Impulse Control Research Articles

Neuroscientific Approaches to Understanding Adolescent Susceptibility to Substance Abuse

Adolescence is a pivotal developmental stage characterised by significant neurobiological changes that heighten susceptibility to substance abuse. This period is marked by the maturation of the brain regions responsible for decision-making and impulse control, alongside an increased sensitivity to rewards driven by dopaminergic pathways. This review aimed to understand adolescent susceptibility to substance abuse using a neuroscientific approach. In line with best practices, data were collected from a variety reliable source to ensure a comprehensive view of the topic. Research studies on adolescent neurodevelopment have contributed to a broader understanding of the physiological and psychological factors at play during adolescence, while grey literature, including expert interviews and focused group discussions, has offered practical insights from frontline professionals, such as psychologists, social workers, and healthcare providers, who deal directly with adolescent substance use. These results demonstrate that the relationship between genetic factors and environmental conditions, such as stress and trauma, intensifies this vulnerability, thereby heightening the likelihood of individuals participating in risky behaviours. This review examines the neuroscientific foundations of substance use during adolescence, highlighting the critical role of timely interventions that utilize neuroplasticity to enhance resilience and reduce risk. By integrating cognitive training and behavioural therapies into public health initiatives, adolescents' cognitive control mechanisms and their propensity for substance abuse can be reduced.

Structural projections to the nucleus accumbens link to impulsive components of human risk preference

Abstract Functional responses in the Nucleus Accumbens (NAcc) to risk- and reward-related cues can predict real-life risk-taking behavior. Since NAcc activity depends on neurotransmission from connected brain regions, projections to the NAcc may also predict risk preference. To quantify risk preference, we employed latent variables previously derived in a comprehensive, independent study examining the psychometric structure of risk preference, which yielded a general risk preference factor as well as several specific factors, including a factor capturing impulsivity. Informed by previous work, we preregistered a set of hypotheses concerning the association between different risk preference factors and fractional anisotropy (or FA, which is sensitive to fiber coherence) for projections to the NAcc from Medial PreFrontal Cortex (MPFC), Anterior Insula, Amygdala, and an inferior tract from the Ventral Tegmental Area (iVTA). We tested our hypotheses in a community sample of 125 healthy human adults. As predicted, bilateral iVTA-NAcc tract FA showed a negative correlation with a psychometric factor that captured impulsivity, generalizing findings from prior research. Also as predicted, FA of the bilateral Amygdala-NAcc tract was positively associated with the impulsivity factor. Contrary to predictions, however, we observed no robust associations between the general risk preference factor and FA for projections from bilateral MPFC, right Anterior Insula, or bilateral Amygdala to the NAcc. Notably, exploratory unilateral analyses revealed an association between the general risk preference factor and left MPFC-NAcc tract FA. Taken together, these findings suggest that impulse control as a facet of risk preference maps onto specific neurobiological targets, while more general facets of risk preference may be supported by structural properties of lateral fronto-striatal projections. Although the exact associated functional mechanisms remain to be fully clarified, conNAcctomic approaches like the one presented here could pave the way for further research into the physiological foundations of risk preference and related constructs.

Active Impulsive Noise Control with Missing Input Data Based on FxImdMCC Algorithm

In this study, we address the challenge of noise reduction in environments characterized by impulsive noise and missing input data in active noise control (ANC) systems, where existing algorithms often fail to deliver satisfactory results. Background noise, especially impulsive noise, poses a significant obstacle to signal processing and noise reduction. Furthermore, data loss during transmission or acquisition further complicates the noise reduction task. In this paper, a filtered-x imputation of the missing data maximum correntropy criterion (FxImdMCC) algorithm is proposed based on an imputation model, least mean square, and the maximum correntropy criterion (MCC), which can effectively reduce the impact of outliers and missing input data. The simulation results demonstrate the efficacy of the proposed FxImdMCC algorithm, which significantly outperforms existing algorithms in the context of active impulsive noise control.

Secure multi-synchronization of heterogeneous dynamical networks with deception attacks via event-triggered impulsive control

Secure multi-synchronization of heterogeneous dynamical networks with deception attacks via event-triggered impulsive control

Exponential Quasi-Synchronization of Fractional-Order Fuzzy Cellular Neural Networks via Impulsive Control

This paper investigates the exponential quasi-synchronization of fractional-order fuzzy cellular neural networks with parameters mismatch via impulsive control. Firstly, under the framework of the generalized Caputo fractional-order derivative, a new fractional-order impulsive differential inequality is established. Secondly, based on this fractional-order impulsive differential inequality, a general criterion for the quasi-synchronization of fractional-order systems is obtained. Then, specific to the fractional-order fuzzy cellular neural network model in this paper, the criteria and error estimation of the exponential quasi-synchronization of fractional-order fuzzy cellular neural networks can be obtained. Finally, two numerical examples are given to illustrate the effectiveness of the obtained results.

Clinical management model for impulse control disorders in Parkinson's disease.

Over the last decade, we have gained a better understanding of impulse control disorder in Parkinson's disease (PD-ICD), a medication complication in PD. Researchers were aware of its complexity and took efforts to learn more about its diagnostic and treatment possibilities. Nevertheless, clinical management for it is currently neglected. We conducted a narrative overview of literature published from 2012 to October 2023 on various aspects of clinical management for PD-ICD. A potential "susceptibility-catalytic-stress" model in the development of PD-ICD was proposed and a profile encoding predictors for PD-ICD was created. Based on these predictors, some methods for prediction were recently developed for better prediction, such as the polymorphic dopamine genetic risk score and the clinic-genetic ICD-risk score. A variety of treatment options, including dose reduction of dopamine receptor agonists (DAs), DAs removal, DAs switch, and add-on therapy, are investigated with inconsistent reports. Based on current findings, we developed a clinical management model prototype centered on prevention, consisting of prediction, prevention, follow-up and monitoring, therapy, and recurrence prevention, for clinical reference, and further proposed 4 key clinical management principles, including standardization, prediction centered, persistence, and whole course.

Management of Carbon Emissions via a Nonzero-Sum Stochastic Differential Game

This study examines an environmental management strategy to effectively cap greenhouse gas (GHG) emissions in an electricity market. To do so, we model a stochastic impulse two-person, nonzero-sum game between a power plant, a representative of electricity production within a country whose primary aim is to maximize profits, and government who is motivated to minimize the social and environmental cost of pollution. We assume that the power plant’s competitive price is equal to the marginal cost whilst the government’s running cost is linear. When the uncontrolled output of GHG emissions evolves as a Geometric Brownian motion, we provide a more dynamic and robust depiction of the interplay between government and the energy sector. We provide solutions to the impulse control problem derived via the quasi-variational inequalities (QVIs). We then present a sufficiency criterion for the existence of a Nash equilibrium for the optimal policy. Ultimately, our use of short-run price competition characterized by strategic supplies for renewable and fossil resources and inclusion of endogenous constraints on production capacity provides a more robust model and an effective framework for the development of policy that allows governments to meet emissions targets whilst guaranteeing energy supply.

Dynamics and event-triggered control of rumor propagation model with saturated incidence and time delay on heterogeneous networks

Considering the impact of user’s cognitive ability in rumor propagation, this paper proposes a new susceptible infection recovery (2SIR) rumor propagation model with saturation incidence and time delay on heterogeneous networks. First, the existence of the equilibria is discussed by using mean field theory and basic reproduction number. Second, the dynamic behaviors of the rumor-free and persistent equilibria are analyzed via the local linearization method, Lyapunov stability theory and irreducible matrix properties. Furthermore, an event-triggered impulsive control strategy is proposed to control the rumor spreaders and some corresponding control conditions are given. Finally, some numerical simulation results and a practical example are presented to verify the correctness of the theoretical results and reflect the impact of cognitive ability and time delay on rumor propagation.

Impulse Controllability for Singular Hybrid Coupled Systems

This study examines the concept of impulse controllability within singular hybrid coupled systems through the utilisation of decentralised proportional plus derivative (P-D) output feedback. By employing the Differential Mean Value Theorem, the nonlinear model can be converted into a linear parameter-varying large-scale system. Our analysis leads to the establishment of algebraic conditions that are both necessary and sufficient for the existence of a decentralised P-D output feedback controller that can guarantee impulse controllability in these complex systems. Moreover, we address the issue of admissibility within these systems by employing matrix trace inequalities. We present a novel sufficient condition for impulse controllability, which offers a new perspective on addressing this challenging problem. To validate our findings, we present numerical examples that demonstrate the effectiveness of the proposed methodologies in practice.

Behavioral disorders in Parkinson disease: current view.

Patients with Parkinson disease (PD) frequently experience several behavioral symptoms, such as anxiety, apathy, irritability, agitation, impulsive control and obsessive-compulsive or REM sleep behavior disorders, which can cause severe psychosocial problems and impair quality of life. Occurring in 30-70% of PD patients, these symptoms can manifest at early stages of the disease, sometimes even before the appearance of classic motor symptoms, while others can develop later. Behavioral changes in PD show distinct patterns of brain atrophy, dopaminergic and serotonergic deterioration, altered neuronal connectivity in frontostriatal, corticolimbic, default mode and other networks due to a cascade linking molecular pathologies and deficits in multiple behavior domains. The changes suggest a multi-system neurodegenerative process in the context of a specific α-synucleinopathy inducing a variety of biochemical and functional changes, the neurobiological basis and clinical relevance of which await further elucidation. This paper is intended to review the recent literature with focus on the main behavioral disturbances in PD patients, their epidemiology, clinical features, risk factors, animal models, neuroimaging findings, pathophysiological backgrounds, and treatment options of these deleterious lesions.

Intermittent Explosive Disorder

Intermittent explosive disorder is characterized by recurrent episodes of inability to resist aggressive impulses, resulting in damage to other people or other people's property. In the history of DSM, it first appeared as 'isolated explosive disorder' in DSM-III. However, with some changes in the diagnostic criteria, it is included under the title of 'destructive, impulse control and conduct disorders' in DSM-5. Although previous studies have shown it is a rare disorder, recent epidemiological studies suggest it may be more common than thought. For this reason, it is essential to master the clinical features and learn the treatment methods in order to recognize people with this disorder and apply the appropriate treatment.

Existence of a mild solution and approximate controllability for fractional random integro-differential inclusions with non-instantaneous impulses

This paper investigates the existence and approximate controllability (ACA) of fractional neutral-type stochastic differential inclusions (NTSDIs) characterized by non-instantaneous impulses within a separable Hilbert space (HS) framework. Employing the Atangana–Baleanu–Caputo (ABC) derivative, we transform the system into an equivalent fixed-point (FP) problem through an integral operator. Subsequently, the Bohnenblust–Karlin FP theorem is leveraged to establish existence results. By assuming ACA of the corresponding linear system, we derive sufficient conditions for the ACA of the nonlinear stochastic impulsive control system. Our analysis relies on concepts from stochastic analysis, fractional calculus, FP theory, semigroup theory, and the theory of multivalued maps (MVMs). The theoretical findings are illustrated through a concrete example.

Optimal Periodic Impulsive Control for Orbital Stabilization of Underactuated Systems

Optimal Periodic Impulsive Control for Orbital Stabilization of Underactuated Systems

Incidental Physical Activity and Physical Fitness Associate with Sustained Attention and Impulse Control in Older Adults

Age-related changes have been observed in sustained attention and impulse control. Deficits in these functions are related to pathological aging. However, research suggests that an active lifestyle may exert a protective effect on cognition in aging. While the association between physical activity and cognitive functioning in older adults has been previously described, few studies have explored the relationship between incidental physical activity and fitness with sustained attention and impulse control in this population. Therefore, this study aimed to evaluate the association between incidental physical activity and various components of fitness and sustained attention and impulsivity in older adults. Fifty-four older adults were recruited (41 females and 13 males) with a mean age of 76.76 years (SD = 8.94). Physical activity levels were assessed using the Yale Physical Activity Survey (YPAS), physical function in healthy older adults was evaluated with the Senior Fitness Test, and sustained attention and impulsivity were measured using a computerized continuous performance task. Significant correlations were found between higher energy expenditure during housework and yardwork activities, and fewer commission errors and shorter reaction times during sustained attention task, and higher sensitivity during impulse control task (rho between 0.35 and 0.40, p < .01, β = 0.80). Additionally, higher scores between agility and balance were associated with better accuracy during the sustained attention task, and faster speed processing correlated to better performance impulse control task (rho between 0.33 and 0.36, p < .05, β = 0.80). Our study highlights the importance of incidental physical activity and various components of fitness on sustained attention and impulse control in aging.

A zero-sum hybrid stochastic differential game with impulse controls

A zero-sum hybrid stochastic differential game with impulse controls

Attention Deficit Hyperactivity Disorder and Sexual Functioning - is there a connection?

Understanding how ADHD affects sexual functioning is key to providing comprehensive care. This review looks into the current research on sexual health in people with ADHD, focusing on how common sexual dysfunction is, how ADHD symptoms might impact sexual behavior, and what role medications play. By summarizing the existing studies, this review aims to highlight what we don’t know yet and suggest future research to improve treatment and patient outcomes. The review covers literature related to sexual functioning in ADHD, particularly looking at connections to hypersexuality, paraphilias, and various sexual behaviors. A thorough search of electronic databases, including PubMed, PsycINFO, and Google Scholar, was conducted using relevant keywords such as 'ADHD,' 'hypersexuality,' 'paraphilias,' 'sexuality,' 'sexual behavior,' and 'sexual violence.' The study duration was 6 months. Common features of ADHD, such as impulsivity, poor impulse control, and difficulties with self-regulation, may contribute to risky sexual behaviors, compulsive sexual behavior, or the development of paraphilic interests. It's important for doctors dealing with ADHD in children to discuss sexual health as the patient nears adolescence and offer guidance on safe sex. Treatment should combine medication with therapy. Since impulsivity seems to play a big role in risky sexual behavior, making contraceptives readily available could be important for sexual health. Longitudinal studies are necessary to better understand the temporal relationships and progression of sexual behaviors and ADHD symptoms over time. Given the potential impact of ADHD on sexual behavior and functioning, healthcare providers should consider screening for ADHD in patients presenting with issues related to hypersexuality, paraphilias, or other sexual concerns.

Resting-state brain activation patterns and network topology distinguish human sign and goal trackers

The “Sign-tracker/Goal-tracker” (ST/GT) is an animal model of individual differences in learning and motivational processes attributable to distinctive conditioned responses to environmental cues. While GT rats value the reward-predictive cue as a mere predictor, ST rats attribute it with incentive salience, engaging in aberrant reward-seeking behaviors that mirror those of impulse control disorders. Given its potential clinical value, the present study aimed to map such model onto humans and investigated resting state functional magnetic resonance imaging correlates of individuals categorized as more disposed to sign-tracking or goal-tracking behavior. To do so, eye-tracking was used during a translationally informed Pavlovian paradigm to classify humans as STs (n = 36) GTs (n = 35) or as Intermediates (n = 33), depending on their eye-gaze towards the reward-predictive cue or the reward location. Using connectivity and network-based approach, measures of resting state functional connectivity and centrality (role of a node as a hub) replicated preclinical findings, suggesting a major involvement of subcortical areas in STs, and dominant cortical involvement in GTs. Overall, the study strengthens the translational value of the ST/GT model, with important implications for the early identification of vulnerable phenotypes for psychopathological conditions such as substance use disorder.

The Daydream Spectrum: The Role of Emotional Dysregulation, Internalized Stigma and Self-Esteem in Maladaptive Daydreaming Among Adults With ADHD, ASD, and Double Diagnosis.

Maladaptive daydreaming (MD) is characterized by vivid, excessive fantasy activity that becomes prioritized over other activities and may result in avoidant coping strategies. Little is known about the relationship between MD and internalized stigma in the neurodivergent sample. The current study aimed to examine emotional dysregulation, escapism and self-perception (self-esteem and internalized stigma) as potential determinants of MD in three groups: adults on the autism spectrum, with ADHD, and both diagnoses ("AuDHD"), including their neurodivergent symptoms (autistic traits, empathizing, ADHD symptoms). A sample of 293 persons (139 with ADHD, 74 on the autism spectrum, and 80 with both diagnoses) completed self-report scales concerning ADHD symptoms, autism spectrum symptoms, empathizing, self-esteem, daydreaming as escapism, emotional dysregulation, maladaptive daydreaming, and internalized stigma. A correlation analysis was implemented. Additionally, a group comparison and quantile regression for the 25th, 50th, and 75th percentile of maladaptive daydreaming in the three groups were executed. The results showed that internalized stigma, emotional dysregulation, escapism, and self-esteem have significant associations with MD in the neurodiverse sample. The ADHD group achieved the lowest scores in emotional dysregulation, discrimination experience, and social withdrawal. The groups did not vary in MD rates, stereotype endorsement, stigma resistance, nonacceptance of emotional responses, and impulse control difficulties. The AuDHD group achieved higher results than the ASD group only in the ADHD symptoms. Quantile regression revealed differences in the predictors of maladaptive daydreaming in the three groups. ADHD symptoms and self-suppression escapism were significant predictors for the higher levels of MD in persons with singular autism or ADHD diagnosis. The results showed no differences in MD rates, although there were significant variations in predictive features among the three samples. The role of internalized stigma and self-esteem was highlighted in the results as significant associates of MD prevalence. These outcomes expand the current knowledge in the context of maladaptive daydreaming, internalized stigma, self-esteem and emotional dysregulation in a neurodiverse sample and allow for proposing clinical applications and further research directions.

Multiclass classification of Autism Spectrum Disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis.

Neurodevelopmental conditions, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), present unique challenges due to overlapping symptoms, making an accurate diagnosis and targeted intervention difficult. Our study employs advanced machine learning techniques to analyze functional magnetic resonance imaging (fMRI) data from individuals with ASD, ADHD, and typically developed (TD) controls, totaling 120 subjects in the study. Leveraging multiclass classification (ML) algorithms, we achieve superior accuracy in distinguishing between ASD, ADHD, and TD groups, surpassing existing benchmarks with an area under the ROC curve near 98%. Our analysis reveals distinct neural signatures associated with ASD and ADHD: individuals with ADHD exhibit altered connectivity patterns of regions involved in attention and impulse control, whereas those with ASD show disruptions in brain regions critical for social and cognitive functions. The observed connectivity patterns, on which the ML classification rests, agree with established diagnostic approaches based on clinical symptoms. Furthermore, complex network analyses highlight differences in brain network integration and segregation among the three groups. Our findings pave the way for refined, ML-enhanced diagnostics in accordance with established practices, offering a promising avenue for developing trustworthy clinical decision-support systems.

Impulse Control Deficits and Loneliness/Depression

This study aimed to assess the prevalence of problematic internet use (PIU) among Brazilian adults and its cognitive and emotional factors. A total of 294 individuals (144 men, 149 women, 1 undisclosed) aged 18 to 55 years (M=29.31, SD=7.99) participated, completing various instruments: a sociodemographic and internet use questionnaire, the generalized problematic internet use scale (GPIUS-2), the online cognition scale (OCS), the depression anxiety stress scale-21 (DASS-21), and the difficulties in emotional regulation scale (DERS). The prevalence of PIU was 17.4% (n=49). Younger participants reported higher rates of PIU. GPIUS-2 scores positively correlated with DERS and DASS-21 subscales. Network analysis highlighted impulse control deficits and loneliness/depression as key factors associated with PIU, with anxiety indirectly related through stress. These findings highlight the link between emotional difficulties and PIU, suggesting the need for guidelines to promote healthier internet use.