Modelling ADHD: A review of ADHD theories through their predictions for computational models of decision-making and reinforcement learning

Cognitive reserve involves decision making and is associated with left parietal and hippocampal hypertrophy in neurodegeneration

Cognitive reserve is the ability to actively cope with brain deterioration and delay cognitive decline in neurodegenerative diseases. It operates by optimizing performance through differential recruitment of brain networks or alternative cognitive strategies. We investigated cognitive reserve using Huntington's disease (HD) as a genetic model of neurodegeneration to compare premanifest HD, manifest HD, and controls. Contrary to manifest HD, premanifest HD behave as controls despite neurodegeneration. By decomposing the cognitive processes underlying decision making, drift diffusion models revealed a response profile that differs progressively from controls to premanifest and manifest HD. Here, we show that cognitive reserve in premanifest HD is supported by an increased rate of evidence accumulation compensating for the abnormal increase in the amount of evidence needed to make a decision. This higher rate is associated with left superior parietal and hippocampal hypertrophy, and exhibits a bell shape over the course of disease progression, characteristic of compensation.

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.

Stimulus valence moderates self-learning

Self-relevance has been demonstrated to impair instrumental learning. Compared to unfamiliar symbols associated with a friend, analogous stimuli linked with the self are learned more slowly. What is not yet understood, however, is whether this effect extends beyond arbitrary stimuli to material with intrinsically meaningful properties. Take, for example, stimulus valence an established moderator of self-bias. Does the desirability of to-be-learned material influence self-learning? Here, in conjunction with computational modelling (i.e. Reinforcement Learning Drift Diffusion Model analysis), a probabilistic selection task was used to establish if and how stimulus valence (i.e. desirable/undesirable posters) impacts the acquisition of knowledge relating to object-ownership (i.e. owned-by-self vs. owned-by-friend). Several interesting results were observed. First, undesirable posters were learned more rapidly for self compared to friend, an effect that was reversed for desirable posters. Second, learning rates were accompanied by associated differences in reward sensitivity toward desirable and undesirable choice selections as a function of ownership. Third, decisional caution was greater for self-relevant (vs. friend relevant) responses. Collectively, these findings inform understanding of self-function and how valence and stimulus relevance mutually influence probabilistic learning.

Optical coherence tomography as a potential surrogate marker of dopaminergic modulation across the life span

The retina has been considered a "window to the brain" and shares similar innervation by the dopaminergic system with the cortex in terms of an unequal distribution of D1 and D2 receptors. Here, we provide a comprehensive overview that Optical Coherence Tomography (OCT), a non-invasive imaging technique, which provides an "in vivo" representation of the retina, shows promise to be used as a surrogate marker of dopaminergic neuromodulation in cognition. Overall, most evidence supports reduced retinal thickness in individuals with dopaminergic dysregulation (e.g., patients with Parkinson's Disease, non-demented older adults) and with poor cognitive functioning. By using the theoretical framework of metacontrol, we derive hypotheses that retinal thinning associated to decreased dopamine (DA) levels affecting D1 families, might lead to a decrease in the signal-to-noise ratio (SNR) affecting cognitive persistence (depending on D1-modulated DA activity) but not cognitive flexibility (depending on D2-modulated DA activity). We argue that the use of OCT parameters might not only be an insightful for cognitive neuroscience research, but also a potentially effective tool for individualized medicine with a focus on cognition. As our society progressively ages in the forthcoming years and decades, the preservation of cognitive abilities and promoting healthy aging will hold of crucial significance. OCT has the potential to function as a swift, non-invasive, and economical method for promptly recognizing individuals with a heightened vulnerability to cognitive deterioration throughout all stages of life.

Impaired flexible reward learning in ADHD patients is associated with blunted reinforcement sensitivity and neural signals in ventral striatum and parietal cortex

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This concerns flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex. Here, we investigated young adults with ADHD (n = 17) as compared to age- and sex-matched controls (n = 17) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used reinforcement learning (RL) models, which informed the analysis of fMRI data. ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from 'noisy' choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in a diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by a marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum. Taken together, we show that impaired flexible behavior in ADHD is due to excessive choice switching ('hyper-flexibility'), which can be detrimental or beneficial depending on the learning environment. Computationally, this resulted from blunted sensitivity to reinforcement of which we detected neural correlates in the attention-control network, specifically in the parietal cortex. These neurocomputational findings remain preliminary due to the relatively small sample size.

Exploration versus exploitation decisions in the human brain: A systematic review of functional neuroimaging and neuropsychological studies

Thoughts and actions are often driven by a decision to either explore new avenues with unknown outcomes, or to exploit known options with predictable outcomes. Yet, the neural mechanisms underlying this exploration-exploitation trade-off in humans remain poorly understood. This is attributable to variability in the operationalization of exploration and exploitation as psychological constructs, as well as the heterogeneity of experimental protocols and paradigms used to study these choice behaviours. To address this gap, here we present a comprehensive review of the literature to investigate the neural basis of explore-exploit decision-making in humans. We first conducted a systematic review of functional magnetic resonance imaging (fMRI) studies of exploration-versus exploitation-based decision-making in healthy adult humans during foraging, reinforcement learning, and information search. Eleven fMRI studies met inclusion criterion for this review. Adopting a network neuroscience framework, synthesis of the findings across these studies revealed that exploration-based choice was associated with the engagement of attentional, control, and salience networks. In contrast, exploitation-based choice was associated with engagement of default network brain regions. We interpret these results in the context of a network architecture that supports the flexible switching between externally and internally directed cognitive processes, necessary for adaptive, goal-directed behaviour. To further investigate potential neural mechanisms underlying the exploration-exploitation trade-off we next surveyed studies involving neurodevelopmental, neuropsychological, and neuropsychiatric disorders, as well as lifespan development, and neurodegenerative diseases. We observed striking differences in patterns of explore-exploit decision-making across these populations, again suggesting that these two decision-making modes are supported by independent neural circuits. Taken together, our review highlights the need for precision-mapping of the neural circuitry and behavioural correlates associated with exploration and exploitation in humans. Characterizing exploration versus exploitation decision-making biases may offer a novel, trans-diagnostic approach to assessment, surveillance, and intervention for cognitive decline and dysfunction in normal development and clinical populations.

Effects of auditory white noise stimulation on sustained attention and response time variability

Introduction

"The moderate brain arousal model" claims that white noise improves attention by optimizing brain arousal. We analyze Conners' Continuous Performance Test-3 (CCPT-3) performance, expecting to find reduced reaction time variability with noise mediated by decrease under long event-rates and in later parts of the test, indicating that noise reverse fall in phasic and tonic arousal.

Methods

Sixty-five children with high or lower ADHD-symptoms from a child psychiatric unit, succeeded to complete the CCPT-3 with and without white noise.

Results

Noise reduced overall variability, improved performance in later parts of the test, and reduced response variability under the longest event rate particularly in the high symptoms group. No overall change in omissions and commissions, but the high symptoms group made fewer omissions during noise compared the low symptom group.

Discussion

The study indicates an arousal effect of noise but should be replicated with other noise variants and amplitudes to improve effect and compliance.

Cognitive-attentional mechanisms of cooperation-with implications for attention-deficit hyperactivity disorder and cognitive neuroscience

People's cooperativeness depends on many factors, such as their motives, cognition, experiences, and the situation they are in. To date, it is unclear how these factors interact and shape the decision to cooperate. We present a computational account of cooperation that not only provides insights for the design of effective incentive structures but also redefines neglected social-cognitive characteristics associated with attention-deficit hyperactivity disorder (ADHD). Leveraging game theory, we demonstrate that the source and magnitude of conflict between different motives affected the speed and frequency of cooperation. Integrating eye-tracking to measure motivation-based information processing during decision-making shows that participants' visual fixations on the gains of cooperation rather than its costs and risks predicted their cooperativeness on a trial-by-trial basis. Using Bayesian hierarchical modeling, we find that a situation's prosociality and participants' past experience each bias the decision-making process distinctively. ADHD characteristics explain individual differences in responsiveness across contexts, highlighting the clinical importance of experimentally studying reactivity in social interactions. We demonstrate how the use of eye-tracking and computational modeling can be used to experimentally investigate social-cognitive characteristics in clinical populations. We also discuss possible underlying neural mechanisms to be investigated in future studies.

Poor learning or hyper-exploration?: A commentary on Hulsbosch et al. (2023)

In an outstanding paper, Hulsbosch et al. (Journal of Child Psychology and Psychiatry, 2023) tested major reinforcement learning theories of attention-deficit/hyperactivity disorder (ADHD). On a reinforcement learning task, children with ADHD needed more trials to reach the criterion in the learning phase and chose the target less often in the extinction phase. These results only partially support either of the theories and may be interpreted as reflecting a general deficit in learning. Still, distinguishing between learning and decision-making stages suggests that poor performance on reinforcement learning tasks by children with ADHD is accounted for by increased exploration or decreased choice consistency rather than deficient learning.

Distinct neural activations correlate with maximization of reward magnitude versus frequency

Choice selection strategies and decision-making are typically investigated using multiple-choice gambling paradigms that require participants to maximize expected value of rewards. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains such that users often choose smaller frequent gains over larger rarely occurring gains, also referred to as melioration. To understand the basis of this subjective tradeoff, we used a simple 2-choice reward task paradigm in 186 healthy human adult subjects sampled across the adult lifespan. Cortical source reconstruction of simultaneously recorded electroencephalography suggested distinct neural correlates for maximizing reward magnitude versus frequency. We found that activations in the parahippocampal and entorhinal areas, which are typically linked to memory function, specifically correlated with maximization of reward magnitude. In contrast, maximization of reward frequency was correlated with activations in the lateral orbitofrontal cortices and operculum, typical areas involved in reward processing. These findings reveal distinct neural processes serving reward frequency versus magnitude maximization that can have clinical translational utility to optimize decision-making.

The computational psychiatry of antisocial behaviour and psychopathy

Antisocial behaviours such as disobedience, lying, stealing, destruction of property, and aggression towards others are common to multiple disorders of childhood and adulthood, including conduct disorder, oppositional defiant disorder, psychopathy, and antisocial personality disorder. These disorders have a significant negative impact for individuals and for society, but whether they represent clinically different phenomena, or simply different approaches to diagnosing the same underlying psychopathology is highly debated. Computational psychiatry, with its dual focus on identifying different classes of disorder and health (data-driven) and latent cognitive and neurobiological mechanisms (theory-driven), is well placed to address these questions. The elucidation of mechanisms that might characterise latent processes across different disorders of antisocial behaviour can also provide important advances. In this review, we critically discuss the contribution of computational research to our understanding of various antisocial behaviour disorders, and highlight suggestions for how computational psychiatry can address important clinical and scientific questions about these disorders in the future.

Altered interaction of physiological activity and behavior affects risky decision-making in ADHD

Background

Adult attention-deficit/hyperactivity disorder (ADHD) is often associated with risky decision-making behavior. However, current research studies are often limited by the ability to adequately reflect daily behavior in a laboratory setting. Over the lifespan impairments in cognitive functions appear to improve, whereas affective functions become more severe. We assume that risk behavior in ADHD arises predominantly from deficits in affective processes. This study will therefore aim to investigate whether a dysfunction in affective pathways causes an abnormal risky decision-making (DM) behavior in adult ADHD.

Methods

Twenty-eight participants with ADHD and twenty-eight healthy controls completed a battery of questionnaires regarding clinical symptoms, self-assessment of behavior and emotional competence. Furthermore, skin conductance responses were measured during the performance in a modified version of the Balloon Analogue Risk Task. A linear mixed-effects model analysis was used to analyze emotional arousal prior to a decision and after feedback display.

Results

Results showed higher emotional arousal in ADHD participants before decision-making (β = -0.12, SE = 0.05, t = -2.63, p < 0.001) and after feedback display (β = -0.14, SE = 0.05, t = -2.66, p = 0.008). Although risky behavior was greater in HC than in ADHD, we found a significant interaction effect of group and anticipatory skin conductance responses regarding the response behavior (β = 107.17, SE = 41.91, t = 2.56, p = 0.011). Post hoc analyses revealed a positive correlation between anticipatory skin conductance responses and reaction time in HC, whereas this correlation was negative in ADHD. Self-assessment results were in line with the objective measurements.

Conclusion

We found altered changes in physiological activity during a risky decision-making task. The results confirm the assumption of an aberrant relationship between bodily response and risky behavior in adult ADHD. However, further research is needed with respect to age and gender when considering physiological activities.

Mechanism-based groups of children with ADHD are associated with distinct domains of impairment

Person-oriented analyses are commonly used to identify subgroups of children with mental health conditions in the hopes that they will meaningfully inform the taxonomy, assessment, and treatment of psychological disorder. However, whether these data-driven groups are demonstrably better at predicting important aspects of adaptive functioning than standard DSM taxonomy has not been established. Using Attention-Deficit-Hyperactivity-Disorder (ADHD) as a model condition, we utilized dimensions of personality and cognitive ability to identify person-centered profiles of school-aged children (N=246) and evaluated the association of these profiles with critical areas of adaptive functioning. A single profile ("Conscientious") represented non-ADHD controls and was characterized by faster drift rate and higher executive functioning scores. Three profiles ("Disagreeable," "Negative Emotionality," and "Extraverted") were identified for children with ADHD. Drift rate, but not executive functioning, distinguished among ADHD profiles, which were also distinctly associated with comorbid externalizing and internalizing psychopathology, social skills, and academic achievement. In contrast, the Diagnostic and Statistical Manual (DSM) presentations were not informative and showed similar patterns of impairment across domains. Person-centered profiles of children with ADHD are associated with distinct adaptive functioning deficits and may be useful in informing clinical practice.

Eye movement behavior in a real-world virtual reality task reveals ADHD in children

Eye movements and other rich data obtained in virtual reality (VR) environments resembling situations where symptoms are manifested could help in the objective detection of various symptoms in clinical conditions. In the present study, 37 children with attention deficit hyperactivity disorder and 36 typically developing controls (9-13 y.o) played a lifelike prospective memory game using head-mounted display with inbuilt 90 Hz eye tracker. Eye movement patterns had prominent group differences, but they were dispersed across the full performance time rather than associated with specific events or stimulus features. A support vector machine classifier trained on eye movement data showed excellent discrimination ability with 0.92 area under curve, which was significantly higher than for task performance measures or for eye movements obtained in a visual search task. We demonstrated that a naturalistic VR task combined with eye tracking allows accurate prediction of attention deficits, paving the way for precision diagnostics.

Effect of stimulant medication on loss of control eating in youth with attention deficit/hyperactivity disorder: a prospective, observational case series study protocol

BACKGROUND

Loss of control eating (LOC-E) in youth predicts the later development of full-syndrome binge-eating disorder (BED), and therefore, could be a relevant target for prevention treatments. To develop these treatments, it is important to understand the underlying disease processes and mechanisms. Based on the putative role of neurocognitive impairments in the pathogenesis of LOC-E, treatments that modulate these neurocognitive factors warrant further exploration. For instance, stimulants are an effective treatment for impulsivity in youth with attention deficit/hyperactivity disorder (ADHD) and have been shown to improve symptoms of BED in adults. Notably, stimulants have not been examined as a treatment for LOC-E in youth. To explore this gap, we aim to measure change in LOC-E episodes and secondary outcomes in youth with comorbid ADHD and LOC-E who are being started on stimulants.

METHODS

We will collect prospective observational data on forty 8-to-13-year-old youth diagnosed with comorbid ADHD and LOC-E who are initiating a stimulant for ADHD. Prior to stimulant initiation, participants will complete baseline measures including LOC-E episode frequency in the last 3 months (primary outcome), and secondary outcomes including disordered eating cognitions, emotions and behaviors, ADHD symptom severity, parental LOC-E, impulsivity and reward sensitivity, and anxiety/mood severity. Outcome measurements will be gathered again at 3-months after initiating the stimulant. Within-patient standardized effect sizes with 95% confidence intervals will be calculated from baseline to 3-month follow-up for all outcomes.

DISCUSSION

Many individuals with LOC-E or binge eating do not fully remit over the course of psychotherapy. Whereas psychotherapy may address psychological and sociocultural domains associated with LOC-E, some individuals with neurocognitive impairments (e.g., ADHD) and neurobiological deficits (e.g., low intrasynaptic dopamine or norepinephrine) may benefit from adjunctive treatment that targets those factors. This will be the first study to provide pilot data for future studies that could examine both the effect of stimulants on LOC-E in youth and underlying mechanisms.

TRIAL REGISTRATION

Trial registration number: NCT05592119.

Prevalence and correlates of hoarding behavior and hoarding disorder in children and adolescents

Although hoarding symptoms are reported to begin in childhood and adolescence, the true prevalence of the disorder in this age group is unknown. This study aims to estimate the prevalence of hoarding disorder (HD) in children and adolescents. The present study was planned as a two-stage epidemiological research. In the first stage, the Children's Saving Inventory (CSI) and informed consent forms were delivered to a group of students' parents. In the second stage, one-on-one psychiatric interviews with a physician were planned with the families and children who had hoarding behavior (HB), as described by their parents. The DSM-5-based HD interview and the Development and Well-Being Assessment (DAWBA) diagnostic tool were used to detect prevalence of HD and comorbid psychiatric disorders. A total of 3249 children were included in the study, and 318 children and their parents were evaluated in the second stage. As a result of the second assessment, 32 out of 318 children met the HD diagnostic criteria. The estimated prevalence of HD was 0.98% (95% CI 0.7-1.4). Hoarding disorder was found more frequently in females (F/M = 3/1). After a logistic regression analysis, variables such as female sex and the presence of any psychopathology were identified as independent correlates of HD. More than half (56.2%) of the children diagnosed as having HD also had a comorbid psychiatric disorder. In the present study, the two-stage evaluation method was used in a large pediatric sample to determine the estimated prevalence of HD, as well as the factors associated with the disorder and comorbid psychiatric disorders.

Neuroprotection in late life attention-deficit/hyperactivity disorder: A review of pharmacotherapy and phenotype across the lifespan

For decades, psychostimulants have been the gold standard pharmaceutical treatment for attention-deficit/hyperactivity disorder (ADHD). In the United States, an astounding 9% of all boys and 4% of girls will be prescribed stimulant drugs at some point during their childhood. Recent meta-analyses have revealed that individuals with ADHD have reduced brain volume loss later in life (>60 y.o.) compared to the normal aging brain, which suggests that either ADHD or its treatment may be neuroprotective. Crucially, these neuroprotective effects were significant in brain regions (e.g., hippocampus, amygdala) where severe volume loss is linked to cognitive impairment and Alzheimer's disease. Historically, the ADHD diagnosis and its pharmacotherapy came about nearly simultaneously, making it difficult to evaluate their effects in isolation. Certain evidence suggests that psychostimulants may normalize structural brain changes typically observed in the ADHD brain. If ADHD itself is neuroprotective, perhaps exercising the brain, then psychostimulants may not be recommended across the lifespan. Alternatively, if stimulant drugs are neuroprotective, then this class of medications may warrant further investigation for their therapeutic effects. Here, we take a bottom-up holistic approach to review the psychopharmacology of ADHD in the context of recent models of attention. We suggest that future studies are greatly needed to better appreciate the interactions amongst an ADHD diagnosis, stimulant treatment across the lifespan, and structure-function alterations in the aging brain.

Front and center: Maturational dysregulation of frontal lobe functional neuroanatomic connections in attention deficit hyperactivity disorder

Frontal lobe function may not universally explain all forms of attention deficit hyperactivity disorder (ADHD) but the frontal lobe hypothesis described supports an internally consistent model for integrating the numerous behaviors associated with ADHD. The paper examines the developmental trajectories of frontal and prefrontal lobe development, framing ADHD as maturational dysregulation concluding that the cognitive, motor, and behavioral abilities of the presumptive majority of ADHD children may not primarily be disordered or dysfunctional but reflect maturational dysregulation that is inconsistent with the psychomotor and cognitive expectations for the child’s chronological and mental age. ADHD children demonstrate decreased activation of the right and middle prefrontal cortex. Prefrontal and frontal lobe regions have an exuberant network of shared pathways with the diencephalic region, also having a regulatory function in arousal as well as with the ascending reticular formation which has a capacity for response suppression to task-irrelevant stimuli. Prefrontal lesions oftentimes are associated with the regulatory breakdown of goal-directed activity and impulsivity. In conclusion, a presumptive majority of childhood ADHD may result from maturational dysregulation of the frontal lobes with effects on the direct, indirect and/or, hyperdirect pathways.

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.

The metacontrol hypothesis as diagnostic framework of OCD and ADHD: A dimensional approach based on shared neurobiological vulnerability

Obsessive-compulsive disorder (OCD) and attention-deficit hyperactivity disorder (ADHD) are multi-faceted neuropsychiatric conditions that in many aspects appear to be each other's antipodes. We suggest a dimensional approach, according to which these partially opposing disorders fall onto a continuum that reflects variability regarding alterations of cortico-striato-thalamo-cortical (CSTC) circuits and of the processing of neural noise during cognition. By using theoretical accounts of human cognitive metacontrol, we develop a framework according to which OCD can be characterized by a chronic bias towards exaggerated cognitive persistence, equivalent to a high signal-to-noise ratio (SNR)-which facilitates perseverative behaviour but impairs mental flexibility. In contrast, ADHD is characterized by a chronic bias towards inflated cognitive flexibility, equivalent to a low SNR-which increases behavioural variability but impairs the focusing on one goal and on relevant information. We argue that, when pharmacology is not feasible, novel treatments of these disorders may involve methods to manipulate the signal-to-noise ratio via non-invasive brain stimulation techniques, in order to normalize the situational imbalance between cognitive persistence and cognitive flexibility.

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.

The potential role of stimulants in treating eating disorders

BACKGROUND

Many individuals with eating disorders remain symptomatic after a course of psychotherapy and pharmacotherapy; therefore, the development of innovative treatments is essential.

METHOD

To learn more about the current evidence for treating eating disorders with stimulants, we searched for original articles and reviews published up to April 29, 2021 in PubMed and MEDLINE using the following search terms: eating disorders, anorexia, bulimia, binge eating, stimulants, amphetamine, lisdexamfetamine, methylphenidate, and phentermine.

RESULTS

We propose that stimulant medications represent a novel avenue for future research based on the following: (a) the relationship between eating disorders and attention deficit/hyperactivity disorder (ADHD); (b) a neurobiological rationale; and (c) the current (but limited) evidence for stimulants as treatments for some eating disorders. Despite the possible benefits of such medications, there are also risks to consider such as medication misuse, adverse cardiovascular events, and reduction of appetite and pathological weight loss. With those risks in mind, we propose several directions for future research including: (a) randomized controlled trials to study stimulant treatment in those with bulimia nervosa (with guidance on strategies to mitigate risk); (b) examining stimulant treatment in conjunction with psychotherapy; (c) investigating the impact of stimulants on "loss of control" eating in youth with ADHD; and (d) exploring relevant neurobiological mechanisms. We also propose specific directions for exploring mediators and moderators in future clinical trials.

DISCUSSION

Although this line of investigation may be viewed as controversial by some in the field, we believe that the topic warrants careful consideration for future research.

Cognitive, emotional, and social functioning of preschoolers with attention deficit hyperactivity problems

BACKGROUND

Attention Deficit Hyperactivity Disorder (ADHD) is associated with deficits in different functional domains. It remains unclear if deficits in different domains are equally strong in early childhood, and which deficits are specific to ADHD. Here, we describe functional domains in preschoolers and assess deficits in children with ADHD problems, by comparing them to preschoolers with other mental health problems or who develop typically.

METHODS

The ADHD Study assessed 1195 ca. 3.5 years old preschoolers through a semi-structured parent interview, parent questionnaires, and with neuropsychological tests. We determined functional domains by applying factor analytic methods to a broad set of questionnaire- and test-scales. Using resulting factor scores, we employed a Bayesian hierarchical regression to estimate functional deficits in children with ADHD.

RESULTS

We found that preschoolers' functioning could be described along the seven relatively independent dimensions activity level and regulation, executive function, cognition, language, emotion regulation, introversion, and sociability. Compared to typically developing preschoolers, those with ADHD had deficits in all domains except introversion and sociability. Only deficits in activity level regulation and executive functions were larger than 0.5 standardised mean deviations and larger than deficits of children with other mental health problems.

CONCLUSIONS

Preschoolers with ADHD have deficits in multiple functional domains, but only impairments in activity level and regulation and executive functions are specific for ADHD and large enough to be clinically significant. Research on functioning in these domains will be important for understanding the development of ADHD, and for improving treatment and prevention approaches.

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different DDM parameters on several brain areas, including the cortex and basal ganglia. Furthermore, we discuss the changes in DDM parameters due to structural and functional impairments in several clinical disorders, including Parkinson's disease, Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive-Compulsive Disorder (OCD), and schizophrenia. This review thus uses DDM to provide a theoretical understanding of different brain disorders.

Cognitive efficiency beats top-down control as a reliable individual difference dimension relevant to self-control

Top-down control of responses is a key construct in cognitive science that is thought to be critical for self-control. It is typically measured by subtracting performance in experimental conditions in which top-down control is theoretically present against performance in matched conditions in which it is assumed to be absent. Recently, however, subtraction-based metrics of top-down control have been criticized for having low test-retest reliability, weak intercorrelations, and little relation to self-report measures of self-control. Concurrently, there is growing evidence that task-general cognitive efficiency, indexed by the drift rate parameter of the diffusion model (Ratcliff, 1978), constitutes a cohesive, reliable individual difference dimension relevant to self-control. However, no previous studies have directly compared latent factors for top-down control (derived from subtraction metrics) with factors for task-general efficiency "head-to-head" in the same sample in terms of their cohesiveness, temporal stability, and relation to self-control. In this re-analysis of a large open data set (Eisenberg et al., 2019; N = 522), we find that top-down control metrics fail to form cohesive latent factors, that the resulting factors have poor temporal stability, and that they exhibit tenuous connections to questionnaire measures of self-control. In contrast, cognitive efficiency measures-drawn from conditions of the same tasks that both are, and are not, assumed to demand top-down control-form a robust, temporally stable factor that correlates with questionnaire measures of self-control. These findings suggest that task-general efficiency is a central individual difference dimension relevant to self-control. Moreover, they go beyond recent measurement-based critiques of top-down control metrics, and instead suggest problems with key theoretical assumptions that have long guided this research paradigm.

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.

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.

ADHD symptoms map onto noise-driven structure-function decoupling between hub and peripheral brain regions

Adults with childhood-onset attention-deficit hyperactivity disorder (ADHD) show altered whole-brain connectivity. However, the relationship between structural and functional brain abnormalities, the implications for the development of life-long debilitating symptoms, and the underlying mechanisms remain uncharted. We recruited a unique sample of 80 medication-naive adults with a clinical diagnosis of childhood-onset ADHD without psychiatric comorbidities, and 123 age-, sex-, and intelligence-matched healthy controls. Structural and functional connectivity matrices were derived from diffusion spectrum imaging and multi-echo resting-state functional MRI data. Hub, feeder, and local connections were defined using diffusion data. Individual-level measures of structural connectivity and structure-function coupling were used to contrast groups and link behavior to brain abnormalities. Computational modeling was used to test possible neural mechanisms underpinning observed group differences in the structure-function coupling. Structural connectivity did not significantly differ between groups but, relative to controls, ADHD showed a reduction in structure-function coupling in feeder connections linking hubs with peripheral regions. This abnormality involved connections linking fronto-parietal control systems with sensory networks. Crucially, lower structure-function coupling was associated with higher ADHD symptoms. Results from our computational model further suggest that the observed structure-function decoupling in ADHD is driven by heterogeneity in neural noise variability across brain regions. By highlighting a neural cause of a clinically meaningful breakdown in the structure-function relationship, our work provides novel information on the nature of chronic ADHD. The current results encourage future work assessing the genetic and neurobiological underpinnings of neural noise in ADHD, particularly in brain regions encompassed by fronto-parietal systems.

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.

A New Spin on Spatial Cognition in ADHD: A Diffusion Model Decomposition of Mental Rotation

OBJECTIVES

Multiple studies have found evidence of task non-specific slow drift rate in ADHD, and slow drift rate has rapidly become one of the most visible cognitive hallmarks of the disorder. In this study, we use the diffusion model to determine whether atypicalities in visuospatial cognitive processing exist independently of slow drift rate.

METHODS

Eight- to twelve-year-old children with (n = 207) and without ADHD (n = 99) completed a 144-trial mental rotation task.

RESULTS

Performance of children with ADHD was less accurate and more variable than non-ADHD controls, but there were no group differences in mean response time. Drift rate was slower, but nondecision time was faster for children with ADHD. A Rotation × ADHD interaction for boundary separation was also found in which children with ADHD did not strategically adjust their response thresholds to the same degree as non-ADHD controls. However, the Rotation × ADHD interaction was not significant for nondecision time, which would have been the primary indicator of a specific deficit in mental rotation per se.

CONCLUSIONS

Poorer performance on the mental rotation task was due to slow rate of evidence accumulation, as well as relative inflexibility in adjusting boundary separation, but not to impaired visuospatial processing specifically. We discuss the implications of these findings for future cognitive research in ADHD.

Impaired Evidence Accumulation as a Transdiagnostic Vulnerability Factor in Psychopathology

There is substantial interest in identifying biobehavioral dimensions of individual variation that cut across heterogenous disorder categories, and computational models can play a major role in advancing this goal. In this report, we focused on efficiency of evidence accumulation (EEA), a computationally characterized variable derived from sequential sampling models of choice tasks. We created an EEA factor from three behavioral tasks in the UCLA Phenomics dataset (n = 272), which includes healthy participants (n = 130) as well-participants with schizophrenia (n = 50), bipolar disorder (n = 49), and attention-deficit/hyperactivity disorder (n = 43). We found that the EEA factor was significantly reduced in all three disorders, and that it correlated with an overall severity score for psychopathology as well as self-report measures of impulsivity. Although EEA was significantly correlated with general intelligence, it remained associated with psychopathology and symptom scales even after controlling for intelligence scores. Taken together, these findings suggest EEA is a promising computationally-characterized dimension of neurocognitive variation, with diminished EEA conferring transdiagnostic vulnerability to psychopathology.

Dissociating direct and indirect effects: a theoretical framework of how latent toxoplasmosis affects cognitive profile across the lifespan

About one-third of the world's population has latent toxoplasmosis, which is typically most prevalent in old age due to its lifelong persistence. Most infected people do not reveal clinically relevant symptoms, but T. gondii might trigger cognitive changes in otherwise asymptomatic individuals. As intact cognitive processes are essential for various achievements and successful aging, this review focuses on the cognitive profile associated with latent toxoplasmosis across the lifespan. It could be explained by a shift in balance between direct effects (increased dopamine synthesis) and indirect effects (neurodegeneration and chronic inflammation, which can decrease dopamine levels). Based thereon, we provide a possibly comprehensive framework of how T. gondii can differently affect cognitive performance across the lifespan (i.e., from increased catecholaminergic signaling in young age to decreased signaling in old age). We outline how future studies may inform our knowledge on the role of individual differences in response to T. gondii and how longitudinal studies can help trace the temporal dynamics in the shift of the balance between direct and indirect effects.

Sex-dependent alterations in behavior, drug responses and dopamine transporter expression in heterozygous DAT-Cre mice

Heterozygous mice that express Cre-recombinase under the dopamine transporter promoter (DAT-Cre knock in mice, or KI) are widely used for targeting midbrain dopamine neurons, under the assumption that their constitutive physiology is not affected. We report here that these mice display striking sex-dependent behavioral and molecular differences in relation to wildtypes (WT). Male and female KI mice were constitutively hyperactive, and male KI mice showed attenuated hyperlocomotor responses to amphetamine. In contrast, female KIs displayed a marked reduction in locomotion ("calming" effect) in response to the same dose of amphetamine. Furthermore, male and female DAT-Cre KI mice showed opposing differences in reinforcement learning, with females showing faster conditioning and males showing slower extinction. Other behavioral variables, including working memory and novelty preference, were not changed compared to WT. These effects were paralleled by differences in striatal DAT expression that disproportionately affected female KI mice. Our findings reveal clear limitations of the DAT-Cre line that must be considered when using this model.

Attention-deficit/hyperactivity disorder and the explore/exploit trade-off

The ability to maximize rewards and minimize the costs of obtaining them is vital to making advantageous explore/exploit decisions. Exploratory decisions are theorized to be greater among individuals with attention-deficit/hyperactivity disorder (ADHD), potentially due to deficient catecholamine transmission. Here, we examined the effects of ADHD status and methylphenidate, a common ADHD medication, on explore/exploit decisions using a 6-armed bandit task. We hypothesized that ADHD participants would make more exploratory decisions than controls, and that MPH would reduce group differences. On separate study days, adults with (n = 26) and without (n = 23) ADHD completed the bandit task at baseline, and after methylphenidate or placebo in counter-balanced order. Explore/exploit decisions were modeled using reinforcement learning algorithms. ADHD participants made more exploratory decisions (i.e., chose options without the highest expected reward value) and earned fewer points than controls in all three study days, and methylphenidate did not affect these outcomes. Baseline exploratory choices were positively associated with hyperactive ADHD symptoms across all participants. These results support several theoretical models of increased exploratory choices in ADHD and suggest the unexplained variance in ADHD decisions may be due to less value tracking. The inability to suppress actions with little to no reward value may be a key feature of hyperactive ADHD symptoms.

Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

Risk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift-diffusion model to extract parameters such as threshold ('a'-amount of evidence accumulated before making a decision), drift rate ('v'-information processing speed) and response bias ('z' apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.

A novel approach to intra-individual performance variability in ADHD

Patients with attention deficit/(hyperactivity) disorder (AD(H)D) show increased intra-individual variability (IIV) in behavioral performance. This likely reflects dopaminergic deficiencies. However, the precise performance profile across time and the pattern of fluctuations within it have not yet been considered, partly due to insufficient methods. Yet, such an analysis may yield important theory-based implications for clinical practice. Thus, in a case-control cross-sectional study, we introduce a new method to investigate performance fluctuations in patients with ADD (n = 76) and ADHD (n = 67) compared to healthy controls (n = 45) in a time estimation task. In addition, we also evaluate the effects of methylphenidate (MPH) treatment on this performance pattern in 29 patients with AD(H)D. Trial-by-trial differences in performance between healthy controls and patients with AD(H)D do not persist continuously over longer time periods. Periods during which no differences in performance between healthy controls and patients occur alternate with periods in which such differences are present. AD(H)D subtype and surprisingly also medication status does not affect this pattern. The presented findings likely reflect (phasic) deficiencies of the dopaminergic system in patients with AD(H)D which are not sufficiently ameliorated by first-line pharmacological treatment. The presented findings carry important clinical and scientific implications.

Cognitive profile in Restless Legs Syndrome: A signal-to-noise ratio account

Restless legs syndrome (RLS) is a common neurological disorder characterized by a sensorimotor condition, where patients feel an uncontrollable urge to move the lower limbs in the evening and/or during the night. RLS does not only have a profound impact on quality of life due to the disturbed night-time sleep, but there is growing evidence that untreated or insufficiently managed RLS might also cause cognitive changes in patients affected by this syndrome. It has been proposed that RLS is caused by alterations in the signal-to-noise ratio (SNR) and in dopamine (DA) neurotransmission in the nervous system. Based on this evidence, we propose the “SNR-DA hypothesis” as an explanation of how RLS could affect cognitive performance. According to this hypothesis, variations/reductions in the SNR underlie RLS-associated cognitive deficits, which follow an inverted U-shaped function: In unmedicated patients, low dopamine levels worsen the SNR, which eventually impairs cognition. Pharmacological treatment enhances DA levels in medicated patients, which likely improves/normalizes the SNR in case of optimal doses, thus restoring cognition to a normal level. However, overmedication might push patients past the optimal point on the inverted U-shaped curve, where an exaggerated SNR potentially impairs cognitive performance relying on cortical noise such as cognitive flexibility. Based on these assumptions of SNR alterations, we propose to directly measure neural noise via “1/f noise” and related metrics to use transcranial random noise stimulation (tRNS), a noninvasive brain stimulation method which manipulates the SNR, as a research tool and potential treatment option for RLS.

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Restless legs syndrome (RLS) is a common neurological disorder.

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RLS is caused by alterations in the SNR ratio and in DA neurotransmission.

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The SNR- DA hypothesis how RLS affects cognitive performance is presented.

Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder

Background

Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated with flatter likelihoods (increased sensory processing noise), and/or difficulties in generating or using predictions. To our knowledge, such hypotheses have never been directly tested.

Methods

We here test these hypotheses by evaluating whether adults diagnosed with ADHD (n = 17) differed from a control group (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of a cloud of coherently moving dots. Unbeknown to the participants, two of the directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in other neurodevelopmental disorders, such as autistic spectrum disorder and schizophrenia.

Results

We found that both groups acquired the prior expectation for the most frequent directions and that these expectations substantially influenced task performance. Overall, there were no group differences in how much the priors influenced performance. However, subtle group differences were found in the influence of the prior over time.

Conclusion

Our findings suggest that the symptoms of inattention and hyperactivity in ADHD do not stem from broad difficulties in developing and/or using low-level perceptual priors.

A non-linear deterministic model of action selection in the basal ganglia to simulate motor fluctuations in Parkinson's disease

Motor fluctuations and dyskinesias are severe complications of Parkinson's disease (PD), especially evident at its advanced stage, under long-term levodopa therapy. Despite their strong clinical prevalence, the neural origin of these motor symptoms is still a subject of intense debate. In this work, a non-linear deterministic neurocomputational model of the basal ganglia (BG), inspired by biology, is used to provide more insights into possible neural mechanisms at the basis of motor complications in PD. In particular, the model is used to simulate the finger tapping task. The model describes the main neural pathways involved in the BG to select actions [the direct or Go, the indirect or NoGo, and the hyperdirect pathways via the action of the sub-thalamic nucleus (STN)]. A sensitivity analysis is performed on some crucial model parameters (the dopamine level, the strength of the STN mechanism, and the strength of competition among different actions in the motor cortex) at different levels of synapses, reflecting major or minor motor training. Depending on model parameters, results show that the model can reproduce a variety of clinically relevant motor patterns, including normokinesia, bradykinesia, several attempts before movement, freezing, repetition, and also irregular fluctuations. Motor symptoms are, especially, evident at low or high dopamine levels, with excessive strength of the STN and with weak competition among alternative actions. Moreover, these symptoms worsen if the synapses are subject to insufficient learning. The model may help improve the comprehension of motor complications in PD and, ultimately, may contribute to the treatment design.

Task experience eliminates catecholaminergic effects on inhibitory control - A randomized, double-blind cross-over neurophysiological study

Catecholaminergic neural transmission plays an important role during the inhibition of prepotent responses. Methylphenidate (MPH) is an important drug that modulates the catecholaminergic system. However, theoretical considerations suggest that the effects of drugs (e.g. MPH) on cognitive control may depend on prior learning effects. Here we investigate this in a conflict-modulated Go/Nogo task and evaluate neurophysiological processes associated with this dynamic using EEG signal decomposition methods and source localization analysis. The behavioral data show that prior learning experiences eliminate effects of MPH on response inhibition processes. On a neurophysiological level, we show that MPH modulates specific processes in medial frontal brain regions. Although MPH seems to consistently modulate neurophysiological processes associated with response inhibition, this is no longer sufficient to modulate behavioral performance once learning or task familiarization processes have taken place. An important consequence of this study finding is that it may be important to adjust MPH dosage depending on learning effects in a specific setting to constantly increase cognitive control functions in that setting. This has important implications for clinical practice, since MPH is the first-line pharmacological therapy in attention-deficit hyperactivity disorder (ADHD). Cross-over study designs with constant doses of MPH can mask effects on cognitive functions. The impact of learning needs careful consideration in cross-over study designs examining catecholaminergic drug effects.

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 literature review on the neurophysiological underpinnings and cognitive effects of transcutaneous vagus nerve stimulation: challenges and future directions

Brain stimulation approaches are important to gain causal mechanistic insights into the relevance of functional brain regions and/or neurophysiological systems for human cognitive functions. In recent years, transcutaneous vagus nerve stimulation (tVNS) has attracted considerable popularity. It is a noninvasive brain stimulation technique based on the stimulation of the vagus nerve. The stimulation of this nerve activates subcortical nuclei, such as the locus coeruleus and the nucleus of the solitary tract, and from there, the activation propagates to the cortex. Since tVNS is a novel stimulation technique, this literature review outlines a brief historical background of tVNS, before detailing underlying neurophysiological mechanisms of action, stimulation parameters, cognitive effects of tVNS on healthy humans, and, lastly, current challenges and future directions of tVNS research in cognitive functions. Although more research is needed, we conclude that tVNS, by increasing norepineprine (NE) and gamma-aminobutyric acid (GABA) levels, affects NE- and GABA-related cognitive performance. The review provides detailed background information how to use tVNS as a neuromodulatory tool in cognitive neuroscience and outlines important future leads of research on tVNS.

Learning Experience Reverses Catecholaminergic Effects on Adaptive Behavior

BACKGROUND

Catecholamines are important for cognitive control and the ability to adapt behavior (e.g., after response errors). A prominent drug that modulates the catecholaminergic system is methylphenidate. On the basis of theoretical consideration, we propose that the effects of methylphenidate on behavioral adaptation depend on prior learning experience.

METHODS

In a double-blind, randomized, placebo-controlled crossover study design, we examined the effect of methylphenidate (0.25 mg/kg) on post error behavioral adaptation processes in a group of n = 43 healthy young adults. Behavioral adaptation processes were examined in a working memory, modulated response selection task. The focus of the analysis was on order effects within the crossover study design to evaluate effects of prior learning/task experience.

RESULTS

The effect of methylphenidate/placebo on post-error behavioral adaptation processes reverses depending on prior task experience. When there was no prior experience with the task, methylphenidate increased post-error slowing and thus intensified behavioral adaptation processes. However, when there was prior task experience, (i.e., when the placebo session was conducted first in the crossover design), methylphenidate even decreased post-error slowing and behavioral adaptation. Effect sizes were large and the power of the observed effects was higher than 95%.

CONCLUSIONS

The data suggest that catecholaminergic effects on cognitive control functions vary as a function of prior learning/task experience. The data establish a close link between learning/task familiarization and catecholaminergic effects for executive functions, which has not yet been studied, to our knowledge, but is of considerable clinical relevance. Theoretical implications are discussed.

Passive perceptual learning modulates motor inhibitory control in superior frontal regions

Response inhibition is of vital importance in the context of controlling inappropriate responses. The role of perceptual processes during inhibitory control has attracted increased interest. Yet, we are far from an understanding of the mechanisms. One candidate mechanism by which perceptual processes may affect response inhibition refers to “gain control” that is closely linked to the signal‐to‐noise ratio of incoming information. A means to modulate the signal‐to‐noise ratio and gain control mechanisms is perceptual learning. In the current study, we examine the impact of perceptual learning (i.e., passive repetitive sensory stimulation) on response inhibition combining EEG signal decomposition with source localization analyses. A tactile GO/NOGO paradigm was conducted to measure action restraint as one subcomponent of response inhibition. We show that passive perceptual learning modulates response inhibition processes. In particular, perceptual learning attenuates the detrimental effect of response automation during inhibitory control. Temporally decomposed EEG data show that stimulus‐related and not response selection processes during conflict monitoring are linked to these effects. The superior and middle frontal gyrus (BA6), as well as the motor cortex (BA4), are associated with the effects of perceptual learning on response inhibition. Reliable neurophysiological effects were not evident on the basis of standard ERPs, which has important methodological implications for perceptual learning research. The results detail how lower level sensory plasticity protocols affect higher‐order cognitive control functions in frontal cortical structures.

Modeling the effects of methylphenidate on interference and evidence accumulation processes using the conflict linear ballistic accumulator

RATIONALE

Although methylphenidate and other stimulants have been demonstrated to improve task performance across a variety of domains, a computationally rigorous account of how these drugs alter cognitive processing remains elusive. Recent applications of mathematical models of cognitive processing and electrophysiological methods to this question have suggested that stimulants improve the integrity of evidence accumulation processes for relevant choices, potentially through catecholaminergic modulation of neural signal-to-noise ratios. However, this nascent line of work has thus far been limited to simple perceptual tasks and has largely omitted more complex conflict paradigms that contain experimental manipulations of specific top-down interference resolution processes.

OBJECTIVES AND METHODS

To address this gap, this study applied the conflict linear ballistic accumulator (LBA), a newly proposed model designed for conflict tasks, to data from healthy adults who performed the Multi-Source Interference Task (MSIT) after acute methylphenidate or placebo challenge.

RESULTS

Model-based analyses revealed that methylphenidate improved performance by reducing individuals' response thresholds and by enhancing evidence accumulation processes across all task conditions, either by improving the quality of evidence or by reducing variability in accumulation processes. In contrast, the drug did not reduce bottom-up interference or selectively facilitate top-down interference resolution processes probed by the experimental conflict manipulation.

CONCLUSIONS

Enhancement of evidence accumulation is a biologically plausible and task-general mechanism of stimulant effects on cognition. Moreover, the assumption that methylphenidate's effects on behavior are only visible with complex executive tasks may be misguided.

Deep Learning Based on Event-Related EEG Differentiates Children with ADHD from Healthy Controls

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neuropsychiatric disorders in childhood and adolescence and its diagnosis is based on clinical interviews, symptom questionnaires, and neuropsychological testing. Much research effort has been undertaken to evaluate the usefulness of neurophysiological (EEG) data to aid this diagnostic process. In the current study, we applied deep learning methods on event-related EEG data to examine whether it is possible to distinguish ADHD patients from healthy controls using purely neurophysiological measures. The same was done to distinguish between ADHD subtypes. The results show that the applied deep learning model (“EEGNet”) was able to distinguish between both ADHD subtypes and healthy controls with an accuracy of up to 83%. However, a significant fraction of individuals could not be classified correctly. It is shown that neurophysiological processes indicating attentional selection associated with superior parietal cortical areas were the most important for that. Using the applied deep learning method, it was not possible to distinguish ADHD subtypes from each other. This is the first study showing that deep learning methods applied to EEG data are able to dissociate between ADHD patients and healthy controls. The results show that the applied method reflects a promising means to support clinical diagnosis in ADHD. However, more work needs to be done to increase the reliability of the taken approach.

The Presynaptic Regulation of Dopamine and Norepinephrine Synthesis Has Dissociable Effects on Different Kinds of Cognitive Conflicts

Goal-directed behavior requires the ability to resolve subliminally or consciously induced response conflicts, both of which may benefit from catecholamine-induced increases in gain control. We investigated the effects of presynaptic differences in dopamine and norepinephrine synthesis with the help of the tyrosine hydroxylase (TH) rs10770141 and the dopamine-β-hydroxylase (DBH) rs1611115, rs6271, and rs1611122 polymorphisms. Conscious and subliminal response conflicts were induced with flanker and prime distractors in (n = 207) healthy young participants while neurophysiological data (EEG) was recorded. The results demonstrated that the increased presynaptic catecholamine synthesis associated with the TH rs10770141 TT genotype improves cognitive control in case of consciously perceived (flanker) conflicts, but not in case of subliminally processed (prime) conflicts. Only norepinephrine seemed to also modulate subliminal conflict processing, as evidenced by better performance of the DBH rs1611122 CC genotype in case of high subliminal conflict load. Better performance was linked to larger conflict-induced modulations in post-response alpha band power arising from parietal and inferior frontal regions, which likely helps to suppress the processing of distracting information. In summary, presynaptic catecholamine synthesis benefits consciously perceived conflicts by improving the suppression of distracting information following a conflict. Subliminal conflicts were modulated via the same mechanism, but only by norepinephrine.