Using the Diffusion Model to Explain Cognitive Deficits in Attention Deficit Hyperactivity Disorder

Assessing the Longitudinal Associations Between Decision-Making Processes and Attention Problems in Early Adolescence

Cognitive functions and psychopathology develop in parallel in childhood and adolescence, but the temporal dynamics of their associations are poorly understood. The present study sought to elucidate the intertwined development of decision-making processes and attention problems using longitudinal data from late childhood (9-10 years) to mid-adolescence (11-13 years) from the Adolescent Brain Cognitive Development (ABCD) Study (n = 8918). We utilised hierarchical drift-diffusion modelling of behavioural data from the stop-signal task, parent-reported attention problems from the Child Behavior Checklist (CBCL), and multigroup univariate and bivariate latent change score models. The results showed faster drift rate was associated with lower levels of inattention at baseline, as well as a greater reduction of inattention over time. Moreover, baseline drift rate negatively predicted change in attention problems in females, and baseline attention problems negatively predicted change in drift rate. Neither response caution (decision threshold) nor encoding- and responding processes (non-decision time) were significantly associated with attention problems. There were no significant sex differences in the associations between decision-making processes and attention problems. The study supports previous findings of reduced evidence accumulation in attention problems and additionally shows that development of this aspect of decision-making plays a role in developmental changes in attention problems in youth.

Transcutaneous auricular vagus nerve stimulation enhanced emotional inhibitory control via increasing intrinsic prefrontal couplings

Background

Inhibitory control represents a core executive function that critically facilitates adaptive behavior and survival in an ever-changing environment. Non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) has been hypothesized to improve behavioral inhibition performance, however the neurocomputational mechanism of taVNS-induced neuroenhancement remains elusive.

Method

In the current study, we investigated the efficacy of taVNS in a sham-controlled between-subject functional near infrared spectroscopy (fNIRS) experiment with an emotional face Go/No-Go paradigm in ninety healthy young adults.

Results

After a data quality check, eighty-two subjects were included in the final data analysis. Behaviorally, the taVNS improved No-Go response accuracy, together with computational modeling using Hierarchical Bayesian estimation of the Drift Diffusion Model (HDDM) indicating that it specifically reduced the information accumulation rate for Go responses, and this was negatively associated with increased accuracy of No-Go responses. On the neural level, taVNS enhanced engagement of the bilateral inferior frontal gyrus (IFG) during inhibition of angry expression faces and modulated functional couplings (FCs) within the prefrontal inhibitory control network. Mediation models revealed that taVNS-induced facilitation of inhibitory control was critically mediated by a decreased information accumulation for Go responses and concomitantly enhanced neurofunctional coupling between the inferior and orbital frontal cortex.

Discussion

Our findings demonstrate a potential for taVNS to improve emotional inhibitory control via reducing pre-potent responses and enhancing FCs within prefrontal inhibitory control networks, suggesting a promising therapeutic role in treating specific disorders characterized by inhibitory control deficits.

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.

A diffusion decision model analysis of the cognitive effects of neurofeedback for ADHD

OBJECTIVE

To examine cognitive effects of neurofeedback (NF) for attention-deficit hyperactivity disorder (ADHD) as a secondary outcome of a randomized clinical trial.

METHOD

In a double-blind randomized clinical trial (NCT02251743), 133 7-10-year olds with ADHD received either 38 sessions of NF (n = 78) or control treatment (n = 55) and performed an integrated visual and auditory continuous performance test at baseline, mid- and end-treatment. We used the diffusion decision model to decompose integrated visual and auditory continuous performance test performance at each assessment into cognitive components: efficiency of integrating stimulus information (v), context sensitivity (cv), response cautiousness (a), response bias (z/a), and nondecision time for perceptual encoding and response execution (Ter). Based on prior findings, we tested whether the components known to be deficient improved with NF and explored whether other cognitive components improved using linear mixed modeling.

RESULTS

Before NF, children with ADHD showed main deficits in integrating stimulus information (v), which led to less accurate and slower responses than healthy controls (p = .008). The NF group showed significantly more improvement in integrating auditory stimulus information (v) than control treatment (significant group-by-time-by-modality effect: p = .044).

CONCLUSIONS

NF seems to improve v, deficient in ADHD. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Disentangling the relationships between motor control and cognitive control in young children with symptoms of ADHD

Children with ADHD experience difficulties with motor and cognitive control. However, the relationships between these symptoms are poorly understood. As a step toward improving treatment, this study investigated associations between specific aspects of motor control and cognitive control in children with varying levels of hyperactive-impulsive symptoms. A heterogeneous sample of 255 children of 4 to 10 years of age (median = 6.50, MAD = 1.36) completed a battery of tests probing motor generation, visuomotor fluency, visuomotor flexibility, cognitive inhibition, verbal and visuospatial working memory, and cognitive flexibility. Their caregivers were interviewed regarding their hyperactive-impulsive symptoms. 25.9% of the main sample met diagnostic criteria for ADHD. Multiple linear regression analysis was used to determine whether specific aspects of motor control were associated with specific aspects of cognitive control, and whether any associations were moderated by hyperactive-impulsive symptoms. Additionally, cognitive modeling (the drift diffusion model approximated with EZ-DM) was used to understand performance on a cognitive inhibition task. Visuomotor fluency was significantly associated with cognitive inhibition. Visuomotor flexibility was significantly associated with cognitive flexibility. There were no significant moderation effects. Cognitive modeling was inconclusive. In conclusion, the ability to fluently perform visually guided continuous movement is linked with the ability to inhibit the effects of distracting information. The ability to spontaneously use visual information to flexibly alter motor responses is related to the ability to cognitively shift from one frame of mind to another. These relationships appear to be quantitatively and qualitatively similar across the childhood hyperactive-impulsive continuum as rated by parents.

Preferential Choice to Exert Cognitive Effort in Children with ADHD: a Diffusion Modelling Account

Greater sensitivity to the cost of effortful engagement has long been implicated in the development of Attention Deficit Hyperactivity Disorder (ADHD). The current study evaluated preferential choice to engage in demanding tasks, and did so in combination with computational methods to interrogate the process of choice. Children aged 8-12 with (n = 49) and without (n = 36) ADHD were administered the cognitive effort discounting paradigm (COG-ED, adapted from Westbrook et al., 2013). Diffusion modelling was subsequently applied to the choice data to allow for a better description of the process of affective decision making. All children showed evidence of effort discounting, but, contrary to theoretical expectations, there was no evidence that children with ADHD judged effortful tasks to be lower in subjective value, or that they maintained a bias towards less effortful tasks. However, children with ADHD developed a much less differentiated mental representation of demand than their non-ADHD counterparts even though familiarity with and exposure to the experience of effort was similar between groups. Thus, despite theoretical arguments to the contrary, and colloquial use of motivational constructs to explain ADHD-related behavior, our findings strongly argue against the presence of greater sensitivity to costs of effort or reduced sensitivity to rewards as an explanatory mechanism. Instead, there appears to be a more global weakness in the metacognitive monitoring of demand, which is a critical precursor for cost-benefit analyses that underlie decisions to engage cognitive control.

The Posterior Cingulate Cortex Reflects the Impact of Anxiety on Drift Rates During Cognitive Processing

BACKGROUND

Generally, anxiety is thought to impair ongoing cognitive operations. Surprisingly, however, anxiety has been shown to improve performance during the Go/NoGo task. Understanding how anxiety can facilitate task performance may shed light on avenues to address the cognitive deficits commonly associated with anxiety.

METHODS

A total of 39 participants (mean age ± SD = 27.5 ± 7.22 years; 18 women) performed a Go/NoGo task during periods of safety and periods of experimental anxiety, induced using the unpredictable delivery of aversive stimuli. Computational analysis and ultrahigh field (7T) functional magnetic resonance imaging were used to determine how induced anxiety affected computational processes and blood oxygen level-dependent responses during the task.

RESULTS

Induced anxiety improved accuracy during the Go/NoGo task. Induced anxiety was associated with an amplified drift rate process, which is thought to reflect increased informational uptake. In addition, changes in drift rate during the anxiety condition were associated with enhanced blood oxygen level-dependent responses within the posterior cingulate cortex during Go trials.

CONCLUSIONS

These results may reflect the impact of induced anxiety on the activity of neurons within the posterior cingulate cortex, whose activity patterns mimic the buildup of evidence accumulation. Collectively, these results shed light on the mechanisms underlying facilitated task performance and suggest that anxiety can improve cognitive processing by enhancing information uptake and increasing activity within the posterior cingulate cortex.

Cognitive markers for efficacy of neurofeedback for attention-deficit hyperactivity disorder - personalized medicine using computational psychiatry in a randomized clinical trial

BACKGROUND

Exploring whether cognitive components (identified by baseline cognitive testing and computational modeling) moderate clinical outcome of neurofeedback (NF) for attention-deficit hyperactivity disorder (ADHD).

METHOD

142 children (aged 7-10) with ADHD were randomly assigned to either NF (n = 84) or control treatment (n = 58) in a double-blind clinical trial (NCT02251743). The NF group received live, self-controlled downtraining of electroencephalographic theta/beta ratio power. The control group received identical-appearing reinforcement from prerecorded electroencephalograms from other children. 133 (78 NF, 55 control) children had cognitive processing measured at baseline with the Integrated Visual and Auditory Continuous Performance Test (IVA2-CPT) and were included in this analysis. A diffusion decision model applied to the IVA2-CPT data quantified two latent cognitive components deficient in ADHD: drift rate and drift bias, indexing efficiency and context sensitivity of cognitive processes involving information integration. We explored whether these cognitive components moderated the improvement in parent- and teacher-rated inattention symptoms from baseline to treatment end (primary clinical outcome).

RESULTS

Baseline cognitive components reflecting information integration (drift rate, drift bias) moderated the improvement in inattention due to NF vs. control treatment (p = 0.006). Specifically, those with either the most or least severe deficits in these components showed more improvement in parent- and teacher-rated inattention when assigned to NF (Cohen's d = 0.59) than when assigned to control (Cohen's d = -0.21).

CONCLUSIONS

Pre-treatment cognitive testing with computational modeling identified children who benefitted more from neurofeedback than control treatment for ADHD.

Ignore the glitch but mind the switch: Positive effects of methylphenidate on cognition in attention deficit hyperactivity disorder are related to prediction gain

Neuropsychological symptoms such as inattention and distractibility constitute a core characteristic of attention deficit hyperactivity disorder (ADHD). Here, we tested the hypothesis that attentional dysfunctions result from a deficit in neural gain modulation, which translates into difficulty in predictively weighting relevant sensory input while ignoring distraction. We compared thirty-seven hitherto untreated adults diagnosed with ADHD and thirty-eight healthy participants with a serial switch-drift task that requires internal models of predictable digit sequences to be either updated or stabilized. Switches between sequences that had to be indicated by key presses and digit omissions within a sequence (drifts) that should be ignored varied by stimulus-bound surprise quantified as Shannon information. To investigate whether catecholaminergic modulation by increasing extracellular norepinephrine and dopamine levels leads to an amelioration in prediction gain, participants were tested twice, with patients receiving a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, in the second session. Patients and controls differed in both updating and stabilizing, depending on the respective event surprise. Specifically, patients showed difficulty in detecting expectable switches, while having greater difficulty to ignore surprising distractions. Thus, underconfident prior beliefs in ADHD may fail to appropriately weight expected relevant input, whereas the gain of neural responses to unexpected irrelevant distractors is increased. Methylphenidate improved both flexibility and stability of prediction and had a positive effect on selective responding over time. Our results suggest that ADHD is associated with an impairment in the use of prior expectations to optimally weight sensory inputs, which is improved by increasing catecholaminergic neurotransmission.

Ahead of the (ROC) Curve: A Statistical Approach to Utilizing Ex-Gaussian Parameters of Reaction Time in Diagnosing ADHD Across Three Developmental Periods

INTRODUCTION

Performance on executive function (EF) tasks is only modestly predictive of a diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), despite the common assumption that EF deficits are ubiquitous to the disorder. The current study sought to determine whether ex-Gaussian parameters of simple reaction time are better able to discriminate between children and adults with and without ADHD, compared with traditional measures of inhibitory control.

METHODS

Receiver Operating Characteristic (ROC) analyses and the area under the curve (AUC) were used to examine the ability of performance on two commonly used tasks of inhibitory control (i.e. stop signal reaction time (SSRT) and go-no-go tasks) to predict ADHD status in preschool (N = 108), middle childhood (N = 309), and young adulthood (N = 133).

RESULTS

Across all samples, SSRT, go-no-go percentage of failed inhibits, and standard deviation of reaction (SDRT) time to "go" trials, all successfully discriminated between individuals with and without ADHD. Ex-Gaussian decomposition of the RT distribution indicated that both larger tau and larger sigma drove findings for SDRT. Contrary to predictions, traditional measures of inhibitory control were equal if not better predictors of ADHD status than ex-Gaussian parameters.

CONCLUSIONS

Findings support ongoing work to quantify the separate contributions of cognitive subprocesses that drive task performance, which in turn is critical to developing and improving process-based approaches in clinical assessment.

The role of parenting in the intergenerational transmission of executive functioning: A genetically informed approach

Deficits in executive functioning both run in families and serve as a transdiagnostic risk factor for psychopathology. The present study employed twin modeling to examine parenting as an environmental pathway underlying the intergenerational transmission of executive functioning in an at-risk community sample of children and adolescents (N = 354 pairs, 167 monozygotic). Using structural equation modeling of multi-informant reports of parenting and a multi-method measure of child executive functioning, we found that better parent executive functioning related to less harsh, warmer parenting, which in turn related to better child executive functioning. Second, we assessed the etiology of executive functioning via the nuclear twin family model, finding large non-shared environmental effects (E = .69) and low-to-moderate heritability (A = .22). We did not find evidence of shared environmental effects or passive genotype-environment correlation. Third, a bivariate twin model revealed significant shared environmental overlap between both warm and harsh parenting and child executive functioning (which may indicate either passive genotype-environment correlation or environmental mediation), and non-shared environmental overlap between only harsh parenting and child executive functioning (indicating an effect of harsh parenting separable from genetic confounds). In summary, genetics contribute to the intergenerational transmission of executive functioning, with environmental mechanisms, including harsh parenting, also making unique contributions.

Event rate effects on children with attention-deficit/hyperactive disorder: Test predictions from the moderate brain arousal model and the neuro-energetics theory using the diffusion decision model

BACKGROUND

Converging evidence has found that the inhibitory control of children with attention-deficit/hyperactive disorder (ADHD) is context-dependent and particularly susceptible to the event rate. The Moderate Brain Arousal (MBA) model predicts a U-shaped curve between event rate and performance as a modulation of brain arousal. The neuroenergetics theory (NeT) proposes that a smaller event rate results in neuronal fatigue and subsequent descent performance. However, previous work applied the traditional one-dimensional index of performance, such as accuracy rate and response time, which might limit the exploration of the event rate effect on the specific underlying process.

AIMS

We used a diffusion decision model (DDM) to study the influence of event rate on inhibition control in children with ADHD and verified the explanation of the MBA model and the NeT.

METHODS AND PROCEDURES

The Stop Signal Task manipulated by four event rate conditions was conducted with 24 children with ADHD (mean age=8.5, males=16) and 29 typical developmental children (TDC) (mean age=9.0, males=12). DDM was applied to compare the differences in the DDM parameters across different event rates.

OUTCOMES AND RESULTS

Compared with TDC, children with ADHD had a smaller drift rate, longer non-decision time, and smaller boundary separation. Although the event rate had little influence on ADHD, the drift rate of the TDC was approximately linear with an increased event rate, and the Ter had a quadratic function relationship with the event rate.

CONCLUSIONS AND IMPLICATIONS

The event rate effect may influence children's performance through dual mechanisms. Neuronal energy supply could regulate information processing and brain arousal to regulate the activation of primary stimuli encoding and motor control. Insight into the multi-mechanism of ADHD cognition deficits would be helpful for clinicians in making objective diagnoses and effective targeted treatments.

On the Need to Improve the Way Individual Differences in Cognitive Function Are Measured With Reaction Time Tasks

The measurement of individual differences in specific cognitive functions has been an important area of study for decades. Often the goal of such studies is to determine whether there are cognitive deficits or enhancements associated with, for example, a specific population, psychological disorder, health status, or age group. The inherent difficulty, however, is that most cognitive functions are not directly observable, so researchers rely on indirect measures to infer an individual’s functioning. One of the most common approaches is to use a task that is designed to tap into a specific function and to use behavioral measures, such as reaction times (RTs), to assess performance on that task. Although this approach is widespread, it unfortunately is subject to a problem of reverse inference: Differences in a given cognitive function can be manifest as differences in RTs, but that does not guarantee that differences in RTs imply differences in that cognitive function. We illustrate this inference problem with data from a study on aging and lexical processing, highlighting how RTs can lead to erroneous conclusions about processing. Then we discuss how employing choice-RT models to analyze data can improve inference and highlight practical approaches to improving the models and incorporating them into one’s analysis pipeline.

Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience

Quantifying individual differences in higher-order cognitive functions is a foundational area of cognitive science that also has profound implications for research on psychopathology. For the last two decades, the dominant approach in these fields has been to attempt to fractionate higher-order functions into hypothesized components (e.g., "inhibition", "updating") through a combination of experimental manipulation and factor analysis. However, the putative constructs obtained through this paradigm have recently been met with substantial criticism on both theoretical and empirical grounds. Concurrently, an alternative approach has emerged focusing on parameters of formal computational models of cognition that have been developed in mathematical psychology. These models posit biologically plausible and experimentally validated explanations of the data-generating process for cognitive tasks, allowing them to be used to measure the latent mechanisms that underlie performance. One of the primary insights provided by recent applications of such models is that individual and clinical differences in performance on a wide variety of cognitive tasks, ranging from simple choice tasks to complex executive paradigms, are largely driven by efficiency of evidence accumulation (EEA), a computational mechanism defined by sequential sampling models. This review assembles evidence for the hypothesis that EEA is a central individual difference dimension that explains neurocognitive deficits in multiple clinical disorders and identifies ways in which in this insight can advance clinical neuroscience research. We propose that recognition of EEA as a major driver of neurocognitive differences will allow the field to make clearer inferences about cognitive abnormalities in psychopathology and their links to neurobiology.

Characterizing Underlying Cognitive Components of ADHD Presentations and Co-morbid Diagnoses: A Diffusion Decision Model Analysis

OBJECTIVE

To Explore whether subtypes and comorbidities of attention-deficit hyperactivity disorder (ADHD) induce distinct biases in cognitive components involved in information processing.

METHOD

Performance on the Integrated Visual and Auditory Continuous Performance Test (IVA-CPT) was compared between 150 children (aged 7 to 10) with ADHD, grouped by DSM-5 presentation (ADHD-C, ADHD-I) or co-morbid diagnoses (anxiety, oppositional defiant disorder [ODD], both, neither), and 60 children without ADHD. Diffusion decision modeling decomposed performance into cognitive components.

RESULTS

Children with ADHD had poorer information integration than controls. Children with ADHD-C were more sensitive to changes in presentation modality (auditory/visual) than those with ADHD-I and controls. Above and beyond these results, children with ADHD+anxiety+ODD had larger increases in response biases when targets became frequent than children with ADHD-only or with ADHD and one comorbidity.

CONCLUSION

ADHD presentations and comorbidities have distinct cognitive characteristics quantifiable using DDM and IVA-CPT. We discuss implications for tailored cognitive-behavioral therapy.

Transcranial direct current stimulation (tDCS) alters the pattern of information processing in children with ADHD: Evidence from drift diffusion modeling

OBJECTIVE

Performance accuracy and reaction time in cognitive tasks are routinely used to evaluate the efficacy of tDCS to affect cognitive task performance. tDCS alters the excitability of targeted brain areas and thereby alters performance of cognitive tasks. The drift diffusion model (DDM) provides some additional measures to explore information processing style, such as (non)decision time, bias for decision, and speed of information processing. DDM parameters are informative for the study of cognitive impairments in children with ADHD. In the present study, we aimed to evaluate the impact of tDCS on cognitive performance via DDM measures.

METHODS

This study conducted DDM modeling and reanalysis of two exploratory, single-blinded, within-subject design experiments, which were published earlier. In the first experiment, twenty- four children with ADHD performed a Go/ No- Go task during anodal or sham tDCS over the right dlPFC. In the second experiment, twenty- five children with ADHD performed the 1- back working memory task during anodal or sham tDCS over the left dlPFC. We reanalyzed the data after DDM modeling.

RESULTS

The conventional performance measures revealed no significant effect of tDCS on No- Go accuracy in the first experiment and 1-back accuracy in the second experiment. The 1-back reaction time and speed-accuracy tradeoff were however improved under the real stimulation condition. The DDM measures identified increased No-Go- bias and decision time with respect to inhibitory control, and an increased threshold and amount of information required for response in the 1- back test.

CONCLUSION

In children with ADHD, anodal tDCS over the right dlPFC induces more conservative and less impulsive decisions. Furthermore, anodal tDCS over the left dlPFC enhanced efficacy of working memory performance with respect to agility and capacity. The experimental results show that drift diffusion modeling is useful for evaluation of the impact of tDCS on the style of information processing.

Disentangling cognitive processes in externalizing psychopathology using drift diffusion modeling: Antagonism, but not disinhibition, is associated with poor cognitive control

Although externalizing psychopathology has been linked to deficits in cognitive control, the cognitive processes underlying this association are unclear. Here, we provide a theoretical account of how research on cognitive processes can help to integrate and distinguish personality and psychopathology. We then apply this account to connect the two major subcomponents of externalizing, Antagonism and Disinhibition, with specific control processes using a battery of inhibitory control tasks and corresponding computational modeling. Participants (final N = 104) completed the flanker, go/no-go, and recent probes tasks, as well as normal and maladaptive personality inventories and measures of psychological distress. We fit participants' task behavior using a hierarchical drift diffusion model (DDM) to decompose their responses into specific cognitive processes. Using multilevel structural equation models, we found that Antagonism was associated with faster RTs on the flanker task and lower accuracy on flanker and go/no-go tasks. These results were complemented by DDM parameter associations: Antagonism was linked to decreased threshold and drift rate parameter estimates in the flanker task and a decreased drift rate on no-go trials. Altogether, our findings indicate that Antagonism is associated with specific impairments in fast (sub-second) inhibitory control processes involved in withholding prepared/prepotent responses and filtering distracting information. Disinhibition and momentary distress, however, were not associated with task performance.

Evidence accumulation and associated error-related brain activity as computationally-informed prospective predictors of substance use in emerging adulthood

RATIONALE

Substance use peaks during the developmental period known as emerging adulthood (ages 18-25), but not every individual who uses substances during this period engages in frequent or problematic use. Although individual differences in neurocognition appear to predict use severity, mechanistic neurocognitive risk factors with clear links to both behavior and neural circuitry have yet to be identified. Here, we aim to do so with an approach rooted in computational psychiatry, an emerging field in which formal models are used to identify candidate biobehavioral dimensions that confer risk for psychopathology.

OBJECTIVES

We test whether lower efficiency of evidence accumulation (EEA), a computationally characterized individual difference variable that drives performance on the go/no-go and other neurocognitive tasks, is a risk factor for substance use in emerging adults.

METHODS AND RESULTS

In an fMRI substudy within a sociobehavioral longitudinal study (n = 106), we find that lower EEA and reductions in a robust neural-level correlate of EEA (error-related activations in salience network structures) measured at ages 18-21 are both prospectively related to greater substance use during ages 22-26, even after adjusting for other well-known risk factors. Results from Bayesian model comparisons corroborated inferences from conventional hypothesis testing and provided evidence that both EEA and its neuroimaging correlates contain unique predictive information about substance use involvement.

CONCLUSIONS

These findings highlight EEA as a computationally characterized neurocognitive risk factor for substance use during a critical developmental period, with clear links to both neuroimaging measures and well-established formal theories of brain function.

Vision as oculomotor reward: cognitive contributions to the dynamic control of saccadic eye movements

Humans and other primates are equipped with a foveated visual system. As a consequence, we reorient our fovea to objects and targets in the visual field that are conspicuous or that we consider relevant or worth looking at. These reorientations are achieved by means of saccadic eye movements. Where we saccade to depends on various low-level factors such as a targets' luminance but also crucially on high-level factors like the expected reward or a targets' relevance for perception and subsequent behavior. Here, we review recent findings how the control of saccadic eye movements is influenced by higher-level cognitive processes. We first describe the pathways by which cognitive contributions can influence the neural oculomotor circuit. Second, we summarize what saccade parameters reveal about cognitive mechanisms, particularly saccade latencies, saccade kinematics and changes in saccade gain. Finally, we review findings on what renders a saccade target valuable, as reflected in oculomotor behavior. We emphasize that foveal vision of the target after the saccade can constitute an internal reward for the visual system and that this is reflected in oculomotor dynamics that serve to quickly and accurately provide detailed foveal vision of relevant targets in the visual field.

Children's inhibitory control abilities in the presence of rewards are related to weight status and eating in the absence of hunger

The Reflective-Impulsive Dual Processes Model suggests that overeating occurs when the temptation to consume food overrides inhibitory control processes. However, how rewards interact with inhibitory control and their relation to children's weight status and food intake is not understood. Here, 7-to-11-year-old children (n = 66; 32 overweight/obese) completed two versions (baseline [i.e., non-reward incentivized/control] and reward incentivized [food, money, no reward]) of a Go/Nogo task. Intake of palatable foods in the absence of hunger (i.e., eating in the absence of hunger-EAH) was measured following a standardized meal. A drift diffusion model was used to characterize children's performance parameters on the Go/Nogo. On the baseline Go/Nogo, children with higher weight status responded more cautiously, but on reward trials for food/money children were more cautions and made more false alarms relative to the no reward condition. Energy intake during EAH positively correlated with FA errors for food and money vs. no reward, but sex moderated this effect such that FA positively associated with EAH in girls but not boys. Independent of sex, FA for money vs. no reward and food vs. money were both positively associated with energy consumed during EAH. These results suggest that the presence of food and money rewards impair inhibitory control processing, especially in children with higher weight status. Further, increased inhibitory control impairment in response to food rewards, specifically, may be a risk factor for disinhibited eating in girls. Though preliminary, results may be useful in the development of targeted treatments to help moderate excess consumption in children.

Computational Modeling of Attentional Impairments in Disruptive Mood Dysregulation and Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

Computational models provide information about cognitive components underlying behavior. When applied to psychopathology-relevant processes, they offer additional insight to observed differences in behavioral performance. Drift diffusion models have been successfully applied to investigate processing efficiency during binary choice tasks. Using these models, we examine the association between psychopathology (irritability and inattention/hyperactivity) and processing efficiency under different attentional demands.

METHOD

A total of 187 youths with attention-deficit/hyperactivity disorder (ADHD), disruptive mood dysregulation disorder (DMDD), both disorders, or no major psychopathology (age, mean ± SD, 13.09 ± 2.55 y, 34% female) completed an Eriksen Flanker task. Of these, 87 youths provided complete data on dimensional measures of the core symptom of DMDD (irritability) and those of ADHD (inattention and hyperactivity).

RESULTS

In a categorical diagnosis-based analysis (n = 187), we found significant interactive effects among ADHD, DMDD, and task condition on processing efficiency, whereby changes in processing efficiency between conflict and nonconflict conditions were larger in youths without psychopathology compared with patients. Analysis of symptom severity (n = 87) across diagnoses similarly revealed an interaction between symptom dimensions and task condition on processing efficiency. Irritability moderated the magnitude of association between inattention symptoms and difference in processing efficiency between conflict and nonconflict conditions.

CONCLUSION

Adapting processing efficiency to cognitive demands may represent a shared cognitive endophenotype for both ADHD and DMDD. Highly irritable and/or inattentive youth may have difficulty adjusting processing efficiency to changing task demands, possibly reflecting impairments in cognitive flexibility.

Slow drift rate predicts ADHD symptomology over and above executive dysfunction

Slow drift rate has become one of the most salient cognitive deficits among children with ADHD, and has repeatedly been found to explain slow, variable, and error-prone performance on tasks of executive functioning (EF). The present study applies the diffusion model to determine whether slow drift rate better predicts parent and teacher ratings of ADHD than standard EF metrics. 201 children aged 8-12 completed two tests of speeded decision-making analyzed with the diffusion model and two traditionally scored tests of EF. Latent EF and drift rate factors each independently predicted the general ADHD factor in a bifactor model of ADHD, with poor EF and slow drift rate associated with greater ADHD symptomology. When both EF and drift rate were entered into the model, slow drift rate (but not EF) continued to predict elevated symptomology. These findings suggest that using drift rate to index task performance improves upon conventional approaches to measuring and conceptualizing cognitive dysfunction in ADHD. Implications for future cognitive research in ADHD are discussed.

Bridging sensory and language theories of dyslexia: Toward a multifactorial model

Competing theories of dyslexia posit that reading difficulties arise from impaired visual, auditory, phonological, or statistical learning mechanisms. Importantly, many theories posit that dyslexia reflects a cascade of impairments emanating from a single “core deficit”. Here we report two studies evaluating core deficit and multifactorial models. In Study 1, we use publicly available data from the Healthy Brain Network to test the accuracy of phonological processing measures for predicting dyslexia diagnosis and find that over 30% of cases are misclassified (sensitivity = 66.7%; specificity = 68.2%). In Study 2, we collect a battery of psychophysical measures of visual motion processing and standardized measures of phonological processing in 106 school‐aged children to investigate whether dyslexia is best conceptualized under a core‐deficit model, or as a disorder with heterogenous origins. Specifically, by capitalizing on the drift diffusion model to analyze performance on a visual motion discrimination experiment, we show that deficits in visual motion processing, perceptual decision‐making, and phonological processing manifest largely independently. Based on statistical models of how variance in reading skill is parceled across measures of visual processing, phonological processing, and decision‐making, our results challenge the notion that a unifying deficit characterizes dyslexia. Instead, these findings indicate a model where reading skill is explained by several distinct, additive predictors, or risk factors, of reading (dis)ability.

ADHD: Current Concepts and Treatments in Children and Adolescents

Attention deficit hyperactivity disorder (ADHD) is among the most frequent disorders within child and adolescent psychiatry, with a prevalence of over 5%. Nosological systems, such as the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) and the International Classification of Diseases, editions 10 and 11 (ICD-10/11) continue to define ADHD according to behavioral criteria, based on observation and on informant reports. Despite an overwhelming body of research on ADHD over the last 10 to 20 years, valid neurobiological markers or other objective criteria that may lead to unequivocal diagnostic classification are still lacking. On the contrary, the concept of ADHD seems to have become broader and more heterogeneous. Thus, the diagnosis and treatment of ADHD are still challenging for clinicians, necessitating increased reliance on their expertise and experience. The first part of this review presents an overview of the current definitions of the disorder (DSM-5, ICD-10/11). Furthermore, it discusses more controversial aspects of the construct of ADHD, including the dimensional versus categorical approach, alternative ADHD constructs, and aspects pertaining to epidemiology and prevalence. The second part focuses on comorbidities, on the difficulty of distinguishing between "primary" and "secondary" ADHD for purposes of differential diagnosis, and on clinical diagnostic procedures. In the third and most prominent part, an overview of current neurobiological concepts of ADHD is given, including neuropsychological and neurophysiological researches and summaries of current neuroimaging and genetic studies. Finally, treatment options are reviewed, including a discussion of multimodal, pharmacological, and nonpharmacological interventions and their evidence base.

Identifying Feigned Cognitive Impairment: Investigating the Utility of Diffusion Model Analyses

Forced-choice performance validity tests are routinely used for the detection of feigned cognitive impairment. The drift diffusion model deconstructs performance into distinct cognitive processes using accuracy and response time measures. It thereby offers a unique approach for gaining insight into examinees' speed-accuracy trade-offs and the cognitive processes that underlie their performance. The current study is the first to perform such analyses using a well-established forced-choice performance validity test. To achieve this aim, archival data of healthy participants, either simulating cognitive impairment in the Word Memory Test or performing it to the best of their ability, were analyzed using the EZ-diffusion model (N = 198). The groups differed in the three model parameters, with drift rate emerging as the best predictor of group membership. These findings provide initial evidence for the usefulness of the drift diffusion model in clarifying the cognitive processes underlying feigned cognitive impairment and encourage further research.

Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology

BACKGROUND

Individuals with attention-deficit/hyperactivity disorder and other externalizing psychopathologies tend to display poor behavioral performance on the go/no-go task, which is thought to reflect deficits in inhibitory control. However, clinical neuroimaging studies using this task have yielded conflicting results, raising basic questions about what the task measures and which aspects of the task relate to clinical outcomes. We used computational modeling to provide a clearer understanding of how neural activations from this task relate to the cognitive mechanisms that underlie performance and to probe the implications of these relationships for clinical research.

METHODS

A total of 143 young adults (8-21 years of age) performed the go/no-go task during functional magnetic resonance imaging scanning. We used the diffusion decision model (DDM), a cognitive modeling approach, to quantify distinct neurocognitive processes that underlie go/no-go performance. We then assessed correlations between DDM parameters and brain activation from standard go/no-go contrasts and assessed relationships of DDM parameters and associated neural measures with clinical ratings.

RESULTS

Right-lateralized prefrontal activations on correct inhibition trials, which are generally assumed to isolate neural processes involved in inhibition, were unrelated to DDM parameters (and other performance indices). However, responses to failed inhibitions in brain regions associated with error monitoring were strongly related to more efficient task performance and correlated with externalizing behavior and attention-deficit/hyperactivity disorder symptoms.

CONCLUSIONS

Our findings cast doubt on conventional interpretations of go/no-go task-related activations as reflecting the neural basis of inhibitory functioning. We instead found evidence that error-related contrasts provide clinically relevant information about neural systems involved in monitoring and optimizing the efficiency of cognitive performance.

A diffusion model analysis of sustained attention in children with attention deficit hyperactivity disorder

OBJECTIVE

Whether children with attention deficit hyperactivity disorder (ADHD) have deficits in sustained attention remains unresolved due to the ongoing use of cognitive paradigms that are not optimized for studying vigilance and the fact that relatively few studies report performance over time.

METHOD

In three independent samples of school-age children with (total N = 128) and without ADHD (total N = 59), we manipulated event rate, difficulty of discrimination, and use signal detection (SDT) and diffusion models (DM) to evaluate the cause of the vigilance decrement during a continuous performance task.

RESULTS

For both groups of children, a bias toward "no-go" over time (as indexed by the SDT parameter B″ and the DM parameter z/a) was responsible for generating the vigilance decrement. However, among children with ADHD, the rate at which information accumulated to make a no-go decision (vNoGo) also increased with time on task, representing a possible secondary mechanism that biases children against engagement. At all time points, children with ADHD demonstrated reduced sensitivity to discriminate targets from nontargets.

CONCLUSION

Children with ADHD are particularly sensitive to the cost of task engagement, but nonspecific slower drift rate may ultimately provide a better conceptualization of the cognitive atypicalities commonly observed in that group. Results are interpreted in the context of updated conceptualizations of sustained attention and vigilance. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

What cognitive processes are "sluggish" in sluggish cognitive tempo?

OBJECTIVE

Sluggish cognitive tempo refers to a constellation of symptoms that include slowed behavior/thinking, reduced alertness, and getting lost in one's thoughts. Despite the moniker "sluggish cognitive tempo," the evidence is mixed regarding the extent to which it is associated globally with slowed (sluggish) mental (cognitive) information processing speed (tempo).

METHOD

A well-characterized clinical sample of 132 children ages 8-13 years (M = 10.34, SD = 1.51; 47 girls; 67% White/non-Hispanic) were administered multiple, counterbalanced neurocognitive tests and assessed for sluggish cognitive tempo symptoms via multiple-informant reports.

RESULTS

Bayesian linear regressions revealed significant evidence against associations between sluggish cognitive tempo and computationally modeled processing speed (BF01 > 3.70), and significant evidence for associations with slower working memory manipulation speed. These findings were consistent across parent and teacher models, with and without control for attention-deficit/hyperactivity disorder inattentive symptoms and IQ. There was also significant evidence linking faster inhibition speed with higher parent-reported sluggish cognitive tempo symptoms.

CONCLUSIONS

These findings provide strong evidence against characterizing children with sluggish cognitive tempo symptoms as possessing a globally sluggish cognitive tempo. Instead, these symptoms appear to be related, to a significant extent, to executive dysfunction characterized by working memory systems that are too slow and inhibition systems that are too fast. Behaviorally, these findings suggest that requiring extra time to rearrange the active contents of working memory delays responding, whereas an overactive inhibition system likely terminates thoughts too quickly and therefore prevents intended behaviors from starting or completing, thereby giving the appearance that children are absent-minded or failing to act when expected. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Inhibitory Control and Information Processing in ADHD: Comparing the Dual Task and Performance Adjustment Hypotheses

Inhibition is a key neurocognitive domain in ADHD that is commonly assessed with the stop-signal task. The stop-signal involves both "go" and "stop" trials; previous research indicates that response times are reliably slower to "go" trials during tasks with vs. without intermittent "stop" trials. However, it is unclear whether this pattern reflects deliberate slowing to maximize inhibitory success (performance adjustment hypothesis) and/or disrupted bottom-up information processing due to increased cognitive demands (dual-task hypothesis). Given the centrality of "go" responding for estimating children's inhibitory speed, finding that children with ADHD slow differently -or for different reasons- has the potential to inform cognitive and self-regulatory theories of ADHD. The current study used a carefully-controlled experimental design to assess the mechanisms underlying stop signal-related slowing in ADHD. Children ages 8-13 with (n = 81) and without ADHD (n = 63) completed the stop-signal task and a control task that differed only in the presence/absence of "stop" trials. Using drift-diffusion modeling, Bayesian repeated-measures ANOVAs revealed a pattern consistent with the performance adjustment hypothesis, such that children adopted more cautious response strategies (BF10 = 6221.78; d = 0.38) but did not show changes in processing speed (BF01 = 3.08; d = 0.12) or encoding/motor speed (BF01 = 5.73; d = 0.07) when inhibition demands were introduced. Importantly, the ADHD/Non-ADHD groups showed equivalent effects of intermittent "stop" trials (BF01 = 4.30-5.56). These findings suggest intact self-regulation/performance monitoring in the context of adapting to increased inhibitory demands in ADHD, which has important implications for the continued isolation of potential mechanisms associated with ADHD symptoms and impairment.

A Low-Level Perceptual Correlate of Behavioral and Clinical Deficits in ADHD

In many studies of attention-deficit hyperactivity disorder (ADHD), stimulus encoding and processing (perceptual function) and response selection (executive function) have been intertwined. To dissociate deficits in these functions, we introduced a task that parametrically varied low-level stimulus features (orientation and color) for fine-grained analysis of perceptual function. It also required participants to switch their attention between feature dimensions on a trial-by-trial basis, thus taxing executive processes. Furthermore, we used a response paradigm that captured task-irrelevant motor output (TIMO), reflecting failures to use the correct stimulus-response rule. ADHD participants had substantially higher perceptual variability than controls, especially for orientation, as well as higher TIMO. In both ADHD and controls, TIMO was strongly affected by the switch manipulation. Across participants, the perceptual variability parameter was correlated with TIMO, suggesting that perceptual deficits are associated with executive function deficits. Based on perceptual variability alone, we were able to classify participants into ADHD and controls with a mean accuracy of about 77%. Participants' self-reported General Executive Composite score correlated not only with TIMO but also with the perceptual variability parameter. Our results highlight the role of perceptual deficits in ADHD and the usefulness of computational modeling of behavior in dissociating perceptual from executive processes.

Testing formal predictions of neuroscientific theories of ADHD with a cognitive model-based approach

Neuroscientific theories of attention-deficit/hyperactivity disorder (ADHD) alternately posit that cognitive aberrations in the disorder are due to acute attentional lapses, slowed neural processing, or reduced signal-to-noise ratios. However, they make similar predictions about behavioral summary statistics (response times [RTs] and accuracy), hindering the field's ability to produce strong and specific tests of these theories. The current study uses the linear ballistic accumulator (LBA; Brown & Heathcote, 2008), a mathematical model of choice RT tasks, to distinguish between competing theory predictions. Children with ADHD (n = 80) and age-matched controls (n = 32) completed a numerosity discrimination paradigm at 2 levels of difficulty, and RT data were fit to the LBA model to test theoretical predictions. Individuals with ADHD displayed slowed processing of evidence for correct responses (signal) relative to their peers but comparable processing of evidence for error responses (noise) and between-trial variability in processing (performance lapses). The findings are inconsistent with accounts that posit an increased incidence of attentional lapses in the disorder and provide partial support for those that posit slowed neural processing and lower signal-to-noise ratios. Results also highlight the utility of well-developed cognitive models for distinguishing between the predictions of etiological theories of psychopathology. (PsycINFO Database Record

Is Poor Working Memory a Transdiagnostic Risk Factor for Psychopathology?

In contrast to historical conceptualizations that framed psychological disorders as distinct, categorical conditions, it is now widely understood that co- and multi-morbidities between disorders are extensive. As a result, there has been a call to better understand the dimensional liabilities that are common to and influence the development of multiple psychopathologies, as supported and exemplified by the National Institutes of Mental Health (NIMH) Research Domain Criteria (RDoC) framework. We use a latent variable SEM approach to examine the degree to which working memory deficits represent a cognitive liability associated with the development of common and discrete dimensions of psychopathology. In a sample of 415 community recruited children aged 8-12 (n = 170 girls), we fit a bi-factor model to parent reports of behavior from the DISC-4 and BASC-2, and included a latent working memory factor as a predictor of the internalizing, externalizing, and general "p-factor." We found that both the general "p-factor" and externalizing (but not internalizing) latent factor were significantly associated with working memory. When a bi-factor model of externalizing symptomology was fit to further explore this relationship, working memory was only correlated with the general externalizing dimension; correlation with specific inattention, hyperactive/impulsive, and oppositional factors did not survive once the general externalizing dimension was taken into consideration. These findings held regardless of the sex of the child. Our results suggest that working memory deficits represent both a common cognitive liability for mental health disorders, and a specific liability for externalizing disorders.

The role of speed in ADHD-related working memory deficits: A time-based resource-sharing and diffusion model account

Several recent commentaries suggest that, for psychological science to move beyond "homuncular" explanations for cognitive control, it is critically important to examine the role of basic and computationally well-defined processes (e.g. cognitive processing speed). Correlational evidence has previously linked slow speed to working memory (WM) deficits in ADHD, but the directionality of this relationship has not been investigated experimentally and the mechanisms through which speed may influence WM are unclear. Herein, we demonstrate in school-aged children with and without ADHD, that manipulating speed (indexed with the diffusion model) within a WM paradigm reduces WM capacity due to an increase in cognitive load, in a manner that is consistent with predictions of the time-based resource-sharing model of WM. Results suggest slow speed is a plausible cause of WM deficits in ADHD, provide a mechanistic account of this relationship, and urge the exploration of non-executive neurocognitive processes in clinical research on etiology.

Modeling Individual Differences in the Go/No-go Task with a Diffusion Model

The go/no-go task is one in which there are two choices, but the subject responds only to one of them, waiting out a time-out for the other choice. The task has a long history in psychology and modern applications in the clinical/neuropsychological domain. In this article we fit a diffusion model to both experimental and simulated data. The model is the same as the two-choice model and assumes that there are two decision boundaries and termination at one of them produces a response and at the other, the subject waits out the trial. In prior modeling, both two-choice and go/no-go data were fit simultaneously and only group data were fit. Here the model is fit to just go/no-go data for individual subjects. This allows analyses of individual differences which is important for clinical applications. First, we fit the standard two-choice model to two-choice data and fit the go/no-go model to RTs from one of the choices and accuracy from the two-choice data. Parameter values were similar between the models and had high correlations. The go/no-go model was also fit to data from a go/no-go version of the task with the same subjects as the two-choice task. A simulation study with ranges of parameter values that are obtained in practice showed similar parameter recovery between the two-choice and go/no-go models. Results show that a diffusion model with an implicit (no response) boundary can be fit to data with almost the same accuracy as fitting the two-choice model to two-choice data.

Evaluating the consequences of impaired monitoring of learned behavior in attention-deficit/hyperactivity disorder using a Bayesian hierarchical model of choice response time

OBJECTIVE

Performance monitoring deficits have been proposed as a cognitive marker involved in the development of attention-deficit/hyperactivity disorder (ADHD), but it is unclear whether these deficits cause impairment when established action sequences conflict with environmental demands. The current study applies a novel data-analytic technique to a well-established sequence learning paradigm to investigate reactions to disruption of learned behavior in ADHD.

METHOD

Children (ages 8-12) with and without ADHD completed a serial reaction time task in which they implicitly learned an 8-item sequence of keypresses over 5 training blocks. The training sequence was replaced with a novel sequence in a transfer block, and returned in 2 subsequent recovery blocks. Response time (RT) data were fit by a Bayesian hierarchical version of the linear ballistic accumulator model, which permitted the dissociation of learning processes from performance monitoring effects on RT.

RESULTS

Sequence-specific learning on the task was reflected in the systematic reduction of the amount of evidence required to initiate a response, and was unimpaired in ADHD. When the novel sequence onset, typically developing children displayed a shift in their attentional state while children with ADHD did not, leading to worse subsequent performance compared to controls.

CONCLUSIONS

Children with ADHD are not impaired in learning novel action sequences, but display difficulty monitoring their implementation and engaging top-down control when they become inadequate. These results support theories of ADHD that highlight the interactions between monitoring processes and changing cognitive demands as the cause of self-regulation and information-processing problems in the disorder. (PsycINFO Database Record