Reorganization of the brain and heart rhythm during autogenic meditation
Autor: Julio Cesar Tafforelli | Publicado: 2015-01-12T06:48:00-08:00






Dae-Keun Kim,1,2&nbsp;Jyoo-Hi Rhee,3&nbsp;and&nbsp;Seung Wan Kang1,2,*










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Abstract


The underlying changes in heart coherence that are associated with reported EEG changes in response to meditation have been explored. We measured EEG and heart rate variability (HRV) before and during autogenic meditation. Fourteen subjects participated in the study. Heart coherence scores were significantly increased during meditation compared to the baseline. We found near significant decrease in high beta absolute power, increase in alpha relative power and significant increases in lower (alpha) and higher (above beta) band coherence during 3~min epochs of heart coherent meditation compared to 3~min epochs of heart non-coherence at baseline. The coherence and relative power increase in alpha band and absolute power decrease in high beta band could reflect relaxation state during the heart coherent meditation. The coherence increase in the higher (above beta) band could reflect cortico-cortical local integration and thereby affect cognitive reorganization, simultaneously with relaxation. Further research is still needed for a confirmation of heart coherence as a simple window for the meditative state.


Keywords:&nbsp;autogenic meditation, EEG, heart, coherence, relaxation, cortical reorganization



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INTRODUCTION

Integrative neurophysiological substrate for transforming human attention and emotion system during meditation process are beginning to be understood by combining both central and peripheral system, brain, and body (Braboszcz et al., 2010;&nbsp;Brankovic, 2013;Kim et al., 2013). Self-regulation of attention is major component of meditation in which practitioners focus his/her attention on a particular physical/mental object in focused attention (FA) meditation and practitioners are instructed to allow any thought, feeling, or sensation to arise in consciousness while maintaining a nonreactive awareness to what is being experienced in open monitoring (OM) meditation (Lutz et al., 2008;&nbsp;Braboszcz et al., 2010).&nbsp;

Slower respiration rate during meditation practice induces changes in cardiovascular activity that correspond to an increase in the activity of the restorative parasympathetic system (Takahashi et al., 2005;&nbsp;Wu and Lo, 2008a;&nbsp;Libby et al., 2012) or increased synchronization, or respiratory sinus arrhythmia (RSA), between the breathing cycle and the heartbeat during meditation (Cysarz and Büssing, 2005;&nbsp;Ditto et al., 2006b;Phongsuphap et al., 2008;&nbsp;Wu and Lo, 2010).



&nbsp;Exercising cognitive control involves changing expectations or judgments about emotional stimuli. In FA practices, attention is focused away from the emotional reaction or emotion is simply being observed in OM practices. In addition, the RSA or parasympathetic activity could enhance emotion regulation by bottom-up process.



The diverse effects of meditation on the body and cognitive and affective processes have been reported so for long. Regular brief mindfulness meditation practice improved electrophysiological markers of allocating efficiency and self regulation of attention (Moore et al., 2012) and depth of information processing of trained meditators was more larger than non-meditators (van Leeuwen et al., 2012).

&nbsp;Many studies revealed that meditation training not only increases brain efficiency in an attention task, but also improve emotion regulation through an attention training (Wadlinger and Isaacowitz, 2010;&nbsp;Kozasa et al., 2012). Furthermore, immune cell telomerase activity or mucosal immunity was reported to be modulated by intensive meditation training in a dose dependent fashion (Fan et al., 2010;&nbsp;Jacobs et al., 2011).



The meditation techniques are now used in clinical settings for patients suffering from emotional and attentional disorders. The practices have been adapted for clinical use based on traditional forms of meditation. Mindfulness-based stress reduction (MBSR) program is recommended as a useful method for improving mental health and reducing symptoms of stress, anxiety, and depression and also recommended in medical disease management to improve health-related quality of life.&nbsp;



Mindfulness-based cognitive therapy (MBCT) is recommended for recovered recurrently depressed patients to prevent depressive relapse (Kabat-Zinn et al., 1992;&nbsp;Fjorback et al., 2011). HRV during meditation-based emotion exposure (MBEE) session combined with high levels of RSA achieved during meditation, turned out to be an excellent index of emotion regulation capacity, which is the capacity to feel, label, and accept emotions (Fabes and Eisenberg, 1997;&nbsp;Hallings-Pott et al., 2005). Recently, mindfulness meditation-related pain relief evidence for unique brain mechanisms in the regulation of pain was also reported (Zeidan et al., 2012).



The EEG signatures of meditation tend to be fairly complex across all bands and differ, as well, with the degree of the subject’s proficiency (Cahn and Polich, 2006). Expanding the current taxonomy of meditation and defining the characteristic neurophysiological signatures of various meditation categories are still important issues in meditation research (Josipovic, 2010;&nbsp;Travis and Shear, 2010) The central observation of this study is the basic course of Autogenic meditation, in other words, Autogenic training (AT).&nbsp;



AT is a self-help relaxation technique easily practiced in daily life that consists of six standard exercises. The first exercise aims at muscular relaxation, which is achieved mainly by repeating a verbal formula to encourage heaviness. Subsequently, the concentration is focused passively on feeling warm, then calming the cardiac activity, slowed respiration, warmth in the abdominal region, and finally coolness in the head (Schultz and Luthe, 1969;&nbsp;Kanji et al., 2006).&nbsp;



AT is a simple meditation practice, easily achievable in daily life, in which focused attention and OM are both incorporated. AT was not investigated so much in the EEG context, and there was only results for one or two channel EEG setting (Dierks et al., 1989;&nbsp;Jacobs and Lubar, 1989). Therefore, EEG signatures of Autogenic meditation including power and functional connectivity, especially coherence, across all frequency band from delta to gamma throughout the brain was thoroughly explored in this study. EEG signatures in specific regions of interest, are certainly important areas for further study.

The effect of Autogenic meditation on autonomic system has also been studied a little. High trait anxiety is associated with reduced HRV and vagal tone. In comparison to mental stress, AT increased HRV and facilitated the vagal control of the heart (Miu et al., 2009). AT significantly decreased cardiac sympathetic nervous activity and significantly increased cardiac parasympathetic nervous activity (Mitani et al., 2006). However, it remains controversial whether spectral analysis of HRV is really an appropriate index for autonomic nervous activity.



Most EEG changes observed during meditation have been increased power and synchronization of alpha, theta, and gamma band activities (Travis and Shear, 2010). However, the conventional HRV index has not shown consistent findings for meditative states (Ditto et al., 2006a;&nbsp;Conrad et al., 2007;&nbsp;Phongsuphap et al., 2008;&nbsp;Wu and Lo, 2008b). It might be due to increases in RSA during slow breathing phase of meditation contributing to the sympathetic power with a range of 0.04–0.15 Hz rather than parasympathetic power of 0.15–0.4 Hz, both bandwidth defined by Task force (Task-Force, 1996;&nbsp;Eckberg, 1997;&nbsp;Heathers, 2012;&nbsp;Kim et al., 2013).

There is another piece of evidence for the peripheral physiological activity t

hat positive emotion is reflected by the novel index of the heart rate variability (HRV), especially, heart coherence (McCraty et al., 2009). The coherent pattern of heart rhythm, a sine wave-like heart rhythm oscillating at a frequency around 0.1 Hz, can be generated by sustained and self induced positive emotion, such as love, appreciation, and compassion (Bradley et al., 2010). It also facilitate higher cognitive functions. Therefore, heart coherence is expected to reflect a positive state of emotion as well as increases in RSA during the meditation.

Meditation training has been studied to understand underlying mechanism of homeostatic regulation based on independent consideration of EEG or HRV activity but has less on dependent consideration of both. Whereas the heart coherence and its dynamic correlation1&nbsp;with EEG alpha band activity was investigated in the previous study (Kim et al., 2013), we focused on Autogenic meditation induced heart coherence changes and accompanied brain activity changes, especially, electroencephalography (EEG) power and coherence in the entire bandwidth from delta to gamma band. We tried to understand the mechanisms by which both the brain and peripherals are interacting in terms of the combination of both the brain and peripheral measures and also tried to expand current taxonomy of meditation and define the neurophysiological signatures of Autogenic meditation. Thereby it would be helpful to determine which meditation styles are more appropriate or helpful to particular person, finally.

We were particularly interested in whether the level of heart coherence as a simple biofeedback training modality could be a candidate surrogate marker for predicting high quality meditative states. This type of data could be useful as research moves forward for practical questions such as whether a simple ubiquitous sensor facilitates powerful meditation as a biofeedback modality and thus, help people recover from an extreme state of homeostatic depletion.