Forest Walking and Forest Qigong Improve Cognitive Function in the Elderly

Forest Walking and Forest Qigong Improve Cognitive Function in the Elderly

 

By John M. de Castro, Ph.D.

 

“forest bathing has received increasing attention due to its health-promoting effects, including enhancing immune functions and decreasing blood pressure in hypertension patients, as well as stress relief effects.” – Genxiang Mao,

 

Modern living is stressful, perhaps, in part because it has divorced us from the natural world that our species was immersed in throughout its evolutionary history. Modern environments may be damaging to our health and well-being simply because the species did not evolve to cope with them. This suggests that returning to nature, at least occasionally, may be beneficial. Indeed, researchers are beginning to study nature walks or what the Japanese call “Forest Bathing” and their effects on our mental and physical health.

 

Mindfulness practices have been found routinely to reduce the psychological and physiological responses to stress and improve mood. People have long reported that walking in nature elevates their mood. It appears intuitively obvious that if mindfulness training occurred in a beautiful natural place, it would greatly improve the effectiveness of mindfulness practice. In fact, being in nature has been shown to improve psychological health.

 

Qigong has been practiced for thousands of years with benefits for health and longevity. Qigong training is designed to enhance function and regulate the activities of the body through regulated breathing, mindful concentration, and gentle movements. Qigong  practice has been found to be effective for an array of physical and psychological issues. Qigong has been shown to help the elderly improve attentionbalance, reducing fallsarthritiscognitive functionmemory, and reduce age related deterioration of the brain. So, it makes sense to further study the ability of Qigong training particularly when practiced in nature to improve well-being in the elderly.

 

In today’s Research News article “Psycho-Electrophysiological Benefits of Forest Therapies Focused on Qigong and Walking with Elderly Individuals.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999348/ ) Yi and colleagues recruited healthy elderly (65 years of age and older) participants and assigned them to one of 3 conditions; no-treatment control, forest walking, or forest Qigong. The forest programs were 2 hours per session twice per week for 6 weeks and included warm-up exercises, stretching, physio-cognitive play, and cool-down along with 50 minutes of either forest walking, or forest Qigong. They were measured before and after training for cognitive impairment, depression, and quality of life. They also had the electroencephalogram (EEG) and electrocardiogram (EKG) recorded. Bioimpedance was used to determine body composition and nutritional metabolism.

 

They found that in comparison to baseline and the no-treatment control condition, the forest qigong group had a significant decrease in depression while the forest walking group had a significant decrease in cognitive impairment and increase in quality of life. In the EEG, the forest walking group had significant increases in Alpha and Beta rhythm power and a significant decrease in low frequency heart rate variability after training while the control and forest qigong groups did not. In addition, the forest qigong group had a significant increase in the upper body bioimpedance phase angle while the forest walking group had a significant increase in the lower body bioimpedance phase angle.

 

Bioimpedance phase angle is an indicator of the metabolic nutrition of the muscles. So, the practice of qigong in the forest appears to increase the metabolic nutritional status of the upper body while walking in the forest appears to increase the metabolic nutritional status of the lower body. This is not surprising as qigong involves frequent arm movements while walking involves more leg movements. Low frequency heart rate variability is an indicator of sympathetic nervous system activity and its decrease in the forest walking group suggests that walking in the forest is physiologically relaxing, reducing activating sympathetic activity. Finally, EEG power is indicative of brain information processing and its increase with forest walking is indicative of an increase in information (cognitive) processing.

 

These findings are interesting and suggest that walking in the forest and qigong in the forest have different effects on elderly individuals. Where forest qigong appears to be superior for decreasing depression and upper body metabolism, forest walking appears to improve cognitive ability, lower body metabolism, and physiological relaxation. Hence qigong in the forest is superior for emotional health while walking in the forest is superior for cognitive health. This suggests that the combination of qigong and walking in the forest may produce better well-being for elderly individual.

 

So, forest walking and forest qigong improve cognitive function in the elderly.

 

Forest bathing, also known as forest therapy or shinrin-yoku in Japanese, is an evidence-based practice of connecting to nature as a way to heal.” – Credible Mind

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Yi, J., Kim, S. G., Khil, T., Shin, M., You, J. H., Jeon, S., Park, G. H., Jeong, A. Y., Lim, Y., Kim, K., Kim, J., Kang, B., Lee, J., Park, J. H., Ku, B., Choi, J., Cha, W., Lee, H. J., Shin, C., Shin, W., … Kim, J. U. (2021). Psycho-Electrophysiological Benefits of Forest Therapies Focused on Qigong and Walking with Elderly Individuals. International journal of environmental research and public health, 18(6), 3004. https://doi.org/10.3390/ijerph18063004

 

Abstract

We developed two distinct forest therapy programs (FTPs) and compared their effects on dementia prevention and related health problems for older adults. One was focused on Qigong practice in the forest (QP) and the other involved active walking in the forest (WP). Both FTPs consisted of twelve 2-h sessions over six weeks and were conducted in an urban forest. We obtained data from 25, 18, and 26 participants aged 65 years or above for the QP, WP, and control groups, respectively. Neuropsychological scores via cognition (MoCA), geriatric depression (GDS) and quality of life (EQ-5D), and electrophysiological variables (electroencephalography, bioimpedance, and heart rate variability) were measured. We analyzed the intervention effects with a generalized linear model. Compared to the control group, the WP group showed benefits in terms of neurocognition (increases in the MoCA score, and alpha and beta band power values in the electroencephalogram), sympathetic nervous activity, and bioimpedance in the lower body. On the other hand, the QP group showed alleviated depression and an increased bioimpedance phase angle in the upper body. In conclusion, both active walking and Qigong in the forest were shown to have distinctive neuropsychological and electrophysiological benefits, and both had beneficial effects in terms of preventing dementia and relieving related health problems for elderly individuals.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999348/

 

Meditation Reduces the Complexity of Brain Activity

Meditation Reduces the Complexity of Brain Activity

 

By John M. de Castro, Ph.D.

 

What happens in your brain when you meditate. . . The overall difference is that our brains stop processing information as actively as they normally would.” – Belle Beth Cooper

 

Meditation training has been shown to improve health and well-being. It has also been found to be effective for a large array of medical and psychiatric conditions, either stand-alone or in combination with more traditional therapies. There are a number of ways that meditation practices produce these benefits, including changes to the brain and physiology. One way to observe the effects of meditation on neural activity is to measure changes in the electroencephalogram (EEG), the rhythmic electrical activity that can be recorded from the scalp.

 

In today’s Research News article “Contrasting Electroencephalography-Derived Entropy and Neural Oscillations With Highly Skilled Meditators.” (See summary below or view the full text of the study at:  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8119624/ ) Young and colleagues recruited experienced meditators who engaged in six different meditation styles (shamatha, vipassana, zazen, dzogchen, tonglen, and visualization). They had on average 21,935 hours of meditation experience. The researchers then recorded the Electroencephalogram (EEG) while the meditators were thinking about their day and also during meditation practice. The EEG recordings were analyzed for entropy and their power spectra.

 

They found that tonglen and zazen meditators had the highest alpha rhythm power during meditation compared to other styles of meditation. But different styles had markedly different patterns. On the other hand, overall, with all meditation types there was a significant reduction in entropy of the brain activity during meditation.

 

The differences in the power spectrum observed with different meditation types probably reflects the different mental activity encouraged by the individual practices, On the other hand there were consistent findings with the entropy measures suggesting a common element of neural activity occurring with meditation regardless of its form.

 

Entropy of the pattern of Electroencephalogram (EEG) activity is a measure of the complexity of the activity. The reduction in entropy observed during meditation suggests that meditation is associated with a simplification of brain activity. This makes sense as during meditation attention is focused, reducing the variety of mental activity. Hence, the simplified mental experiences during meditation are reflected in a simplified neural activity.

 

So, meditation reduces the complexity of brain activity.

 

“It seems the longer you do meditation, the better your brain will be at self-regulation. You don’t have to consume as much energy at rest and you can more easily get yourself into a more relaxed state.” – Bin He

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Jacob H. Young, Martha E. Arterberry, Joshua P. Martin. Contrasting Electroencephalography-Derived Entropy and Neural Oscillations With Highly Skilled Meditators. Front Hum Neurosci. 2021; 15: 628417. Published online 2021 Apr 30. doi: 10.3389/fnhum.2021.628417

 

Abstract

Meditation is an umbrella term for a number of mental training practices designed to improve the monitoring and regulation of attention and emotion. Some forms of meditation are now being used for clinical intervention. To accompany the increased clinical interest in meditation, research investigating the neural basis of these practices is needed. A central hypothesis of contemplative neuroscience is that meditative states, which are unique on a phenomenological level, differ on a neurophysiological level. To identify the electrophysiological correlates of meditation practice, the electrical brain activity of highly skilled meditators engaging in one of six meditation styles (shamatha, vipassana, zazen, dzogchen, tonglen, and visualization) was recorded. A mind-wandering task served as a control. Lempel–Ziv complexity showed differences in nonlinear brain dynamics (entropy) during meditation compared with mind wandering, suggesting that meditation, regardless of practice, affects neural complexity. In contrast, there were no differences in power spectra at six different frequency bands, likely due to the fact that participants engaged in different meditation practices. Finally, exploratory analyses suggest neurological differences among meditation practices. These findings highlight the importance of studying the electroencephalography (EEG) correlates of different meditative practices.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8119624/

 

Improve the Brains Ability to Directly Control Computers with Mindfulness

Improve the Brains Ability to Directly Control Computers with Mindfulness

 

By John M. de Castro, Ph.D.

 

“Meditation has been widely practiced for well-being and improving health,” said He. Our work demonstrates that it can also enhance a person’s mental power for mind control, and may facilitate broad use of noninvasive brain-computer interface technology.” – Bin He

 

It has long been a dream to develop methods to allow the brain to directly alter external devices. The efforts have been focused on developing a brain-computer interface such that recorded electrical activity of the brain is interfaced with a computer allowing control of the computer by the activity. It is hypothesized that a brain computer interface might be able to provide an alternative method to control muscles in patients with severe neuromuscular diseases.

 

Brain-computer interface methods have been developed but suffer from long training times before the participant is capable of affecting the computer activity. Meditation has been shown to alter the activity of the brain. Meditation training may make the individual better at controlling their brain activity. Hence, an interesting research question is to investigate whether meditation training will improve the ability to learn to control a computer with the brain’s electrical activity.

 

In today’s Research News article “Frontolimbic alpha activity tracks intentional rest BCI control improvement through mindfulness meditation.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994299/ ) Jiang and colleagues recruited healthy adults without brain-computer interface experience and randomly assigned them to a wait-list control condition or to receive 8 weeks of Mindfulness-Based Stress Reduction (MBSR) program. After training they all participated in 6 or 10 weekly, 1-hour, brain-computer interface training sessions. Their brain electrical activity was recorded with an electroencephalogram (EEG). The electrical activity occurring in the motor cortex was connected to a computer which moved a cursor over the screen. The participants were asked to try to move the cursor left or right by imagining opening and closing the left or right hand, to move the cursor up by imagining opening and closing both hands and down by resting.

 

They found that compared to the wait-list control group the Mindfulness-Based Stress Reduction (MBSR) group had significantly greater improvement in the brain-computer interface task over sessions. They also found that the MBSR group had significantly greater alpha rhythm (8-12 hz. in the EEG) power in the frontal and limbic regions of the brain. They also found that over training there was decreased frontolimbic connectivity in the MBSR group while the wait-list control group had greater connectivity. Finally, the greater the increase in alpha rhythm power in the MBSR group, the greater the increase in the brain-computer interface task performance over sessions.

 

These results suggest that mindfulness training improves the individual’s ability to learn to control a computer with brain activity. Underlying this improved performance appears to be changes in the electrical activity of the brain at rest and during task performance. Mindfulness training is known to improve attention and reduce mind wandering. This may be how mindfulness training improves the individual’s ability to learn to control the computer with brain activity. It remains for future research to investigate this possibility.

 

So, improve the brains ability to directly control computers with mindfulness.

 

the emphasis on present-moment experience may allow expert meditators to self-regulate brain activity which could translate into enhanced [Brain-Computer Interface] control. Self-regulation supported by attentional control, emotional control, and self-awareness may additionally help users aim at a state of effortless relaxation, which has been hypothesized to improve [Brain-Computer Interface] control.” – James R. Stieger

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Jiang, H., Stieger, J., Kreitzer, M. J., Engel, S., & He, B. (2021). Frontolimbic alpha activity tracks intentional rest BCI control improvement through mindfulness meditation. Scientific reports, 11(1), 6818. https://doi.org/10.1038/s41598-021-86215-0

 

Abstract

Brain–computer interfaces (BCIs) are capable of translating human intentions into signals controlling an external device to assist patients with severe neuromuscular disorders. Prior work has demonstrated that participants with mindfulness meditation experience evince improved BCI performance, but the underlying neural mechanisms remain unclear. Here, we conducted a large-scale longitudinal intervention study by training participants in mindfulness-based stress reduction (MBSR; a standardized mind–body awareness training intervention), and investigated whether and how short-term MBSR affected sensorimotor rhythm (SMR)-based BCI performance. We hypothesize that MBSR training improves BCI performance by reducing mind wandering and enhancing self-awareness during the intentional rest BCI control, which would mainly be reflected by modulations of default-mode network and limbic network activity. We found that MBSR training significantly improved BCI performance compared to controls and these behavioral enhancements were accompanied by increased frontolimbic alpha activity (9–15 Hz) and decreased alpha connectivity among limbic network, frontoparietal network, and default-mode network. Furthermore, the modulations of frontolimbic alpha activity were positively correlated with the duration of meditation experience and the extent of BCI performance improvement. Overall, these data suggest that mindfulness allows participant to reach a state where they can modulate frontolimbic alpha power and improve BCI performance for SMR-based BCI control.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7994299/

 

Improve Attention in Older Individuals with Exercise and Mindfulness

Improve Attention in Older Individuals with Exercise and Mindfulness

 

By John M. de Castro, Ph.D.

 

“engaging in mindfulness meditation training improves the maintenance of goal-directed visuospatial attention and may be a useful strategy for counteracting cognitive decline associated with aging.” – Peter Malinowski

 

One of the primary effects of mindfulness training is an improvement in the ability to pay attention to the task at hand and ignore interfering stimuli. This is an important consequence of mindfulness training and produces improvements in thinking, reasoning, and creativity. The importance of heightened attentional ability to the individual’s ability to navigate the demands of complex modern life cannot be overstated. It helps in school, at work, in relationships, or simply driving a car. As important as attention is, it’s surprising that little is known about the mechanisms by which mindfulness improves attention

 

There is evidence that mindfulness training improves attention by altering the brain. It appears That mindfulness training increases the size, connectivity, and activity of areas of the brain that are involved in paying attention. A common method to study the activity of the nervous system is to measure the electrical signal at the scalp above brain regions. Changes in this activity are measurable with mindfulness training.

 

One method to observe attentional processing in the brain is to measure the changes in the electrical activity that occur in response to specific stimuli. These are called event-related, or evoked, potentials or ERPs. The signal following a stimulus changes over time. The fluctuations of the signal after specific periods of time are thought to measure different aspects of the nervous system’s processing of the stimulus. The N2 response in the evoked potential (ERP) is a negative going electrical response occurring between a 1 to 3 tenths of a second following the target stimulus presentation. The N2 component is thought to reflect cognitive control. The P3 response is a positive going electrical response occurring between a 3 to 6 tenths of a second following the target. The P3 component is thought to reflect attentional processing.

 

In today’s Research News article “Behavioral and ERP Correlates of Long-Term Physical and Mental Training on a Demanding Switch Task.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940199/ ) Burgos and colleagues recruited healthy adults aged 44-65 years. They were separated into groups of participants who practiced for at least 5 years either Tai Chi, Meditation, aerobic exercise, meditation and exercise, or were sedentary. The participants performed a visuospatial task switch test that required the participants to respond to the position of a dot on a screen with the same or opposite hand or to switch back and forth between the two after 2 trials. This measures executive attention. As they were performing the task the electroencephalogram (EEG) was recorded and the evoked potentials to the dot recorded.

 

They found that on the visuospatial task switch test the Tai Chi and Meditation plus exercise groups performed best, the aerobic exercise group intermediate, and the sedentary group worst. Performance was measured by the reaction times on the switch trials and also on the proportionate change in reaction times on switch trials. In the evoked potentials in the frontal and parietal cortical areas, the groups that had mental plus physical training (Tai Chi and Meditation plus exercise groups) had significantly larger N2 responses on switch trials than the meditation or exercise alone groups. They also found that the larger the N2 response the better the performance on the switch task.

 

These are interesting results. But the groups were composed of people who chose to engage in these differing activities and the groups may be composed of people who differ in other ways other than the chosen activity. It would be best in future research if random assignment and training were used. Nevertheless, the results suggest that executive attention is best in people who practice mental and physical exercises. These are superior to either alone and particularly superior to being sedentary.  It was not studied here, but the better performance in attentional ability would predict better overall performance in life and resistance to the mental decline with aging.

 

Both the performance on the task and the N2 responses reflect better executive control of attention. This means that the participants who performed both mindfulness and physical exercise improved their ability to control attention. Mindfulness practices such as Tai Chi and meditation are known to alter the brain and improve attention. But the reason why exercise supplements these benefits is unknown. It is possible that exercise isn’t responsible for improvement but that sedentariness is responsible for deterioration and exercise acts to prevent this deterioration. Nevertheless, the results are clear mindfulness plus physical activity alters the brain in such a way as to improve the individual’s ability to control attention.

 

So, improve attention in older individuals with exercise and mindfulness.

 

mindfulness may be a way to improve our cognitive control as we age by teaching us to improve our ability to focus our attention on a particular task.” – Holy Tiret

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Burgos, P. I., Cruz, G., Hawkes, T., Rojas-Sepúlveda, I., & Woollacott, M. (2021). Behavioral and ERP Correlates of Long-Term Physical and Mental Training on a Demanding Switch Task. Frontiers in psychology, 12, 569025. https://doi.org/10.3389/fpsyg.2021.569025

 

Abstract

Physical and mental training are associated with positive effects on executive functions throughout the lifespan. However, evidence of the benefits of combined physical and mental regimes over a sedentary lifestyle remain sparse. The goal of this study was to investigate potential mechanisms, from a source-resolved event-related-potential perspective, that could explain how practicing long-term physical and mental exercise can benefit neural processing during the execution of an attention switching task. Fifty-three healthy community volunteers who self-reported long-term practice of Tai Chi (n = 10), meditation + exercise (n = 16), simple aerobics (n = 15), or a sedentary lifestyle (n = 12), aged 47.8 ± 14.6 (SD) were included in this analysis. All participants undertook high-density electroencephalography recording during a switch paradigm. Our results indicate that people who practice physical and mental exercise perform better in a task-switching paradigm. Our analysis revealed an additive effect of the combined practice of physical and mental exercise over physical exercise only. In addition, we confirmed the participation of frontal, parietal and cingulate areas as generators of event-related-potential components (N2-like and P3-like) commonly associated to the performance of switch tasks. Particularly, the N2-like component of the parietal and frontal domains showed significantly greater amplitudes in the exercise and mental training groups compared with aerobics and sedentary groups. Furthermore, we showed better performance associated with greater N2-like amplitudes. Our multivariate analysis revealed that activity type was the most relevant factor to explain the difference between groups, with an important influence of age, and body mass index, and with small effects of educational years, cardiovascular capacity, and sex. These results suggest that chronic combined physical and mental training may confer significant benefits to executive function in normally aging adults, probably through more efficient early attentional processing. Future experimental studies are needed to confirm our results and understand the mechanisms on parieto-frontal networks that contribute to the cognitive improvement associated with practicing combined mental and aerobic exercise, while carefully controlling confounding factors, such as age and body mass index.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940199/

 

 

Meditation Improves the Ability to Interface the Brain to Computers

Meditation Improves the Ability to Interface the Brain to Computers

 

By John M. de Castro, Ph.D.

 

Brain–computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind–body awareness training (MBAT) can improve BCI learning.” – ScienceDaily

 

It has long been a dream to develop methods to allow the brain to directly alter external devices. The efforts have been focused on developing a brain-computer interface such that recorded electrical activity of the brain is interfaced with a computer allowing control of the computer by the activity. It is hypothesized that a brain computer interface might be able to provide an alternative method to control muscles in patients with severe neuromuscular diseases.

 

Brain-computer interface methods have been developed but suffer from long training times before the participant is capable of affecting the computer activity. Meditation has been shown to alter the activity of the brain. Meditation training may make the individual better at controlling their brain activity. Hence, an interesting research question is to investigate whether meditation practitioners are better able to learn to control a computer with the brain’s electrical activity.

 

In today’s Research News article “Effects of Long-Term Meditation Practices on Sensorimotor Rhythm-Based Brain-Computer Interface Learning.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858648/ ) Jiang and colleagues recruited 2 groups of healthy adults without brain-computer interface experience; one with at least two years of meditation practice and one without meditation experience. They were all measured for mindfulness. They all participated in 6 weekly, 1-hour, brain-computer interface training. Their brain electrical activity was recorded with an electroencephalogram (EEG) the electrical activity in the motor cortex was connected to a computer which moved a cursor over the screen. The participants were asked to try to move the cursor left or right by imagining opening and closing the left or right hand, to move the cursor up by imagining opening and closing both hands and down by resting.

 

They found that the meditators had significantly better performance throughout training. Improvement occurred at approximately the same rate but the meditators started off at a higher baseline. The recording of alpha rhythm power over the motor cortex increased in both groups over training. In addition, they found that the higher the level of mindfulness before training, the better the performance with the meditators having significantly higher levels of mindfulness.

 

This is an interesting study but it should be kept in mind that the meditators may be different from non-meditators in ways other than the meditation practice. Being better able to control their brain activity may be characteristic of people who choose to meditate, Nevertheless, the results demonstrate that adults can alter the electrical activity in their motor cortex by imagining opening and closing their hands and that they can learn to increase this with feedback from a moving cursor. Meditators appear to have a leg up in learning this task with being better able to control their brain activity right from the beginning. This suggests that meditation practice improves the individual’s ability to alter their brain activity making them capable of learning a brain-computer interface task faster.

 

So, meditation improves the ability to interface the brain to computers.

 

Brain–computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind–body awareness training (MBAT) can improve BCI learning.” – James Stieger

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Jiang, X., Lopez, E., Stieger, J. R., Greco, C. M., & He, B. (2021). Effects of Long-Term Meditation Practices on Sensorimotor Rhythm-Based Brain-Computer Interface Learning. Frontiers in neuroscience, 14, 584971. https://doi.org/10.3389/fnins.2020.584971

 

Abstract

Sensorimotor rhythm (SMR)-based brain–computer interfaces (BCIs) provide an alternative pathway for users to perform motor control using motor imagery. Despite the non-invasiveness, ease of use, and low cost, this kind of BCI has limitations due to long training times and BCI inefficiency—that is, the SMR BCI control paradigm may not work well on a subpopulation of users. Meditation is a mental training method to improve mindfulness and awareness and is reported to have positive effects on one’s mental state. Here, we investigated the behavioral and electrophysiological differences between experienced meditators and meditation naïve subjects in one-dimensional (1D) and two-dimensional (2D) cursor control tasks. We found numerical evidence that meditators outperformed control subjects in both tasks (1D and 2D), and there were fewer BCI inefficient subjects in the meditator group. Finally, we also explored the neurophysiological difference between the two groups and showed that the meditators had a higher resting SMR predictor, more stable resting mu rhythm, and a larger control signal contrast than controls during the task.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858648/

 

Socially Mindful Behavior is Perceived Positively and Evokes Brain Responses

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Socially Mindful Behavior is Perceived Positively and Evokes Brain Responses

 

By John M. de Castro, Ph.D.

 

“Being socially mindful is more than being polite. It’s also more than just being aware of others. It is being aware that our decisions may limit or eliminate choices for others. It refers to our focus on making decisions that recognize our shared humanity and interdependence.” – Saundra Schrock

Humans are social animals. This is a great asset for the species as the effort of the individual is amplified by cooperation. In primitive times, this cooperation was essential for survival. But in modern times it is also essential, not for survival but rather for making a living and for the happiness of the individual. Mindfulness has been found to increase prosocial emotions such as compassion, and empathy and prosocial behaviors such as altruism. So, being mindful socially is very important. But, the research on social mindfulness is in its infancy.

 

One method to observe social mindfulness processing in the brain is to measure the changes in the electrical activity that occur in response to observing socially mindful or unmindful stimuli. These are called event-related potentials or ERPs; the signal following a stimulus changes over time. The fluctuations of the signal after specific periods of time are thought to measure different aspects of the nervous system’s processing of the stimulus. The Feedback Related Negativity (FRN) response in the evoked potential (ERP) is a negative going electrical response occurring between a 2.5 to 3.0 tenths of a second following the target stimulus presentation. The FRN component is thought to be a response to negative outcomes.

 

In today’s Research News article “Social Mindfulness Shown by Individuals With Higher Status Is More Pronounced in Our Brain: ERP Evidence.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988832/ ) Lu and colleagues recruited adult participants and had them input number sequences into a computer as fast as they could. They were then told that they ranked either low, medium, of high on the task. But all participants were told that they were medium. They then engaged in a computerized social mindfulness task in which they made choices that impacted the availability of choices for another participant. If the participant chose in such a way to limit the choices of the other participant it was considered socially unmindful. Then while the participants had their electroencephalogram (EEG) recorded they were shown the responses on the social mindfulness task or socially mindful and socially unmindful trials of actors with different statuses. They were then asked to rate the actors on pleasantness and likeability, and how much they were willing to share a reward with the other.

 

They found that after observing a socially mindful choice, the participants rate the actor as significantly more pleasant and likeable and were willing to share more of the reward than after a socially unmindful choice. In addition, the Feedback Related Negativity (FRN) response in the EEG was more negative after socially mindful choices but only for moderate and high status actors. Low status actors were rated as significantly more pleasant and likeable.

 

These are interesting results but the experimental context is artificial and there is no way to determine if the results reflect what would happen in real-world contexts. But the results suggest that people respond positively to others being socially mindful. In addition, the Feedback Related Negativity (FRN) response in the EEG demonstrated that the effect of a socially mindful choice on an observer occurs very rapidly and can be detected very early in the brain. The results also suggest that the social status of the individual modulates the impact of their social mindful choices on others.

 

These results suggest that social mindfulness is an impactful factor on how we perceive others. This could tend to promote group cohesion and reward prosocial behaviors by perceiving and responding to considerate people more positively. Hence, people are drawn to socially mindful people.

 

So, socially mindful behavior is perceived positively and evokes brain responses.

 

Social mindfulness is correlated with prosocial values (i.e., valuing others’ outcomes and being willing to cooperate), but it is not the same.” – Joachim Kruger

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Lu, J., Huang, X., Liao, C., Guan, Q., Qi, X. R., & Cui, F. (2020). Social Mindfulness Shown by Individuals With Higher Status Is More Pronounced in Our Brain: ERP Evidence. Frontiers in neuroscience, 13, 1432. https://doi.org/10.3389/fnins.2019.01432

 

Abstract

“Social mindfulness” refers to being thoughtful of others and considering their needs before making decisions, and can be characterized by low-cost and subtle gestures. The present study compared the behavioral and neural responses triggered by observing others’ socially mindful/unmindful choices and how these responses were modulated by the social status of the agency. At the behavioral level, observing socially mindful choices made observers feel better, rate the actors as more likable, and behave more cooperatively than did observing socially unmindful choices. Analysis of event-related potentials in the brain revealed that compared with socially unmindful choices, mindful choices elicited more negative feedback-related negativity (FRN). Notably, while this effect of social mindfulness was only significant when the actor’s social status was medium and high, it was undetectable when the actor’s social status was low. These results demonstrate that the social mindfulness of others can be rapidly detected and processed, as reflected by FRN, even though it does not seem to receive further, more elaborate evaluation. These findings indicated that low-cost cooperative behaviors such as social mindfulness can also be detected and appreciated by our brain, which may result in better mood and more cooperative behaviors in the perceivers. Besides, the perception of social mindfulness is sensitive to important social information, such as social status.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988832/

 

Neurofeedback in Novice Meditators Can Alter Brain Activity like that Observed in Expert Meditators

Neurofeedback in Novice Meditators Can Alter Brain Activity like that Observed in Expert Meditators

 

By John M. de Castro, Ph.D.

 

Modern researchers and practitioners are finding a possible new solution to these challenges by using EEG biofeedback to increase awareness of subtle states of consciousness and speed the learning process.” – Jeff Tarrant

 

Meditation training has been shown to improve health and well-being. It has also been found to be effective for a large array of medical and psychiatric conditions, either stand-alone or in combination with more traditional therapies. As a result, meditation training has been called the third wave of therapies. But meditation can be challenging to learn and many people become discouraged and drop the practice. But modern neuroscience has developed a tool called neurofeedback that can assist the meditator in improving the meditative experience.

 

In today’s Research News article “Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344173/ ) Brandmeyer and Delorme recruited healthy meditation-naïve adults and assigned them to either a neurofeedback group or to an age and gender matched active sham control group. Training occurred over 2 weeks in 8 sessions. All participants had their electroencephalogram (EEG) recorded while performing breath focused meditation while receiving feedback as to the level of theta activity (4-6 hz.) from the frontal midline. They were instructed to try to increase the level of frontal midline theta. The neurofeedback group received feedback based upon their own brain activity while the sham group received the feedback, not from their own brain activity but from the activity of their paired experimental participant. At the beginning and end of the 8 training sessions the participants were measured for executive functioning including memory, sustained attention, and focused attention.

 

They found that the neurofeedback produced a significant progressive increase in frontal midline theta power over the 8 sessions while the sham control had none. The neurofeedback group also had a significant improvement in short-term memory while the sham group had a significant deterioration in short-term memory. While the neurofeedback group was performing the short-term memory task, they had a significant increase in gamma activity in the EEG which was absent in the sham group.

 

A strength of the present study is that the control condition was active and the participants went through the same protocol as the neurofeedback participants with the sole difference being that the neurofeedback participants received feedback on their own brain activity while the sham group did not. This is an excellent control condition that accounts for many potential sources of confounding. So, the results can be interpreted as due to the neurofeedback and not some other spurious cause.

 

High levels of midline frontal theta power in the EEG is characteristic of experienced meditators. It can be speculated that the neurofeedback procedure by increasing midline frontal theta power produce brain activity in novices similar to that produced by years of meditation training. The improved short-term memory is also observed in expert meditators. This suggests that neurofeedback may be used to rapidly improve meditation. It remains for future studies to examine whether the increased midline frontal theta power is associated with increased depth of meditation. If so, this may be a method to rapidly improve meditation in novices.

 

So, neurofeedback in novice meditators can alter brain activity like that observed in expert meditators.

 

Effective meditation practice is associated with several specific patterns of brain waves. This is one reason why neurofeedback is so effective, you can literally teach your brain to take on the right brain wave pattern for the style of meditation you are trying to practice.” – James V. Hardt

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Brandmeyer, T., & Delorme, A. (2020). Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation. Frontiers in human neuroscience, 14, 246. https://doi.org/10.3389/fnhum.2020.00246

 

Abstract

Cortical oscillations serve as an index of both sensory and cognitive processes and represent one of the most promising candidates for training and targeting the top-down mechanisms underlying executive functions. Research findings suggest that theta (θ) oscillations (3–7 Hz) recorded over frontal-midline electrodes are broadly associated with a number of higher-order cognitive processes and may serve as the mechanistic backbone for cognitive control. Frontal-midline theta (FMθ) oscillations have also been shown to inversely correlate with activity in the default mode network (DMN), a network in the brain linked to spontaneous thought processes such as mind-wandering and rumination. In line with these findings, we previously observed increased FMθ oscillations in expert meditation practitioners during reported periods of focused-attention meditation practice when compared to periods of mind-wandering. In an effort to narrow the explanatory gap by directly connecting observed neurophysiological activity in the brain to the phenomenological nature of reported experience, we designed a methodologically novel and adaptive neurofeedback protocol with the aim of modulating FMθ while having meditation novice participants implement breath-focus strategies derived from focused-attention mediation practices. Participants who received eight sessions of the adaptive FMθ-meditation neurofeedback protocol were able to significantly modulate FMθ over frontal electrodes using focused-attention meditation strategies relative to their baseline by the end of the training and demonstrated significantly faster reaction times on correct trials during the n-back working memory task assessed before and after the FMθ-meditation neurofeedback protocol. No significant differences in frontal theta activity or behavior were observed in the active control participants who received age and gender matched sham neurofeedback. These findings help lay the groundwork for the development of brain training protocols and neurofeedback applications that aim to train features of the mental states and traits associated with focused-attention meditation.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344173/

 

Improve Attention and the Brain Systems Underlying Attention with Meditation

Improve Attention and the Brain Systems Underlying Attention with Meditation

 

By John M. de Castro, Ph.D.

 

the primary outcome of meditation may be to control attention and internal state in the face of the barrage of stimuli, negative and otherwise, that we experience everyday.” – Aaron D. Nitzkin

 

One of the primary effects of mindfulness training is an improvement in the ability to pay attention to the task at hand and ignore interfering stimuli. This is an important consequence of mindfulness training and produces improvements in thinking, reasoning, and creativity. The importance of heightened attentional ability to the individual’s ability to navigate the demands of complex modern life cannot be overstated. It helps in school, at work, in relationships, or simply driving a car. As important as attention is, it’s surprising that little is known about the mechanisms by which mindfulness improves attention

 

There is evidence that mindfulness training improves attention by altering the brain. It appears That mindfulness training increases the size, connectivity, and activity of areas of the brain that are involved in paying attention. A common method to study the activity of the nervous system is to measure the electrical signal at the scalp above brain regions. Changes in this activity are measurable with mindfulness training.

 

One method to observe attentional processing in the brain is to measure the changes in the electrical activity that occur in response to specific stimuli. These are called event-related, or evoked, potentials or ERPs. The signal following a stimulus changes over time. The fluctuations of the signal after specific periods of time are thought to measure different aspects of the nervous system’s processing of the stimulus. The P3 response in the evoked potential (ERP) is a positive going electrical response occurring between a 2.5 to 5 tenths of a second following the target stimulus presentation. The P3 component is thought to reflect attentional processing.

 

In today’s Research News article “Focused attention meditation training modifies neural activity and attention: longitudinal EEG data in non-meditators.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304517/ ) Yoshida and colleagues recruited meditation-naïve college students and randomly assigned them to receive either focused meditation training or relaxation training, listening to classical music. The training occurred once a week for 30 minutes for 8 weeks. They also practiced meditation or relaxation at home for 10 minutes per day. They were measured before and after training for mindfulness. They also had brain activity measured with an electroencephalogram (EEG) before, during and after either a 5-minute meditation or relaxation and while performing an oddball task where they were asked to respond whenever a different tone the usual was presented. The evoked potentials to the tone presentations were recorded.

 

They found that in comparison to baseline and the relaxation group, the group that received focused meditation training had significantly faster reactions to the target stimuli during the oddball task. The evoked potentials to the oddball stimuli also demonstrated significantly larger P3 potentials in the meditation group. They also report that during meditation there was a significant increase in theta rhythm power in the EEG particularly in the frontal regions of the brain. They also found that only after 8 weeks of meditation training the greater the increase in theta power during meditation the smaller the increase in P3 magnitude during the oddball task.

 

These results suggest that meditation training produces an improvement in attention both behaviorally during the oddball task and also in the brain’s response to the stimuli. The results demonstrated that these changes occurred only after 8 weeks of meditation training and not after relaxation training. That mindfulness training improves attention and the P3 response in the evoked potential has been demonstrated previously.

 

Hence, meditation training in meditation-naïve college students improves attention both in the brain and in behavior. This improved attention should, although not investigated, produce improved performance in college academics. It remains for future research to investigate this hypothesis.

 

So, improve attention and the brain systems underlying attention with meditation.

 

Nondirective meditation yields more marked changes in electrical brain wave activity associated with wakeful, relaxed attention, than just resting without any specific mental technique.” – ScienceDaily

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Yoshida, K., Takeda, K., Kasai, T., Makinae, S., Murakami, Y., Hasegawa, A., & Sakai, S. (2020). Focused attention meditation training modifies neural activity and attention: longitudinal EEG data in non-meditators. Social cognitive and affective neuroscience, 15(2), 215–224. https://doi.org/10.1093/scan/nsaa020

 

Abstract

Focused attention meditation (FAM) is a basic meditation practice that cultivates attentional control and monitoring skills. Cross-sectional studies have highlighted high cognitive performance and discriminative neural activity in experienced meditators. However, a direct relationship between neural activity changes and improvement of attention caused by meditation training remains to be elucidated. To investigate this, we conducted a longitudinal study, which evaluated the results of electroencephalography (EEG) during three-stimulus oddball task, resting state and FAM before and after 8 weeks of FAM training in non-meditators. The FAM training group (n = 17) showed significantly higher P3 amplitude during the oddball task and shorter reaction time (RT) for target stimuli compared to that of the control group (n = 20). Furthermore, a significant negative correlation between F4-Oz theta band phase synchrony index (PSI) during FAM and P3 amplitude during the oddball task and a significant positive correlation between F4-Pz theta band PSI during FAM and P3 amplitude during the oddball task were observed. In contrast, these correlations were not observed in the control group. These findings provide direct evidence of the effectiveness of FAM training and contribute to our understanding of the mechanisms underpinning the effects of meditation on brain activity and cognitive performance.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304517/

 

Meditation on Different States of Consciousness Produces Different Brain Activity

Meditation on Different States of Consciousness Produces Different Brain Activity

 

By John M. de Castro, Ph.D.

 

“Meditation is just self-directed neuroplasticity. In other words, you are directing the change of your brain by inwardly and consciously directing attention in a particular way. You’re using the mind to change the brain, like a child crafting a Playdough structure.” – Liam McClintock

 

Mindfulness training has been shown to improve health and well-being. It has also been found to be effective for a large array of medical and psychiatric conditions, either stand-alone or in combination with more traditional therapies. How exactly mindfulness practices produce their benefits is unknown. It is known that meditation practice alters states of consciousness and alters brain activity.

 

It is possible to investigate the relationships between consciousness and brain activity. One way is to measure changes in the electroencephalogram (EEG), the rhythmic electrical activity that can be recorded from the scalp. The recorded activity can be separated into frequency bands. Delta activity consists of oscillations in the 0.5-3 cycles per second band. Theta activity in the EEG consists of oscillations in the 4-8 cycles per second band. Alpha activity consists of oscillations in the 8-12 cycles per second band. Beta activity consists of oscillations in the 15-25 cycles per second band while Gamma activity occurs in the 35-45 cycles per second band. Changes in these brain activities can be compared during different forms of meditation with different conscious content.

 

In today’s Research News article “Large effects of brief meditation intervention on EEG spectra in meditation novices.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649620/ ) Stapleton and colleagues recruited healthy meditation-naïve adults and had them attend a 3-day meditation training workshop where seated meditation to music was practiced 3 times per day. The participants were instructed to focus on different states (emotions, gratitude, surrendering, emotions, future events, oneness, energy, future intentions, and moving energy) during the meditations. During before, during, and after each meditation brain activity was recorded with an electroencephalogram (EEG).

 

They found that from the baseline to the end of the meditations there was a significant global increase in both Theta (4-8 hz.) and Gamma (35-45 hz.) rhythms in the EEG. These activities normally occur during information processing in the brain. They also found that different meditations produced different patterns of EEG activity. Delta activity was increased to the greatest extent by meditations on gratitude, elevated emotions, and energy. Theta activity was increased to the greatest extent by meditations on gratitude, elevated emotions, and future intention. Alpha activity was increased to the greatest extent by meditations on gratitude, oneness, and future intention. Beta activity was increased to the greatest extent by meditations on gratitude, future events, elevated emotions, and future intention. Finally, Gamma activity was increased to the greatest extent by meditations on gratitude, energy, and future intention.

 

These results suggest that different conscious content during meditation is reflected in differences in the activity of the brain in novice meditators. These understandings may be useful in identifying conscious content in real time during meditation. But these results need to be replicated in experienced meditators.

 

So, meditation on different states of consciousness produces different brain activity.

 

mindfulness . . . has come to describe a meditation-based practice whose aim is to increase one’s sense of being in the present, but it has also been used to describe a nonmeditative state in which subjects set aside their mental distractions to pay greater attention to the here and now.” – Alvin Powell

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

 

Stapleton, P., Dispenza, J., McGill, S., Sabot, D., Peach, M., & Raynor, D. (2020). Large effects of brief meditation intervention on EEG spectra in meditation novices. IBRO reports, 9, 290–301. https://doi.org/10.1016/j.ibror.2020.10.006

 

Abstract

This study investigated the impact of a brief meditation workshop on a sample of 223 novice meditators. Participants attended a three-day workshop comprising daily guided seated meditation sessions using music without vocals that focused on various emotional states and intentions (open focus). Based on the theory of integrative consciousness, it was hypothesized that altered states of consciousness would be experienced by participants during the meditation intervention as assessed using electroencephalogram (EEG). Brainwave power bands patterns were measured throughout the meditation training workshop, producing a total of 5616 EEG scans. Changes in conscious states were analysed using pre-meditation and post-meditation session measures of delta through to gamma oscillations. Results suggested the meditation intervention had large varying effects on EEG spectra (up to 50 % increase and 24 % decrease), and the speed of change from pre-meditation to post-meditation state of the EEG co-spectra was significant (with 0.76 probability of entering end-meditation state within the first minute). There was a main 5 % decrease in delta power (95 % HDI = [−0.07, −0.03]); a global increase in theta power of 29 % (95 % HDI = [0.27, 0.33]); a global increase of 16 % (95 % HDI = [0.13, 0.19]) in alpha power; a main effect of condition, with global beta power increasing by 17 % (95 % HDI = [0.15, 0.19]); and an 11 % increase (95 % HDI = [0.08, 0.14]) in gamma power from pre-meditation to end-meditation. Findings provided preliminary support for brief meditation in altering states of consciousness in novice meditators. Future clinical examination of meditation was recommended as an intervention for mental health conditions particularly associated with hippocampal impairments.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649620/

 

Unique Brain Activity Registers Internal Attentional States During Meditation

Unique Brain Activity Registers Internal Attentional States During Meditation

 

By John M. de Castro, Ph.D.

 

“Your brain is actually shaped by your thoughts and your behaviors. . . meditation can help boost attention and keep the brain sharp. . .  mindful breath awareness may improve attention and help curb impulsive behavior” – Grace Bullock

 

There has accumulated a large amount of research demonstrating that mindfulness has significant benefits for psychological, physical, and spiritual wellbeing. It even improves high level thinking known as executive function and emotion regulation and compassion. One of the primary effects of mindfulness training is an improvement in the ability to pay attention to the task at hand and ignore interfering stimuli. This is an important consequence of mindfulness training and produces improvements in thinking, reasoning, and creativity. The importance of heightened attentional ability to the individual’s ability to navigate the demands of complex modern life cannot be overstated. It helps in school, at work, in relationships, or simply driving a car. As important as attention is, it’s surprising that little is known about the mechanisms by which mindfulness improves attention.

 

There is evidence that mindfulness training improves attention by altering the brain. It appears That mindfulness training increases the size, connectivity, and activity of areas of the brain that are involved in paying attention. But there are various states of attention including meditation-related states: breath attention, mind wandering, and self-referential processing, and control states e.g. attention to feet and listening to ambient sounds. It is not known what changes occur in the brain during these five different modes and if they can be used to better discriminate the nature of attentional changes during meditation.

 

In today’s Research News article “Focus on the Breath: Brain Decoding Reveals Internal States of Attention During Meditation.” (See summary below or view the full text of the study at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483757/ ) Weng and colleagues recruited healthy adult meditators (at least 5 years of experience) and non-meditators. They were given a series of tasks while having their brains scanned with functional Magnetic Resonance Imaging (fMRI). They were asked for 16-50 seconds to 1) pay attention to their breath, 2) let the mind wander, 3) think about past events, 4) pay attention to their feet, and 5) pay attention to ambient sounds. The 5 conditions were repeated multiple times in random orders. They then performed a 10-minute breath following meditation followed by a repeat of the premeditation tasks. Artificial intelligence was employed to determine unique neural activity associated with each of the 5 mental states for each participant.

 

They found unique individual brain activity patterns for each participant and could reliably distinguish different individual patterns for the 5 mental states. They then used these individualized patterns in an attempt to determine mental state during the breath focused meditation. They found that the individualized patterns identified for following the breath were present a greater percentage of time than the mind wandering or self-referential states when engaging in breath focused meditation. Further they found that the greater the amount of time for each participant in the breath following brain pattern the larger the rating by the participant of their engagement with breath following.

 

This was a proof of concept study. But it successfully demonstrated that unique individual patterns of brain activity can be identified for 5 mental states. These could be reliably differentiated. It also showed that these patterns could be used to identify breath following during breath following meditation. This suggests that this method may be used to identify mental states during ongoing meditation sessions. This could be a powerful research tool for future investigations of the mental states occurring during meditation.

 

So, unique brain activity registers internal attentional states during meditation.

 

Mindfulness training can help change patterns of brain activity because the synapses within these attentional networks can strengthen or weaken with use. So, join a mindful meditation class or download a mindful meditation app and train your brain to get out of the default mode network and be present!” – Mclean Bolton

 

CMCS – Center for Mindfulness and Contemplative Studies

 

This and other Contemplative Studies posts are also available on Google+ https://plus.google.com/106784388191201299496/posts and on Twitter @MindfulResearch

 

Study Summary

Weng, H. Y., Lewis-Peacock, J. A., Hecht, F. M., Uncapher, M. R., Ziegler, D. A., Farb, N., Goldman, V., Skinner, S., Duncan, L. G., Chao, M. T., & Gazzaley, A. (2020). Focus on the Breath: Brain Decoding Reveals Internal States of Attention During Meditation. Frontiers in Human Neuroscience, 14, 336. https://doi.org/10.3389/fnhum.2020.00336

Abstract

Meditation practices are often used to cultivate interoception or internally-oriented attention to bodily sensations, which may improve health via cognitive and emotional regulation of bodily signals. However, it remains unclear how meditation impacts internal attention (IA) states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to: (1) learn and recognize internal attentional states relevant for meditation during a directed IA task; and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N = 16), we first used MVPA to develop single-subject brain classifiers for five modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states [i.e., meditation-related states: breath attention, mind wandering (MW), and self-referential processing, and control states: attention to feet and sounds]. Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all volumes were tested, N = 2,160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, MW, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to MW or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483757/