Evaluating Multivariate MRI Maps of Body Awareness
Status: | Recruiting |
---|---|
Healthy: | No |
Age Range: | 25 - 65 |
Updated: | 12/8/2018 |
Start Date: | June 1, 2016 |
End Date: | January 31, 2021 |
Contact: | Helen Y Weng, PhD |
Email: | Helen.Weng@ucsf.edu |
Phone: | 415-514-8445 |
Evaluating Multivariate MRI Maps of Body Awareness: A Pilot Functional Magnetic Resonance Imaging (fMRI) Study of Breath Meditation
Meditation skills, or paying attention to internal mental states, are thought to improve
people's health. This study is developing a new brain measure of meditation skills, called
the EMBODY Task, using functional magnetic resonance imaging (fMRI). The investigators are
testing whether pattern recognition methods can be applied to fMRI data to identify mental
states during meditation, including attention to the body and to thoughts. This task is being
developed in meditation practitioners and non-meditators. The goal is to understand what
people are paying attention to during meditation using brain data. The investigators
hypothesize that pattern recognition technology will be able to identify different mental
states that occur during meditation.
people's health. This study is developing a new brain measure of meditation skills, called
the EMBODY Task, using functional magnetic resonance imaging (fMRI). The investigators are
testing whether pattern recognition methods can be applied to fMRI data to identify mental
states during meditation, including attention to the body and to thoughts. This task is being
developed in meditation practitioners and non-meditators. The goal is to understand what
people are paying attention to during meditation using brain data. The investigators
hypothesize that pattern recognition technology will be able to identify different mental
states that occur during meditation.
The investigators are developing a new functional magnetic resonance imaging (fMRI) task (the
EMBODY Task) to measure mental states during meditation using pattern recognition or machine
learning technology. This task is being piloted and validated in 20 meditators and 20 control
participants, in two waves of pilot testing. Meditators will have practiced meditation for at
least the 5 years, at least 90 minutes weekly. Control participants will have little to no
meditation experience and will be age- and gender-matched to each meditator. All participants
will be MRI-compatible, healthy with no health conditions that affect breathing, have no
current psychiatric disorder, and not be taking psychotropic medications.
In the EMBODY Task, participants will be instructed to pay attention to areas of the body,
their thoughts, sounds in the scanner, and to stop paying attention, in short intervals
(16-45s). They will also meditate on their breath for 10 minutes. The investigators will
determine whether pattern recognition technology can distinguish 5 mental states, and whether
these brain patterns can be used to identify mental states during meditation. The
investigators hypothesize that all 5 mental states will be distinguished by pattern
recognition in the meditators, and potentially in the controls. Investigators also
hypothesize that meditators should pay attention to their breath longer during meditation
compared to controls.
EMBODY Task) to measure mental states during meditation using pattern recognition or machine
learning technology. This task is being piloted and validated in 20 meditators and 20 control
participants, in two waves of pilot testing. Meditators will have practiced meditation for at
least the 5 years, at least 90 minutes weekly. Control participants will have little to no
meditation experience and will be age- and gender-matched to each meditator. All participants
will be MRI-compatible, healthy with no health conditions that affect breathing, have no
current psychiatric disorder, and not be taking psychotropic medications.
In the EMBODY Task, participants will be instructed to pay attention to areas of the body,
their thoughts, sounds in the scanner, and to stop paying attention, in short intervals
(16-45s). They will also meditate on their breath for 10 minutes. The investigators will
determine whether pattern recognition technology can distinguish 5 mental states, and whether
these brain patterns can be used to identify mental states during meditation. The
investigators hypothesize that all 5 mental states will be distinguished by pattern
recognition in the meditators, and potentially in the controls. Investigators also
hypothesize that meditators should pay attention to their breath longer during meditation
compared to controls.
Inclusion Criteria:
- Healthy adults, 25-65 years of age.
- Meditators will be affiliated with meditation centers that are based in the Vipassana
tradition or Zen traditions. In the past 5 years, meditators will have a consistent
practice in mindfulness of body practices, where consistent practice is defined as
practicing for at least 90 minutes in a typical week. They will also have had at least
14 days of total silent retreat practice in the past 5 years. At least half of total
practice time as reported by the participants will be engaged in mindfulness of body
practices (e.g., breath meditation, body scan, mindfulness of emotions, mindful yoga,
walking meditation).
- Non-meditator control group. Within the past 3 years, participants will not have
engaged in regular meditation (including from courses such as Mindfulness-Based Stress
Reduction, Mindfulness-Based Cognitive Therapy, and Dialectical Behavioral Therapy),
yoga, or other mind-body practice (such as Tai Chi, Feldenkrais, sensory awareness, or
related practices), defined as more than 20 minutes of practice at least two times per
week. If there is experience with mind-body practices prior to the past 3 years, it
should not include an extended period of consistent practice (such as 20 min daily
practice for a year or more) or a period of intensive practice longer than 7 days
(e.g., 10-day silent retreat).
Exclusion Criteria:
Participants who endorse:
1. being smokers;
2. chronic or recurrent bronchial or pulmonary disease requiring medical attention;
3. having been diagnosed with sleep apnea;
4. a history of an upper or lower respiratory tract infection in the 6 weeks preceding
the study;
5. pregnancy;
6. diseases that restrain chest or abdominal breathing, such as ankylosing spondylitis,
systemic lupus, chronic abdominal pain, chronic liver or kidney diseases,
7. can not fit comfortably in the MRI scanner.
8. potentially confounding medical conditions that impact breathing (e.g.,asthma,
congestive heart failure, and emphysema that are not well-controlled), could impact
attention to the breath (e.g., chronic pain conditions that are not well-managed), or
impact neural functioning (e.g., multiple sclerosis, neurological diseases, brain
injury);
9. currently experiencing a mental health condition (e.g., anxiety, depression, panic
disorder, post-traumatic stress disorder, attention deficit and hyperactivity
disorder) or past severe mental illness such as bipolar disorder, schizophrenia, or
severe substance abuse disorder.
10. use of psychotropic medications in the past year
11. current use of medications that potentially can affect the respiratory system or the
interoceptive focus in the past week (including narcotics, benzodiazepines); if the
research assistant is unclear about a specific medication, the physician on the study
(Dr. Rick Hecht) will be asked and will decide;
12. health behaviors that could affect respiration (e.g., DSM-IV diagnosis of substance
use disorder, use of major recreational drugs in the past year—heroin, cocaine, etc.);
13. any high-level training in a field that could impact body awareness and is not
associated with mind-body practices (e.g., professional athletes or dancers, marathon
runners);
14. lack of ability to speak and read English fluently (instructions and questionnaires
will be in English only and foreign language translations will have to await future
studies);
15. For participants who consent to the fMRI study, exclusion criteria include
contra-indications for safety and data quality in the MRI scanner (see MRI screening
form): presence of ferromagnetic metal on or in the body, pregnancy, movement disorder
which prevents lying still in the scanner, claustrophobia, braces, and corrected
vision that is not within +/- 8.
We found this trial at
1
site
Click here to add this to my saved trials