Impulsivity and Response Inhibition Related Brain Networks in Adolescents With Internet Gaming Disorder: A Preliminary Study Utilizing Resting-State fMRI

Multimodal neuroimaging fusion unravel structural-functional-neurotransmitter change in Parkinson's disease with impulse control disorders

BACKGROUND

Impulse control disorders (ICD) in Parkinson's disease (PD) is highly multifactorial in etiology and has intricate neural mechanisms. Our multimodal neuroimaging study aimed to investigate the specific patterns of structure-function-neurotransmitter interactions underlying ICD.

METHODS

Thirty PD patients with ICD (PD-ICD), 30 without ICD (PD-NICD) and 32 healthy controls (HCs) were recruited. Gyrification and perivascular spaces (PVS) were computed to capture the alternations of cortical surface morphology and glymphatic function. Seed-based functional connectivity (FC) were performed to identify the corresponding functional changes. Further, JuSpace toolbox were employed for cross-modal correlations to evaluate whether the spatial patterns of functional alterations in ICD patients were associated with specific neurotransmitter system.

RESULTS

Compared to PD-NICD, PD-ICD patients showed hypogyrification and enlarged PVS volume fraction in the left orbitofrontal gyrus (OFG), as well as decreased FC between interhemispheric OFG. The interhemispheric OFG connectivity reduction was associated with spatial distribution of μ-opioid pathway (r = -0.186, p = 0.029, false discovery rate corrected). ICD severity was positively associated with the PVS volume fraction of left OFG (r = 0.422, p = 0.032). Furthermore, gyrification index (LGI) and percent PVS (pPVS) in OFG and their combined indicator showed good performance in differentiating PD-ICD from PD-NICD.

CONCLUSIONS

Our findings indicated that the co-altered structure-function-neurotransmitter interactions of OFG might be involved in the pathogenesis of ICD.

Problematic Gaming and Gambling: A Systematic Review of Task-Specific EEG Protocols

Even though gaming and gambling bear similar problematic behavioral aspects, there are no recognizable neurophysiological biomarkers or features characterizing and/or distinguishing these conditions. A systematic review of the literature with a focus on methods was performed in PubMed, Scopus, Web of Science (Web of Science Core Collection), EBSCOhost Research Databases (APA PsycINFO; APA PsycArticles; OpenDissertations; ERIC) databases. Following search terms were used to search the databases: ERP, "event related potential*", EP, "evoked potential*", SS, "steady state", EEG, electroencephal*; gam*. Data about the participants (total number, gender, age), main aim of the study and information about the experimental setup (experimental task description, stimuli used, ERPs measured (latency windows and placement of the electrodes), process evaluated) was extracted. A total of 24 studies were revised (problematic gaming - 16, pathological gambling - 8). The experimental protocols could be grouped into 3 main target domains (Cue-reactivity, General Information processing and Reward Processes & Risk Assessment). Sample-related limitations (small sample sizes, gender differences, differences between the groups regarding potential confounding variables) and heterogeneity regarding the experimental tasks, implementation and interpretation reviewed. Gambling-related research is highly focused on the investigation of the reward-related processes, whereas gaming-related research is mostly focused on the altered aspects of more general information processing. A vast heterogeneity regarding the ERP experimental paradigms being used and lack of clear guidelines and standardized procedures prevents identification of measures capable to reliably discriminate or characterize the population susceptible to addictive behavior or being able to diagnose and monitor these disorders.

Influence of reinforcement learning on the inhibitory control of Internet gaming disorder

Reward processing dysfunction and inhibition control deficiency have been observed in Internet gaming disorder (IGD). However, it is still unclear whether the previous reinforcement learning depends on reward/punishment feedback influences on the cognitive inhibitory control of IGD. This study compared the differences between an IGD group and healthy people without game experiences in the probability selection task and the subsequent stop signal task by the method of behavioral experiments, in order to explore whether the reward learning ability is impaired in the IGD group. We also discuss the influence of previous reward learning on subsequent inhibition control. The results showed that (1) during the reward learning phase, the IGD group's accuracy was significantly lower than that of the control group; (2) compared with the control group, the IGD group's reaction times were longer in the transfer phase; (3) for no-go trials of the inhibitory control phase after reward learning, the accuracy of the reward-related stimulation in the IGD group was lower than that of punishment-related or neutral stimulation, but there was no significant difference among the three conditions in the control group. These findings indicated that the reinforcement learning ability of the IGD group was impaired, which further caused the abnormal response to reinforcement stimuli.

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults

Impulsive traits (i.e., the tendency to act without forethought regardless of negative outcomes) are frequently found in healthy populations. When exposed to risk factors, individuals may develop debilitating disorders of impulse control (addiction, substance abuse, gambling) characterized by behavioral and cognitive deficits, eventually leading to huge socioeconomic costs. With the far-reaching aim of preventing the onset of impulsive disorders, it is relevant to investigate the topological organization of functional brain networks associated with impulsivity in sub-clinical populations. Taking advantage of the open-source LEMON dataset, we investigated the topological features of resting-state functional brain networks associated with impulsivity in younger (n = 146, age: 20-35) and older (n = 61, age: 59-77) individuals, using a graph-theoretical approach. Specifically, we computed indices of segregation and integration at the level of specific circuits and nodes known to be involved in impulsivity (frontal, limbic, and striatal networks). In younger individuals, results revealed that impulsivity was associated with a more widespread, less clustered and less efficient functional organization, at all levels of analyses and in all selected networks. Conversely, impulsivity in older individuals was associated with reduced integration and increased segregation of striatal regions. Speculatively, such alterations of functional brain networks might underlie behavioral and cognitive abnormalities associated with impulsivity, a working hypothesis worth being tested in future research. Lastly, differences between younger and older individuals might reflect the implementation of age-specific adaptive strategies, possibly accounting for observed differences in behavioral manifestations. Potential interpretations, limitations and implications are discussed.

Prefrontal Dopamine in Flexible Adaptation to Environmental Changes: A Game for Two Players

Deficits in cognitive flexibility have been characterized in affective, anxiety, and neurodegenerative disorders. This paper reviews data, mainly from studies on animal models, that support the existence of a cortical-striatal brain circuit modulated by dopamine (DA), playing a major role in cognitive/behavioral flexibility. Moreover, we reviewed clinical findings supporting misfunctioning of this circuit in Parkinson's disease that could be responsible for some important non-motoric symptoms. The reviewed findings point to a role of catecholaminergic transmission in the medial prefrontal cortex (mpFC) in modulating DA's availability in the nucleus accumbens (NAc), as well as a role of NAc DA in modulating the motivational value of natural and conditioned stimuli. The review section is accompanied by a preliminary experiment aimed at testing weather the extinction of a simple Pavlovian association fosters increased DA transmission in the mpFC and inhibition of DA transmission in the NAc.

Neuroimaging findings in adolescent gaming disorder: a systematic review

OBJECTIVES

Gaming disorder is a growing concern affecting adolescents, exacerbated by the impact of recent COVID-19 restrictions. The World Health Organization has recently included gaming disorder in the 11th International Classification of Diseases (ICD-11). However, there is still an ongoing debate about the validity and reliability of the proposed clinical criteria, despite growing neurobiological evidence in this cohort. Systematic reviews in this area have focused mainly on adults or mixed adult/adolescent populations. Therefore, this systematic review explored the neuroimaging literature in adolescents (under 18 years old) with gaming disorder.

METHODS

Using PRISMA 2020 guidelines, 3288 primary studies were identified from PubMed, CINAHL Plus, PsycINFO and Web of Science. After applying inclusion and exclusion criteria (appropriate title, abstract, comparison group used within study, English-language, neuroimaging and mean age under 18), 24 studies were included in this review.

RESULTS

Functional and structural brain alterations in adolescent gaming disorder were noted across several imaging modalities, including electroencephalogram (EEG), functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (MRI). Compared with healthy controls, adolescents with gaming disorder demonstrated neurological changes comparable to substance addiction, namely impairments in emotional regulation, reward-seeking, inhibition and increased risky decision-making. Positive brain adaptations in the areas of visuospatial processing and memory were observed.

CONCLUSIONS

A number of key brain regions are affected in adolescent gaming disorder. These findings can help clinicians understand adolescent presentations with gaming disorder from a neurobiological perspective. Future studies should focus on forming a robust neurobiological and clinical framework for adolescent gaming disorder.

The involvement of spontaneous brain activity in natural recovery from internet gaming disorder: A resting-state fMRI study

OBJECTIVE

Internet gaming disorder (IGD) can seriously impair an individual's physical and mental health. However, unlike the majority of those suffering from substance addiction, individuals with IGD may recover without any professional intervention. Understanding the brain mechanisms of natural recovery from IGD may provide new insight into how to prevent addiction and implement more targeted interventions.

METHODS

Sixty individuals with IGD were scanned by using a resting-state fMRI to assess brain region changes associated with IGD. After 1 year, 19 individuals with IGD no longer met the IGD criteria and were considered recovered (RE-IGD), 23 individuals still met the IGD criteria (PER-IGD), and 18 individuals left the study. The brain activity in resting state between 19 RE-IGD individuals and 23 PER-IGD individuals was compared by using regional homogeneity (ReHo). Additionally, brain structure and cue-craving functional MRIs were collected to further support the results in the resting-state.

RESULTS

The resting-state fMRI results revealed that activity in brain regions responsible for reward and inhibitory control [including the orbitofrontal cortex (OFC), the precuneus and the dorsolateral prefrontal cortex (DLPFC)] was decreased in the PER-IGD individuals compared to RE-IGD individuals. In addition, significant positive correlations were found between mean ReHo values in the precuneus and self-reported craving scores for gaming, whether among the PER-IGD individuals or the RE-IGD individuals. Furthermore, we found similar results in that brain structure and cue-craving differences exist between the PER-IGD individuals and RE-IGD individuals, specifically in the brain regions associated with reward processing and inhibitory control (including the DLPFC, anterior cingulate gyrus, insula, OFC, precuneus, and superior frontal gyrus).

CONCLUSION

These findings indicate that the brain regions responsible for reward processing and inhibitory control are different in PER-IGD individuals, which may have consequences on natural recovery. Our present study provides neuroimaging evidence that spontaneous brain activity may influence natural recovery from IGD.

Abnormal resting-state functional connectome in methamphetamine-dependent patients and its application in machine-learning-based classification

Brain resting-state functional connectivity (rsFC) has been widely analyzed in substance use disorders (SUDs), including methamphetamine (MA) dependence. Most of these studies utilized Pearson correlation analysis to assess rsFC, which cannot determine whether two brain regions are connected by direct or indirect pathways. Moreover, few studies have reported the application of rsFC-based graph theory in MA dependence. We evaluated alterations in Tikhonov regularization-based rsFC and rsFC-based topological attributes in 46 MA-dependent patients, as well as the correlations between topological attributes and clinical variables. Moreover, the topological attributes selected by least absolute shrinkage and selection operator (LASSO) were used to construct a support vector machine (SVM)-based classifier for MA dependence. The MA group presented a subnetwork with increased rsFC, indicating overactivation of the reward circuit that makes patients very sensitive to drug-related visual cues, and a subnetwork with decreased rsFC suggesting aberrant synchronized spontaneous activity in subregions within the orbitofrontal cortex (OFC) system. The MA group demonstrated a significantly decreased area under the curve (AUC) for the clustering coefficient (Cp) (Pperm < 0.001), shortest path length (Lp) (Pperm = 0.007), modularity (Pperm = 0.006), and small-worldness (σ, Pperm = 0.004), as well as an increased AUC for global efficiency (E.glob) (Pperm = 0.009), network strength (Sp) (Pperm = 0.009), and small-worldness (ω, Pperm < 0.001), implying a shift toward random networks. MA-related increased nodal efficiency (E.nodal) and altered betweenness centrality were also discovered in several brain regions. The AUC for ω was significantly positively associated with psychiatric symptoms. An SVM classifier trained by 36 features selected by LASSO from all topological attributes achieved excellent performance, cross-validated prediction area under the receiver operating characteristics curve, accuracy, sensitivity, specificity, and kappa of 99.03 ± 1.79, 94.00 ± 5.78, 93.46 ± 8.82, 94.52 ± 8.11, and 87.99 ± 11.57%, respectively (Pperm < 0.001), indicating that rsFC-based topological attributes can provide promising features for constructing a high-efficacy classifier for MA dependence.

Applying network analysis to understand the relationships between impulsivity and social media addiction and between impulsivity and problematic smartphone use

BACKGROUND

Prior studies have revealed the relationships between impulsivity and social media addiction (SMA) and between impulsivity and problematic smartphone use (PSU) based on total scores on standardized self-report scales. However, there has been a lack of studies exploring how the dimensions of impulsivity and components of SMA or PSU are interrelated. The present study aimed to investigate the structural relationships between the dimensions of impulsivity and components of SMA and PSU and determine the critical bridge node using network analysis.

METHODS

A total of 325 healthy adults aged 18-36 years participated in the study. SMA and PSU were assessed using the Bergen Social Media Addiction Scale (BSMAS) and Smartphone Application-Based Addiction Scale (SABAS), respectively. Impulsivity was measured by the Barratt Impulsiveness Scale Version 11 (BIS-11). Network analysis was used to construct an SMA-Impulsivity network and a PSU-Impulsivity network. Bridge centrality (bridge expected influence, BEI) was estimated to identify influential bridge nodes.

RESULTS

In addition to relationships within each community, network analysis revealed that the dimensions of impulsivity were closely associated with the components of SMA and PSU. Particularly, I2 "motor impulsivity" had a relatively strong connection with SMA3 "mood modification" and SMA4 "relapse" in the SMA-Impulsivity network, and with PSU2 "conflict" and PSU5 "withdrawal" in the PSU-Impulsivity network. Moreover, I2 "motor impulsivity" was identified as the most critical bridge node in both networks.

CONCLUSION

These findings demonstrate potential pathways between different dimensions of impulsivity and the components of SMA and PSU, providing new evidence relevant to understanding the underlying mechanisms that account for how highly impulsive individuals develop SMA and PSU, and highlight the critical bridge node-motor impulsivity-that may be a promising and effective target for the prevention and treatment of SMA and PSU.