Limbic and Executive Meso- and Nigrostriatal Tracts Predict Impulsivity Differences in Attention-Deficit/Hyperactivity Disorder

In vivo structural connectivity of the reward system along the hippocampal long axis

Recent work has identified a critical role for the hippocampus in reward-sensitive behaviors, including motivated memory, reinforcement learning, and decision-making. Animal histology and human functional neuroimaging have shown that brain regions involved in reward processing and motivation are more interconnected with the ventral/anterior hippocampus. However, direct evidence examining gradients of structural connectivity between reward regions and the hippocampus in humans is lacking. The present study used diffusion MRI (dMRI) and probabilistic tractography to quantify the structural connectivity of the hippocampus with key reward processing regions in vivo. Using a large sample of subjects (N = 628) from the human connectome dMRI data release, we found that connectivity profiles with the hippocampus varied widely between different regions of the reward circuit. While the dopaminergic midbrain (ventral tegmental area) showed stronger connectivity with the anterior versus posterior hippocampus, the ventromedial prefrontal cortex showed stronger connectivity with the posterior hippocampus. The limbic (ventral) striatum demonstrated a more homogeneous connectivity profile along the hippocampal long axis. This is the first study to generate a probabilistic atlas of the hippocampal structural connectivity with reward-related networks, which is essential to investigating how these circuits contribute to normative adaptive behavior and maladaptive behaviors in psychiatric illness. These findings describe nuanced structural connectivity that sets the foundation to better understand how the hippocampus influences reward-guided behavior in humans.

An in vivo Dissection, and Analysis of Socio-Affective Symptoms related to Cerebellum-Midbrain Reward Circuitry in Humans

Emerging research in non-human animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white-matter connectivity in humans using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections from the cerebellum to the VTA predominantly originate in the right hemisphere, interposed nucleus, and paravermal cortex, and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared to other lobules. We discovered a medial-to-lateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socio-affective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socio-affective regulation.

Moderating effects of impulsivity and morning cortisol on the genotype-phenotype relationship of attention deficit hyperactivity disorder in young adults

Dysregulation of the morning cortisol response in young adults with attention deficit hyperactivity disorder (ADHD) has been shown to underlie several of the alterations present in their lives. Thus, the interaction of this mechanism with genetic and behavioural characteristics could explain a large proportion of the aetiology of ADHD in this population. For these reasons, the present study explores the associations of 30 single nucleotide polymorphisms (SNPs) previously identified as significant (after correction for multiple comparisons) in the aetiology of ADHD with an assessment of morning cortisol and impulsivity traits in a group of 120 adults aged 18-24 years. Participants were recruited through private centres of neuropsychology and psychiatry, as well as through events in local universities. Morning cortisol within 30 min of awakening and motor impulsivity traits were shown to moderate the effect of SNP rs10129500 on the severity of the symptoms of ADHD measured by the Adult Self-Report Scale. This variant associated with cortisol-binding globulin would explain the low concentrations of this hormone found in young adults with high symptoms of ADHD, which is accentuated when there are high levels of impulsivity. The proposed model allows for transferring the theoretical relationships between the dimensions that explain the aetiology of ADHD to an applied exploratory model with good performance.

Using Hot and Cool Measures to Phenotype and Predict Functional Outcomes Across Dimensions of ADHD and Typical Development in Adolescents

Multiple pathway models propose that attention deficit hyperactivity disorder (ADHD) arises from dysfunction in separate systems comprised of a "cool" or cognitive pathway versus a "hot" or emotional/reward pathway. Interactions between these pathways and the degree of maturation may further determine functional outcomes for adolescents ranging from those diagnosed with ADHD to typical development (TD). We used a latent profile analysis on rating scales and behavioral task performance assessing emotion, irritability, impulsivity, risk-taking, future orientation, and processing speed (PS) to identify subgroups of TD adolescents and adolescents with ADHD (N = 152) based on the hot and cool pathway model. We identified four classes: 1) High-Complex Challenges; 2) Moderate-Mixed Challenges; 3) Non-Emotive Impulsivity; and 4) High Regulation and Control. A multiple pathway model of ADHD is supported with classes differing in degree of emotional lability and irritability, types of impulsivity, and ability to use future consequences to modulate impulsivity and PS. The classes differed regarding functional behavior, with the High-Complex class demonstrating the most severe functional challenges in academic-related functioning. The Moderate-Mixed class also displayed significant functional challenges but with moderate emotional lability and irritability ratings. The Non-Emotive Impulsivity class exhibited low emotionality and low irritability, yet high impulsivity with limited negative functional consequences, and was composed of a mix of ADHD and TD adolescents. Differences between classes suggest ADHD symptomatology may represent both categorical and dimensional differences. Precision health interventions may be more effective in addressing the specific challenges associated with the classes rather than a one-size-fits-all approach to treating ADHD.

Early childhood exposure to environmental phenols and parabens, phthalates, organophosphate pesticides, and trace elements in association with attention deficit hyperactivity disorder (ADHD) symptoms in the CHARGE study

BACKGROUND

A growing body of literature investigated childhood exposure to environmental chemicals in association with attention-deficit/hyperactivity disorder (ADHD) symptoms, but limited studies considered urinary mixtures of multiple chemical classes. This study examined associations of concurrent exposure to non-persistent chemicals with ADHD symptoms in children diagnosed with autism spectrum disorder (ASD), developmental delay (DD), and typical development (TD).

METHODS

A total of 549 children aged 2-5 years from the Childhood Autism Risks from Genetics and Environment (CHARGE) case-control study were administered the Aberrant Behavior Checklist (ABC). This study focused on the ADHD/noncompliance subscale and its two subdomains (hyperactivity/impulsivity, inattention). Sixty-two chemicals from four classes (phenols/parabens, phthalates, organophosphate pesticides, trace elements) were quantified in child urine samples, and 43 chemicals detected in > 70% samples were used to investigate their associations with ADHD symptoms. Negative binomial regression was used for single-chemical analysis, and weighted quantile sum regression with repeated holdout validation was applied for mixture analysis for each chemical class and all chemicals. The mixture analyses were further stratified by diagnostic group.

RESULTS

A phthalate metabolite mixture was associated with higher ADHD/noncompliance scores (median count ratio [CR] = 1.10; 2.5th, 97.5th percentile: 1.00, 1.21), especially hyperactivity/impulsivity (median CR = 1.09; 2.5th, 97.5th percentile: 1.00, 1.25). The possible contributors to these mixture effects were di-2-ethylhexyl phthalate (DEHP) metabolites and mono-2-heptyl phthalate (MHPP). These associations were likely driven by children with ASD as these were observed among children with ASD, but not among TD or those with DD. Additionally, among children with ASD, a mixture of all chemicals was associated with ADHD/noncompliance and hyperactivity/impulsivity, and possible contributors were 3,4-dihydroxy benzoic acid, DEHP metabolites, MHPP, mono-n-butyl phthalate, and cadmium.

CONCLUSIONS

Early childhood exposure to a phthalate mixture was associated with ADHD symptoms, particularly among children with ASD. While the diverse diagnostic profiles limited generalizability, our findings suggest a potential link between phthalate exposure and the comorbidity of ASD and ADHD.

Association of emotional and behavioral problems with the development of the substantia nigra, subthalamic nucleus, and red nucleus volumes and asymmetries from childhood to adolescence: A longitudinal cohort study

The substantia nigra (SN), subthalamic nucleus (STN), and red nucleus (RN) have been widely studied as important biomarkers of degenerative diseases. However, how they develop in childhood and adolescence and are affected by emotional behavior has not been studied thus far. This population-based longitudinal cohort study used data from a representative sample followed two to five times. Emotional and behavioral problems were assessed with the Strengths and Difficulties Questionnaire (SDQ). Linear mixed models were used to map developmental trajectories and behavioral regulation. Using an innovative automated image segmentation technique, we quantified the volumes and asymmetries of the SN, STN and RN with 1226 MRI scans of a large longitudinal sample of 667 subjects aged 6-15 years and mapped their developmental trajectories. The results showed that the absolute and relative volumes of the bilateral SN and right STN showed linear increases, while the absolute volume of the right RN and relative volume of the bilateral RN decreased linearly, these effects were not affected by gender. Hyperactivity/inattention weakened the increase in SN volume and reduced the absolute volume of the STN, conduct problems impeded the RN volume from decreasing, and emotional symptoms changed the direction of SN lateralization. This longitudinal cohort study mapped the developmental trajectories of SN, STN, and RN volumes and asymmetries from childhood to adolescence, and found the association of emotional symptoms, conduct problems, and hyperactivity/inattention with these trajectories, providing guidance for preventing and intervening in cognitive and emotional behavioral problems.

Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelopmental disorder in children and has a high chance of persisting in adulthood. The development of individualized, efficient, and reliable treatment strategies is limited by the lack of understanding of the underlying neural mechanisms. Diverging and inconsistent findings from existing studies suggest that ADHD may be simultaneously associated with multivariate factors across cognitive, genetic, and biological domains. Machine learning algorithms are more capable of detecting complex interactions between multiple variables than conventional statistical methods. Here we present a narrative review of the existing machine learning studies that have contributed to understanding mechanisms underlying ADHD with a focus on behavioral and neurocognitive problems, neurobiological measures including genetic data, structural magnetic resonance imaging (MRI), task-based and resting-state functional MRI (fMRI), electroencephalogram, and functional near-infrared spectroscopy, and prevention and treatment strategies. Implications of machine learning models in ADHD research are discussed. Although increasing evidence suggests that machine learning has potential in studying ADHD, extra precautions are still required when designing machine learning strategies considering the limitations of interpretability and generalization.

Midbrain-Hippocampus Structural Connectivity Selectively Predicts Motivated Memory Encoding

Motivation is a powerful driver of learning and memory. Functional MRI studies show that interactions among the dopaminergic midbrain substantia nigra/ventral tegmental area (SN/VTA), hippocampus, and nucleus accumbens (NAc) are critical for motivated memory encoding. However, it is not known whether these effects are transient and purely functional, or whether individual differences in the structure of this circuit underlie motivated memory encoding. To quantify individual differences in structure, diffusion-weighted MRI and probabilistic tractography were used to quantify SN/VTA-striatum and SN/VTA-hippocampus pathways associated with motivated memory encoding in humans. Male and female participants completed a motivated source memory paradigm. During encoding, words were randomly assigned to one of three conditions, reward ($1.00), control ($0.00), or punishment (-$1.00). During retrieval, participants were asked to retrieve item and source information of the previously studied words and were rewarded or penalized according to their performance. Source memory for words assigned to both reward and punishment conditions was greater than those for control words, but there were no differences in item memory based on value. Anatomically, probabilistic tractography results revealed a heterogeneous, topological arrangement of the SN/VTA. Tract density measures of SN/VTA-hippocampus pathways were positively correlated with individual differences in reward-and-punishment-modulated memory performance, whereas density of SN/VTA-striatum pathways showed no association. This novel finding suggests that pathways emerging from the human SV/VTA are anatomically separable and functionally heterogeneous. Individual differences in structural connectivity of the dopaminergic hippocampus-VTA loop are selectively associated with motivated memory encoding.SIGNIFICANCE STATEMENT Functional MRI studies show that interactions among the SN/VTA, hippocampus, and NAc are critical for motivated memory encoding. This has led to competing theories that posit either SN/VTA-NAc reward prediction errors or SN/VTA-hippocampus signals underlie motivated memory encoding. Additionally, it is not known whether these effects are transient and purely functional or whether individual differences in the structure of these circuits underlie motivated memory encoding. Using diffusion-weighted MRI and probabilistic tractography, we show that tract density measures of SN/VTA-hippocampus pathways are positively correlated with motivated memory performance, whereas density of SN/VTA-striatum pathways show no association. This finding suggests that anatomic individual differences of the dopaminergic hippocampus-VTA loop are selectively associated with motivated memory encoding.

Reduced basal ganglia tissue-iron concentration in school-age children with attention-deficit/hyperactivity disorder is localized to limbic circuitry

Dopamine-related abnormalities in the basal ganglia have been implicated in attention-deficit/hyperactivity disorder (ADHD). Iron plays a critical role in supporting dopaminergic function, and reduced brain iron and serum ferritin levels have been linked to ADHD symptom severity in children. Furthermore, the basal ganglia is a central brain region implicated in ADHD psychopathology and involved in motor and reward functions as well as emotional responding. The present study repurposed diffusion tensor imaging (DTI) to examine effects of an ADHD diagnosis and sex on iron deposition within the basal ganglia in children ages 8-12 years. We further explored associations between brain iron levels and ADHD symptom severity and affective symptoms. We observed reduced iron levels in children with ADHD in the bilateral limbic region of the striatum, as well as reduced levels of iron-deposition in males in the sensorimotor striatal subregion, regardless of diagnosis. Across the whole sample, iron-deposition increased with age in all regions. Brain-behavior analyses revealed that, across diagnostic groups, lower tissue-iron levels in bilateral limbic striatum correlated with greater ADHD symptom severity, whereas lower tissue-iron levels in the left limbic striatum only correlated with anxious, depressive and affective symptom severity. This study sheds light on the neurobiological underpinnings of ADHD, specifically highlighting the localization of tissue-iron deficiency in limbic regions, and providing support for repurposing DTI for brain iron analyses. Our findings highlight the need for further investigation of iron as a biomarker in the diagnosis and treatment of ADHD and sex differences.