Varieties of attention-deficit/hyperactivity disorder-related intra-individual variability

The neural and genetic underpinnings of different developmental trajectories of Attention-Deficit/Hyperactivity Symptoms in children and adolescents

BACKGROUND

The trajectory of attention-deficit hyperactivity disorder (ADHD) symptoms in children and adolescents, encompassing descending, stable, and ascending patterns, delineates their ADHD status as remission, persistence or late onset. However, the neural and genetic underpinnings governing the trajectory of ADHD remain inadequately elucidated.

METHODS

In this study, we employed neuroimaging techniques, behavioral assessments, and genetic analyses on a cohort of 487 children aged 6-15 from the Children School Functions and Brain Development project at baseline and two follow-up tests for 1 year each (interval 1: 1.14 ± 0.32 years; interval 2: 1.14 ± 0.30 years). We applied a Latent class mixed model (LCMM) to identify the developmental trajectory of ADHD symptoms in children and adolescents, while investigating the neural correlates through gray matter volume (GMV) analysis and exploring the genetic underpinnings using polygenic risk scores (PRS).

RESULTS

This study identified three distinct trajectories (ascending-high, stable-low, and descending-medium) of ADHD symptoms from childhood through adolescence. Utilizing the linear mixed-effects (LME) model, we discovered that attention hub regions served as the neural basis for these three developmental trajectories. These regions encompassed the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), responsible for inhibitory control; the right inferior parietal lobule (IPL), which facilitated conscious focus on exogenous stimuli; and the bilateral middle frontal gyrus/precentral gyrus (MFG/PCG), accountable for regulating both dorsal and ventral attention networks while playing a crucial role in flexible modulation of endogenous and extrinsic attention. Furthermore, our findings revealed that individuals in the ascending-high group exhibited the highest PRS for ADHD, followed by those in the descending-medium group, with individuals in the stable-low group displaying the lowest PRS. Notably, both ascending-high and descending-medium groups had significantly higher PRS compared to the stable-low group.

CONCLUSIONS

The developmental trajectory of ADHD symptoms in the general population throughout childhood and adolescence can be reliably classified into ascending-high, stable-low, and descending-medium groups. The bilateral MFG/PCG, left ACC/mPFC, and right IPL may serve as crucial brain regions involved in attention processing, potentially determining these trajectories. Furthermore, the ascending-high pattern of ADHD symptoms exhibited the highest PRS for ADHD.

Association between intra-individual variability and prefrontal cortex activity measured by functional Near Infrared Spectroscopy (fNIRS) in children with ADHD

This study uses fNIRS to determine whether there is a difference in the relationship between intra-individual variability and frontal lobe activity between ADHD patients and typically developing children. A total of 28 subjects (14 in ADHD patient group and 14 in control group) participated in this study. The subjects were tested for K-SADS and intelligence, and then the frontal lobe activity of the subjects was measured by continuous performance test, using functional near-infrared spectroscopy (NIRSIT). Processing speed index was significantly lower in the ADHD patient group than in the control group (p = .04). The CPT test results showed a positive correlation in the activity of the right dorsolateral prefrontal region in the patient group, but not at a statistically significant level. In the control group, activity showed a significant level of negative correlation with commission and hit reaction time standard deviation (p = .023; p = .063 respectively). In contrary to ADHD patient group, activation of the right dorsolateral prefrontal area was significantly correlated with reduction of intra-individual variability. This result showing that the relationship between activation of the right dorsolateral prefrontal area of the ADHD patient group and intra-individual variability shows a different pattern from typically developing children.

Differences in Ex-Gaussian Parameters from Response Time Distributions Between Individuals with and Without Attention Deficit/Hyperactivity Disorder: A Meta-analysis

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in childhood and adolescence. Differences in reaction times (RT) in cognitive tasks have been consistently observed between ADHD and typical participants. Instead of estimating means and standard deviations, fitting non-symmetrical distributions like the ex-Gaussian, characterized by three parameters (µ, σ, and τ), account for the whole RT distributions. A meta-analysis is performed with all the available literature using ex-Gaussian distributions for comparisons between individuals with ADHD and controls. Results show that τ and σ are generally greater for ADHD samples, while µ tends to be larger for typical groups but only for younger ages. Differences in τ are also moderated by ADHD subtypes. τ and σ show, respectively, quadratic and linear relationships with inter-stimulus intervals from Continuous Performance Test and Go/No Go tasks. Furthermore, tasks and cognitive domains influence the three parameters. Interpretations of ex-Gaussian parameters and clinical implications of these findings are also discussed. Fitting ex-Gaussian distributions to RT data is a useful way to explore differences between individuals with ADHD and healthy controls.

Low-frequency variability in theta activity modulates the attention-fluctuation across task and resting states

Sustained attention is not constant but fluctuates influencing our task performance. Albeit intensive investigations, it remains unclear whether the attention-fluctuation during tasks is derived from its spontaneous fluctuation in the resting state. Here, we addressed this issue by investigating the attention-fluctuation in both task and resting states, through the EEG measurement of theta-variability. We found significant rest-task modulation of theta-variability, i.e., reduced theta-variability in the task state compared to the resting state. This task and rest modulation was manifested in the low-frequency of theta-variability (<0.1 Hz). Furthermore, the low-frequency theta-variability exhibited a significant rest-task correlation, however, only the low-frequency theta-variability in the task state but not in the resting state was correlated with the behavioral performance. These findings shed light on the low-frequency feature of attention-fluctuation, and advanced our understanding of sustained attention by suggesting that the theta-variability in low-frequencies was relevant to attention level in task state.

Advancing ecological validity and clinical utility in virtual reality-based continuous performance test: exploring the effects of task difficulty and environmental distractors

Introduction

Researchers have highlighted concerns regarding the limited diagnostic utility and ecological validity of the Continuous Performance Test (CPT). Recent advancements in VR-based CPTs have attempted to address these concerns by simulating real-life scenarios and enhancing attention deficit hyperactivity disorder (ADHD) diagnosis; however, certain areas require improvement for obtaining reliable data from both healthy individuals and those with ADHD. To tackle these issues, we developed an enhanced VR-based CPT program featuring four distinct difficulty levels, advancing toward home-based assessment.

Method

Our feasibility study involved subjects without ADHD to establish a normative profile for VR-based CPT before extending it to ADHD assessment. Our sample included 20 Korean adults. They received a VR device with the VR-based CPT program installed and were asked to perform 1-2 blocks per day at home. Participants were instructed to complete 12 blocks over the subsequent 2 weeks. Psychological assessments and electroencephalograms (EEGs) were administered before and after the program. Post-study usability measures were also collected.

Result

Higher commission errors were notably evident in the "very high" difficulty level which featured complex stimuli and increased distraction. A notable correlation emerged between the overall distraction level and CPT accuracy, along with a significant link between intensity scores and commission errors. No significant differences were found in psychological assessment and there were no significant changes in the Theta-Beta Ratio (TBR) index before and after the program. The usability of our program was fair.

Discussion

The study reveals that the newly designed VR-CPT program, simulating diverse real-life environments and offering varying task difficulty levels, proved acceptable and feasible. The key point of our study was that the adjustment and segmentation of difficulty levels in the VR-based CPT were achieved, and that this effort was validated by examining the impact of different levels of difficulty on CPT measures. Implementing this experimental setup in a home-based environment increased ecological validity, as well as clinical utility. Limitations and suggested directions for further investigation are described in detail.

Exploring the steps of learning: computational modeling of initiatory-actions among individuals with attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is characterized by difficulty in acting in a goal-directed manner. While most environments require a sequence of actions for goal attainment, ADHD was never studied in the context of value-based sequence learning. Here, we made use of current advancements in hierarchical reinforcement-learning algorithms to track the internal value and choice policy of individuals with ADHD performing a three-stage sequence learning task. Specifically, 54 participants (28 ADHD, 26 controls) completed a value-based reinforcement-learning task that allowed us to estimate internal action values for each trial and stage using computational modeling. We found attenuated sensitivity to action values in ADHD compared to controls, both in choice and reaction-time variability estimates. Remarkably, this was found only for first-stage actions (i.e., initiatory actions), while for actions performed just before outcome delivery the two groups were strikingly indistinguishable. These results suggest a difficulty in following value estimation for initiatory actions in ADHD.

100 days of Adolescence: Elucidating Externalizing Behaviors Through the Daily Assessment of Inhibitory Control

Inhibitory control is a transdiagnostic risk factor for externalizing behaviors, particularly during adolescence. Despite advances in understanding links between inhibitory control and externalizing behaviors across youth on average, significant questions remain about how these links play out in the day-to-day lives of individual adolescents. The goals of the current study were to: (1) validate a novel 100-occasion measure of inhibitory control; (2) assess links between day-to-day fluctuations in inhibitory control and individual differences in externalizing behaviors; and (3) illustrate the potential of intensive longitudinal studies for person-specific analyses of adolescent externalizing behaviors. Participants were 106 youth (57.5% female, Mage = 13.34 years; SDage = 1.92) who completed a virtual baseline session followed by 100 daily surveys, including an adapted Stroop Color Word task designed to assess inhibitory control. Results suggested that the novel task was generally reliable and valid, and that inhibitory control fluctuated across days in ways that were meaningfully associated with individual differences in baseline impulsive behaviors. Results of illustrative personalized analyses suggested that inhibitory control had more influence in the daily networks of adolescents who used substances during the 100 days than in a matched set of adolescents who did not. This work marks a path forward in intensive longitudinal research by validating a novel inhibitory control measure, revealing that daily fluctuations in inhibitory control may be a unique construct broadly relevant to adolescent externalizing problems, and at the same time, highlighting that links between daily inhibitory control and impulsive behaviors are adolescent-specific.

Distinct developmental changes in regional gray matter volume and covariance in individuals with attention-deficit hyperactivity disorder: A longitudinal voxel-based morphometry study

BACKGROUND

Very few studies have investigated longitudinal clinical cohorts of attention-deficit/hyperactivity disorder (ADHD). Moreover, how baseline brain changes could affect the development of ADHD symptoms later in life remains elusive. Therefore, we aimed to fill this gap by exploring brain and clinical changes in youth with ADHD using a longitudinal design.

METHODS

This prospective study consisted of 74 children and adolescents with ADHD and 50 age-, sex-, intelligence-matched typically developing controls (TDC), evaluated at baseline (aged 7-19 years) and re-evaluated 5.3 years later (a mean follow-up latency). We applied voxel-based morphometry to characterize brain structures, followed by both mass-univariate and multivariate structural covariance statistics to identify brain regions with significant diagnosis-by-time interactions from late childhood/adolescence to early adulthood. We used the cross-lagged panel model to investigate the longitudinal association between structural brain metrics and core ADHD symptoms.

RESULTS

The mass-univariate statistic revealed significant diagnosis-by-time interactions in the right striatum and the sixth lobule of the cerebellum. This was expressed by increased striatal and decreased cerebellar volume in ADHD, while TDC showed inverse volume changes over time. The multivariate method showed significant diagnosis-by-time interactions in a structural covariance network consisting of the regions involved in the functional sensory-motor and default-mode networks. Higher baseline right striatal and cerebellar volumes were associated with elevated ADHD symptoms at follow-up.

CONCLUSIONS

Our findings suggest a temporal association between the divergent development of striatal and cerebellar regions and dynamical ADHD phenotypic expression through young adulthood. These results highlight a potential brain marker of future outcomes.

Resting-state EEG dynamics help explain differences in response control in ADHD: Insight into electrophysiological mechanisms and sex differences

Reductions in response control (greater reaction time variability and commission error rate) are consistently observed in those diagnosed with attention-deficit/hyperactivity disorder (ADHD). Previous research suggests these reductions arise from a dysregulation of large-scale cortical networks. Here, we extended our understanding of this cortical-network/response-control pathway important to the neurobiology of ADHD. First, we assessed how dynamic changes in three resting-state EEG network properties thought to be relevant to ADHD (phase-synchronization, modularity, oscillatory power) related with response control during a simple perceptual decision-making task in 112 children/adolescents (aged 8-16) with and without ADHD. Second, we tested whether these associations differed in males and females who were matched in age, ADHD-status and ADHD- subtype. We found that changes in oscillatory power (as opposed to phase-synchrony and modularity) are most related with response control, and that this relationship is stronger in ADHD compared to controls. Specifically, a tendency to dwell in an electrophysiological state characterized by high alpha/beta power (8-12/13-30Hz) and low delta/theta power (1-3/4-7Hz) supported response control, particularly in those with ADHD. Time in this state might reflect an increased initiation of alpha-suppression mechanisms, recruited by those with ADHD to suppress processing unfavourable to response control. We also found marginally significant evidence that this relationship is stronger in males compared to females, suggesting a distinct etiology for response control in the female presentation of ADHD.

Bayesian dynamical system analysis of the effects of methylphenidate in children with attention-deficit/hyperactivity disorder: a randomized trial

Methylphenidate is a widely used and effective treatment for attention-deficit/hyperactivity disorder (ADHD), yet the underlying neural mechanisms and their relationship to changes in behavior are not fully understood. Specifically, it remains unclear how methylphenidate affects brain and behavioral dynamics, and the interplay between these dynamics, in individuals with ADHD. To address this gap, we used a novel Bayesian dynamical system model to investigate the effects of methylphenidate on latent brain states in 27 children with ADHD and 49 typically developing children using a double-blind, placebo-controlled crossover design. Methylphenidate remediated greater behavioral variability on a continuous performance task in children with ADHD. Children with ADHD exhibited aberrant latent brain state dynamics compared to typically developing children, with a single latent state showing particularly abnormal dynamics, which was remediated by methylphenidate. Additionally, children with ADHD showed brain state-dependent hyper-connectivity in the default mode network, which was also remediated by methylphenidate. Finally, we found that methylphenidate-induced changes in latent brain state dynamics, as well as brain state-related functional connectivity between salience and default mode networks, were correlated with improvements in behavioral variability. Taken together, our findings reveal a novel latent brain state dynamical process and circuit mechanism underlying the therapeutic effects of methylphenidate in childhood ADHD. We suggest that Bayesian dynamical system models may be particularly useful for capturing complex nonlinear changes in neural activity and behavioral variability associated with ADHD. Our approach may be of value to clinicians and researchers investigating the neural mechanisms underlying pharmacological treatment of psychiatric disorders.

Methylphenidate is more effective to improve inhibitory control and working memory compared to tDCS in children and adolescents with attention deficit/hyperactivity disorder: a proof-of-concept study

Introduction

Attention-deficit/hyperactivity disorder (ADHD) is characterized by an inappropriate, pervasive and persistent pattern of inattention, hyperactivity, and/or impulsivity and associated with substantial functional impairment. Despite considerable advances in the understanding and management of ADHD, some patients do not respond well to methylphenidate (MPH), the first-choice pharmacological treatment. Over the past decades, among non-invasive brain stimulation techniques, transcranial direct current stimulation (tDCS) has proven to be an effective and safe technique to improve behavior and cognition in children with neurodevelopmental disorders, including ADHD, by modifying cortical excitability. However, the effect of tDCS has never been directly compared with that of the MPH. The present randomized sham-controlled trial evaluated the effect of a single session of anodal tDCS compared with the administration of a single dose of MPH in children and adolescents with ADHD.

Methods

After completing baseline assessment (T0), 26 children and adolescents with ADHD were exposed to 3 conditions with a 24-h interval-sessions: (A) a single session of anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC); (B) a single session of sham tDCS over the left DLPFC; (C) a single dose of MPH.

Results

Our results showed that after administering a single dose of MPH, children and adolescents with ADHD improved inhibitory control and visual-spatial WM compared with baseline, anodal, and sham tDCS. However, a single session of active tDCS over the left DLPFC was not effective compared with either baseline or sham tDCS.

Discussion

In conclusion, our protocol in ADHD involving a single tDCS session did not demonstrate consistent improvements in neurocognitive features compared with baseline, sham tDCS, or single MPH administration. Different protocols need to be developed to further test the effectiveness of tDCS in improving ADHD symptoms.

Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?

Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures - to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42113-022-00162-1.

Intra-individual variability in task performance after cognitive training is associated with long-term outcomes in children

The potential benefits and mechanistic effects of working memory training (WMT) in children are the subject of much research and debate. We show that after five weeks of school-based, adaptive WMT 6-9 year-old primary school children had greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times compared to controls. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability is useful in quantifying the immediate impact of cognitive training interventions, being a better predictor of academic skills and well-being 6-12 months after the end of training than task accuracy. Taken together, our results suggest that attention control is the initial mechanism that leads to the long-run benefits from adaptive WMT. Selective and sustained attention abilities may serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.

Can children and adolescents with ADHD use attention to maintain verbal information in working memory?

Children and adolescents with attentional-deficit/hyperactivity disorder (ADHD) present deficits in working memory (WM), but accounts for this phenomenon are still lacking. In this study, we used two variations of a complex-span task to test whether a specific WM mechanism, attentional refreshing, causes these deficits. Attentional refreshing is a maintenance strategy based on the sequential switch of attention between maintaining and processing information in WM. Its use is evidenced by a decrease in recall performance proportional to the distraction of attention away from the memoranda. In this study, we designed two experiments requiring children and adolescents with ADHD symptoms to maintain sequences of letters for subsequent recall, while performing a distracting task. In Experiment 1, the distracting task consisted of reading digits aloud. In Experiment 2, it consisted in making spatial judgements. The pace of the distracting tasks was varied to manipulate the level of attentional distraction. We observed that recall in ADHD participants was higher in the distracting conditions that give attention more opportunity to refresh letters. Moreover, ADHD participants had a similar recall performance to their age-matched typically developing peers. This study shows first evidence that individuals with ADHD can use attention to maintain verbal information in WM and calls for more research to understand their WM development.

Which Measures From a Sustained Attention Task Best Predict ADHD Group Membership?

Difficulty with sustaining attention to a task is a hallmark of ADHD. It would be useful to know which measures of sustained attention best predict a diagnosis of ADHD. Participants were 129 children with a diagnosis of ADHD and 129 matched controls who completed the fixed Sustained Attention to Response Task (SART). The number of commission and omission errors, standard deviation of response time (SDRT), tau, fast and slow frequency variability, d-prime, and mu were able to successfully classify children with and without ADHD. The mean response time, criterion, and sigma were not able to classify participants. The best classifiers were d-prime (0.75 Area Under the Receiver Operated Characteristic), tau (.74), SDRT (0.74), omission errors (0.72), commission errors (0.71), and SFAUS (0.70). This list of the best classifier measures derived from the SART may prove useful for the planning of future studies.

Default mode network mediates low-frequency fluctuations in brain activity and behavior during sustained attention

The low-frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default-mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01-0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention-fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain-behavior relationship.

Examining the Effect of Transcranial Electrical Stimulation and Cognitive Training on Processing Speed in Pediatric Attention Deficit Hyperactivity Disorder: A Pilot Study

Objective

Processing Speed (PS), the ability to perceive and react fast to stimuli in the environment, has been shown to be impaired in children with attention deficit hyperactivity disorder (ADHD). However, it is unclear whether PS can be improved following targeted treatments for ADHD. Here we examined potential changes in PS following application of transcranial electric stimulation (tES) combined with cognitive training (CT) in children with ADHD. Specifically, we examined changes in PS in the presence of different conditions of mental fatigue.

Methods

We used a randomized double-blind active-controlled crossover study of 19 unmedicated children with ADHD. Participants received either anodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (dlPFC) or transcranial random noise stimulation (tRNS), while completing CT, and the administration order was counterbalanced. PS was assessed before and after treatment using the MOXO-CPT, which measures PS in the presence of various conditions of mental fatigue and cognitive load.

Results

tRNS combined with CT yielded larger improvements in PS compared to tDCS combined with CT, mainly under condition of increased mental fatigue. Further improvements in PS were also seen in a 1-week follow up testing.

Conclusion

This study provides initial support for the efficacy of tRNS combined with CT in improving PS in the presence of mental fatigue in pediatric ADHD.

Aerobic Exercise Alleviates the Impairment of Cognitive Control Ability Induced by Sleep Deprivation in College Students: Research Based on Go/NoGo Task

The purpose of this study was to observe whether aerobic exercise is able to alleviate the impairment of cognitive control ability in college students by sleep deprivation through cognitive control (Go-NoGo task) and blood-based markers. Taking 30 healthy college students (15 males and 15 females) as participants, using a random cross-over design within groups, respectively perform one night of sleep deprivation and one night of normal sleep (8 h). The exercise intervention modality was to complete a 30-min session of moderate-intensity aerobic exercise on a power bicycle. Change in cognitive control was assessed using the Go/NoGo task paradigm; 5-ht and blood glucose contentwere determined by enzyme-linked immuno sorbent assay and glucose oxidase electrode Measurement, respectively. The results showed that sleep deprivation could significantly reduce the response inhibition ability and response execution ability, and significantly reduce the blood 5-ht content (p< 0.01). Thirty minutes of moderate intensity aerobic exercise intervention significantly increased response inhibition ability and response execution ability, significantly increased blood 5-ht content (p<0.01), and did not change serum glucose levels. Conclusion: An acute aerobic exercise can alleviate the cognitive control impairment caused by sleep deprivation, and 5-ht may be one of the possible mechanisms by which aerobic exercise alleviates the cognitive control impairment caused by sleep deprivation.

Using Neural Networks to Uncover the Relationship between Highly Variable Behavior and EEG during a Working Memory Task with Distractors

Value-driven attention capture (VDAC) occurs when previously rewarded stimuli capture attention and impair goal-directed behavior. In a working memory (WM) task with VDAC-related distractors, we observe behavioral variability both within and across individuals. Individuals differ in their ability to maintain relevant information and ignore distractions. These cognitive components shift over time with changes in motivation and attention, making it difficult to identify underlying neural mechanisms of individual differences. In this study, we develop the first participant-specific feedforward neural network models of reaction time from neural data during a VDAC WM task. We used short epochs of electroencephalography (EEG) data from 16 participants to develop the feedforward neural network (NN) models of RT aimed at understanding both WM and VDAC. Using general linear models (GLM), we identified 20 EEG features to predict RT across participants (r=0.53±0.08). The linear model was compared to the NN model, which improved the predicted trial-by-trial RT for all participants (r=0.87±0.04). We found that right frontal gamma-band activity and fronto-posterior functional connectivity in the alpha, beta, and gamma bands explain individual differences. Our study shows that NN models can link neural activity to highly variable behavior and can identify potential new targets for neuromodulation interventions.

The Infraslow Frequency Oscillatory Transcranial Direct Current Stimulation Over the Left Dorsolateral Prefrontal Cortex Enhances Sustained Attention

Background

The vigilance fluctuation and decrement of sustained attention have large detrimental consequences to most tasks in daily life, especially among the elderly. Non-invasive brain stimulations (e.g., transcranial direct current stimulation, tDCS) have been widely applied to improve sustained attention, however, with mixed results.

Objective

An infraslow frequency oscillatory tDCS approach was designed to improve sustained attention.

Methods

The infraslow frequency oscillatory tDCS (O-tDCS) over the left dorsolateral prefrontal cortex at 0.05 Hz was designed and compared with conventional tDCS (C-tDCS) to test whether this new protocol improves sustained attention more effectively. The sustained attention was evaluated by reaction time and accuracy.

Results

Compared with the C-tDCS and sham, the O-tDCS significantly enhanced sustained attention by increasing response accuracy, reducing response time, and its variability. These effects were predicted by the evoked oscillation of response time at the stimulation frequency.

Conclusion

Similar to previous studies, the modulation effect of C-tDCS on sustained attention is weak and unstable. In contrast, the O-tDCS effectively and systematically enhances sustained attention by optimizing vigilance fluctuation. The modulation effect of O-tDCS is probably driven by neural oscillations at the infraslow frequency range.

A Neuro-Computational Model for Discrete-Continuous Dual-Task Process

Studies on dual-task (DT) procedures in human behavior are important, as they can offer great insight into the cognitive control system. Accordingly, a discrete-continuous auditory-tracking DT experiment was conducted in this study with different difficulty conditions, including a continuous mouse-tracking task concurrent with a discrete auditory task (AT). Behavioral results of 25 participants were investigated via different factors, such as response time (RT), errors, and hesitations (pauses in tracking tasks). In DT, synchronization of different target neuron units was observed in corresponding brain regions; consequently, a computational model of the stimulus process was proposed to investigate the DT interference procedure during the stimulus process. This generally relates to the bottom-up attention system that a neural resource allocates for various ongoing stimuli. We proposed a black-box model based on interactions and mesoscopic behaviors of neural units. Model structure was implemented based on neurological studies and oscillator units to represent neural activities. Each unit represents one stimulus feature of task concept. Comparing the model's output behavior with the experiment results (RT) validates the model. Evaluation of the proposed model and data on RT implies that the stimulus of the AT affects the DT procedure in the model output (84% correlation). However, the continuous task is not significantly changed (26% correlation). The continuous task simulation results were inconsistent with the experiment, suggesting that continuous interference occurs in higher cognitive processing regions and is controlled by the top-down attentional system. However, this is consistent with the psychological research finding of DT interference occurring in response preparation rather than the stimulus process stage. Furthermore, we developed the proposed model by adding qualitative interpretation and saving the model's generality to address various types of discrete continuous DT procedures. The model predicts a justification method for brain rhythm interactions by synchronization, and manipulating parameters would produce different behaviors. The decrement of coupling parameter and strength factor would predict a similar pattern as in Parkinson's disease and ADHD disorder, respectively. Also, by increasing the similarity factor among the features, the model's result shows automatic task performance in each task.

Lower fractional anisotropy of the corticothalamic tract and increased response time variability in adult patients with ADHD

BACKGROUND

Intraindividual intertrial variability has been suggested as an endophenotype of attention-deficit/hyperactivity disorder (ADHD). It is usually evaluated as response time variability (RTV) in reaction time tasks, and RTV has emerged as a robust and stable feature of ADHD. Among attempts to elucidate the neurobiological underpinnings of RTV, it has been suggested that alterations in white matter microstructure may explain RTV.

METHODS

We used diffusion tensor imaging (DTI) in a group of 53 adults with ADHD and 50 healthy controls. We obtained RTV parameters from a simple reaction-time task, in which participants were asked to respond to the appearance of white crosses on a screen using button presses.

RESULTS

We observed significant between-group differences for the ex-Gaussian parameter τ, indicating that the mean of extremely slow responses was greater for adults with ADHD than controls. Fractional anisotropy (FA) derived from DTI was significantly different between groups in 2 clusters of the corticothalamic tract. In the ADHD group, relatively decreased FA values were significantly associated with the parameter τ, such that lower FA values in the corticothalamic tract predicted greater τ as an index of RTV. We did not observe this association in healthy controls.

LIMITATIONS

For comparison with previous studies, we used FA as a dependent variable of interest. However, although this metric is sensitive to white matter structural properties, there are ambiguities in its interpretation.

CONCLUSION

Even in a simple reaction-time task, RTV proved again to be a stable feature of ADHD. It was associated with altered white matter structural properties of the corticothalamic tract in adults with ADHD.

A review of objective assessments for hyperactivity in attention deficit hyperactivity disorder

Hyperactivity is one of the three core symptoms of attention deficit hyperactivity disorder (ADHD) that is a common childhood mental disorder. Objective assessments of hyperactivity are seldom utilized compared with measures of inattention and impulsivity during clinical diagnosis and evaluation. Acceleration-sensitive devices (e.g., Actigraph) and motion tracking systems (e.g., QbTest) are two main groups of devices that can be used to objectively measure hyperactivity. The Actigraph and QbTest have good discriminant validity, convergent validity, and sensitivity to the effects of stimulants. Furthermore, the assessment setting (i.e., research laboratory, school, or home) can greatly influence the presence and severity of hyperactivity. Nevertheless, objective assessments for hyperactivity have poor ability to distinguish ADHD from other disorders, or among the three types of ADHD. Thus, further studies are needed to assess objective measurements of hyperactivity in terms of discriminant and convergent validity, test-retest reliability in different settings, and correlations with brain activity.

Alterations in Structural and Functional Connectivity in ADHD: Implications for Theories of ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is increasingly viewed as a disorder of brain connectivity. We review connectivity-based theories of ADHD including the default mode network (DMN) interference and multiple network hypotheses. We outline the main approaches used to study brain connectivity in ADHD: diffusion tensor imaging and resting-state functional connectivity. We discuss the basic principles underlying these methods and the main analytical approaches used and consider what the findings have told us about connectivity alterations in ADHD. The most replicable finding in the diffusion tensor imaging literature on ADHD is lower fractional anisotropy in the corpus callosum, a key commissural tract which connects the brain's hemispheres. Meta-analyses of resting-state functional connectivity studies have failed to identify spatial convergence across studies, with the exception of meta-analyses focused on specific networks which have reported within-network connectivity alterations in the DMN and between the DMN and the fronto-parietal control and salience networks. Overall, methodological heterogeneity between studies and differences in sample characteristics are major barriers to progress in this area. In addition, females, adults and medication-naïve/unmedicated individuals are under-represented in connectivity studies, comorbidity needs to be assessed more systematically, and longitudinal research is needed to investigate whether ADHD is characterized by maturational delays in connectivity.

Reduced Power in Fronto-Parietal Theta EEG Linked to Impaired Attention-Sampling in Adult ADHD

Attention-deficit/hyperactivity disorder (ADHD) in adults is understudied, especially regarding neural mechanisms such as oscillatory control of attention sampling. We report an electroencephalography (EEG) study of such cortical mechanisms, in ADHD-diagnosed adults during administration of Test of Variables of Attention (TOVA), a gold-standard continuous performance test for ADHD that measures the ability to sustain attention and inhibit impulsivity. We recorded 53 adults (28 female, 25 male, aged 18-60), and 18 matched healthy controls, using 128-channel EEG. We analyzed sensor-space features established as neural correlates of attention: timing-sensitivity and phase-synchrony of response activations, and event-related (de)synchronization (ERS/D) of α and θ frequency band activity; in frontal and parietal scalp regions. TOVA test performance significantly distinguished ADHD adults from neurotypical controls, in commission errors, response time variability (RTV) and d' (response sensitivity). The ADHD group showed significantly weaker target-locked and response-locked amplitudes, that were strongly right-lateralized at the N2 wave, and weaker phase synchrony (longer reset poststimulus). They also manifested significantly less parietal prestimulus 8-Hz θ ERS, less frontal and parietal poststimulus 4-Hz θ ERS, and more frontal and parietal prestimulus α ERS during correct trials. These differences may reflect excessive modulation of endogenous activity by strong entrainment to stimulus (α), combined with deficient modulation by neural entrainment to task (θ), which in TOVA involves monitoring stimulus spatial location (not predicted occurrence onset which is regular and task-irrelevant). Building on the hypotheses of θ coding for relational structure and rhythmic attention sampling, our results suggest that ADHD adults have impaired attention sampling in relational categorization tasks.

Assessing Cognitive Function in Multiple Sclerosis With Digital Tools: Observational Study

Background

Cognitive impairment (CI) is one of the most prevalent symptoms of multiple sclerosis (MS). However, it is difficult to include cognitive assessment as part of MS standard care since the comprehensive neuropsychological examinations are usually time-consuming and extensive.

Objective

To improve access to CI assessment, we evaluated the feasibility and potential assessment sensitivity of a tablet-based cognitive battery in patients with MS.

Methods

In total, 53 participants with MS (24 [45%] with CI and 29 [55%] without CI) and 24 non-MS participants were assessed with a tablet-based cognitive battery (Adaptive Cognitive Evaluation [ACE]) and standard cognitive measures, including the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test (PASAT). Associations between performance in ACE and the SDMT/PASAT were explored, with group comparisons to evaluate whether ACE modules can capture group-level differences.

Results

Correlations between performance in ACE and the SDMT (R=–0.57, P<.001), as well as PASAT (R=–0.39, P=.01), were observed. Compared to non-MS and non-CI MS groups, the CI MS group showed a slower reaction time (CI MS vs non-MS: P<.001; CI MS vs non-CI MS: P=.004) and a higher attention cost (CI MS vs non-MS: P=.02; CI MS vs non-CI MS: P<.001).

Conclusions

These results provide preliminary evidence that ACE, a tablet-based cognitive assessment battery, provides modules that could potentially serve as a digital cognitive assessment for people with MS.

Trial Registration

ClinicalTrials.gov NCT03569618; https://clinicaltrials.gov/ct2/show/NCT03569618

Cognitive Dimensions of Learning in Children With Problems in Attention, Learning, and Memory

A data-driven, transdiagnostic approach was used to identify the cognitive dimensions linked with learning in a mixed group of 805 children aged 5 to 18 years recognised as having problems in attention, learning and memory by a health or education practitioner. Assessments included phonological processing, information processing speed, short-term and working memory, and executive functions, and attainments in word reading, spelling, and maths. Data reduction methods identified three dimensions of phonological processing, processing speed and executive function for the sample as a whole. This model was comparable for children with and without ADHD. The severity of learning difficulties in literacy was linked with phonological processing skills, and in maths with executive control. Associations between cognition and learning were similar across younger and older children and individuals with and without ADHD, although stronger links between learning-related problems and both executive skills and processing speed were observed in children with ADHD. The results establish clear domain-specific cognitive pathways to learning that distinguish individuals in the heterogeneous population of children struggling to learn.

The Interplay Between Prenatal Adversity, Offspring Dopaminergic Genes, and Early Parenting on Toddler Attentional Function

Background: Few studies have explored the complex gene-by-prenatal environment-by-early postnatal environment interactions that underlie the development of attentional competence. Here, we examined if variation in dopamine-related genes interacts with prenatal adversity to influence toddler attentional competence and whether this influence is buffered by early positive maternal behavior. Methods: From the Maternal Adversity, Vulnerability and Neurodevelopment cohort, 134 participants (197 when imputing missing data) had information on prenatal adversity (prenatal stressful life events, prenatal maternal depressive symptoms, and birth weight), five dopamine-related genes (DAT1, DRD4, DRD2, COMT, BDNF), observed maternal parenting behavior at 6 months and parent-rated toddler attentional competence at 18 and 24 months. The Latent Environmental and Genetic Interaction (LEGIT) approach was used to examine genes-by-prenatal environment-by-postnatal environment interactions while controlling for sociodemographic factors and postnatal depression. Results: Our hypothesis of a three-way interaction between prenatal adversity, dopamine-related genes, and early maternal parenting behavior was not confirmed. However, consistent two-way interactions emerged between prenatal adversity and dopamine-related genes; prenatal adversity and maternal parenting behavior, and dopamine-related genes and maternal parenting behavior in relation to toddler attentional competence. Significant interaction effects were driven by the DAT1, COMT, and BDNF genotypes; prenatal stressful life events; maternal sensitivity, tactile stimulation, vocalization, and infant-related activities. Conclusions: Multiple dopamine-related genes affected toddler attentional competence and they did so in interaction with prenatal adversity and the early rearing environment, separately. Effects were already visible in young children. Several aspects of early maternal parenting have been identified as potential targets for intervention.

The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project design and methodologies: a dimensional approach to understanding neurobiological and genetic aetiology

Background

ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters.

Methods

The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics.

Conclusion

The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00457-3.

Increased integration between default mode and task-relevant networks in children with ADHD is associated with impaired response control

Default mode network (DMN) dysfunction is theorized to play a role in attention lapses and task errors in children with attention-deficit/hyperactivity disorder (ADHD). In ADHD, the DMN is hyperconnected to task-relevant networks, and both increased functional connectivity and reduced activation are related to poor task performance. The current study extends existing literature by considering interactions between the DMN and task-relevant networks from a brain network perspective and by assessing how these interactions relate to response control. We characterized both static and time-varying functional brain network organization during the resting state in 43 children with ADHD and 43 age-matched typically developing (TD) children. We then related aspects of network integration to go/no-go performance. We calculated participation coefficient (PC), a measure of a region’s inter-network connections, for regions of the DMN, canonical cognitive control networks (fronto-parietal, salience/cingulo-opercular), and motor-related networks (somatomotor, subcortical). Mean PC was higher in children with ADHD as compared to TD children, indicating greater integration across networks. Further, higher and less variable PC was related to greater commission error rate in children with ADHD. Together, these results inform our understanding of the role of the DMN and its interactions with task-relevant networks in response control deficits in ADHD.

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The DMN is more integrated with task-relevant networks in children with ADHD.

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Higher and less variable DMN integration relates to poorer response control in ADHD.

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DMN dysfunction may play a key role in response control deficits in ADHD.

Monte Carlo Simulation of a Modified Chi Distribution Considering Asymmetry in the Generating Functions: Application to the Study of Health-Related Variables

Random variables in biology, social and health sciences commonly follow skewed distributions. Many of these variables can be represented by exGaussian functions; however, in practice, they are sometimes considered as Gaussian functions when statistical analysis is carried out. The asymmetry can play a fundamental role which can not be captured by central tendency estimators such as the mean. By means of Monte Carlo simulations, the effect of a small asymmetry in the generating functions of the chi distribution is studied. To this end, the k generating functions are taken as exGaussian functions. The limits of this approximation are tested numerically for the practical case of three health-related variables: one physical (body mass index) and two cognitive (verbal fluency and short-term memory). This work is in line with our previous works on a physics-inspired mathematical model to represent the reaction times of a group of individuals.

Nucleus Accumbens Stimulation Modulates Inhibitory Control by Right Prefrontal Cortex Activation in Obsessive-Compulsive Disorder

Inhibitory control is considered a compromised cognitive function in obsessive-compulsive (OCD) patients and likely linked to corticostriatal circuitry disturbances. Here, 9 refractory OCD patients treated with deep brain stimulation (DBS) were evaluated to address the dynamic modulations of large-scale cortical network activity involved in inhibitory control after nucleus accumbens (NAc) stimulation and their relationship with cortical thickness. A comparison of DBS "On/Off" states showed that patients committed fewer errors and exhibited increased intraindividual reaction time variability, resulting in improved goal maintenance abilities and proactive inhibitory control. Visual P3 event-related potentials showed increased amplitudes during Go/NoGo performance. Go and NoGo responses increased cortical activation mainly over the right inferior frontal gyrus and medial frontal gyrus, respectively. Moreover, increased cortical activation in these areas was equally associated with a higher cortical thickness within the prefrontal cortex. These results highlight the critical role of NAc DBS for preferentially modulating the neuronal activity underlying sustained speed responses and inhibitory control in OCD patients and show that it is triggered by reorganizing brain functions to the right prefrontal regions, which may depend on the underlying cortical thinning. Our findings provide updated structural and functional evidence that supports critical dopaminergic-mediated frontal-striatal network interactions in OCD.

Critical Dynamics in Spontaneous Resting-State Oscillations Are Associated With the Attention-Related P300 ERP in a Go/Nogo Task

Sustained attention is the ability to continually concentrate on task-relevant information, even in the presence of distraction. Understanding the neural mechanisms underlying this ability is critical for comprehending attentional processes as well as neuropsychiatric disorders characterized by attentional deficits, such as attention deficit hyperactivity disorder (ADHD). In this study, we aimed to investigate how trait-like critical oscillations during rest relate to the P300 evoked potential-a biomarker commonly used to assess attentional deficits. We measured long-range temporal correlations (LRTC) in resting-state EEG oscillations as index for criticality of the signal. In addition, the attentional performance of the subjects was assessed as reaction time variability (RTV) in a continuous performance task following an oddball paradigm. P300 amplitude and latencies were obtained from EEG recordings during this task. We found that, after controlling for individual variability in task performance, LRTC were positively associated with P300 amplitudes but not latencies. In line with previous findings, good performance in the sustained attention task was related to higher P300 amplitudes and earlier peak latencies. Unexpectedly, we observed a positive relationship between LRTC in ongoing oscillations during rest and RTV, indicating that greater criticality in brain oscillations during rest relates to worse task performance. In summary, our results show that resting-state neuronal activity, which operates near a critical state, relates to the generation of higher P300 amplitudes. Brain dynamics close to criticality potentially foster a computationally advantageous state which promotes the ability to generate higher event-related potential (ERP) amplitudes.

Human Reaction Times: Linking Individual and Collective Behaviour Through Physics Modeling

An individual’s reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function. In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the ex-Gaussian function which are known to correlate with cognitive disorders. Based on the recent evidence of correlations between the reaction time series to visual stimuli produced by different individuals within a group, we go beyond and propose a Physics-inspired model to represent the reaction time data of a coetaneous group of individuals. In doing so, a Maxwell–Boltzmann-like distribution appeared, the same distribution as for the velocities of the molecules in an Ideal Gas model. We describe step by step the methodology we use to go from the individual reaction times to the distribution of the individuals response within the coetaneous group. In practical terms, by means of this model we also provide a simple entropy-based methodology for the classification of the individuals within the collective they belong to with no need for an external reference which can be applicable in diverse areas of social sciences.

Individual Variability in Reaction Time and Prediction of Clinical Response to Methylphenidate in Adult ADHD: A Prospective Open Label Study Using Conners' Continuous Performance Test II

Objective: The aim of this study was to examine whether reaction time parameters in adult patients with ADHD could predict their response to methylphenidate (MPH). Method: Previously unmedicated patients (N = 123) were administered the Conners' Continuous Performance Test II (CPT II) at baseline and after 6 weeks of treatment with immediate-release MPH. In addition to traditional CPT measures, we extracted intraindividual raw data and analyzed time series using linear and nonlinear mathematical models. Results: Clinical responders, assessed with the Clinical Global Impression-Improvement scale, showed significant normalization of target failures, reduced variability and skewness, and increased complexity of reaction time series after 6 weeks of treatment, while nonresponders showed no significant changes. Prior to treatment, responders had significantly higher variability and skewness, combined with lower complexity, compared with nonresponders. Conclusion: These results show that the CPT test is useful in the evaluation of treatment response to MPH.

The Association between Executive Functions and Body Weight/BMI in Children and Adolescents with ADHD

Despite the increasing body of research on Attention Deficit Hyperactivity Disorder (ADHD), the results of the studies assessing the relationship between executive function deficit and the risk of obesity in people with ADHD are incongruent. Our study aimed to assess the relationship between measures of executive functions and body weight and Body Mass Index (BMI) in children and adolescents with ADHD and control subjects. The study group consisted of 58 subjects aged from 8 to 17 years with ADHD. The Control group consisted of 62 healthy age and sex-matched participants from primary and secondary schools. Weight, height, and BMI measurements were standardized. The Sustained Attention to Response Test (SART) and the Attention Network Test (ANT) were used to assess executive functions. Based on the analysis of the correlation and analysis of moderation, we found that subjects with higher weight in the study group presented a lower efficiency of the inhibition processes and gave more impulsive and incorrect answers. The occurrence of impulsive reactions might contribute to the risk of excessive weight in children and adolescents with ADHD.

Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis

Previous studies in children with attention-deficit/hyperactivity disorder (ADHD) have observed functional brain network disruption on a whole-brain level, as well as on a sub-network level, particularly as related to the default mode network, attention-related networks, and cognitive control-related networks. Given behavioral findings that children with ADHD have more difficulty sustaining attention and more extreme moment-to-moment fluctuations in behavior than typically developing (TD) children, recently developed methods to assess changes in connectivity over shorter time periods (i.e., "dynamic functional connectivity"), may provide unique insight into dysfunctional network organization in ADHD. Thus, we performed a dynamic functional connectivity (FC) analysis on resting state fMRI data from 38 children with ADHD and 79 TD children. We used Hidden semi-Markov models (HSMMs) to estimate six network states, as well as the most probable sequence of states for each participant. We quantified the dwell time, sojourn time, and transition probabilities across states. We found that children with ADHD spent less total time in, and switched more quickly out of, anticorrelated states involving the default mode network and task-relevant networks as compared to TD children. Moreover, children with ADHD spent more time in a hyperconnected state as compared to TD children. These results provide novel evidence that underlying dynamics may drive the differences in static FC patterns that have been observed in ADHD and imply that disrupted FC dynamics may be a mechanism underlying the behavioral symptoms and cognitive deficits commonly observed in children with ADHD.

Task-specific modulation of PFC activity for matching-rule governed decision-making

Storing information from incoming stimuli in working memory (WM) is essential for decision-making. The prefrontal cortex (PFC) plays a key role to support this process. Previous studies have characterized different neuronal populations in the PFC for working memory judgements based on whether an originally presented stimulus matches a subsequently presented one (matching-rule decision-making). However, much remains to be understood about this mechanism at the population level of PFC neurons. Here, we hypothesized differences in processing of feature vs. spatial WM within the PFC during a matching-rule decision-making task. To test this hypothesis, the modulation of neural activity within the PFC during two types of decision-making tasks (spatial WM and feature WM) in comparison to a passive fixation task was determined. We discovered that neural population-level activity within the PFC is different for the match vs. non-match condition exclusively in the case of the feature-specific decision-making task. For this task, the non-match condition exhibited a greater firing rate and lower trial-to-trial variability in spike count compared to the feature-match condition. Furthermore, the feature-match condition exhibited lower variability compared to the spatial-match condition. This was accompanied by a faster behavioral response time for the feature-match compared to the spatial-match WM task. We attribute this lower across-trial spiking variability and behavioral response time to a higher task-relevant attentional level in the feature WM compared to the spatial WM task. The findings support our hypothesis for task-specific differences in the processing of feature vs. spatial WM within the PFC. This also confirms the general conclusion that PFC neurons play an important role during the process of matching-rule governed decision-making.

Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention

Children with Attention Deficit Hyperactivity Disorder (ADHD) have prominent deficits in sustained attention that manifest as elevated intra-individual response variability and poor decision-making. Influential neurocognitive models have linked attentional fluctuations to aberrant brain dynamics, but these models have not been tested with computationally rigorous procedures. Here we use a Research Domain Criteria approach, drift-diffusion modeling of behavior, and a novel Bayesian Switching Dynamic System unsupervised learning algorithm, with ultrafast temporal resolution (490 ms) whole-brain task-fMRI data, to investigate latent brain state dynamics of salience, frontoparietal, and default mode networks and their relation to response variability, latent decision-making processes, and inattention. Our analyses revealed that occurrence of a task-optimal latent brain state predicted decreased intra-individual response variability and increased evidence accumulation related to decision-making. In contrast, occurrence and dwell time of a non-optimal latent brain state predicted inattention symptoms and furthermore, in a categorical analysis, distinguished children with ADHD from controls. Importantly, functional connectivity between salience and frontoparietal networks predicted rate of evidence accumulation to a decision threshold, whereas functional connectivity between salience and default mode networks predicted inattention. Taken together, our computational modeling reveals dissociable latent brain state features underlying response variability, impaired decision-making, and inattentional symptoms common to ADHD. Our findings provide novel insights into the neurobiology of attention deficits in children.

Examining the Overlap Between ADHD and Autism Spectrum Disorder (ASD) Using Candidate Endophenotypes of ADHD

Objective: Recent discussions of aetiological overlap between ADHD and Autism Spectrum Disorder (ASD) require comparative studying of these disorders.

METHOD

We examined performance of ASD patients with (ASD+) and without (ASD-) comorbid ADHD, ADHD patients, and controls for selected putative endophenotypes of ADHD: Intrasubject Variability (ISV) of reaction times, working memory (WM), inhibition, and temporal processing.

RESULTS

We found that patients with ADHD or ASD+, but not ASD-, had elevated ISV across the entire task battery and temporal processing deficits, and that none of the groups were impaired in WM or inhibition. High levels of ISV and generally poor performance in ASD+ patients were only partially due to additive effects of the pure disorders.

CONCLUSION

Overall, we conclude that, within our limited but heterogeneous task battery, ISV and temporal processing deficits are most sensitive to ADHD symptomatology and that controlling for ADHD comorbidity is mandatory when assessing ISV in autism.

Monte Carlo Simulation of a Modified Chi Distribution with Unequal Variances in the Generating Gaussians. A Discrete Methodology to Study Collective Response Times

The Chi distribution is a continuous probability distribution of a random variable obtained from the positive square root of the sum of k squared variables, each coming from a standard Normal distribution (mean = 0 and variance = 1). The variable k indicates the degrees of freedom. The usual expression for the Chi distribution can be generalised to include a parameter which is the variance (which can take any value) of the generating Gaussians. For instance, for k = 3, we have the case of the Maxwell-Boltzmann (MB) distribution of the particle velocities in the Ideal Gas model of Physics. In this work, we analyse the case of unequal variances in the generating Gaussians whose distribution we will still represent approximately in terms of a Chi distribution. We perform a Monte Carlo simulation to generate a random variable which is obtained from the positive square root of the sum of k squared variables, but this time coming from non-standard Normal distributions, where the variances can take any positive value. Then, we determine the boundaries of what to expect when we start from a set of unequal variances in the generating Gaussians. In the second part of the article, we present a discrete model to calculate the parameter of the Chi distribution in an approximate way for this case (unequal variances). We also comment on the application of this simple discrete model to calculate the parameter of the MB distribution (Chi of k = 3) when it is used to represent the reaction times to visual stimuli of a collective of individuals in the framework of a Physics inspired model we have published in a previous work.

Methylphenidate for attention problems in epilepsy patients: Safety and efficacy

Children with attention deficit hyperactivity disorder (ADHD) have an increased risk of seizures, and children with epilepsy have an increased prevalence of ADHD. Adults with epilepsy often have varying degrees of attentional dysfunction due to multiple factors, including anti-seizure medications, frequent seizures, interictal discharges, underlying lesions, and psychiatric comorbidities. Currently, there are no approved medications for the treatment of epilepsy-related attentional dysfunction. Methylphenidate (MPH) is a stimulant, FDA-approved for the treatment of ADHD, and often used for ADHD in the setting of pediatric epilepsy. Large database and registry studies indicate safety of MPH in children with ADHD and epilepsy, with no significant effect on seizure frequency. Small single-dose and open-label studies suggest efficacy of MPH in adults with epilepsy-related attention deficits. Methylphenidate represents a possible treatment for attentional dysfunction due to epilepsy, but large, randomized, placebo-controlled, double-blinded studies are needed.

The Missing Link Between Memory and Reinforcement Learning

Reinforcement learning systems usually assume that a value function is defined over all states (or state-action pairs) that can immediately give the value of a particular state or action. These values are used by a selection mechanism to decide which action to take. In contrast, when humans and animals make decisions, they collect evidence for different alternatives over time and take action only when sufficient evidence has been accumulated. We have previously developed a model of memory processing that includes semantic, episodic and working memory in a comprehensive architecture. Here, we describe how this memory mechanism can support decision making when the alternatives cannot be evaluated based on immediate sensory information alone. Instead we first imagine, and then evaluate a possible future that will result from choosing one of the alternatives. Here we present an extended model that can be used as a model for decision making that depends on accumulating evidence over time, whether that information comes from the sequential attention to different sensory properties or from internal simulation of the consequences of making a particular choice. We show how the new model explains both simple immediate choices, choices that depend on multiple sensory factors and complicated selections between alternatives that require forward looking simulations based on episodic and semantic memory structures. In this framework, vicarious trial and error is explained as an internal simulation that accumulates evidence for a particular choice. We argue that a system like this forms the "missing link" between more traditional ideas of semantic and episodic memory, and the associative nature of reinforcement learning.

Transcranial Direct Current Stimulation to the Left Dorsolateral Prefrontal Cortex Improves Cognitive Control in Patients With Attention-Deficit/Hyperactivity Disorder: A Randomized Behavioral and Neurophysiological Study

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder associated with significant morbidity and mortality that may affect over 5% of children and approximately 2.8% of adults worldwide. Pharmacological and behavioral therapies for ADHD exist, but critical symptoms such as dysexecutive deficits remain unaffected. In a randomized, sham-controlled, double-blind, crossover mechanistic study, we assessed the cognitive and physiological effects of transcranial direct current stimulation (tDCS) in 40 adult patients with ADHD in order to identify diagnostic (cross-sectional) and treatment biomarkers (targets).

METHODS

Patients performed three experimental sessions in which they received 30 minutes of 2 mA anodal tDCS targeting the left dorsolateral prefrontal cortex, 30 minutes of 2 mA anodal tDCS targeting the right dorsolateral prefrontal cortex, and 30 minutes of sham. Before and after each session, half the patients completed the Eriksen flanker task and the other half completed the stop signal task while we assessed behavior (reaction time, accuracy) and neurophysiology (event-related potentials).

RESULTS

Anodal tDCS to the left dorsolateral prefrontal cortex modulated cognitive (reaction time) and physiological (P300 amplitude) measures in the Eriksen flanker task in a state-dependent manner, but no effects were found in the stop signal reaction time of the stop signal task.

CONCLUSIONS

These findings show procognitive effects in ADHD associated with the modulation of event-related potential signatures of cognitive control, linking target engagement with cognitive benefit, proving the value of event-related potentials as cross-sectional biomarkers of executive performance, and mechanistically supporting the state-dependent nature of tDCS. We interpret these results as an improvement in cognitive control but not action cancellation, supporting the existence of different impulsivity constructs with overlapping but distinct anatomical substrates, and highlighting the implications for the development of individualized therapeutics.

Machinery Failure Approach and Spectral Analysis to Study the Reaction Time Dynamics over Consecutive Visual Stimuli: An Entropy-Based Model

The reaction times of individuals over consecutive visual stimuli have been studied using an entropy-based model and a failure machinery approach. The used tools include the fast Fourier transform and a spectral entropy analysis. The results indicate that the reaction times produced by the independently responding individuals to visual stimuli appear to be correlated. The spectral analysis and the entropy of the spectrum yield that there are features of similarity in the response times of each participant and among them. Furthermore, the analysis of the mistakes made by the participants during the reaction time experiments concluded that they follow a behavior which is consistent with the MTBF (Mean Time Between Failures) model, widely used in industry for the predictive diagnosis of electrical machines and equipment.

The interactive effects of test-retest and methylphenidate administration on cognitive performance in youth with ADHD: A double-blind placebo-controlled crossover study

Studies have shown that Methylphenidate (MPH) affects cognitive performance on the neuropsychological tests and clinical symptoms of individuals diagnosed with attention deficit/hyperactivity disorder (ADHD). This study investigated the acute effects of MPH on neuropsychological tests to explore the interaction between MPH and test-retest effects. Twenty youths with ADHD were tested before and after MPH intake in a double-blind placebo-controlled crossover design and compared to twenty matched controls. Participants were tested on a range of standardized tasks including sustained attention to response, N-Back, and Word/Color Stroop. Identical tasks were administered twice each testing day, before and 1 hour after MPH/Placebo administration. Healthy controls were tested similarly with no intervention. Decreases in response time (RT) variability across tasks and in commission errors were found in ADHD after MPH. Conversely, a significant increase in RT variability and increase in omission errors were observed after the placebo. In the control group, RT variability and omission errors increased whereas commission errors decreased, suggesting fatigue and practice effects, respectively. Test-retest reliability was higher in controls than ADHD. It is suggested that cognitive tests are sensitive objective measures for the assessment of responses to MPH in ADHD but are also affected by repetition and fatigue.