A Brief Review of the EEG Literature on Mindfulness and Fear Extinction and its Potential Implications for Posttraumatic Stress Symptoms (PTSS)

Short-term meditation training alters brain activity and sympathetic responses at rest, but not during meditation

Although more people are engaging in meditation practices that require specialized training, few studies address the issues associated with nervous activity pattern changes brought about by such training. For beginners, it remains unclear how much practice is needed before objective physiological changes can be detected, whether or not they are similar across the novices and what are the optimal strategies to track these changes. To clarify these questions we recruited individuals with no prior meditation experience. The experimental group underwent an eight-week Taoist meditation course administered by a professional, while the control group listened to audiobooks. Both groups participated in audio-guided, 34-min long meditation sessions before and after the 8-week long intervention. Their EEG, photoplethysmogram, respiration, and skin conductance were recorded during the mediation and resting state periods. Compared to the control group, the experimental group exhibited band-specific topically organized changes of the resting state brain activity and heart rate variability associated with sympathetic system activation. Importantly, no significant changes were found during the meditation process prior and post the 8-week training in either of the groups. The absence of notable changes in CNS and ANS activity indicators during meditation sessions, for both the experimental and control groups, casts doubt on the effectiveness of wearable biofeedback devices in meditation practice. This finding redirects focus to the importance of monitoring resting state activity to evaluate progress in beginner meditators. Also, 16 h of training is not enough for forming individual objectively different strategies manifested during the meditation sessions. Our results contributed to the development of tools to objectively monitor the progress in novice meditators and the choice of the relevant monitoring strategies. According to our findings, in order to track early changes brought about by the meditation practice it is preferable to monitor brain activity outside the actual meditation sessions.

Conflict Dynamics of Post-Retrieval Extinction: A Comparative Analysis of Unconditional and Conditional Reminders Using Skin Conductance Responses and EEG

The post-retrieval extinction paradigm, rooted in reconsolidation theory, holds promise for enhancing extinction learning and addressing anxiety and trauma-related disorders. This study investigates the impact of two reminder types, mild US-reminder (US-R) and CS-reminder (CS-R), along with a no-reminder extinction, on fear recovery prevention in a categorical fear conditioning paradigm. Scalp EEG recordings during reminder and extinction processes were conducted in a three-day design. Results show that the US-R group exhibits a distinctive extinction learning pattern, characterized by a slowed-down yet successful process and pronounced theta-alpha desynchronization (source-located in the prefrontal cortex) during CS processing, followed by enhanced synchronization (source-located in the anterior cingulate) after shock cancellation in extinction trials. These neural dynamics correlate with the subtle advantage of US-R in the Day 3 recovery test, presenting faster spontaneous recovery fading and generally lower fear reinstatement responses. Conversely, the CS reminder elicits CS-specific effects in later episodic tests. The unique neural features of the US-R group suggest a larger prediction error and subsequent effortful conflict learning processes, warranting further exploration.

An 8-week compassion and mindfulness-based exposure therapy program improves posttraumatic stress symptoms

The persistence of posttraumatic stress symptoms (PTSS) can be debilitating. However, many people experiencing such symptoms may not qualify for or may not seek treatment. Potentially contributing to ongoing residual symptoms of PTSS is emotion dysregulation. Meanwhile, the research area of mindfulness and compassion has grown to imply emotion regulation as one of its underlying mechanisms; yet, its influence on emotion regulation in PTSS cohort is unknown. Here, we explored the potential effectiveness of an 8-week Compassion-oriented and Mindfulness-based Exposure Therapy (CoMET) for individuals with PTSS using a waitlist control design. A total of 28 individuals (27 females, age range = 18-39 years) participated in the study (17 CoMET; 11 waitlist control). Following CoMET, participants reported significant decreases in PTSS severity (from clinical to non-clinical levels), emotion dysregulation and experiential avoidance, as well as significant increases in mindfulness, self-compassion and quality of life. Electroencephalogram-based brain network connectivity analysis revealed an increase in alpha-band connectivity following CoMET in a network that includes the amygdala, suggesting that CoMET successfully induced changes in functional connectivity between brain regions that play a crucial role in emotion regulation. In sum, the current study demonstrated promising intervention outcomes of CoMET in effectively alleviating the symptoms of PTSS via enhanced emotion regulation.

Open monitoring meditation alters the EEG gamma coherence in experts meditators: The expert practice exhibit greater right intra-hemispheric functional coupling

AIM

This study investigated the differences in frontoparietal EEG gamma coherence between expert meditators (EM) and naïve meditators (NM).

MATERIAL AND METHODS

This is a cross-sectional study with a sample of twenty-one healthy adults divided under two groups (experts meditators vs. naive-meditators), with analyzing the intra-hemispheric coherence of frontoparietal gamma oscillations by electroencephalography during the study steps: EEG resting-state 1, during the open presence meditation practice, and EEG resting-state 2.

RESULTS

The findings demonstrated greater frontoparietal EEG coherence in gamma for experts meditators in the Fp1-P3, F4-P4, F8-P4 electrode pairs during rest 1 and rest 2 (p ≤ 0.0083). In addition, we evidenced differences in the frontoparietal EEG coherence for expert meditators in F4-P4, F8-P4 during the meditation (p ≤ 0.0083).

CONCLUSION

Our results can support evidence that the connectivity of the right frontoparietal network acts as a biomarker of the enhanced Open monitoring meditation training.

Source separation on single channel EEG: A pilot study on effect of transcranial alternating current stimulation on scalp meridian

Brain electrical stimulation has shown the capability to modulate neural activities in a variety of ways. Compared with transcranial direct current stimulation(tDCS), transcranial alternating current stimulation (tACS) may affect brain activities differently through a frequency-based mechanism. This pilot study applied tACS to the scalp following the meridian (Jingluo) of traditional Chinese medicine to explore its potential neural modulation effect. A wearable electroencephalogram (EEG) device was used to measure the frontal activity in a female participant before and after tACS longitudinally. A combined method of singular spectrum analysis (SSA)-independent components analysis (ICA) was applied to separate potential artifacts from ocular and other irrelevant sources. The results demonstrated that SSA-ICA could effectively separate signals from different sources especially the ocular artifact. EEG spectrum analysis showed that short-term tACS could increase the power of delta waves. This study has good implications for the use of tACS and SSA-ICA method for the study of brain activities. Future research is needed to refine more optimum parameters of tACS and SSA-ICA to make the evidence more solid.Clinical Relevance- tACS may influence the brain wave oscillations through the frequency-based mechanism. SSA-ICA method helps to broaden the use of wearable EEG devices for various clinical applications.

Neural Decoding of Multi-Modal Imagery Behavior Focusing on Temporal Complexity

Mental imagery behaviors of various modalities include visual, auditory, and motor behaviors. Their alterations are pathologically involved in various psychiatric disorders. Results of earlier studies suggest that imagery behaviors are correlated with the modulated activities of the respective modality-specific regions and the additional activities of supramodal imagery-related regions. Additionally, despite the availability of complexity analysis in the neuroimaging field, it has not been used for neural decoding approaches. Therefore, we sought to characterize neural oscillation related to multimodal imagery through complexity-based neural decoding. For this study, we modified existing complexity measures to characterize the time evolution of temporal complexity. We took magnetoencephalography (MEG) data of eight healthy subjects as they performed multimodal imagery and non-imagery tasks. The MEG data were decomposed into amplitude and phase of sub-band frequencies by Hilbert-Huang transform. Subsequently, we calculated the complexity values of each reconstructed time series, along with raw data and band power for comparison, and applied these results as inputs to decode visual perception (VP), visual imagery (VI), motor execution (ME), and motor imagery (MI) functions. Consequently, intra-subject decoding with the complexity yielded a characteristic sensitivity map for each task with high decoding accuracy. The map is inverted in the occipital regions between VP and VI and in the central regions between ME and MI. Additionally, replacement of the labels into two classes as imagery and non-imagery also yielded better classification performance and characteristic sensitivity with the complexity. It is particularly interesting that some subjects showed characteristic sensitivities not only in modality-specific regions, but also in supramodal regions. These analyses indicate that two-class and four-class classifications each provided better performance when using complexity than when using raw data or band power as input. When inter-subject decoding was used with the same model, characteristic sensitivity maps were also obtained, although their decoding performance was lower. Results of this study underscore the availability of complexity measures in neural decoding approaches and suggest the possibility of a modality-independent imagery-related mechanism. The use of time evolution of temporal complexity in neural decoding might extend our knowledge of the neural bases of hierarchical functions in the human brain.