State-trait influences of Vipassana meditation practice on P3 EEG dynamics

Intrinsic neural timescales exhibit different lengths in distinct meditation techniques

Meditation encompasses a range of practices employing diverse induction techniques, each characterized by a distinct attentional focus. In Mantra meditation, for instance, practitioners direct their attention narrowly to a given sentence that is recursively repeated, while other forms of meditation such as Shoonya meditation are induced by a wider attentional focus. Here we aimed to identify the neural underpinnings and correlates associated with this spectrum of distinct attentional foci. To accomplish this, we used EEG data to estimate the brain's intrinsic neural timescales (INTs), that is, its temporal windows of activity, by calculating the Autocorrelation Window (ACW) of the EEG signal. The autocorrelation function measures the similarity of a timeseries with a time-lagged version of itself by correlating the signal with itself on different time lags, consequently providing an estimation of INTs length. Therefore, through using the ACW metric, our objective was to explore whether there is a correspondence between the length of the brain's temporal windows of activity and the width of the attentional scope during various meditation techniques. This was performed on three groups of highly proficient practitioners belonging to different meditation traditions, as well as a meditation-naïve control group. Our results indicated that practices with a wider attentional focus, like Shoonya meditation, exhibit longer ACW durations compared to practices requiring a narrower attentional focus, such as Mantra meditation or body-scanning Vipassana meditation. Together, we demonstrated that distinct meditation techniques with varying widths of attentional foci exhibit unique durations in their brain's INTs. This may suggest that the width of the attentional scope during meditation relates and corresponds to the width of the brain's temporal windows in its neural activity. SIGNIFICANCE STATEMENT: Our research uncovered the neural mechanisms that underpin the attentional foci in various meditation techniques. We revealed that distinct meditation induction techniques, featured by their range of attentional widths, are characterized by varying lengths of intrinsic neural timescales (INTs) within the brain, as measured by the Autocorrelation Window function. This finding may bridge the gap between the width of attentional windows (subjective) and the width of the temporal windows in the brain's neural activity (objective) during different meditation techniques, offering a new understanding of how cognitive and neural processes are related to each other. This work holds significant implications, especially in the context of the increasing use of meditation in mental health and well-being interventions. By elucidating the distinct neural foundations of different meditation techniques, our research aims to pave the way for developing more tailored and effective meditation-based treatments.

A systematic review and activation likelihood estimation meta-analysis of fMRI studies on arousing or wake-promoting effects in Buddhist meditation

Conventional Buddhist texts illustrate meditation as a condition of relaxed alertness that must fend against extreme hypoarousal (sleep, drowsiness) and extreme hyperarousal (restlessness). Theoretical, neurophysiological, and neuroimaging investigations of meditation have highlighted the relaxing effects and hypoarousing without emphasizing the alertness-promoting effects. Here we performed a systematic review supported by an activation-likelihood estimate (ALE) meta-analysis in an effort to counterbalance the surfeit of scholarship emphasizing the hypoarousing and relaxing effects of different forms of Buddhist meditation. Specifically, the current systematic review-cum-meta-analytical review seeks to highlight more support for meditation's wake-promoting effects by drawing from neuroimaging research during wakefulness and meditation. In this systematic review and meta-analysis of 22 fMRI studies, we aim to highlight support for Buddhist meditation's wake-promoting or arousing effects by identifying brain regions associated with alertness during meditation. The most significant peaks were localized medial frontal gyrus (MFG) and precuneus. We failed to determine areas ostensibly common to alertness-related meditation such as the medial prefrontal cortex (mPFC), superior parietal lobule, basal ganglia, thalamus, most likely due to the relatively fewer fMRI investigations that used wakefulness-promoting meditation techniques. Also, we argue that forthcoming research on meditation, related to alertness or wakefulness, continues to adopt a multi-modal method to investigate the correlation between actual behaviors and neural networks connected to Buddhist meditation. Moreover, we recommend the implementation of fMRI paradigms on Buddhist meditation with clinically diagnosed participants to complement recent trends in psychotherapy such as mindfulness-based cognitive therapy (MBCT).

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture

Mindfulness training is associated with improvements in psychological wellbeing and cognition, yet the specific underlying neurophysiological mechanisms underpinning these changes are uncertain. This study uses a novel brain-inspired artificial neural network to investigate the effect of mindfulness training on electroencephalographic function. Participants completed a 4-tone auditory oddball task (that included targets and physically similar distractors) at three assessment time points. In Group A (n = 10), these tasks were given immediately prior to 6-week mindfulness training, immediately after training and at a 3-week follow-up; in Group B (n = 10), these were during an intervention waitlist period (3 weeks prior to training), pre-mindfulness training and post-mindfulness training. Using a spiking neural network (SNN) model, we evaluated concurrent neural patterns generated across space and time from features of electroencephalographic data capturing the neural dynamics associated with the event-related potential (ERP). This technique capitalises on the temporal dynamics of the shifts in polarity throughout the ERP and spatially across electrodes. Findings support anteriorisation of connection weights in response to distractors relative to target stimuli. Right frontal connection weights to distractors were associated with trait mindfulness (positively) and depression (inversely). Moreover, mindfulness training was associated with an increase in connection weights to targets (bilateral frontal, left frontocentral, and temporal regions only) and distractors. SNN models were superior to other machine learning methods in the classification of brain states as a function of mindfulness training. Findings suggest SNN models can provide useful information that differentiates brain states based on distinct task demands and stimuli, as well as changes in brain states as a function of psychological intervention.

Meditation, well-being and cognition in heartfulness meditators - A pilot study

Meditative practices can vary considerably in technique as well as their effects. Heartfulness is a popular meditation technique that includes in its repertoire, a unique passive form of meditation. We carried out a pilot study recruiting male heartfulness meditators (proficient n = 24, with 6-28 years of meditation experience; novice n = 24, 5 to 16 months of experience) and subsequently recruited matched controls (n = 15). We examined well-being, and carried out high-density EEG recordings to examine indices of meditation and cognition in these groups. Well-being scores were significantly higher for the proficient meditators as compared to novice and intermediate for the controls. We did not find any group differences in cognitive processing. During meditation, enhanced occipital gamma was found in proficient meditators as compared to controls. We discuss the findings from this pilot study and suggest avenues for future research.

A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram

Meditation practices, originated from ancient traditions, have increasingly received attention due to their potential benefits to mental and physical health. The scientific community invests efforts into scrutinizing and quantifying the effects of these practices, especially on the brain. There are methodological challenges in describing the neural correlates of the subjective experience of meditation. We noticed, however, that technical considerations on signal processing also don't follow standardized approaches, which may hinder generalizations. Therefore, in this article, we discuss the usage of the electroencephalogram (EEG) as a tool to study meditation experiences in healthy individuals. We describe the main EEG signal processing techniques and how they have been translated to the meditation field until April 2020. Moreover, we examine in detail the limitations/assumptions of these techniques and highlight some good practices, further discussing how technical specifications may impact the interpretation of the outcomes. By shedding light on technical features, this article contributes to more rigorous approaches to evaluate the construct of meditation.

The Effect of Meditation on Comprehension of Statements About One-Self and Others: A Pilot ERP and Behavioral Study

The main goal of this study was to examine the effect of long-term meditation practice on behavioral indicators and ERP peak characteristics during an error-recognition task, where participants were presented with emotionally negative (evoking anxiety or aggression) written sentences describing self-related or non-self-related emotional state and personality traits. In total, 200 sentences written in Russian with varying emotional coloring were presented during the task, with half of the sentences containing a grammatical error that the participants were asked to identify. The EEG was recorded in age-matched control individuals (n = 17) and two groups of Samatha meditators with relatively short- (3–5 years’ experience, n = 18) and long-term (10–30 years’ experience, n = 18) practice experience. Task performance time (TPT) and accuracy of error detection (AED) were chosen as behavioral values. Amplitude, time latency and cortical distribution of P300 and P600 peaks of ERP were used as a value of speech-related brain activity. All statistical effects of meditation were estimated, controlling for age and sex. No behavioral differences between two groups of meditators were found. General TPT was shorter for both groups of meditators compared to the control group. Non-meditators reacted significantly slower to sentences about aggression than to sentences about anxiety or non-emotional sentences, whereas no significance was found between meditator groups. Non-meditators had better AED for the sentences about one-self than for the sentences about other people, whereas the meditators did not show any significant difference. The amplitude of P300 peak in frontal and left temporal scalp regions was higher for long-term meditators in comparison with both intermediate and control groups. The latency of P300 and P600 in left frontal and temporal regions positively correlated with TPT, whereas the amplitude of P300 in these regions had a negative correlation with TPT. We demonstrate that long-term meditation practice increases the ability of an individual to process negative emotional stimuli. The differences in behavioral reactions after onset of negative information that was self-related and non-self-related, which is typical for non-meditators, disappeared due to the influence of meditation. ERP results could be interpreted as a value of increase in voluntary control over emotional state during meditational practice.