Statistical analyses of structural magnetic resonance imaging of the head of the caudate nucleus in Colombian children with attention-deficit hyperactivity disorder

Alterations in Striatal Architecture and Biochemical Markers' Levels During Postnatal Development in the Rat Model of an Attention Deficit/Hyperactivity Disorder (ADHD)

Attention deficit/hyperactivity disorder (ADHD) is defined as a neurodevelopmental condition. The precise underlying mechanisms remain incompletely elucidated. A body of research suggests disruptions in both the cellular architecture and neuronal function within the brain regions of individuals with ADHD, coupled with disturbances in the biochemical parameters. This study seeks to evaluate the morphological characteristics with a volume measurement of the striatal regions and a neuron density assessment within the studied areas across different developmental stages in Spontaneously Hypertensive Rats (SHRs) and Wistar Kyoto Rats (WKYs). Furthermore, the investigation aims to scrutinize the levels and activities of specific markers related to immune function, oxidative stress, and metabolism within the striatum of juvenile and maturing SHRs compared to WKYs. The findings reveal that the most pronounced reductions in striatal volume occur during the juvenile stage in SHRs, alongside alterations in neuronal density within these brain regions compared to WKYs. Additionally, SHRs exhibit heightened levels and activities of various markers, including RAC-alpha serine/threonine-protein kinase (AKT-1), glucocorticoid receptor (GCsRβ), malondialdehyde (MDA), sulfhydryl groups (-SH), glucose (G), iron (Fe), lactate dehydrogenase (LDH). alanine transaminase (ALT), and aspartate transaminase (AST). In summary, notable changes in striatal morphology and elevated levels of inflammatory, oxidative, and metabolic markers within the striatum may be linked to the disrupted brain development and maturation observed in ADHD.

The Limbic System in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: A Longitudinal Structural Magnetic Resonance Imaging Analysis

Background

During childhood and adolescence, attention-deficit/hyperactivity disorder (ADHD) is associated with changes in symptoms and brain structures, but the link between brain structure and function remains unclear. The limbic system, often termed the "emotional network," plays an important role in a number of neurodevelopmental disorders, yet this brain network remains largely unexplored in ADHD. Investigating the developmental trajectories of key limbic system structures during childhood and adolescence will provide novel insights into the neurobiological underpinnings of ADHD.

Methods

Structural magnetic resonance imaging data (380 scans), emotional regulation (Affective Reactivity Index), and ADHD symptom severity (Conners 3 ADHD Index) were measured at up to 3 time points between 9 and 14 years of age in a sample of children and adolescents with ADHD (n = 57) and control children (n = 109).

Results

Compared with the control group, the ADHD group had lower volume of the amygdala (left: β standardized [β_std] = -0.38; right: β_std = -0.34), hippocampus (left: β_std = -0.44; right: β_std = -0.34), cingulate gyrus (left: β_std = -0.42; right: β_std = -0.32), and orbitofrontal cortex (right: β_std = -0.33) across development (9-14 years). There were no significant group-by-age interactions in any of the limbic system structures. Exploratory analysis found a significant Conners 3 ADHD Index-by-age interaction effect on the volume of the left mammillary body (β_std = 0.17) in the ADHD group across the 3 study time points.

Conclusions

Children and adolescents with ADHD displayed lower volume and atypical development in limbic system structures. Furthermore, atypical limbic system development was associated with increased symptom severity, highlighting a potential neurobiological correlate of ADHD severity.

Cortical Thickness Abnormalities in Attention Deficit Hyperactivity Disorder Revealed by Structural Magnetic Resonance Imaging: Newborns to Young Adults

Attention deficit hyperactivity disorder is a neurodevelopmental condition for which we have an incomplete understanding, and so brain imaging methods, such as magnetic resonance imaging (MRI) may be able to assist in characterizing and understanding the presentation of the brain in an ADHD population. Statistical and computational methods were used to compare participants with attention deficit hyperactivity disorder (ADHD) and neurotypical controls at a variety of developmental stages to assess detectable abnormal neurodevelopment potentially associated with ADHD and to assess our ability to diagnose and characterize the condition from real-world clinical magnetic resonance imaging (MRI) examinations. T1-weighted structural MRI examinations (n=993; 0-31 years old [YO]) were obtained from neurotypical controls and 637 examinations were obtained from patients with ADHD (0-26 YO). Measures of average (mean) regional cortical thickness were acquired, alongside the first reporting of regional cortical thickness variability (as assessed with the standard deviation [SD]) in ADHD. A comparison between the inattentive and combined (inattentive and hyperactive) subtypes of ADHD is also provided. A preliminary independent validation was also performed on the publicly available ADHD200 dataset. Relative to controls, subjects with ADHD had, on average, lowered SD of cortical thicknesses and increased mean thicknesses across several key regions potentially linked with known symptoms of ADHD, including the precuneus, supramarginal gyrus, etc.

ADHD-inattentive versus ADHD-Combined subtypes: A severity continuum or two distinct entities? A comprehensive analysis of clinical, cognitive and neuroimaging data

The current study aimed to explore the multimodal differences between the inattentive ADHD (ADHD-I) subtype and the combined ADHD (ADHD-C) subtype. A large sample of medication-naïve children with pure ADHD (i.e., without any comorbidity) (145 with ADHD-I, 132 with ADHD-C) and healthy controls (n = 98) were recruited. A battery of multiple scales and cognitive tests were utilized to assess the clinical and cognitive profiles of each individual. In addition, structural and diffusion magnetic resonance imaging (MRI) were acquired for 120 subjects with ADHD and 85 controls. Regional gray matter volume, white matter volume, and diffusion tensors, e.g., axial diffusivity (AD), were compared among the three groups in a whole-brain voxel-wise manner. Compared with healthy controls, both ADHD groups exhibited elevated levels of behavioral and emotional problems. The ADHD-C group had more behavioral problems and emotional liability, as well as less anxiety, than the ADHD-I group. The two ADHD groups were equally impaired in most cognitive domains, with the exception of sustained attention. Compared with healthy controls, the ADHD-C group showed a high gray matter volume (GMV) in the bilateral thalamus and a high white matter volume in the body of the corpus callosum, while the ADHD-I group presented an elevated GMV mainly in the left precentral gyrus and posterior cingulate cortex. Compared with participants with ADHD-C and healthy controls, subjects with ADHD-I showed increased AD in widespread brain regions. Our study has revealed a distinct, interconnected pattern of behavioral, cognitive, and brain structural characteristics in children with different ADHD subtypes.

No support for white matter connectivity differences in the combined and inattentive ADHD presentations

Evidence from functional neuroimaging studies support neural differences between the Attention Deficit Hyperactivity Disorder (ADHD) presentation types. It remains unclear if these neural deficits also manifest at the structural level. We have previously shown that the ADHD combined, and ADHD inattentive types demonstrate differences in graph properties of structural covariance suggesting an underlying difference in neuroanatomical organization. The goal of this study was to examine and validate white matter brain organization between the two subtypes using both scalar and connectivity measures of brain white matter. We used both tract-based spatial statistical (TBSS) and tractography analyses with network-based Statistics (NBS) and graph-theoretical analyses in a cohort of 35 ADHD participants (aged 8-17 years) defined using DSM-IV criteria as combined (ADHD-C) type (n = 19) or as predominantly inattentive (ADHD-I) type (n = 16), and 28 matched neurotypical controls. We performed TBSS analyses on scalar measures of fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivity to assess differences in WM between ADHD types and controls. NBS and graph theoretical analysis of whole brain inter-regional tractography examined connectomic differences and brain network organization, respectively. None of the scalar measures significantly differed between ADHD types or relative to controls. Similarly, there were no tractography connectivity differences between the two subtypes and relative to controls using NBS. Global and regional graph measures were also similar between the groups. A single significant finding was observed for nodal degree between the ADHD-C and controls, in the right insula (corrected p = .029). Our result of no white matter differences between the subtypes is consistent with most previous findings. These findings together might suggest that the white matter structural architecture is largely similar between the DSM-based ADHD presentations is similar to the extent of being undetectable with the current cohort size.

Attention-deficit/hyperactivity disorder is characterized by a delay in subcortical maturation

Although previous studies have found that ADHD is characterized by a delay in cortical maturation, it is not clear whether this phenomenon was secondary to developmental trajectories in subcortical regions (caudate, putamen, pallidum, thalamus, hippocampus and amygdala). Using the ADHD-200 dataset, we estimated subcortical volumes in 339 individuals with ADHD and 568 typically developing controls. We defined the growth trajectory of each subcortical structure, delineating a phase of childhood increase followed by an adolescent decrease in subcortical volumes using a quadratic growth model. From these trajectories, the age of attaining peak subcortical volumes was derived and used as an index of subcortical maturation. We found that subcortical structures (caudate, putamen, pallidum, thalamus, hippocampus and amygdala) followed curvilinear trajectories similar to those reported in previous studies. The volumes of these subcortical structures in ADHD were also delayed in the developmental trajectory, which suggested that ADHD may be characterized by a delay in subcortical maturation. This delay may lead to a shift in which individuals with ADHD go through the process of pruning the nerve connections that is part of the normal maturation process during adolescence. Further, we also found that the asymmetric development of subcortical structures was abnormal in ADHD, which resulted from the imbalance of the maturation delay of bilateral subcortical structures. The subcortical maturation delay may play an important role in the pathophysiology of ADHD. Our findings provide new potential targets to investigate the pathophysiology of ADHD.

Exploring the Neural Structures Underlying the Procedural Memory Network as Predictors of Language Ability in Children and Adolescents With Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder

Introduction: There is significant overlap in the type of structural language impairments exhibited by children with autism spectrum disorder (ASD) and children with attention deficit hyperactivity disorder (ADHD). This similarity suggests that the cognitive impairment(s) contributing to the structural language deficits in ASD and ADHD may be shared. Previous studies have speculated that procedural memory deficits may be the shared cognitive impairment. The procedural deficit hypothesis (PDH) argues that language deficits can be explained by differences in the neural structures underlying the procedural memory network. This hypothesis is based on the premise that the neural structures comprising the procedural network support language learning. In this study, we aimed to test the PDH in children with ASD, ADHD, and typical development (TD).

Methods: One hundred and sixty-three participants (ages 10–21): 91 with ASD, 26 with ADHD, and 46 with TD, completed standardized measures of cognitive and language ability as well as structural magnetic resonance imaging. We compared the structural language abilities, the neural structures underlying the procedural memory network, and the relationship between structural language and neural structure across diagnostic groups.

Results: Our analyses revealed that while the structural language abilities differed across ASD, ADHD, and TD groups, the thickness, area, and volume of the structures supporting the procedural memory network were not significantly different between diagnostic groups. Also, several neural structures were associated with structural language abilities across diagnostic groups. Only two of these structures, the inferior frontal gyrus, and the left superior parietal gyrus, are known to be linked to the procedural memory network.

Conclusions: The inferior frontal gyrus and the left superior parietal gyrus, have well-established roles in language learning independent of their role as part of the procedural memory system. Other structures such as the caudate and cerebellum, with critical roles in the procedural memory network, were not associated with structural language abilities across diagnostic groups. It is unclear whether the procedural memory network plays a fundamental role in language learning in ASD, ADHD, and TD.

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder

Objective: Insights to underlying neural mechanisms in attention deficit hyperactivity disorder (ADHD) have emerged from neuroimaging research; however, the neural mechanisms that distinguish ADHD subtypes remain inconclusive.

Method: We reviewed 19 studies integrating magnetic resonance imaging [MRI; structural (sMRI), diffusion, functional MRI (fMRI)] findings into a framework exploring pathophysiological mechanisms underlying the combined (ADHD-C) and predominantly inattentive (ADHD-I) ADHD subtypes.

Results: Despite equivocal structural MRI results, findings from fMRI and DTI imaging modalities consistently implicate disrupted connectivity in regions and tracts involving frontal striatal thalamic in ADHD-C and frontoparietal neural networks in ADHD-I. Alterations of the default mode, cerebellum, and motor networks in ADHD-C and cingulo-frontoparietal attention and visual networks in ADHD-I highlight network organization differences between subtypes.

Conclusion: Growing evidence from neuroimaging studies highlight neurobiological differences between ADHD clinical subtypes, particularly from a network perspective. Understanding brain network organization and connectivity may help us to better conceptualize the ADHD types and their symptom variability.

Attention-Deficit/Hyperactivity Disorder Predominantly Inattentive Subtype/Presentation: Research Progress and Translational Studies

Research on the predominantly inattentive attention-deficit/hyperactivity disorder (ADHD-PI) subtype/presentation is important given its high prevalence, but paradoxically it is under-recognized and undertreated. The temporal stability of the inattention symptom could impact the high worldwide prevalence of ADHD-PI. Some evidence suggests differences in the nature of attentional deficit in ADHD-PI vs. that in other subtypes. Impairments in neuropsychological, neurocognitive, and social functioning are also evident in ADHD-PI, which could be specific to the subtype (e.g., processing speed, social perception, and skills), or differ from others in severity. Neuroimaging studies have also revealed ADHD-PI-specific neuropathological abnormalities and those that are shared with other subtypes. ADHD-PI is highly comorbid with learning and internalizing (e.g., anxiety and depression) disorders. There is no solid evidence for ADHD-PI-specific genetic etiologies and differential responses of subtypes to ADHD medications. Translational studies have used the Wistar Kyoto/NCrl substrain which requires further characterizations as an ADHD-PI model. Overall, ADHD-PI research has been conducted in the context of the Diagnostic and Statistical Manual, which arguably does not conform to the widely recognized "dimensional" view of ADHD. The Research Domain Criteria has been proposed to provide a novel framework for understanding the nature of neuropsychiatric illnesses and ultimately improve their diagnosis and treatment.

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder

Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I (n = 16) or as ADHD-C (n = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be reflected in distinct aberrations in underlying brain organization.

Multi-modal, Multi-measure, and Multi-class Discrimination of ADHD with Hierarchical Feature Extraction and Extreme Learning Machine Using Structural and Functional Brain MRI

Structural and functional MRI unveil many hidden properties of the human brain. We performed this multi-class classification study on selected subjects from the publically available attention deficit hyperactivity disorder ADHD-200 dataset of patients and healthy children. The dataset has three groups, namely, ADHD inattentive, ADHD combined, and typically developing. We calculated the global averaged functional connectivity maps across the whole cortex to extract anatomical atlas parcellation based features from the resting-state fMRI (rs-fMRI) data and cortical parcellation based features from the structural MRI (sMRI) data. In addition, the preprocessed image volumes from both of these modalities followed an ANOVA analysis separately using all the voxels. This study utilized the average measure from the most significant regions acquired from ANOVA as features for classification in addition to the multi-modal and multi-measure features of structural and functional MRI data. We extracted most discriminative features by hierarchical sparse feature elimination and selection algorithm. These features include cortical thickness, image intensity, volume, cortical thickness standard deviation, surface area, and ANOVA based features respectively. An extreme learning machine performed both the binary and multi-class classifications in comparison with support vector machines. This article reports prediction accuracy of both unimodal and multi-modal features from test data. We achieved 76.190% (p < 0.0001) classification accuracy in multi-class settings as well as 92.857% (p < 0.0001) classification accuracy in binary settings. In addition, we found ANOVA-based significant regions of the brain that also play a vital role in the classification of ADHD. Thus, from a clinical perspective, this multi-modal group analysis approach with multi-measure features may improve the accuracy of the ADHD differential diagnosis.

Global and local grey matter reductions in boys with ADHD combined type and ADHD inattentive type

Attention-deficit/hyperactivity disorder (ADHD) has reliably been associated with global grey matter reductions but local alterations are largely inconsistent with perhaps the exception of the caudate nucleus. The aim of this study was to examine local and global brain volume differences between typically developing children (TD) and children with a diagnosis of ADHD. We also addressed whether these parameters would differ between children with the ADHD-combined type (ADHD-C) and those with the ADHD-inattentive type (ADHD-I). Using an ROI approach caudate volume differences were also examined. 79 boys between the ages of 8 and 17 participated in the study. Of those 33 met diagnostic criteria for the ADHD-C and 15 for the ADHD-I subtype. 31 boys were included in the TD group. Structural magnetic resonance imaging data were analysed using voxel-based morphometry. The ADHD group had significantly lower global and local grey matter volumes within clusters in the bilateral frontal, right parietal and right temporal regions compared to TD. A significant group by age interaction was found for right caudate nucleus volume. No differences between the ADHD-C and ADHD-I groups were found. Right caudate nucleus volume and age are more strongly related in ADHD than in TD consistent with previous research.

Multiclass Classification for the Differential Diagnosis on the ADHD Subtypes Using Recursive Feature Elimination and Hierarchical Extreme Learning Machine: Structural MRI Study

The classification of neuroimaging data for the diagnosis of certain brain diseases is one of the main research goals of the neuroscience and clinical communities. In this study, we performed multiclass classification using a hierarchical extreme learning machine (H-ELM) classifier. We compared the performance of this classifier with that of a support vector machine (SVM) and basic extreme learning machine (ELM) for cortical MRI data from attention deficit/hyperactivity disorder (ADHD) patients. We used 159 structural MRI images of children from the publicly available ADHD-200 MRI dataset. The data consisted of three types, namely, typically developing (TDC), ADHD-inattentive (ADHD-I), and ADHD-combined (ADHD-C). We carried out feature selection by using standard SVM-based recursive feature elimination (RFE-SVM) that enabled us to achieve good classification accuracy (60.78%). In this study, we found the RFE-SVM feature selection approach in combination with H-ELM to effectively enable the acquisition of high multiclass classification accuracy rates for structural neuroimaging data. In addition, we found that the most important features for classification were the surface area of the superior frontal lobe, and the cortical thickness, volume, and mean surface area of the whole cortex.

Comparison of brain volume abnormalities between ADHD and conduct disorder in adolescence

BACKGROUND

Previous studies of brain structure abnormalities in conduct disorder and attention-deficit/hyperactivity disorder (ADHD) samples have been limited owing to cross-comorbidity, preventing clear understanding of which structural brain abnormalities might be specific to or shared by each disorder. To our knowledge, this study was the first direct comparison of grey and white matter volumes in diagnostically "pure" (i.e., no comorbidities) conduct disorder and ADHD samples.

METHODS

Groups of adolescents with noncormobid conduct disorder and with noncomorbid, combined-subtype ADHD were compared with age- and sex-matched controls using DARTEL voxel-based analysis of T1-weighted brain structure images. Analysis of variance with post hoc analyses compared whole brain grey and white matter volumes among the groups.

RESULTS

We included 24 adolescents in each study group. There was an overall 13% reduction in grey matter volume in adolescents with conduct disorder, reflecting numerous frontal, temporal, parietal and subcortical deficits. The same grey matter regions typically were not abnormal in those with ADHD. Deficits in frontal lobe regions previously identified in studies of patients with ADHD either were not detected, or group differences from controls were not as strong as those between the conduct disorder and control groups. White matter volume measurements did not differentiate conduct disorder and ADHD.

LIMITATIONS

Our modest sample sizes prevented meaningful examination of individual features of ADHD or conduct disorder, such as aggression, callousness, or hyperactive versus inattentive symptom subtypes.

CONCLUSION

The evidence supports theories of frontotemporal abnormalities in adolescents with conduct disorder, but raises questions about the prominence of frontal lobe and striatal structural abnormalities in those with noncomorbid, combined-subtype ADHD. The latter point is clinically important, given the widely held belief that ADHD is associated with numerous frontal lobe structural deficits, a conclusion that is not strongly supported following direct comparison of diagnostically pure groups. The results are important for future etiological studies, particularly those seeking to identify how early expression of specific brain structure abnormalities could potentiate the risk for antisocial behaviour.

Automatic brain caudate nuclei segmentation and classification in diagnostic of Attention-Deficit/Hyperactivity Disorder

We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods.

Validity of DSM-IV attention deficit/hyperactivity disorder symptom dimensions and subtypes

Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) criteria for attention deficit/hyperactivity disorder (ADHD) specify two dimensions of inattention and hyperactivity-impulsivity symptoms that are used to define three nominal subtypes: predominantly hyperactive-impulsive type (ADHD-H), predominantly inattentive type (ADHD-I), and combined type (ADHD-C). To aid decision making for DSM-5 and other future diagnostic systems, a comprehensive literature review and meta-analysis of 546 studies was completed to evaluate the validity of the DSM-IV model of ADHD. Results indicated that DSM-IV criteria identify individuals with significant and persistent impairment in social, academic, occupational, and adaptive functioning when intelligence, demographic factors, and concurrent psychopathology are controlled. Available data overwhelmingly support the concurrent, predictive, and discriminant validity of the distinction between inattention and hyperactivity-impulsivity symptoms, and indicate that nearly all differences among the nominal subtypes are consistent with the relative levels of inattention and hyperactivity-impulsivity symptoms that define the subtypes. In contrast, the DSM-IV subtype model is compromised by weak evidence for the validity of ADHD-H after first grade, minimal support for the distinction between ADHD-I and ADHD-C in studies of etiological influences, academic and cognitive functioning, and treatment response, and the marked longitudinal instability of all three subtypes. Overall, we conclude that the DSM-IV ADHD subtypes provide a convenient clinical shorthand to describe the functional and behavioral correlates of current levels of inattention and hyperactivity-impulsivity symptoms, but do not identify discrete subgroups with sufficient long-term stability to justify the classification of distinct forms of the disorder. Empirical support is stronger for an alternative model that would replace the subtypes with dimensional modifiers that reflect the number of inattention and hyperactivity-impulsivity symptoms at the time of assessment. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Effect of dopamine transporter genotype on caudate volume in childhood ADHD and controls

Polymorphism of the dopamine transporter genotype (DAT1) confers a small but significant susceptibility to attention deficit hyperactivity disorder (ADHD). We examined whether the volume of the head of caudate, a striatal structure with high DAT expression that is important for inhibitory function, differs by DAT1 in children diagnosed with the disorder relative to age and IQ matched controls. Volume of the head of caudate was delineated in the right and left hemisphere and compared between 7- and 13-year-old children with and without ADHD (combined type) who were carriers of two (10/10) or one (9/10) copy of the 10-repeat DAT1 allele. Caudate volumes were overall smaller in 10/10 than 9/10 children, particularly in the left than right hemisphere. While DAT1 effects did not vary by ADHD diagnosis, overall caudate volumes were smaller in ADHD relative to control children. Altered caudate development associated with 10-repeat homozygosity of DAT1 may contribute susceptibility to ADHD.

Striatal volume changes in a rat model of childhood attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common childhood neuropsychiatric disorders. Based on neuroimaging studies, the striatum is reported to be abnormal in size, but it is still not clear how they change during developmental stages. Spontaneously hypertensive rats (SHRs) are the commonly used animal model for ADHD. We investigated volume differences of the striatum at various ages before puberty in SHRs versus a control strain, Wistar-Kyoto rats (WKYs). Volumes of the bilateral striatum were measured using micrographs of Nissl-stained serial sections in both strains of rats at the ages of 4, 5, 6, 7, 8, 9, and 10weeks (n=4, each strain at each age). The results demonstrated that the age of a significant striatal volume difference between SHRs and WKYs was 5weeks; however, there was no significant difference for the corresponding total brain volume at each matched age. It suggested that the timing for striatal abnormalities in ADHD occurs during an early stage of childhood.

Differential abnormalities of the head and body of the caudate nucleus in attention deficit-hyperactivity disorder

The aim of the study is to present a new method for the segmentation of the caudate nucleus and use it to compare the caudate heads and bodies of an attention deficit-hyperactivity disorder (ADHD) group with those of a control group. We used a 1.5-T system to acquire magnetic resonance brain scans from 39 children with ADHD, as defined by DSM-IV TR, and 39 age, handedness and IQ matched controls. The new method for caudate head and body segmentation was applied to obtain semi-automatic volumes and asymmetric patterns. Bilateral volumetric measures of the head, body, and head-body of the caudate nuclei were compared within groups and between ADHD and control groups. Although the group factor was not significant, there were first and second order interactions. The analysis of simple effects showed that the right body and right head+body of the ADHD group was significantly smaller than in the control group, although the ADHD right caudate head was bigger. No ADHD within-group caudate differences were found. Controls showed a significantly larger left caudate head and a significantly bigger caudate right body and right head+body. Our new method for segmenting the caudate nucleus detected differential abnormalities of the right caudate head and body in the ADHD group, explaining previous heterogeneous findings in the literature.

Imaging genetics in ADHD: a focus on cognitive control

This paper evaluates neuroimaging of cognitive control as an endophenotype for investigating the role of dopamine genes in ADHD. First, this paper reviews both data-driven and theory-driven approaches from genetics and neuroimaging. Several viable candidate genes have been implicated in ADHD, including the dopamine DRD4 and DAT1 genes. Neuroimaging studies have resulted in a good understanding of the neurobiological basis of deficits in cognitive control in this disorder. Second, this paper discusses imaging genetics in ADHD. Papers to date have taken one of two approaches: whereas early papers investigated the effects of one or two candidate genes on many brain areas, later papers constrained regions of interest by gene expression patterns. These papers have largely focused on cognitive control and the dopamine circuits involved in this ability. The results show that neuroimaging of cognitive control is useful as an endophenotype in investigating dopamine gene effects in ADHD. Other avenues of investigation are suggested by a combination of data- and theory-driven approaches in both genetics and neuroimaging.

Neurobiology of attention deficit hyperactivity disorder

This article addresses the current understanding of the neurobiological bases of attention deficit hyperactivity disorder (ADHD), focusing on empiric research findings that connect genetic and environmental factors to structural and functional brain abnormalities, ultimately leading to a set of age-dependent behavioral manifestations. Section one presents evidence for genetic risk factors for ADHD and discusses the role of potential environmental factors in the etiology of the disorder. Section two focuses on brain imaging studies and how they have helped generate different hypotheses regarding the pathophysiology of ADHD. Finally, the article addresses the longitudinal course of symptoms in ADHD from infancy to adulthood in an attempt to place biological findings for this complex brain disorder in the context of maturation and development.

Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder

BACKGROUND

Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues.

METHODS

We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author.

RESULTS

Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference=.408, p<.001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences.

CONCLUSIONS

This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.

Magnetic resonance imaging volumetric analysis of the putamen in children with ADHD: combined type versus control

OBJECTIVE

Volumetric differences in the putamen of boys with ADHD combined subtype with psychopathic traits and controls are investigated.

METHOD

The putamen in 24 archival magnetic resonance imaging scans of 12 boys in residential treatment with symptoms of ADHD and psychopathic traits and 12 community control boys are analyzed using Display software.

RESULTS

There are no differences found in the total, left, and right putamen volumes across the ADHD or control group. A significant reversal of asymmetry across groups is found; children with ADHD more frequently have a smaller left putamen than right. In contrast, the control group more frequently has a smaller right than left putamen.

CONCLUSION

A reversal of symmetry in the putamen (as found in the caudate) may relate to ADHD symptomology as well as to psychopathic traits.

Anatomical and functional brain imaging in adult attention-deficit/hyperactivity disorder (ADHD)--a neurological view

In this review, we discuss current structural and functional imaging data on ADHD in a neurological and neuroanatomical framework. At present, the literature on adult ADHD is somewhat sparse, and so results from imaging have to therefore be considered mainly from the childhood or adolescence perspective. Most work has considered the impairment of executive functions (motor execution, inhibition, working memory), and as such a number of attention networks and their anatomical correlates are discussed in this review (e.g. the cerebello-(thalamo-)-striato-cortical network seems to play a pivotal role in ADHD pathology from childhood to adulthood). The core findings in ADHD imaging are alterations in the architecture and function of prefrontal cortex and cerebellum. The dorsal part of anterior cingulated cortex (dACC) is an important region for decision making, and executive control is impaired in adult ADHD. Finally, dysfunction of basal ganglia is a consistent finding in childhood and adulthood ADHD, reflecting dysregulation of fronto-striatal circuitry. The cerebellum, and its role in affect and cognition, is also persistently implicated in the pathology of ADHD.

Revisiting the role of the prefrontal cortex in the pathophysiology of attention-deficit/hyperactivity disorder

Most neural models for the pathophysiology of attention-deficit/hyperactivity disorder (ADHD) have centered on the prefrontal cortex and its interconnections with the striatum and other subcortical structures. However, research only partially supports these models, and they do not correspond with the development of the prefrontal cortex and its interrelated neurocircuitry. The neural and functional development of the prefrontal cortex more closely parallels recovery from ADHD as indicated by the developmental remission of symptomatology. The authors hypothesize that ADHD is due to noncortical dysfunction that manifests early in ontogeny, remains static throughout the lifetime, and is not associated with the remission of symptomatology. Data supporting this neurodevelopmental model of prefrontal cortex function in ADHD are reviewed. Research and treatment implications are discussed.

Brain development and ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is characterized by excessive inattention, hyperactivity, and impulsivity, either alone or in combination. Neuropsychological findings suggest that these behaviors result from underlying deficits in response inhibition, delay aversion, and executive functioning which, in turn, are presumed to be linked to dysfunction of frontal-striatal-cerebellar circuits. Over the past decade, magnetic resonance imaging (MRI) has been used to examine anatomic differences in these regions between ADHD and control children. In addition to quantifying differences in total cerebral volume, specific areas of interest have been prefrontal regions, basal ganglia, the corpus callosum, and cerebellum. Differences in gray and white matter have also been examined. The ultimate goal of this research is to determine the underlying neurophysiology of ADHD and how specific phenotypes may be related to alterations in brain structure.

Right hemisphere brain morphology, attention-deficit hyperactivity disorder (ADHD) subtype, and social comprehension

Social comprehension involves empathy for others' experiences and appropriate responses to nonverbal cues. Previous research using magnetic resonance imaging (MRI) has suggested a relationship between brain morphology and psychiatric syndromes, such as attention-deficit hyperactivity disorder (ADHD), that typically entail social difficulties. The right hemisphere, specifically, has been associated with social skill deficits, and numerous studies have also associated ADHD with social skill deficits. No studies, however, have examined the association of ADHD subtype with both social comprehension and right-hemisphere morphology. Fifty-nine children (6-12 years old) underwent MRI, from which the right hemisphere was classified into four morphologic subtypes. Children were also grouped by ADHD subtype or clinical control status. From Behavior Assessment System for Children (BASC) items, a social comprehension subscale was constructed. Analyses revealed significant differences in social comprehension based on ADHD subtype. Differences in social comprehension based on ADHD status were especially pronounced in children with atypical right-hemisphere morphology. Thus, the diagnosis of ADHD might be associated with underlying risk in the area of social comprehension, especially for children with atypical right-hemisphere morphology.

Validation of two rating scales for attention-deficit hyperactivity disorder diagnosis in Colombian children

This study assesses the validity of the Behavioral Assessment System for Children-parent and teacher questionnaires for attention-deficit hyperactivity disorder diagnosis in a randomized sample of 344 Colombian children (145 cases, 199 controls), males and females, ages 6 to 11, with an estimated Wechsler Full Scale Intelligence Quotient over 70. The assessment protocol for both groups included psychiatric, neurologic, and psychological interviews, parent and teacher rating forms, and an Attention-Deficit Hyperactivity Disorder Checklist. All Behavioral Assessment System for Children-parent and teacher dimensions, except withdrawal and somatization, significantly differentiated cases and controls. Parents and teachers rated attention-deficit hyperactivity disorder combined type children as significantly more aggressive. Both questionnaires had good discriminant accuracy for detecting cases and control children, but accuracy for discriminating between attention-deficit hyperactivity disorder subtypes was poor. The Behavioral Assessment System for Children-parent and teacher questionnaires for 6- to 11-year-olds may be useful tools for diagnosing the presence of attention-deficit hyperactivity disorder. Additional assessment methods will be needed to discriminate between the subtypes.

Structural brain imaging of attention-deficit/hyperactivity disorder

Many investigators have hypothesized that attention-deficit/hyperactivity disorder (ADHD) involves structural and functional brain abnormalities in frontal-striatal circuitry. Although our review suggests that there is substantial support for this hypothesis, a growing literature demonstrates widespread abnormalities affecting other cortical regions and the cerebellum. Because there is only one report studying adults with ADHD, this summary is based on children. A key limitation of the literature is that most of the studies until recently have been underpowered, using samples of fewer than 20 subjects per group. Nevertheless, these studies are largely consistent with the most comprehensive and definitive study (Castellanos et al 2002). Moreover, studies differ in the degree to which they address the influence of medications, comorbidities, or gender, and most have not addressed potentially important sources of heterogeneity such as family history of ADHD, subtype, or perinatal complications. Despite these limitations, a relatively consistent picture has emerged. The most replicated alterations in ADHD in childhood include significantly smaller volumes in the dorsolateral prefrontal cortex, caudate, pallidum, corpus callosum, and cerebellum. These results suggest that the brain is altered in a more widespread manner than has been previously hypothesized. Developmental studies are needed to address the evolution of this brain disorder into adulthood.

Neural Substrates of Childhood Attention-Deficit/Hyperactivity Disorder: Electroencephalographic and Magnetic Resonance Imaging Evidence

Research methods based on electroencephalogram (EEG) and anatomical and functional MRI have been used with increasing frequency in the study of childhood Attention-Deficit/Hyperactivity Disorder (ADHD). Both methods are safe and noninvasive, and their results can complement each other because of the good temporal (but relatively poorer spatial) resolution of EEG and the good spatial (but relatively poorer temporal) resolution of MRI. These methods are described, and associated recent research on childhood ADHD is summarized and critically examined. Results of this research support theories of ADHD that focus on a frontal-striatal neurological circuitry substrate, which has been implicated in neuropsychological executive functioning. A number of issues, however, such as the specificity of this finding for ADHD, remain unresolved. We conclude with an overview of advances and issues to be considered in future research on the neural substrates of childhood ADHD and advocate a developmental-contextual perspective on this disorder that acknowledges the reciprocal relations between neural structures and functions.

A review of the biological bases of ADHD: what have we learned from imaging studies?

Attention Deficit Hyperactivity Disorder (ADHD) is a common and impairing neuropsychiatric disorder with onset at preschool age. Although a significant amount of progress has been made investigating the neurobiology of this disorder, its precise etiology still remains unclear. Converging evidence from studies of the neuropharmacology, genetics, neuropsychology, and neuroimaging of ADHD imply the involvement of fronto-striatal circuitry in ADHD. However, while it does appear that poor inhibitory control and the deficits in fronto-striatal circuitry associated with it are central, there is evidence to suggest that more posterior cerebral areas are also implicated in this disorder. Anatomical studies suggest widespread reductions in volume throughout the cerebrum and cerebellum, while functional imaging studies suggest that affected individuals activate more diffuse areas than controls during the performance of cognitive tasks. The future impact of new MR imaging methodologies on the field is discussed.