Mantra meditation (MM) is one of the simplest and most effective meditative practices suitable for both novice and skillful meditators. It has attracted a significant number of practitioners for various health benefits or for spiritual inspiration. The scope of this review article focuses on the examination of the health benefits of practicing MM without considering the motivation by spiritual rewarding or cultivation. Through the examination, we attempt to confirm and to add scientific evidence on the benefits of mental and physical health to the practitioners. We review a large number of the recent studies of MM for understanding the mechanism in yielding medical benefits and for analyzing the quantitative evidence of the trial outcomes. The review covers four important areas: stress, anxiety, hypertension, and immunity, with the hope to evoke more studies to refine the current evidence and to encourage more studies in other promising areas. Furthermore, the review gives more attention or discussion on more recent, original, and stronger studies. The discussion can include the strong or weak points of the reviewed studies. The review discovers evidence that MM can provide various degrees of beneficial effects on the four areas considered. Studies with larger participants, superior quality, and a few others are recommended to draw firm conclusions. Several promising research areas and directions are also suggested.

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Context: Functional magnetic resonance imaging (fMRI) studies on mental training techniques such as meditation have reported benefits like increased attention and concentration, better emotional regulation, as well as reduced stress and anxiety. Although several studies have examined functional activation and connectivity in long-term as well as short-term meditators from different meditation traditions, it is unclear if long-term meditation practice brings about distinct changes in network properties of brain functional connectivity that persist during task performance. Indeed, task-based functional connectivity studies of meditators are rare. Aims: This study aimed to differentiate between long-term and short-term Rajayoga meditators based on functional connectivity between regions of interest in the brain. Task-based fMRI was captured as the meditators performed an engaging task. The graph theoretical-based functional connectivity measures of task-based fMRI were calculated using CONN toolbox and were used as features to classify the two groups using Machine Learning models. Subjects and Methods: In this study, we recruited two age and sex-matched groups of Rajayoga meditators from the Brahma Kumaris tradition that differed in the duration of their meditation experience: Long-term practitioners (n = 12, mean 13,596 h) and short-term practitioners (n = 10, mean 1095 h). fMRI data were acquired as they performed an engaging task and functional connectivity metrics were calculated from this data. These metrics were used as features in training machine learning algorithms. Specifically, we used adjacency matrices generated from graph measures, global efficiency, and local efficiency, as features. We computed functional connectivity with 132 ROIs as well as 32 network ROIs. Statistical Analysis Used: Five machine learning models, such as logistic regression, SVM, decision tree, random forest, and gradient boosted tree, were trained to classify the two groups. Accuracy, precision, sensitivity, selectivity, area under the curve receiver operating characteristics curve were used as performance measures. Results: The graph measures were effective features, and tree-based algorithms such as decision tree, random forest, and gradient boosted tree yielded the best performance (test accuracy >84% with 132 ROIs) in classifying the two groups of meditators. Conclusions: Our results support the hypothesis that long-term meditative practices alter brain functional connectivity networks even in nonmeditative contexts. Further, the use of adjacency matrices from graph theoretical measures of high-dimensional fMRI data yields a promising feature set for machine learning classifiers.

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Background: Office workers who need to use a computer while maintaining a static position for prolonged periods have more chance of having low back pain (LBP). Objective: The objective of the study is to investigate the effect of yoga on stress, anxiety, depression, and spinal mobility in computer users with chronic LBP (CLBP). Materials and Methods: In this randomized control trial, eighty computer users (42.6 ± 8.45 years of age; suffering from CLBP since 5.20 ± 3.01 years; 51 males and 29 females) who use a computer for their professional work, recruited from Bengaluru, India, were randomized into two groups: yoga group (n = 40) and physical exercise group (n = 40). The yoga group practiced an integrated module comprising yoga postures and mindfulness meditation, and the physical exercise group practiced physical exercise designed for LBP (1 h/day, 3 days/week for 16 weeks). Assessments of dial-type goniometer and Depression Anxiety Stress Scale-42 were performed at baseline, after 8 weeks, and after 16 weeks. Results: Stress, anxiety, and depression scores were significantly lower in the yoga group as compared to the physical exercise group at 16 weeks (P < 0.001), whereas spinal flexion (P < 0.001), spinal extension (P < 0.001), right lateral flexion (P = 0.001), and left lateral flexion (P = 0.007) scores were significantly higher in the yoga group as compared to the physical exercise group at 16 weeks. Conclusion: Yoga is more effective in reducing stress, anxiety, and depression and improving spinal mobility in computer users with CLBP than physical exercise designed for LBP.

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Yoga is a traditional Indian way of keeping the mind and body fit, through physical postures (asanas), voluntarily regulated breathing (pranayama), meditation, and relaxation techniques. The recent pandemic has seen a huge surge in numbers of yoga practitioners, many practicing without proper guidance. This study was proposed to ease the work of such practitioners by implementing deep learning-based methods, which can estimate the correct pose performed by a practitioner. The study implemented this approach using four different deep learning architectures: EpipolarPose, OpenPose, PoseNet, and MediaPipe. These architectures were separately trained using the images obtained from S-VYASA Deemed to be University. This database had images for five commonly practiced yoga postures: tree pose, triangle pose, half-moon pose, mountain pose, and warrior pose. The use of this authentic database for training paved the way for the deployment of this model in real-time applications. The study also compared the estimation accuracy of all architectures and concluded that the MediaPipe architecture provides the best estimation accuracy.

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Background: Among a rapidly aging population, there is increased need for neuroprotective interventions promoting healthy neurological aging. Mind-body interventions, such as Kundalini yoga, are actively being explored as accessible means to encourage healthy aging. However, little remains known about the neurobiological effects of Kundalini yoga. Aims: This pilot randomized-controlled trial (RCT) examined the potential neuroprotective effects of Kundalini yoga in older adults. Methods: We conducted an RCT with 11 healthy meditation-naïve older adults. Participants were randomized to a Kundalini yoga or psychoeducation intervention. Structural magnetic resonance imaging data were obtained at baseline and 12-week follow-up. The primary outcome measure was gray matter volume of the bilateral hippocampi and bilateral posterior cingulate cortex. Results: We found significant right hippocampal volume increases specific to the Kundalini yoga group (P = 0.034, η_p² = 0.408). Conclusions: These findings provide initial neurobiological support for the neuroprotective effects of Kundalini yoga.

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Context: We employed two classification methods that characterize psycho-somatotype categorization to understand motor and cognitive performance. The Trunk Index produces three somatotypes/body type categories: ectomorphs, mesomorphs, and endomorphs, and Prakriti classifications categorizes people into three categories: Vata, Pitta, and Kapha. Comparing these two categorization methods offers insights into anthropometric measures that combine psychological and physical characteristics to account for motor and cognitive behavior. Aims: The present study examined variations in cognitive and motor performances using the two typologies – prakriti and somato body types using cross-sectional study design. Subjects and Methods: The study employed fifty-eight healthy young adults, classified into prakriti (vata, pitta, kapha) and ecto-, meso-, endo- morph body types, to examine their cognitive performance (reaction time [RT] and accuracy), and motor performance (posture stability and posture accuracy) in standing yoga postures. Statistical Analysis Used: Analysis of covariance was performed to compare the cognitive and postural performance across the three somato and prakriti types after adjusting for age and gender as covariates. Post-hoc analysis of Bonferroni was performed with the consideration of Levene's test. Partial correlations were employed to investigate the correlation between postural stability and cognitive performance measures for each of the prakriti- and somato-body types as well as between the prakriti typology (scores) and trunk index values (adjusting the effects of age and gender as control variables). A P < 0.05 was selected at the statistical significance level. SPSS 26.0 version was used for the analysis. Results: Cognitive performance was observed to vary in terms of RT across somato- and prakriti body types (P < 0.05). Postural stability and cognitive performance are positively connected only for ectomorph body types (P < 0.05). Variations in motor performance were not significant. Barring ectomorph type, no other somato- and prakriti body types showed significant relationships between postural stability and cognitive performance. Likewise, the association between the features used for prakriti classification, and the trunk index scores showed marginal significance, only for a small subset of physical features of prakriti assessment (P = 0.055) (P1). Conclusions: Comparing classifications that use psychophysical attributes might offer insights into understanding variations in measures of motor and cognitive performance in a sample of healthy individuals.

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Background: There is growing evidence and increasing interest for systemic integration of medicine (synergistic and evidence-based combination of different systems along with conventional biomedicine). The National Institute of Mental Health and Neurosciences (NIMHANS), an Institute of National Importance and a tertiary mental and neurological healthcare hospital situated in Bengaluru, India, has established one such integrative model. The present manuscript traces the history and describes the important steps followed in this integrative approach. Methodology: The NIMHANS model followed a stage-wise two-step approach: (1) First stage – Starting with Integration of Yoga: The process began more than a decade ago, with integrating yoga into a clinical department (rather than an exclusive research-based approach) of the institute which had relatively high clinical service load (For example, Department of Psychiatry in NIMHANS). Yoga was gradually formalized into academic and clinical activities (outpatient and inpatient services) by appointing a Yoga faculty with a medical background with an MD/PhD in Yoga. The research was primarily directed by the clinical observations of patients receiving yoga therapy. (2) Second stage: Adding an appropriate and compatible discipline from Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homeopathy (AYUSH) system (Ayurveda in this case): The center for yoga gradually evolved into the Department of Integrative Medicine with the appointment of faculty from the Ayurveda stream. In this model, specialists from each discipline provide clinical inputs after simultaneous consultation with the patient through systemic integration in clinical, academic, and research domains rather than mere co-location of AYUSH services with mainstream medicine. Conclusion: The NIMHANS model of integration suggests the application of yoga into mainstream clinical service as the first step toward integration. Yoga should be added as a formalized clinical discipline with systemic integration. Gradually, other feasible systems of traditional medicine from AYUSH can be integrated at a later stage in a step-by-step manner based on clinical practice and evidence.

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Context: “Surya Namaskar” (SN) may be used as a need-based short-duration aerobic activity in a confined space to establish as a substitute of an equivalent routine physical training in challenging stressful conditions. Materials and Methods: Noninvasive oxygen-kinetics metabolic responses between SN and endurance work on bicycle ergometry (BE) were compared across different phases of maximal oxygen uptake percentage (%VO_{2 max}). SN, comprising three complete rounds per min (36 beats/min of a metronome; SN consists of 12 poses per round), was performed rhythmically and continuously for 5 min to simulate an incremental BE test (25 watts/2 min at 60 rpm). Results: SN results in a significant (P < 0.05) greater increase of arteriovenous oxygen difference at 71%–80% VO_{2 max} while keeping a low respiratory exchange ratio (P < 0.01 and 0.001) at 41%–80% VO_{2 max} exercising state. Conclusions: SN could be an ideal form of aerobic exercise instead of BE.

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It is proposed that consciousness is different from awareness. Consciousness can be thought of as a dualistic, embodied, and embedded cognitive process, whereas awareness is a nondual and nonlocal process. Nonlocal awareness is the ever-present, ever-fresh, and an affective self-awareness that can be aware of itself as well as of the ongoing subject-object duality, and cognitive conscious contents. This nonlocal awareness is our default mode state. Although very few of us are aware of it due to our habitual mental preoccupation and mind-wandering. We need to relax, learn to meditate, let go of all preoccupations, and return to our default mode state of being, which is peaceful, silent, fulfilling, energetic, and ever-fresh. Then, one feels effortlessly alive and free and at home in the world. This is the essence of meditation for living a happy, peaceful, and meaningful life. The rest of the article provides details of meditative presence, yoga meditation, and mindfulness meditation with their current practice and applications. The main focus of the article is on the neurobiology of meditation, which is discussed in detail. It covers the experientially perceived mind-space including personal, peripersonal, and extrapersonal space, the concepts of mind in the Western and Eastern literature, and the neurobiological foundation in the brain stem, reticular-limbic system, forebrain including the five thalamo-cortical-basal ganglia circuits, multiple sensory modalities, integrated perception, speech production, language communication, voluntary movements, and intentional actions. The wholeness of conscious mind is expressed as bio-psycho-social-abstract/spiritual.

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Introduction: The philosophical tenets of yoga such as Ashtanga yoga (AY) and Trigunas are seldom considered while designing yoga programs for chronic diseases. This randomized control trial explored the impact of AY principle-based yoga on the anthropometric indices, personality traits, and quality of life (QoL) in abdominal obesity (AO). Materials and Methods: Sixty-two participants with AO were randomized (n = 31 in each arm) into an AY arm or general yoga (GY) arm. For 12 weeks, both the AY and the GY received the same yoga protocol; however, the AY received an additional AY-based orientation session fortnightly. Changes in waist circumference, hip circumference (HC), height, weight, body mass index (BMI), waist–hip ratio, Vedic Personality Inventory for gunas, and World Health Organization QoL-BREF were measured at baseline and at the end of 12 weeks. Results: By the end of 12 weeks, the AY arm significantly differed from the GY arm in HC (P = 0.05) and BMI scores (P = 0.03). The AY arm has shown a significant increase in the sattva guna (P < 0.001) and reduction in the rajas (P < 0.001) and tamas gunas (P = 0.03). There was a significant improvement in the physical and social QoL domain, whereas the other variables examined remained insignificant. The increase in sattva guna was negatively correlated with waist circumference (P = −0.489) and BMI (r = −0.553). Conclusion: Exposing participants to progressive AY philosophy can change the personality traits which are further associated with melioration in the determiners of AO. Future yoga programs for chronic disorders may consider including AY philosophy for substantive outcomes.

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Context: Emotion regulation (ER) is vital for well-being. Yogic personality traits, gunas, influence the expression of ER. Aims: To investigate the expression of ER based on guna-related personality traits employing explicit, implicit, and objective eye-tracking techniques. Settings and Design: Quota sampling was used, with a cross-sectional design with three groups, sattva, rajas, and tamas. Three hundred and ninety-four female students were screened and finally, 30 from sattva, 34 from rajas, and 36 from tamas were analyzed. Methods: Participants were given State and Trait Mindfulness Scales, Gita Inventory, Social Desirability Scale, state-trait anxiety inventory, Adult Attachment Scale, and Emotional Regulation Questionnaire. ER-Implicit Association Test (ER-IAT) and Eye Tracker were also used to evaluate the participants. Statistical Analysis Used: One-way repeated-measures analysis of variance was used to examine differences between sattva, rajas, and tamas. Results: Sattva group adopted a higher level of regulation strategy, ER-IAT scores were positive for sattva, negative for rajas and tamas. Mindfulness was highest and anxiety was least in sattva. In the eye tracker, within the non-emotional areas of interest (eAOI) regions of pleasant condition, and eAOI regions of unpleasant condition, sattva group had considerably higher dwell time. Pupil dilation was lowest in sattva for all the conditions, both within and outside eAOIs. Conclusions: Sattva guna was found to foster healthy ER, and other psychological attributes. Conscious cultivation of sattva is needed for healthy emotional life.

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Spinocerebellar ataxias (SCAs) comprise a large heterogeneous group of autosomal dominant cerebellar ataxias. Despite availability of various conventional treatments, reducing disability and improving the quality of life is a challenge in this condition. In the present case report, based on the clinical symptoms and site of pathology, an Ayurveda-based diagnosis of kaphavruta vayana and kaphavruta udana was considered. Therapeutic measures such as rookshana (drying therapy), vatahara (measures to pacifying vata), balya (strengthening), and brimhana (nourishing) regimens were adopted along with oral medications and specific yoga practices. The objective of the treatment was to improve stability, posture, and balance. After 10 weeks of integrative treatment, a demonstrable improvement was observed in scale for assessment and rating of ataxia Scale for the Assessment and Rating of Ataxia (SARA), fall risk, and limit of stability (using computerized dynamic posturography). Hence, an integrated Ayurveda and Yoga-based lifestyle regimen may serve as a useful adjuvant in improving fall risk and limit of stability in patients with SCAs.

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