Aberrant Long-Range Temporal Correlations in Depression Are Attenuated after Psychological Treatment

The spontaneous oscillatory activity in the human brain shows long-range temporal correlations (LRTC) that extend over time scales of seconds to minutes. Previous research has demonstrated aberrant LRTC in depressed patients; however, it is unknown whether the neuronal dynamics normalize after psychological treatment. In this study, we recorded EEG during eyes-closed rest in depressed patients (N = 71) and healthy controls (N = 25), and investigated the temporal dynamics in depressed patients at baseline, and after attending either a brief mindfulness training or a stress reduction training. Compared to the healthy controls, depressed patients showed stronger LRTC in theta oscillations (4–7 Hz) at baseline. Following the psychological interventions both groups of patients demonstrated reduced LRTC in the theta band. The reduction of theta LRTC differed marginally between the groups, and explorative analyses of separate groups revealed noteworthy topographic differences. A positive relationship between the changes in LRTC, and changes in depressive symptoms was observed in the mindfulness group. In summary, our data show that aberrant temporal dynamics of ongoing oscillations in depressive patients are attenuated after treatment, and thus may help uncover the mechanisms with which psychotherapeutic interventions affect the brain

data

data and script

Effects of conscious connected breathing on cortical brain activity, mood and state of consciousness in healthy adults

Breathwork as a means of inducing non-ordinary states of consciousness is gaining traction as a potential therapeutic modality. We examined the effects of breathwork (in the form of connected breathing) on electroencephalography (EEG) and mood in 20 healthy participants (aged between 23 and 39 years (female = 11, Mage = 29). In addition, to compare with other means of inducing non-ordinary states of consciousness, we assessed the subjective effects of breathwork using the 11 Dimension Altered State of Consciousness questionnaire. EEG spectral power analysis of eyes closed rest recordings before and after the breathwork session showed a decrease in delta (1–4 Hz) and theta (4–8 Hz) frequencies in frontotemporal and parietal regions, respectively no changes were seen in Alpha (9–12 Hz) and Beta (12–30 Hz) bands. However, after decomposing the beta waves in Beta 1 (12–15 Hz), Beta 2 (15–20 Hz), Beta 3 (20–30 Hz), decreases in power were observed across Beta1 and Beta 2 in parietotemporal regions. Notably, the spectral power in gamma increased in experienced practitioners. Scores on the Profile of Mood States questionnaire showed a reduction in negative affect (anger, tension, confusion, and depression) and an increase in esteem. Scores on the 11D-ASC scale indicated that subjective experiences during breathwork were similar to those after medium to high doses of psilocybin, suggesting the occurrence of experiences of mystical quality. Present results indicate that breathwork changes brain activity and mood, and induces mystical experiences. These results are promising and suggest that such techniques could be useful to improve mental well-being

Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance

Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift toward the less volatile sub-critical state. To test these ideas, we recorded electroencephalography (EEG) from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that ‘resting-state criticality’ of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity

Controlling the Temporal Structure of Brain Oscillations by Focused Attention Meditation

Our focus of attention naturally fluctuates between different sources of information even when we desire to focus on a single object. Focused attention (FA) meditation is associated with greater control over this process, yet the neuronal mechanisms underlying this ability are not entirely understood. Here, we hypothesize that the capacity of attention to transiently focus and swiftly change relates to the critical dynamics emerging when neuronal systems balance at a point of instability between order and disorder. In FA meditation, however, the ability to stay focused is trained, which may be associated with a more homogeneous brain state. To test this hypothesis, we applied analytical tools from criticality theory to EEG in meditation practitioners and meditation-naïve participants from two independent labs. We show that in practitioners—but not in controls—FA meditation strongly suppressed long-range temporal correlations (LRTC) of neuronal oscillations relative to eyes-closed rest with remarkable consistency across frequency bands and scalp locations. The ability to reduce LRTC during meditation increased after one year of additional training and was associated with the subjective experience of fully engaging one's attentional resources, also known as absorption. Sustained practice also affected normal waking brain dynamics as reflected in increased LRTC during an eyes-closed rest state, indicating that brain dynamics are altered beyond the meditative state. Taken together, our findings suggest that the framework of critical brain dynamics is promising for understanding neuronal mechanisms of meditative states and, specifically, we have identified a clear electrophysiological correlate of the FA meditation state

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

Scaling behaviour in music and cortical dynamics interplay to mediate music listening pleasure

The pleasure of music listening regulates daily behaviour and promotes rehabilitation in healthcare. Human behaviour emerges from the modulation of spontaneous timely coordinated neuronal networks. Too little is known about the physical properties and neurophysiological underpinnings of music to understand its perception, its health benefit and to deploy personalized or standardized music-therapy. Prior studies revealed how macroscopic neuronal and music patterns scale with frequency according to a 1/fα relationship, where a is the scaling exponent. Here, we examine how this hallmark in music and neuronal dynamics relate to pleasure. Using electroencephalography, electrocardiography and behavioural data in healthy subjects, we show that music listening decreases the scaling exponent of neuronal activity and—in temporal areas—this change is linked to pleasure. Default-state scaling exponents of the most pleased individuals were higher and approached those found in music loudness fluctuations. Furthermore, the scaling in selective regions and timescales and the average heart rate were largely proportional to the scaling of the melody. The scaling behaviour of heartbeat and neuronal fluctuations were associated during music listening. Our results point to a 1/fresonance between brain and music and a temporal rescaling of neuronal activity in the temporal cortex as mechanisms underlying music appreciation

Results PANAS (positive affect).

<p>Results PANAS (positive affect).</p

Mood has an effect on average reaction time and reaction-time temporal structure.

<p>Participants in the negative mood condition showed worse performnce than particiapnts in the neutral (t65 = 2.07, <i>p</i> = .042) and positve mood condition (t40 = 2.39, <i>p</i> = .022). Additionally, the temporal strucutre of reaction time series differed between positive—negative (t40 = 2.53, <i>p</i> = .016), Error bars represent 95% confidence intervals.</p

A model of attention fluctuations to explain non-random fluctuations in reaction times.

<p>(A) Our model is based on the hypothesis that attention fluctuates on a spectrum from highly external to highly internal with a non-random temporal structure, shown here for a DFA exponent of 0.8. The <i>black dots</i> indicate moments that target stimuli appear in the CTET experiment, which results in (B) a reaction-time series with a similar temporal structure under the assumption that reaction times are shorter when attention is strongly focused on external as opposed to internal sources of information. (C) 1/f signal produced with simulated sampling, showed a robust estimation of underlying temporal correlation with infrequent, semi-random sampling (<i>p</i> <.00001).</p