Longitudinal developmental trajectories of inhibition and white-matter maturation of the fronto-basal-ganglia circuits

Visualizing changes in cerebral hemodynamics in children with ADHD who have discontinued methylphenidate: A pilot study on using brain function for medication discontinuation decisions

OBJECTIVE

This study undertook neuropharmacological research on the clinical course of controlled medication discontinuation to guide practitioners who are considering stopping medications for youths with attention-deficit hyperactivity disorder (ADHD).

METHODS

This study analyzed the data for 14 ADHD children (12 male and 2 female) in two datasets: The children prescribed methylphenidate (MPH) were at an initial mean age of 7.5 years (SD = 1.70, range: 6-11) with a mean ADHD-Rating Score (ADHD-RS) of 26.6 (SD = 8.64, range 15-40). The children who discontinued MPH based on clinical judgment were at a mean age of 12.21 years (SD = 2.12, range: 8-15) with a mean ADHD-RS of 15.9 (SD = 6.86, range 5-27). The go/no-go task was used to assess response inhibition, while functional near-infrared spectroscopy (fNIRS) was used to measure cerebral hemodynamics. Oxygenated hemoglobin (Oxy-Hb) values from fNIRS data were analyzed for each subject, focusing on past and current measurements. Baseline was set at 10 s pre-task, with interval means from 4 to 24 s analyzed. One-sample t-tests were used to evaluate brain activity magnitude.

RESULTS

The results of the study demonstrate that the children who had discontinued the medication exhibited activation in specific brain regions including the frontopolar cortex and the right ventrolateral prefrontal cortex. Activation (t = 2.363, p = 0.034, Cohen's d = 0.632) was found especially in the right dorsolateral prefrontal cortex during the performance of the go/no-go task. These activated areas were consistent with those observed in a previous study comparing brain activity during a go/no-go task between children with ADHD and healthy children.

CONCLUSION

The present study showed differences in cerebral hemodynamics before and after discontinuation of MPH in ADHD children whose ADHD symptoms did not recur after MPH was discontinued. In the near future, further investigations that include control groups will be conducted to demonstrate the effects of MPH prior to discontinuation based on the changes in cerebral blood flow in the right prefrontal cortex, which is involved in behavioral inhibition, as observed in this study. This and future research will facilitate the development of criteria for discontinuing treatment.

Connectome-based prediction modeling of cognitive control using functional and structural connectivity

BACKGROUND

Cognitive control involves flexibly configuring mental resources and adjusting behavior to achieve goal-directed actions. It is associated with the coordinated activity of brain networks, although it remains unclear how both structural and functional brain networks can predict cognitive control. Connectome-based predictive modeling (CPM) is a powerful tool for predicting cognitive control based on brain networks.

METHODS

The study used CPM to predict cognitive control in 102 healthy adults from the UCLA Consortium for Neuropsychiatric Phenomics dataset and further compared structural and functional connectome characteristics that support cognitive control.

RESULTS

Our results showed that both structural (r values 0.263-0.375) and functional (r values 0.336-0.503) connectomes can significantly predict individuals' cognitive control subcomponents. There is overlap between the functional and structural networks of all three cognitive control subcomponents, particularly in the frontoparietal (FP) and motor (Mot) networks, while each subcomponent also has its own unique weight prediction network. Overall, the functional and structural connectivity that supports different cognitive control subcomponents manifests overlapping and distinct spatial patterns.

CONCLUSIONS

The structural and functional connectomes provide complementary information for predicting cognitive control ability. Integrating information from both connectomes offers a more comprehensive understanding of the neural underpinnings of cognitive control.

Developmental patterns of inhibition and fronto-basal-ganglia white matter organisation in healthy children and children with attention-deficit/hyperactivity disorder

There is robust evidence implicating inhibitory deficits as a fundamental behavioural phenotype in children with attention-deficit/hyperactivity disorder (ADHD). However, prior studies have not directly investigated the role in which white matter properties within the fronto-basal-ganglia circuit may play in the development of inhibitory control deficits in this group. Combining recent advancements in brain-behavioural modelling, we mapped the development of stop-signal task (SST) performance and fronto-basal-ganglia maturation in a longitudinal sample of children aged 9-14 with and without ADHD. In a large sample of 135 ADHD and 138 non-ADHD children, we found that the ADHD group had poorer inhibitory control (i.e., longer stop-signal reaction times) across age compared to non-ADHD controls. When applying the novel parametric race model, this group effect was driven by higher within-subject variability (sigma) and higher number of extreme responses (tau) on stop trials. The ADHD group also displayed higher within-subject variability on correct responses to go stimuli. Moreover, we observed the ADHD group committing more task-based failures such as responding on stop trials (trigger failures) and omissions on go trials (go failures) compared to non-ADHD controls, suggesting the contribution of attentional lapses to poorer response inhibition performance. In contrast, longitudinal modelling of fixel-based analysis measures revealed no significant group differences in the maturation of fronto-basal-ganglia fibre cross-section in a subsample (74 ADHD and 73 non-ADHD children). Finally, brain-behavioural models revealed that age-related changes in fronto-basal-ganglia morphology (fibre cross-section) were significantly associated with reductions in the variability of the correct go-trial responses (sigma.true) and skew of the stop-trial distribution (tauS). However, this effect did not differ between ADHD and typically developing children. Overall, our findings support the growing consensus suggesting that attentional deficits subserve ADHD-related inhibitory dysfunction. Furthermore, we show novel evidence suggesting that while children with ADHD are consistently performing worse on the SST than their non-affected peers, they appear to have comparable rates of neurocognitive maturation across this period.

On the (un)reliability of common behavioral and electrophysiological measures from the stop signal task: Measures of inhibition lack stability over time

Response inhibition, the intentional stopping of planned or initiated actions, is often considered a key facet of control, impulsivity, and self-regulation. The stop signal task is argued to be the purest inhibition task we have, and it is thus central to much work investigating the role of inhibition in areas like development and psychopathology. Most of this work quantifies stopping behavior by calculating the stop signal reaction time as a measure of individual stopping latency. Individual difference studies aiming to investigate why and how stopping latencies differ between people often do this under the assumption that the stop signal reaction time indexes a stable, dispositional trait. However, empirical support for this assumption is lacking, as common measures of inhibition and control tend to show low test-retest reliability and thus appear unstable over time. The reasons for this could be methodological, where low stability is driven by measurement noise, or substantive, where low stability is driven by a larger influence of state-like and situational factors. To investigate this, we characterized the split-half and test-retest reliability of a range of common behavioral and electrophysiological measures derived from the stop signal task. Across three independent studies, different measurement modalities, and a systematic review of the literature, we found a pattern of low temporal stability for inhibition measures and higher stability for measures of manifest behavior and non-inhibitory processing. This pattern could not be explained by measurement noise and low internal consistency. Consequently, response inhibition appears to have mostly state-like and situational determinants, and there is little support for the validity of conceptualizing common inhibition measures as reflecting stable traits.

ModelArray: An R package for statistical analysis of fixel-wise data

Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data.