Dysfunction of right-hemisphere attentional networks in attention deficit hyperactivity disorder

Contributions of brain regions to machine learning-based classifications of attention deficit hyperactivity disorder (ADHD) utilizing EEG signals

OBJECTIVE

The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids with attention deficit hyperactivity disorder (ADHD) from healthy controls. The EEG signals are acquired during cognitive tasks to distinguish children with ADHD from their counterparts.

METHODOLOGY

The EEG data recorded in cognitive exercises was filtered using low pass Bessel filter and notch filters to remove artifacts, by the data set owners. To identify unique EEG patterns, we used many well-known classifiers, including Naïve Bayes (NB), Random Forest, Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost and Linear Discriminant Analysis (LDA), to identify distinct EEG patterns. Input features comprised EEG data from nineteen channels, individually and in combination.

FINDINGS

Study indicates that EEG-based categorization can differentiate between individuals with ADHD and healthy individuals with accuracy of 84%. The RF classifier achieved a maximum accuracy of 0.84 when particular region combinations were used. Evaluation of classification performance utilizing hemisphere-specific EEG data yielded promising outcomes, particularly in the right hemisphere channels.

NOVELTY

The study goes beyond traditional methodologies by investigating the effect of regional data on categorization results. The contributions of various brain regions to these classifications are being extensively researched. Understanding the role of different brain regions in ADHD can lead to better diagnosis and treatment options for individuals with ADHD. The study of categorization ability, utilizing EEG data specific to each hemisphere, particularly channels in the right hemisphere region, provides further granularity to the findings.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

OBJECTIVE

Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

METHODS

We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

RESULTS

There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

CONCLUSION

Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

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

BACKGROUND

Impulsivity is a defining characteristic of attention-deficit/hyperactivity disorder (ADHD), which has been associated with substance use disorders, higher accident rates, and lower educational and occupational outcomes. The meso- and nigrostriatal pathways of the dopamine system are hypothesized to be functionally heterogeneous, supporting diverse cognitive functions and impairments, including those associated with ADHD. We tested whether human midbrain pathways (where dopaminergic cell bodies originate) between the substantia nigra (SN) and ventral tegmental area (VTA) and the striatum differed between participants with ADHD and typically developing adolescent and young adult participants. We also assessed whether pathway connectivity predicted impulsivity regardless of diagnosis.

METHODS

Diffusion tensor imaging data were used to predict impulsivity (parent and self-report ratings, task-based behavioral measures) from participants with ADHD and typically developing adolescent and young adult participants (n = 155; 86 male, 69 female). Using probabilistic tractography, we mapped these pathways and divided the tracts into limbic, executive, and sensorimotor based on frontostriatal connectivity. ADHD and typically developing participants differed on all behavioral measures of impulsivity. We used correlation and machine learning analyses to test for a relationship between tract probabilities and impulsivity regardless of diagnosis.

RESULTS

Participants with ADHD had stronger structural connectivity between SN/VTA regions and the limbic striatum, weaker connectivity with the executive striatum, and no significant differences in sensorimotor tracts. Increased tract integrity between the limbic striatal and SN/VTA regions predicted greater impulsivity, while increased integrity between executive striatal and SN/VTA regions predicted reduced impulsivity.

CONCLUSIONS

These findings support the theory that functional diversity in the dopamine system is an important consideration for understanding dysfunction in ADHD.

Decreased resting gamma activity in adult attention deficit/hyperactivity disorder

Objectives: To delineate task-free gamma activity in adult ADHD and healthy control subjects based on high-density EEG recordings. Relationship of gamma activity with symptom severity was also examined, since gamma activity is considered to be an index of network functions in the brain that underlie higher-order cognitive processes.Methods: Spontaneous EEG was recorded in adult ADHD subjects (N = 42; 25 methylphenidate-naïve and 17 on methylphenidate treatment) and controls (N = 59) with eyes open. EEG absolute power gamma was investigated in the gamma₁ (30.25-39 Hz) and gamma₂ (39.25-48 Hz) frequency bands.Results: Gamma₁ and gamma₂ activity was diminished in ADHD compared with healthy control subjects. The difference between ADHD and controls was the most pronounced in the right centroparietal region for both gamma₁ and gamma₂. Inverse associations were found between gamma₁ and gamma₂ activity and ADHD symptoms in centroparietal scalp regions.Conclusions: Gamma activity is reduced in adult ADHD, and the reduction has a predominantly right centroparietal distribution. Our findings are consistent with childhood ADHD literature with respect to diminished posterior gamma activity in patients, which may reflect altered dorsal attention network functions. Gamma abnormalities might provide a link between neurophysiological functioning and neuropsychological deficiencies, thereby offering an opportunity to investigate the neurobiological mechanisms that underlie the clinical symptoms of ADHD.

Visuospatial Asymmetries Arise from Differences in the Onset Time of Perceptual Evidence Accumulation

Healthy subjects tend to exhibit a bias of visual attention whereby left hemifield stimuli are processed more quickly and accurately than stimuli appearing in the right hemifield. It has long been held that this phenomenon arises from the dominant role of the right cerebral hemisphere in regulating attention. However, methods that would enable more precise understanding of the mechanisms underpinning visuospatial bias have remained elusive. We sought to finely trace the temporal evolution of spatial biases by leveraging a novel bilateral dot motion detection paradigm. In combination with electroencephalography, this paradigm enables researchers to isolate discrete neural signals reflecting the key neural processes needed for making these detection decisions. These include signals for spatial attention, early target selection, evidence accumulation, and motor preparation. Using this method, we established that three key neural markers accounted for unique between-subject variation in visuospatial bias: hemispheric asymmetry in posterior α power measured before target onset, which is related to the distribution of preparatory attention across the visual field; asymmetry in the peak latency of the early N2c target-selection signal; and, finally, asymmetry in the onset time of the subsequent neural evidence-accumulation process with earlier onsets for left hemifield targets. Our development of a single paradigm to dissociate distinct processing components that track the temporal evolution of spatial biases not only advances our understanding of the neural mechanisms underpinning normal visuospatial attention bias, but may also in the future aid differential diagnoses in disorders of spatial attention.SIGNIFICANCE STATEMENT The significance of this research is twofold. First, it shows that individual differences in how humans direct their attention between left and right space reflects physiological differences in how early the brain starts to accumulate evidence for the existence of a visual target. Second, the novel methods developed here may have particular relevance to disorders of attention, such as unilateral spatial neglect. In the case of spatial neglect, pathological inattention to left space could have multiple underlying causes, including biased attention, impaired decision formation, or a motor deficit related to one side of space. Our development of a single paradigm to dissociate each of these components may aid in supporting more precise differential diagnosis in such heterogeneous disorders.

Brain lateralization and self-reported symptoms of ADHD in a population sample of adults: a dimensional approach

Many clinical studies reported a compromised brain lateralization in patients with Attention-Deficit/Hyperactivity Disorder (ADHD) without being conclusive about whether the deficit existed in the left or right hemisphere. It is well-recognized that studying ADHD dimensionally is more controlled for comorbid problems and medication effects, and provides more accurate assessment of the symptoms. Therefore, the present study applied the dimensional approach to test the relationship between brain lateralization and self-reported ADHD symptoms in a population sample. Eighty-five right-handed university students filled in the Conners' Adult ADHD Rating Scales and performed a lateralization reaction time task. The task consists of two matching conditions: one condition requires nominal identification for letters tapping left hemisphere specialization (Letter Name-Identity condition) and the other one requires physical and visuospatial identification for shapes tapping right hemisphere specialization (Shape Physical-Identity condition). The letters or shapes to be matched are presented in left or right visual field of a fixation cross. For both task conditions, brain lateralization was indexed as the difference in mean reaction time between left and right visual field. Linear regression analyses, controlled for mood symptoms reported by a depression, anxiety, and stress scale, showed no relationship between the variables. These findings from a population sample of adults do not support the dimensionality of lateralized information processing deficit in ADHD symptomatology. However, group comparison analyses showed that subjects with high level of inattention symptoms close to or above the clinical cut-off had a reduced right hemisphere processing in the Shape Physical-Identity condition.

Behavioral consequences of aberrant alpha lateralization in attention-deficit/hyperactivity disorder

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is characterized by problems in directing and sustaining attention. Recent findings suggest that alpha oscillations (8-12 Hz) are crucially involved in gating information between brain regions when allocating attention. The current study investigates whether aberrant modulation of alpha oscillations contributes to attention problems in ADHD patients.

METHODS

Magnetoencephalographic signals were recorded in adults with ADHD (n = 17) and healthy control subjects (n = 18) while they performed a visuospatial attention task. Cues directed attention to the left or right visual hemifield with an 80% validity with respect to the upcoming target.

RESULTS

Unlike the control group, subjects with ADHD showed a higher accuracy for invalidly cued right targets compared with invalidly cued left targets (p = .04). This coincided with an inability of the ADHD subjects to sustain the posterior hemispheric alpha lateralization in the period before the target for the left cue condition (p = .011). Furthermore, the control group showed a strong correlation between the degree of alpha lateralization and the magnitude of the cueing effect assessed in terms of accuracy (rs = .71, p = .001) and reaction times (rs =-.81, p<.001). These correlations were absent in the ADHD group.

CONCLUSIONS

Our results demonstrate that subjects with ADHD have a failure in sustaining hemispheric alpha lateralization when cued to the left, resulting in an attentional bias to the right visual hemifield. These findings suggest that aberrant modulations of alpha oscillations reflect attention problems in ADHD and might be related to the neurophysiological substrate of the disorder.