EEG Spectral Changes Before and After an Eight-week Intervention Period of Preksha Meditation
Chintan Joshi
November 10, 2016 DOI: 10.25148/etd.fidc001244 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Pre-post intervention study |
|---|---|
| Sample size | 13 |
| Population | Novice meditators |
| Intervention | Preksha meditation |
| Duration | 8-week intervention, 3 sessions per week |
| Topics | Meditation |
| Keywords | Electroencephalography Audiology Pattern recognition psychology Artificial intelligence Cognitive psychology Clinical psychology |
| Citations | 1 |
| Key points | A support vector machine algorithm could not discriminate between different forms of Preksha meditation based on EEG spectral power, with classification accuracy of only 6-12%. |
Abstract
Various types of meditation techniques, primarily categorized into concentrative and mindfulness meditation, have evolved over the years to enhance the physiological and psychological well-being of people in all walks of life. However, the scientific knowledge of the impact of meditation on physiological and psychological well-being is very limited. Electroencephalography (EEG) was used to study the effect of a sequence of different forms of Preksha meditation on brain activity. EEG data from 13 novice participants (10 females, 3 males; Age: 19-49 yrs) were collected while meditating for the first time (pre) and at the end of an eight week (post) intervention period (3 meditation sessions/week). EEG spectral power densities were calculated in delta (1-4Hz), theta (4-8Hz), alpha (8-13Hz), beta (13-40Hz) and gamma (40-100Hz) bands. A Support vector machine algorithm based on the radial basis function kernel was used to classify different forms of Preksha meditation. The SVM classification was able to differentiate the brain activity amongst the forms of Preksha meditation with 6-12% accuracy only. These accuracies are extremely low and the classification was not able to discriminate between different forms of meditation within a session. It is therefore concluded, that the format of Preksha meditation utilized did not elicit clear changes in EEG, discernable using the SVM algorithm.
Comparable studies
Other non-randomized and open-label trials on meditation, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Mindfulness-Based Stress Reduction in Relation to Quality of Life, Mood, Symptoms of Stress, and Immune Parameters in Breast and Prostate Cancer Outpatients Early-stage breast and prostate cancer patients | 2003 | Pre-post intervention study | n = 59 |
| Exploring self‐compassion and empathy in the context of mindfulness‐based stress reduction (MBSR) Community sample | 2010 | Pre-post intervention study | |
| Mindfulness-Based Stress Reduction Lowers Psychological Distress In Medical Students Second-year medical students | 2003 | Prospective nonrandomized cohort-controlled study | n = 302 |
| Intensive meditation training, immune cell telomerase activity, and psychological mediators. Retreat participants and matched controls | 2011 | Controlled trial with wait-list control group | n = 60 |
| The Effectiveness of Mindfulness Training for Children with ADHD and Mindful Parenting for their Parents Children aged 8-12 with ADHD and their parents | 2011 | Within-group waitlist controlled trial | n = 22 |
Citations in the library
Cites 18
- Alterations in Brain and Immune Function Produced by Mindfulness Meditation Psychosomatic Medicine July 1, 2003
- Meditation experience is associated with increased cortical thickness Neuroreport November 7, 2005
- Long-term meditators self-induce high-amplitude gamma synchrony during mental practice Proceedings of the National Academy of Sciences November 8, 2004
- Mindfulness Training Improves Working Memory Capacity and GRE Performance While Reducing Mind Wandering Psychological Science March 28, 2013
- The psychological effects of meditation: A meta-analysis. Psychological Bulletin May 14, 2012
and 13 more in the library