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Emotional working memory training reduces rumination and alters the EEG microstate in anxious individuals.

ABSTRACT: Rumination is an important etiological factor of anxiety pathology, with its mechanism related to the deficit of working memory. The current study examined whether working memory training (WM-T) and emotional working memory training (EWM-T) could reduce rumination in anxious individuals. The participants with high trait anxiety underwent 21 days of mobile applications-based WM-T (n = 34), EWM-T (n = 36) or placebo control (n = 36), with questionnaires, cognitive tasks, and resting electroencephalogram (EEG) as the pre-post-test indicators. The results revealed that two training groups obtained comparable operation span increases (WM-T: d = 0.53; EWM-T: d = 0.65), updating improvement (WM-T: d = 0.43; EWM-T: d = 0.60) and shifting improvement (WM-T: d = 0.49; EWM-T: d = 0.72). Furthermore, compared to the control group, the EWM-T showed significant self-reported rumination reduction (d = 0.69), increased inhibition ability (d = 0.72), as well as modification of resting EEG microstate C parameters (Duration C: d = 0.42, Coverage C: d = 0.39), which were closely related to rumination level (r ~ 0.4). The WM-T group also showed the potential to reduced self-reported rumination (d = 0.45), but with the absence of the observable inhibition improvement and resting EEG changes. The correlation analysis suggested that the emotional benefits of WM-T depending more on improved updating and shifting, and that of EWM-T depending more on improved inhibition ability. The advantage to add emotional distractions into general working memory training for targeting rumination related anxiety has been discussed.

SUBMITTER: Pan DN

PROVIDER: S-EPMC7689328 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Emotional working memory training reduces rumination and alters the EEG microstate in anxious individuals.

Pan Dong-Ni DN Hoid Delhii D Gu Ruo-Lei RL Li Xuebing X

NeuroImage. Clinical 20201103

Rumination is an important etiological factor of anxiety pathology, with its mechanism related to the deficit of working memory. The current study examined whether working memory training (WM-T) and emotional working memory training (EWM-T) could reduce rumination in anxious individuals. The participants with high trait anxiety underwent 21 days of mobile applications-based WM-T (n = 34), EWM-T (n = 36) or placebo control (n = 36), with questionnaires, cognitive tasks, and resting electroencepha ...[more]

PMID: 33395979

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Project description:IntroductionThe competing neurobehavioral decision systems theory conceptualizes addictive behavior, such as cigarette smoking, as arising from the imbalance between stronger impulsive relative to weaker executive decision processes. Working memory trainings may enhance executive decision processes, yet few studies have evaluated its efficacy on substance misuse, with mixed evidence. The current study is the first to evaluate the efficacy of a working memory training on cigarette smoking. We consider the moderating role of delay discounting (DD), or the preference for smaller, immediately available rewards relative to larger, delayed rewards, which has been associated with smoking onset, progression, and resumption. The investigation focuses on individuals living in high-poverty, low-resource environments due high burden of tobacco-related disease they experience.Aims and methodsThe study utilized a subset of data (N = 177 individuals who smoke) generated from a randomized clinical trial that is evaluating the efficacy of working memory training for improving health-related outcomes. Participants were randomized to complete up to 15 sessions of the active, working memory training or a control training.ResultsFindings showed that among participants who were randomized to the working memory condition, those with higher rates of baseline DD demonstrated decreases in cigarette smoking (p = .05). Conversely, individuals randomized to the control condition, who had higher rates of baseline DD exhibited increases in cigarette smoking (p = .025).ConclusionsResults suggest that DD may be an important indicator of working memory training outcomes and a possible approach for effectively targeting treatments in the future.ImplicationsDD is important indicator of working memory training outcomes on cigarette smoking. The findings suggest the possibility to effectively target treatments considering the impact of DD. Given that rates of DD tend to be higher among individuals from low-resource communities, and that computer-based working memory training programs are relatively low-cost and scalable, these findings suggest this approach may have specific utility for adults at heightened risk for cigarette use.This study was registered with ClinicalTrials.gov (Identifier NCT03501706).

Project description:EEG microstate sequence analysis quantifies properties of ongoing brain electrical activity which is known to exhibit complex dynamics across many time scales. In this report we review recent developments in quantifying microstate sequence complexity, we classify these approaches with regard to different complexity concepts, and we evaluate excess entropy as a yet unexplored quantity in microstate research. We determined the quantities entropy rate, excess entropy, Lempel-Ziv complexity (LZC), and Hurst exponents on Potts model data, a discrete statistical mechanics model with a temperature-controlled phase transition. We then applied the same techniques to EEG microstate sequences from wakefulness and non-REM sleep stages and used first-order Markov surrogate data to determine which time scales contributed to the different complexity measures. We demonstrate that entropy rate and LZC measure the Kolmogorov complexity (randomness) of microstate sequences, whereas excess entropy and Hurst exponents describe statistical complexity which attains its maximum at intermediate levels of randomness. We confirmed the equivalence of entropy rate and LZC when the LZ-76 algorithm is used, a result previously reported for neural spike train analysis (Amigó et al., Neural Comput 16:717-736, https://doi.org/10.1162/089976604322860677 , 2004). Surrogate data analyses prove that entropy-based quantities and LZC focus on short-range temporal correlations, whereas Hurst exponents include short and long time scales. Sleep data analysis reveals that deeper sleep stages are accompanied by a decrease in Kolmogorov complexity and an increase in statistical complexity. Microstate jump sequences, where duplicate states have been removed, show higher randomness, lower statistical complexity, and no long-range correlations. Regarding the practical use of these methods, we suggest that LZC can be used as an efficient entropy rate estimator that avoids the estimation of joint entropies, whereas entropy rate estimation via joint entropies has the advantage of providing excess entropy as the second parameter of the same linear fit. We conclude that metrics of statistical complexity are a useful addition to microstate analysis and address a complexity concept that is not yet covered by existing microstate algorithms while being actively explored in other areas of brain research.

Dataset Information

Emotional working memory training reduces rumination and alters the EEG microstate in anxious individuals.

Publications

Emotional working memory training reduces rumination and alters the EEG microstate in anxious individuals.

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