Low-Theta Electroencephalography Coherence Predicts Cigarette Craving in Nicotine Addiction

Effects of brief mindfulness training on smoking cue-reactivity in tobacco use disorder: Study protocol for a randomized controlled trial

BACKGROUND

The prevalence of Tobacco Use Disorder (TUD) represents a significant and pressing global public health concern, with far-reaching and deleterious consequences for individuals, communities, and healthcare systems. The craving caused by smoking cue is an important trigger for relapse, fundamentally hindering the cessation of cigarette smoking. Mindfulness interventions focusing on cue-reactivity was effective for the treatment of related dependence. Brief mindfulness training (BMT) meets the short-term needs for intervention but the effects still need to be examined. The objective of the present study is to investigate the impact of BMT intervention on smoking cue-reactivity among Chinese college students with TUD, to uncover the dynamic models of brain function involved in this process.

METHOD

A randomized control trial (RCT) based on electroencephalography (EEG) was designed. We aim to recruit 90 participants and randomly assign to the BMT and control group (CON) with 1:1 ratio. A brief mindfulness training will be administered to experimental group. After the intervention, data collection will be conducted in the follow-up stage with 5 timepoints of assessments. EEG data will be recorded during the smoking cue-reactivity task and 'STOP' brief mindfulness task. The primary outcomes include subjective reports of smoking craving, changes in EEG indicators, and mindfulness measures. The secondary outcomes will be daily smoking behaviours, affect and impulsivity, as well as indicators reflecting correlation between mindfulness and smoking cue-reactivity. To evaluate the impact of mindfulness training, a series of linear mixed-effects models will be employed. Specifically, within-group effects will be examined by analysing the longitudinal data. Additionally, the effect size for all statistical measurements will be reported, offering a comprehensive view of the observed effects.

DISCUSSION

The current study aims to assess the impact of brief mindfulness-based intervention on smoking cue-reactivity in TUD. It also expected to enhance our understanding of the underlying processes involved in brain function and explore potential EEG biomarkers at multiple time points.

TRIAL REGISTRATION

Trial registration number: ChiCTR2300069363, registered on 14 March 2023. Protocol Version 1.0., 10 April 2023.

Changes in distinct brain systems identified with fMRI during smoking cessation treatment with varenicline: a review

BACKGROUND

Varenicline is considered one of the most effective treatment options for smoking cessation. Nonetheless, it is only modestly effective. A deeper comprehension of the effects of varenicline by means of the in-depth review of relevant fMRI studies may assist in paving the development of more targeted and effective treatments.

METHODOLOGY

A search of PubMed and Google Scholar databases was conducted with the keywords "functional magnetic resonance imaging" or "fMRI", and "varenicline". All peer-reviewed articles regarding the assessment of smokers with fMRI while undergoing treatment with varenicline and meeting the predefined criteria were included.

RESULTS

Several studies utilizing different methodologies and targeting different aspects of brain function were identified. During nicotine withdrawal, decreased mesocorticolimbic activity and increased amygdala activity, as well as elevated amygdala-insula and insula-default-mode-network functional connectivity are alleviated by varenicline under specific testing conditions. However, other nicotine withdrawal-induced changes, including the decreased reward responsivity of the ventral striatum, the bilateral dorsal striatum and the anterior cingulate cortex are not influenced by varenicline suggesting a task-dependent divergence in neurocircuitry activation. Under satiety, varenicline treatment is associated with diminished cue-induced activation of the ventral striatum and medial orbitofrontal cortex concomitant with reduced cravings; during the resting state, varenicline induces activation of the lateral orbitofrontal cortex and suppression of the right amygdala.

CONCLUSIONS

The current review provides important clues with regard to the neurobiological mechanism of action of varenicline and highlights promising research opportunities regarding the development of more selective and effective treatments and predictive biomarkers for treatment efficacy.

Cue-reactivity targeted smoking cessation intervention in individuals with tobacco use disorder: a scoping review

Objectives

Cue-reactivity is a critical step leading to the emergence of addictive psychology and the triggering of addictive behaviors within the framework of addiction theory and is considered a significant risk factor for addiction-related behaviors. However, the effect of cue-reactivity targeted smoking cessation intervention and the cue-reactivity paradigms used in the randomized controlled trials varies, which introduces more heterogeneity and makes a side-by-side comparison of cessation responses difficult. Therefore, the scoping review aims to integrate existing research and identify evidence gaps.

Methods

We searched databases in English (PubMed and Embase) and Chinese (CNKI and Wanfang) using terms synonymous with 'cue' and 'tobacco use disorder (TUD)' to April 2023, and via hand-searching and reference screening of included studies. Studies were included if they were randomized controlled trials taking cue-reactivity as an indicator for tobacco use disorder (TUD) defined by different kinds of criteria.

Results

Data were extracted on each study's country, population, methods, timeframes, outcomes, cue-reactivity paradigms, and so on. Of the 2,944 literature were retrieved, 201 studies met the criteria and were selected for full-text screening. Finally, 67 pieces of literature were selected for inclusion and data extraction. The results mainly revealed that non-invasive brain stimulation and exercise therapy showed a trend of greater possibility in reducing subjective craving compared to the remaining therapies, despite variations in the number of research studies conducted in each category. And cue-reactivity paradigms vary in materials and mainly fall into two main categories: behaviorally induced craving paradigm or visually induced craving paradigm.

Conclusion

The current studies are still inadequate in terms of comparability due to their heterogeneity, cue-reactivity can be conducted in the future by constructing a standard library of smoking cue materials. Causal analysis is suggested in order to adequately screen for causes of addiction persistence, and further explore the specific objective cue-reactivity-related indicators of TUD.

Targeting electroencephalography for alcohol dependence: A narrative review

BACKGROUND

Electroencephalography (EEG)-based electrophysiological techniques have made progress in diagnosing and treating alcohol dependence in recent years.

AIMS

The article reviews the latest literature in this field.

MATERIALS AND METHODS

Alcohol dependence, which is common and prone to relapsing, poses a serious threat to individuals, families, and society. At present, the objective detection methods for alcohol dependence in clinic are not enough. As electrophysiological techniques developed in psychiatry, some researches on EEG-based monitoring methods are of great significance in the diagnosis and treatment of alcohol dependence.

DISCUSSION

As electrophysiological techniques developed in psychiatry, some researches on EEG-based monitoring methods such as resting electroencephalography (REEG), event-related potentials (ERP), event-related oscillations (ERO), and polysomnography (PSG), was reported.

CONCLUSION

In this paper, the status of electrophysiological researches on EEG in alcoholics are reviewed in detail.

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.

Correlation between abnormal brain network activity and electroencephalogram microstates on exposure to smoking-related cues

BACKGROUND

Research into neural mechanisms underlying cue-induced cigarette craving has attracted considerable attention for its significant role in treatments. However, there is little understanding about the effects of exposure to smoking-related cues on electroencephalogram (EEG) microstates of smokers, which can reflect abnormal brain network activity in several psychiatric disorders.

AIMS

To explore whether abnormal brain network activity in smokers on exposure to smoking-related cues would be captured by EEG microstates.

METHOD

Forty smokers were exposed to smoking and neutral imagery conditions (cues) during EEG recording. Behavioural data and parameters for microstate topographies associated with the auditory (A), visual (B), salience and memory (C) and dorsal attention networks (D) were compared between conditions. Correlations between microstate parameters and cigarette craving as well as nicotine addiction characteristics were also analysed.

RESULTS

The smoking condition elicited a significant increase in the duration of microstate classes B and C and in the duration and contribution of class D compared with the neutral condition. A significant positive correlation between the increased duration of class C (smoking minus neutral) and increased craving ratings was observed, which was fully mediated by increased posterior alpha power. The increased duration and contribution of class D were both positively correlated with years of smoking.

CONCLUSIONS

Our results indicate that smokers showed abnormal EEG microstates when exposed to smoking-related cues compared with neutral cues. Importantly, microstate class C (duration) might be a biomarker of cue-induced cigarette craving, and class D (duration and contribution) might reflect the relationship between cue-elicited activation of the dorsal attention network and years of smoking.

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.

Behavioral and Brain Reactivity Associated With Drug-Related and Non-Drug-Related Emotional Stimuli in Methamphetamine Addicts

Background

Methamphetamine addicts can experience severe emotional processing disorders, with abnormal responses to emotional and drug-related stimuli. These aberrant behaviors are one of the key factors leading to relapse. Nevertheless, the characteristics of addicts’ responses to drug-related stimuli and their responses to emotional stimuli remain controversial.

Methods

52 methamphetamine addicts from China passively viewed three different categories of images: Drug-related; positive emotional; and negative emotional. In the first task, participants completed a 9-point Self-Assessment Manikin (SAM) scale, rating the valence of each image. In the second, they performed a cued-action task while electroencephalography (EEG) data were recorded.

Result

Drug-related images were rated negatively, with an average rating of 3.57. However, reaction times to drug-related stimuli were significantly faster than for negative stimuli (p = 0.030), and were indistinguishable from positive stimuli (p > 0.99). Similarly, EPN amplitudes evoked by drug-related images were significantly larger than those evoked by negative stimuli (p < 0.001), but no different than positive stimuli (p > 0.99). LPP amplitudes evoked by drug-related stimuli were significantly smaller than those evoked by negative (p < 0.001) and positive stimuli (p = 0.004).

Conclusion

Despite negative self-assessments of drug-related imagery, MA-addicts reaction times were no slower than positive reactions. Similarly, drug-related and positive imagery EPN amplitudes were indistinguishable. Together, these results suggest increased attentional resources were allocated to the processing of drug-related stimuli and the pathways responsible partially overlap with the those recruited in processing positive emotional imagery in addicts. Moreover, in the late stage of visual processing, MA-addicts showed reduced brain activity in response to drug-related stimuli, suggesting reverse inhibition in response preparation and emotional appraisal. These findings may provide a reference for clinicians treating drug-taking behavior and for the development of new models of rehabilitation therapy.

Predicting Parkinson's disease using gradient boosting decision tree models with electroencephalography signals

INTRODUCTION

Parkinson's disease (PD) is a neurodegenerative disorder with only symptomatic treatments currently available. Although correct, early diagnoses of PD are important, the existing diagnostic method based on pathologic examinations only has an accuracy of approximately 80.6%. Although electroencephalography (EEG)-based assistive technology has been introduced, it has been difficult to implement in practice due to the high computational complexity and low accuracy of the analysis methods. This study proposed a fast, accurate PD prediction method using the Hjorth parameter and the gradient boosting decision tree (GBDT) algorithm.

METHOD

We used an open EEG dataset with 41 PD patients and 41 healthy controls (HCs); EEG signals were recorded from participants at the University of New Mexico (PD: 27 vs. HC: 27) and University of Iowa (PD: 14 vs. HC: 14). We explored the analytic time segment and frequency range in which the Hjorth parameter best represents the EEG characteristics of PD patients.

RESULTS

Our best model (CatBoost-based) distinguished PD patients from controls with an accuracy of 89.3%, an area under the receiver operating characteristics curve (AUC) of 0.912, an F-score of 0.903, and an odds ratio of 115.5. These results showed that our models outperformed those of all other previous works and were even superior to previously known pathologic examination-based diagnoses with long-term follow-up (accuracy = 83.9%).

CONCLUSION

The proposed methods are expected to be utilized as an effective method for improving the diagnosis of PD.

Neuropsychophysiological Measures of Alcohol Dependence: Can We Use EEG in the Clinical Assessment?

Addiction management is complex, and it requires a bio-psycho-social perspective, that ought to consider the multiple etiological and developmental factors. Because of this, a large amount of resources has been allocated to assess the vulnerability to dependence, i.e., to identify the processes underlying the transition from substance use to dependence, as well as its course, in order to determine the key points in its prevention, treatment, and recovery. Consequently, knowledge \from neuroscience must be taken into account, which is why different initiatives have emerged with this objective, such as the "Research Domain Criteria" (RDoC), and the "Addiction Neuroclinical Assessment" (ANA). Particularly, neuropsychophysiological measures could be used as markers of cognitive and behavioral attributes or traits in alcohol dependence, and even trace clinical change. In this way, the aim of this narrative review is to provide an overview following ANA clinical framework, to the most robust findings in neuropsychophysiological changes in alcohol dependence, that underlie the main cognitive domains implicated in addiction: incentive salience, negative emotionality, and executive functioning. The most consistent results have been found in event-related potential (ERP) analysis, especially in the P3 component, that could show a wide clinical utility, mainly for the executive functions. The review also shows the usefulness of other components, implicated in affective and substance-related processing (P1, N1, or the late positive potential LPP), as well as event-related oscillations, such as theta power, with a possible use as vulnerability or clinical marker in alcohol dependence. Finally, new tools emerging from psychophysiology research, based on functional connectivity or brain graph analysis could help toward a better understanding of altered circuits in alcohol dependence, as well as communication efficiency and effort during mental operations. This review concludes with an examination of these tools as possible markers in the clinical field and discusses methodological differences, the need for more replicability studies and incipient lines of work. It also uses consistent findings in psychophysiology to draw possible treatment targets and cognitive profiles in alcohol dependence.