Abnormal resting-state EEG power and impaired inhibition control in young smokers

Chronic effects of tobacco smoking on electrical brain activity: A systematic review on electroencephalography studies

Despite significant strides in reducing smoking prevalence globally, tobacco use remains a leading contributor to ill health and premature death worldwide. While the detrimental impacts of smoking on various organs are well-established, its specific effects on nervous system function remain an area of ongoing investigation. This systematic review delves into the neurobiological effects of smoking, particularly through the lens of resting-state electroencephalography (EEG). A systematic search was conducted in May 2024 in PubMed, Embase, and Web of Science databases, and all available evidence comparing resting-state EEG findings between smokers and non-smokers was assessed. The 13 included studies investigated a total of 684 participants, with a median female percentage of of 25 % (range: 0-100), and the age of participants ranged from 18 to approximately 73 years. Alterations in the alpha band were the most prevalent findings observed in the EEG of smokers compared to non-smokers, observed in 8 studies, suggesting changes in the attention and cognitive functions of smokers. However, findings regarding the specific direction and location of changes were not consistent. Additionally, changes in delta, theta, and beta bands were identified on a less frequent basis. There was evidence suggesting that the observed neural oscillation changes are influenced by various factors, including the number of cigarettes used, pack years of smoking, age of smoking initiation, and smoking cessation status. These findings underscore the multifaceted nature of the impact of smoking on brain activity, especially on cognition and the attentional system.

The relationship between behavioral inhibition and resting electroencephalography: A neuroelectrophysiological study

Investigating the neurophysiological indicators of behavioral inhibition is crucial; however, despite numerous studies on the relationship between behavioral inhibition and resting-state electroencephalography (rs-EEG), the findings have yielded inconsistent results. Furthermore, these investigations primarily focused on reactive inhibition while neglecting intentional inhibition. Therefore, this study aimed to reassess the correlation between reactive inhibition and rs-EEG metrics while also exploring the association between intentional inhibition and rs-EEG. Power spectrum analysis and microstate analysis were employed to extract rs-EEG, whereas the Free Two-Choice Oddball task was utilized for assessing both reactive and intentional inhibition among 95 participants. The results revealed no significant correlations between reactive inhibition and rs-EEG metrics. However, intentional inhibition exhibited a negative correlation with relative power in delta and beta bands but a positive correlation with relative power in alpha band. Moreover, intentional inhibition demonstrated a negative correlation with occurrence rate and contribution of microstate A but a positive correlation with duration of microstate D. Additionally, it displayed a negative relationship with the transition probability between microstate A and C but a positive relationship with the transition probability between microstate C and D. The regression analysis revealed that the occurrence rate of microstate A can negatively predict intentional inhibition. Overall, this study advances theoretical understanding as well as empirical research in this field by addressing gaps in rs-EEG evidence for intentional inhibition while providing potential neuropsychological indicators for its assessment.

Abnormal power and spindle wave activity during sleep in young smokers

Introduction

Smoking is associated with significant alterations in sleep architecture. Previous studies have revealed changes in the subjective sleep of young smokers, but research on objective sleep assessment using polysomnography (PSG) is limited. This study aims to explore electroencephalography (EEG) power and sleep spindle activity during the sleep of young smokers, as well as to assess the relationship between sleep and smoking variables.

Methods

We collected overnight PSG data from 19 young smokers and 16 non-smokers and assessed nicotine dependence and cumulative effects using the Fagerstrom Nicotine Dependence Test (FTND) and pack-year. Power spectral analysis and sleep spindle detection are used to analyze EEG activity during sleep.

Results

Compared to the non-smokers, young smokers showed increased alpha power in the frontal and central regions and decreased delta power in the central region. The frontal region showed enhanced sleep spindle duration and density. Notably, both relative alpha power and sleep spindle duration in frontal showed a positive correlation with Pack-year.

Discussion

Sleep EEG power and sleep spindle activity in frontal may serve as biomarkers to assess the sleep quality of young smokers. It may improve the understanding of the relationship of sleep and smoking.

Individual peak alpha frequency does not index individual differences in inhibitory cognitive control

Previous work has indicated that individual differences in cognitive performance can be predicted by characteristics of resting state oscillations, such as individual peak alpha frequency (IAF). Although IAF has previously been correlated with cognitive functions, such as memory, attention, or mental speed, its link to cognitive conflict processing remains unexplored. The current work investigated the relationship between IAF and inhibitory cognitive control in two well-established conflict tasks, Stroop and Navon task, while also controlling for alpha power, theta power, and the 1/f offset of aperiodic broadband activity. In Bayesian analyses on a large sample of 127 healthy participants, we found substantial evidence against the assumption that IAF predicts individual abilities to spontaneously exert cognitive control. Similarly, our findings yielded substantial evidence against links between cognitive control and resting state power in the alpha and theta bands or between cognitive control and aperiodic 1/f offset. In sum, our results challenge frameworks suggesting that an individual's ability to spontaneously engage attentional control networks may be mirrored in resting state EEG characteristics.

Persistent impacts of smoking on resting-state EEG in male chronic smokers and past-smokers with 20 years of abstinence

Smoking is a severe addictive health risk behavior and notorious for the high likelihood of relapse after attempted cessation. Such an addictive pattern in smoking has been associated with neurobiological changes in the brain. However, little is known whether the neural changes associated with chronic smoking persist after a long period of successful abstinence. To address this question, we examined resting state EEG (rsEEG) in chronic smokers who have been smoking for 20 years or more, past-smokers who have been successfully abstaining for 20 years or more, and never-smokers. Both current-smokers and past-smokers showed significantly decreased relative theta power than never-smokers, showcasing persistent effect of smoking on the brain. Other rsEEG features in alpha frequency band demonstrated distinctive patterns associated with active smoking, such that compared to never-smokers, only current-smokers, but not past-smokers, showed significantly higher relative power, EEG reactivity-power changes between eyes-closed and eyes-open conditions-, and coherence between channels. Furthermore, individual variabilities across these rsEEG biomarkers were accounted for by individuals' self-reported smoking history and nicotine dependence in current- and past- smokers. These data suggest the persistent effect of smoking on the brain even after sustained remission for 20 years.

Increased resting-state alpha coherence and impaired inhibition control in young smokers

Exposure to nicotine is the first cause of entirely preventable death killing, which is commonly initiated in adolescence. Previous studies revealed the changes of electroencephalography (EEG) and inhibition control in smokers. However, little is known about the specific link between alpha coherence during the resting state and inhibition control ability in young smokers. The present study aimed to investigate inter-hemispherical and frontal-parietal alpha coherence changes and assessed the relationships between alpha coherence and inhibition control in young smokers. We collected resting-state EEG data from 23 young smokers and 24 healthy controls. Inhibition control ability was assessed by a Go/NoGo task. Compared to healthy controls, young smokers exhibited increased inter-hemispherical and frontal-parietal alpha coherence. Furthermore, young smokers committed more NoGo errors in the Go/NogGo task. It is noteworthy that alpha coherence at the frontal electrode sites was positively correlated with NoGo errors in healthy controls, whereas inverse correlations were observed in young smokers. Our findings suggested that alterations of alpha coherence may provide support to the earlier nicotine-dependence-related research findings, which may help us to understand the neuropathology of inhibitory control in young smokers.

Comparison of frontostriatal circuits in adolescent nicotine addiction and internet gaming disorder

BACKGROUND

Recently, there has been significantly increased participation in online gaming and other addictive behaviors particularly in adolescents. Tendencies to avoid social interaction and become more involved in technology-based activities pose the danger of creating unhealthy addictions. Thus, the presence of relatively immature cognitive control and high risk-taking properties makes adolescence a period of major changes leading to an increased rate of emotional disorders and addiction.

AIMS

The critical roles of frontostriatal circuits in addiction have become the primary focus associated with reward in the striatum and cognitive control in the PFC. Internet gaming disorder (IGD) and nicotine addiction are currently becoming more and more serious.

METHODS

In the light of neuroimaging, the similarity between brain mechanisms causing substance use disorder (SUD) and IGD have been described in previous literature.

RESULTS

In particular, two distinct brain systems affect the way we act accounting for uncharacteristic neural function in addiction: the affective system comprises of the striatum driven by emotional, reward-related, and internal stimuli, and a cognitive system consisting of the prefrontal cortex (PFC) supporting the ventral affective system's actions via inhibitory control.

DISCUSSION AND CONCLUSION

Therefore, as a novel concept, we focused on the implication of frontostriatal circuits in nicotine addiction and IGD by reviewing the main findings from our studies compared to those of others. We hope that all of these neuroimaging findings can lead to effective intervention and treatment for addiction especially during this critical period.

Altered resting-state electroencephalography microstate characteristics in young male smokers

The development of nicotine addiction was associated with the abnormalities of intrinsic functional networks during the resting state in young adult smokers. As a whole-brain imaging approach, EEG microstate analysis treated multichannel EEG recordings as a series of quasi-steady microscopic states which were related to the resting-state networks (RSNs) found by fMRI. The aim of this study was to examine whether the resting-state EEG microstate analysis may provide novel insights into the abnormal temporal properties of intrinsic brain activities in young smokers. We used 64-channel resting-state EEG datasets to investigate alterations in microstate characteristics between twenty-five young smokers and 25 age- and gender-matched non-smoking controls. Four classic EEG microstates (microstate A, B, C, and D) were obtained, and the four temporal parameters of each microstate were extracted, i.e., duration, occurrence, coverage, and transition probabilities. Compared with non-smoking controls, young smokers showed decreased occurrence of microstate C and increased duration of microstate D. Furthermore, both the duration and coverage of microstate D were significantly negatively correlated with Fagerstrom Test of Nicotine Dependence (FTND) in young smoker group. The complex changes in the microstate time-domain parameters might correspond to the abnormalities of RSNs in analyses of FC measured with fMRI in the previous studies and indicate the altered specific brain functions in young smokers. Microstate D could be potentially represented as a selective biomarker for predicting the dependence degree of adolescent smokers on cigarettes. These results suggested that EEG microstate analysis might detect the deviant functions of large-scale cortical activities in young smokers and provide a new perspective for the study of brain networks of adolescent smokers.