traits within each community. We found that discrete subgroups were identified that characterized distinct connectivity profiles in the reward system. Importantly, which connections were atypical in ADHD relative to the control children were specific to the community membership. Our findings showed that children with ADHD and typically developing children could be classified into distinct subgroups according to brain functional connectivity. Results also suggested that the differentiation in “functional” subgroups is related to specific behavioral characteristics, in this case impulsivity. Thus, combining neuroimaging data and community detection might be a valuable approach to elucidate heterogeneity in ADHD etiology and examine ADHD neurobiology

Altered cortico-striatal-thalamic connectivity in relation to spatial working memory capacity in children with ADHD

Introduction: Attention deficit hyperactivity disorder (ADHD) captures a heterogeneous group of children, who are characterized by a range of cognitive and behavioral symptoms. Previous resting state functional connectivity (rs-fcMRI) studies have sought to understand the neural correlates of ADHD by comparing connectivity measurements between those with and without the disorder, focusing primarily on cortical-striatal circuits mediated by the thalamus. To integrate the multiple phenotypic features associated with ADHD and help resolve its heterogeneity, it is helpful to determine how specific circuits relate to unique cognitive domains of the ADHD syndrome. Spatial working memory has been proposed as a key mechanism in the pathophysiology of ADHD.Methods: We correlated the rs-fcMRI of five thalamic regions of interest with spatial span working memory scores in a sample of 67 children aged 7-11 years (ADHD and typically developing children; TDC). In an independent dataset, we then examined group differences in thalamo-striatal functional connectivity between 70 ADHD and 89 TDC (7-11 years) from the ADHD-200 dataset. Thalamic regions of interest were created based on previous methods that utilize known thalamo-cortical loops and rs-fcMRI to identify functional boundaries in the thalamus.Results/Conclusions: Using these thalamic regions, we found atypical rs-fcMRI between specific thalamic groupings with the basal ganglia. To identify the thalamic connections that relate to spatial working memory in ADHD, only connections identified in both the correlational and comparative analyses were considered. Multiple connections between the thalamus and basal ganglia, particularly between medial and anterior dorsal thalamus and the putamen, were related to spatial working memory and also altered in ADHD. These thalamo-striatal disruptions may be one of multiple atypical neural and cognitive mechanisms that relate to the ADHD clinical phenotype

Structural and Functional Rich Club Organization of the Brain in Children and Adults

<div><p>Recent studies using Magnetic Resonance Imaging (MRI) have proposed that the brain’s white matter is organized as a rich club, whereby the most highly connected regions of the brain are also highly connected to each other. Here we use both functional and diffusion-weighted MRI in the human brain to investigate whether the rich club phenomena is present with functional connectivity, and how this organization relates to the structural phenomena. We also examine whether rich club regions serve to integrate information between distinct brain systems, and conclude with a brief investigation of the developmental trajectory of rich-club phenomena. In agreement with prior work, both adults and children showed robust structural rich club organization, comprising regions of the superior medial frontal/dACC, medial parietal/PCC, insula, and inferior temporal cortex. We also show that these regions were highly integrated across the brain’s major networks. Functional brain networks were found to have rich club phenomena in a similar spatial layout, but a high level of segregation between systems. While no significant differences between adults and children were found structurally, adults showed significantly greater functional rich club organization. This difference appeared to be driven by a specific set of connections between superior parietal, insula, and supramarginal cortex. In sum, this work highlights the existence of both a structural and functional rich club in adult and child populations with some functional changes over development. It also offers a potential target in examining atypical network organization in common developmental brain disorders, such as ADHD and Autism.</p></div

Community detection in functional and structural group networks from healthy adults.

<p>Brain regions are colored according to which community they belong to. In the functional network (left), six predominant communities were identified, comprising the Default Mode (red), Cingulo-opercular (pink), Fronto-parietal (yellow), Visual (blue), Orbitofrontal/Limbic (dark red), and Somatosensory (light blue) systems. Communities resembling analogues of the functional systems were identified in the structural network as well (right).</p

Regions that overlap between functional and structural rich clubs in adults.

<p>Overlapping regions, colored in yellow, defined as having degree k> = 14 in both the structural and functional group networks (the rich clubs). Structural-only and functional-only rich nodes are colred in green and red, respectively.</p

Rich club phenomena in structural group network of adults.

<p>(<b>a</b>) Regions comprising the structural rich club are displayed on an average brain surface. Degree k> = 14 was used to define rich club nodes, reflecting the peak value observed in the weighted rich club coefficient curve in (b). Results highlight the involvement of medial parietal/PCC, superior frontal/ACC, insula, and inferior temporal cortex. (<b>b</b>) Rich club coefficients relative to random are shown as weighted in red and as unweighted in dark red. Significant values (p<.05) are signified with an asterisk. (<b>c</b>) Rich club regions from (<b>a</b>) are colored according to community assignments. Below, a spring embedded graph shows rich club nodes and links between them, reflecting a high level of integration between systems. (<b>d, e</b>) Rich club regions with a high Community Index (C > = 3) and a high Distribution Index (D> = 10) are colored. A large proportion of regions are colored, reflecting high levels of integration.</p

Overview of processing pipeline for each subject.

<p><i>Region Selection:</i> T1-weighted image segmentation and parcellation resulted in a white matter mask for further diffusion data processing, as well as 219 cortical regions of interest (ROIs) covering the whole brain (the same ROIs were used for functional and structural analyses). <i>Structural Connections</i>: High-angular diffusion weighted MRI was acquired, and deterministic fiber tractography was performed throughout the white matter mask using a qball scheme. For each unique pair of ROIs, a connection weight was computed as the number of fibers with ends terminating upon them (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0088297#s2" target="_blank">Materials and Methods</a>). This resulted in a weighted network of structural connectivity across the whole brain. <i>Functional Connections:</i> Resting-state BOLD data (rs-fcMRI) was acquired, and timecourses were generated by averaging signal intensity across all voxels within a given region. Cross-correlations between regions were then used to generate the functional connectivity network.</p