Suche

Yogic breathing techniques are fundamental to the physical and mental practice of yoga. They are closely connected to meditation, which involves the observation of breath. There are many yogic techniques based on the active regulation of the breath. Breathing practices influence many processes in the body, e.g. heart rate variability, and the mind, e.g. relaxation and stress, through their impact on the autonomic nervous system. This study intended to investigate differential effects of four yogic breathing techniques: (1) ujjayi—relaxation through slowing down the breath, (2) paced breathing—enhancement of concentration by following a precise protocol of slowdown breathing, (3) kapalabhati—raising wakefulness by mild hyperventilation, and (4) alternate nostril breathing—balancing the autonomic nervous system by alternating breath between the two nostrils. This study was conducted on 36 participants, who learned each technique within two weeks of an eight-week program and practiced them daily. After each technique, mindfulness, perceived stress, and physical well-being were assessed based on questionnaires. Ujjayi breathing, showed a relaxing effect, reduced stress, increased peacefulness, and the feeling of being at ease/leisure. Paced breathing resulted in a greater awareness of inner experiences. Kapalabhati showed a significant increase in vitality and joy of life, and alternate nostril breathing showed no hypothesis-compliant changes. The findings of this study suggest several beneficial and differential effects of these breathing techniques; therefore, they could be employed as tools for self-regulation in therapeutic contexts.

Meditation is an umbrella term for a vast range of contemplative practices. Former proposals have struggled to do justice to this variety. To our knowledge, there is to date no comprehensive overview of meditation techniques spanning all major traditions. The present studies aimed at providing such a comprehensive list of meditation techniques.

A Ganzfeld is a homogenized visual and auditory perceptual field which can induce altered states of consciousness (ASC; Metzger, 1929; Schmidt & Prein, 2019). Using a balanced intrasubject design, we compared participants' experience during two differently colored (red, green) 25-min Ganzfeld sessions with brown noise as acoustic stimulation. Participants were exposed to the colored visual field through commercially available goggles and to brown noise over headphones. We selected 67 participants with some prior meditation experience to increase the probability that they would engage meaningfully with this specifically restricted stimulus situation. We tested the functional components of the standard cognitive model of time perception (Zakay & Block, 1997) in a path analysis for direct (red vs. green light) and indirect effects (arousal, attention) on subjective duration and perceived passage of time. Subjective arousal and valence states were measured using the Self-Assessment Manikin (SAM). The amount of attention directed to time and the perceived passage of time were rated with standard visual analog scales (VAS). Participants also estimated the duration of each Ganzfeld exposure. The session with the red visual field lasted significantly longer than did the green session (μ(red) = 23.1 min; μ(green) = 19.8 min). After the green session, participants rated their arousal level to have significantly decreased; after the red session, individuals on average felt emotionally less positive. Multiple path analyses revealed that the effect of color on estimated duration is completely mediated through higher arousal levels during the red Ganzfeld session. In turn, the higher arousal level generates a longer subjective estimate of duration. For induction of relaxation in studies probing altered states of consciousness employing the Ganzfeld technique, we recommend using the green light.

There is lack of research on effects of red wine on consciousness when drank in wine bars designed to enhance the pleasurableness of the wine drinking experience. Effects of a moderate dose of red wine (≈ 40.98 g of ethanol) on consciousness were examined in a naturalistic study taking place in a wine bar located in one of the most touristic areas of Lisbon, Portugal. One hundred two participants drank in one of three conditions: alone, in dyad, or in groups up to six people. Red wine increased pleasure and arousal, decreased the awareness of time, slowed the subjective passage of time, increased the attentional focus on the present moment, decreased body awareness, slowed thought speed, turned imagination more vivid, and made the environment become more fascinating. Red wine increased insightfulness and originality of thoughts, increased sensations of oneness with the environment, spiritual feelings, all-encompassing love, and profound peace. All changes in consciousness occurred regardless of volunteers drinking alone, in dyad or in group. Men and women did not report different changes in consciousness. Older age correlated with greater increases in pleasure. Younger age correlated with greater increases in fascination with the environment of the wine bar. Drinking wine in a contemporaneous Western environment designed to enhance the pleasurableness of the wine drinking experience may trigger changes in consciousness commonly associated with mystical-type states.

Background: The retina has gained increasing attention in non-ophthalmological research in recent years. The pattern electroretinogram (PERG), a method to evaluate retinal ganglion cell function, has been used to identify objective correlates of the essentially subjective state of depression. A reduction in the PERG contrast gain was demonstrated in patients with depression compared to healthy controls with normalization after remission. PERG responses are not only modulated by stimulus contrast, but also by check size and stimulation frequency. Therefore, the rationale was to evaluate potentially more feasible procedures for PERG recordings in daily diagnostics in psychiatry. Methods: Twenty-four participants (12 patients with major depression (MDD) and 12 age- and sex-matched healthy controls) were examined in this pilot study. We investigated PERG amplitudes for two steady-state pattern reversal frequencies (12.5/18.75 rps) and four sizes of a checkerboard stimulus (0.8°, 1.6°, 3.2°, and 16°) to optimize the PERG recordings in MDD patients. Results: Smaller PERG amplitudes in MDD patients were observed for all parameters, whereby the extent of the reduction appeared to be stimulus-specific. The most pronounced decline in the PERG of MDD patients was observed at the higher stimulation frequency and the finest pattern, whilst responses for the largest check size were less affected. Following the PERG ratio protocol for early glaucoma, where similar stimulus dependent modulations have been reported, we calculated PERG ratios (0.8°/16°) for all participants. At the higher frequency (18.75 rps), significantly reduced ratios were observed in MDD patients. Conclusion: The "normalization" of the PERG responses-via building a ratio-appears to be a very promising approach with regard to the development of an objective biomarker of the depressive state, facilitating inter-individual assessments of PERG recordings in patients with psychiatric disorders.

The electroencephalography (EEG) is a well-established non-invasive method in neuroscientific research and clinical diagnostics. It provides a high temporal but low spatial resolution of brain activity. To gain insight about the spatial dynamics of the EEG, one has to solve the inverse problem, i.e., finding the neural sources that give rise to the recorded EEG activity. The inverse problem is ill-posed, which means that more than one configuration of neural sources can evoke one and the same distribution of EEG activity on the scalp. Artificial neural networks have been previously used successfully to find either one or two dipole sources. These approaches, however, have never solved the inverse problem in a distributed dipole model with more than two dipole sources. We present ConvDip, a novel convolutional neural network (CNN) architecture, that solves the EEG inverse problem in a distributed dipole model based on simulated EEG data. We show that (1) ConvDip learned to produce inverse solutions from a single time point of EEG data and (2) outperforms state-of-the-art methods on all focused performance measures. (3) It is more flexible when dealing with varying number of sources, produces less ghost sources and misses less real sources than the comparison methods. It produces plausible inverse solutions for real EEG recordings from human participants. (4) The trained network needs <40 ms for a single prediction. Our results qualify ConvDip as an efficient and easy-to-apply novel method for source localization in EEG data, with high relevance for clinical applications, e.g., in epileptology and real-time applications.