

ORIGINAL ARTICLE 

Year : 2016  Volume
: 4
 Issue : 1  Page : 1623 

Efficacy of vedic mathematics and yogic breathing in school children: A pilot study
Vasant Venkatraman Shastri^{1}, Alex Hankey^{1}, Bhawna Sharma^{2}, Sanjib Patra^{3}
^{1} Division of Yoga and Physical Sciences, SVYASA University, Bengaluru, India ^{2} Department of Biology, Sri Sai Angels PU College, Chikmagalur, Karnataka, India ^{3} Division of Yoga and Life Sciences, SVYASA University, Bengaluru, India
Date of Web Publication  17Aug2017 
Correspondence Address: Vasant Venkatraman Shastri SVYASA, # 19, Eknath Bhawan, Gavipuram Circle, K.G. Nagar, Bengaluru  560 019, Karnataka India
Source of Support: None, Conflict of Interest: None  Check 
DOI: 10.4103/ijny.ijoyppp_3_16
Background: Anxiety can cause problems in examination performance, particularly mathematics. This study aimed to compare two methods of reducing math anxiety in 8^{th}–10^{th} standards, Yoga pranayama and Vedic mathematics (VM). We report a randomized controlled trial comparing effects of these on working memory, math anxiety, and cognitive flexibility. Subjects and Methods: Forty higher secondary students, resident at Sri Sai Angels School Chikkamagaluru were randomly assigned to Yogic Breathing, VM, and Jogging (JG) groups with 14, 13, and 13 children, respectively. Intervention: Children in Yoga breathing (YB) and VM groups attended 7days' workshop on Pranayama and VM, respectively. Others went JG every day. Assessments: Mathematics Anxiety Rating ScaleRevised, STROOP test, Children's Cognitive Assessment Questionnaire, and digit span test were administered pre and post the intervention. Analysis: SPSS17 was used for nonparametric prepost comparison tests (Wilcoxon) and group comparisons tests (Mann–Whitney). Results: Math anxiety decreased most in VM (−11.77 ± 10.47; P < 0.01). Others: YB (−4.08 ± 4.99; P < 0.05); JG, (−3.75 ± 16.94). Changes in cognitive flexibility and reaction to cognitive stress were VM (++9.77 ± 5; P < 0.001); YB (+5.38 ± 5.38; P < 0.01) and JG (+8.58 ± 9.91; P < 0.05). Selfdefeating cognition scores decreased in YB (−1.77 ± 1.83; P < 0.01) and VM (−1.38 ± 3.2), but not JG (+0.67 ± 1.44). Digit span scores were similar in all groups. Conclusion: VM and YB showed small improvement in cognitive skills and decrease in math anxiety compared to JG. The study suggests that a 7day VM workshop can decrease math anxiety, which might help enhance cognitive skills. Calming effects of pranayama practices are the probable cause for YB group improvements.
Keywords: Cognitive skills, math anxiety, pranayama, school children, Vedic mathematics
How to cite this article: Shastri VV, Hankey A, Sharma B, Patra S. Efficacy of vedic mathematics and yogic breathing in school children: A pilot study. Int J Yoga  Philosop Psychol Parapsychol 2016;4:1623 
How to cite this URL: Shastri VV, Hankey A, Sharma B, Patra S. Efficacy of vedic mathematics and yogic breathing in school children: A pilot study. Int J Yoga  Philosop Psychol Parapsychol [serial online] 2016 [cited 2024 Mar 1];4:1623. Available from: https://www.ijoyppp.org/text.asp?2016/4/1/16/213078 
Introducction   
To qualify for better career options when leaving school, good abilities in mathematics and associated cognitive skills are important. Students with math anxiety show strong tendencies to avoid mathematics, however.^{[1],[2]} High math anxiety, low working memory, and poor math performance have been shown to be strongly correlated.^{[3],[4],[5]} High math anxiety correlates with low selfconcept, suggesting that it deeply undermines student selfconfidence.^{[6]} Math anxiety can also influence a student's decisionmaking abilities ^{[7]} so that stressful situations can have immediate physiological impact, for example, difficulty in breathing, increased heart rate, upset stomach, and lightheadedness.^{[8]}
Many methods have been studied and applied to reduce math anxiety or to improve math performance in school children.^{[8],[9]} Yoga has consistently proved an effective way to reduce anxiety; the power of Yoga breathing (YB) exercises to do so has been well characterized, and they are now well understood. A completely different approach is offered by the program of Vedic mathematics (VM), which has proved popular in schools that have adopted it and is said to improve performance (James Glover, Kenneth Williams: private communication), though no quantitative results have yet been reported. Out of concern to help improve student performance on professional math examinations the present study aimed to compare the effects of VM and YB modules on math anxiety and related cognitive skills in high school students aged 13–15.
Vedic mathematics
The methods of VM were first suggested by Swami Bharati Krsna Tirtha, the Shankaracharya of Puri (18841960), in a posthumously published book of that title.^{[10]} They have been applied in many schools in various different countries worldwide, and widely expanded in their possible applications. High school mathematics has long been a popular application, possibly because before becoming a monk, the Shankaracharya was a teacher of high school mathematics. He may well have tailored his cognitions so that they would have useful applications at that level. They have certainly proved popular in that context, with many students privately reporting greater enjoyment of solving math problems, even those with little previous enjoyment of mathematics.
VM consists of 16 sūtras (formulae), each of which suggests a particular pattern to solve some kind of math problem, along with 16 upasūtras (subformulae). Having learned the sutras and their possible applications, students can then choose whichever most appeals to them to solve any problem with which they are faced. One possible way that VM may help student confidence could, therefore, be by suggesting different strategies involving fewer steps to solve a given math problem. Offering such choice of alternative solutions can help students feel that math classes are entertaining. Classes can become amusing sessions of pattern finding in the form of interesting, alternative VM algorithms, appropriate to solving particular problems. These can be easily and effectively presented by school teachers, and function as teaching aids to handle math anxiety;^{[11]} they also improve cognitive load, so certain VM techniques may be hypothesized to have a positive impact on working memory.
VM is not a new branch of mathematics, but a set of unique approaches to simplifying problemsolving. The sutras and upasutras suggest thinking patterns to help solve arithmetical, algebraic, or geometric calculations common in high school mathematics.^{[12]} VM patterns reduce cumbersomelooking calculations in the conventional approach to simple ones.^{[13]}
They have also been applied in digital signal processing such as construction of shortest algorithms for multipliers in circuits to optimize chip area ^{[14],[15],[16]} and other similar applications. In multiplier circuits, the pattern given in the Urdhva Tiryakbhyam sutra gives the most efficient algorithm, minimizing delays for multiplication of all types of numbers.^{[17]} Such applications of VM algorithms improve efficiency of machines rather than mental processes.
Shortened algorithms for mental calculations may impact cognitive processes, however, eventually improving math anxiety and performance.^{[7]} VM methods have not previously been investigated as teaching aids in educational and cognitive research. Here, we report results of using a VM module both to develop cognitive skills and manage math anxiety.
Yogic breathing (pranayama)
Yoga pranayama is well known to improve conditions in both clinical and nonclinical situations. Evidence that pranayama reduces stress levels and improves individual wellbeing is strong.^{[18]} Pranayama has also been found to decrease state and trait anxiety levels.^{[19]}
Uninostril breathing (left nostril breathing or right nostril breathing) and alternate nostril breathing (Nadishodhana pranayama) can bring positive changes in cognitive tasks.^{[20]} They may help sharpen the critical faculty and creativity and may also bring balance between the left and right halves of the brain.^{[21]} In addition, Kapalabhati, Bhastrika, and Nadishodhana, i.e. both fast and slow pranayamas, and Pranava (OM) chanting can be used to reduce stress levels and to improve cognitive skills, particularly working memory.^{[22]}
Methods   
Subjects
Forty boys studying in 8^{th}, 9^{th}, 10^{th} standards, at Sri Sai Angels School, Chikkamagaluru, were randomly assigned to: Yogic breathing group (YB – 14), VM group (VM – 13), and Jogging (JG) group (JG – 13). The design of the study was explained to parents/guardians, and signed informed consent was obtained.
Design
Three group, prepost random control design [Figure 1]. Randomization was performed using an internet random number generator.^{[23]}  Figure 1: Study design: The sample was divided randomly (with the help of random number generator) into three groups: Yoga breathing, Vedic mathematics, and Jogging. The baseline data were collected, and then respective intervention was given for 7 days to the groups. Postdata were collected after the intervention
Click here to view 
Assessment instruments used
Mathematics Anxiety Rating ScaleRevised
This 24item instrument is designed to measure anxiety related to involvement in statistics and mathematic courses.^{[24]} The instrument is a revised version of a 98item scale by Richardson and Suinn.^{[25]} The current version is more focused on situation specific (state) anxiety, general (trait) anxiety, and test anxiety. The instrument comprises two subscales: Learning mathematics anxiety (LMA) which pertains to the process of learning of math and statistics; and evaluation mathematic anxiety (EMA) measuring anxiety over tests on math and statistics. The sum of LMA and EMA is taken as total mathematics anxiety (TMA).
Scoring  Respondents rate each item on a 5point scale from “low anxiety” to “high anxiety.” Scores are the sum of the item ratings and range from 24 to 120 for the total scale.
STROOP
The STROOP test consists of three subtasks measuring cognitive flexibility, creativity, and reaction to cognitive stress.^{[26]} J.R. Stroop first developed it in 1935.^{[27]} The test consists of three subtasks. The stimulus material for each of these subtasks is shown on a white sheet of paper. The 100 stimuli for each subtask are distributed evenly in a 10×10 matrix on each sheet of paper. The first subtask shows colour words in random order (red, blue, yellow, green) printed in black ink. Subtask 2 displays solid colour patches in one of these four basic colours. The third subtask contains colour words printed in an incongruous ink colour for example, the word yellow printed in red ink. The subject's task on the word subtask is to read aloud the colour words; on the colour to name the coloured patches or asterisks; and on the colour word to name the colors of the ink, ignoring the printed color word. Maximum of 45 seconds per subtask was given to the subject. Scoring was done using number of item completed on each subtask.
Children's Cognitive Assessment Questionnaire
This 40item instrument measures selfdefeating and selfenhancing cognitions associated with testanxiety.^{[28]} The instrument was originally developed for hypothesis testing on the relationship between cognition and testanxiety or task performance. The theoretical perspective asserts that selfdefeating thoughts inhibit performance while selfenhancing thoughts facilitate it. The Children's Cognitive Assessment Questionnaire (CCAQ) focuses on negative selfevaluations (NSEs) and positive selfevaluations as reflecting selfdefeating and selfenhancing cognitions, respectively. It also assesses selfdistracting thoughts (“offtask thoughts;” [OFFT]) and cognitions which focus one's attention on the task (“ontask thoughts”). The CCAQ uses these four aspects as subscales.
Scoring  Each of 40 items is answered true or false, scoring 1/0. Total score for each subscale is the number of items answered “true”, ranging from 0 to 10. Higher scores reflect more thoughts indicative of testanxiety.
Digit span test
This test measures working memory.^{[29]} Here, we used the 2011 computerized version of the Digit span test developed by Inquisit software.^{[30]} Each participant is given 14 trials observing a sequence of digits (starting with three digitslevel 3), presented for 1 s each, after which the participant is asked to recall the digit sequence and type the answer into a presented textbox. If the response is correct (in digits and presentation order), the participant moves up to the next level (e.g., level 4). If the response is incorrect, the same level is presented a second time. If a consecutive error occurs, the participant moves back down to a lower level, starting over.
The first time a participant makes a consecutive error, span is set to the last correctly recalled number of digits (e.g., if participant reaches level 8, but answers incorrectly both times, the span is set to 7).
Interventions
YB group and VM group students attended workshops on Pranayama and VM (Appendix I), respectively, (30 min at 6.00 am and 6.30 am, respectively, every day for 7 days). Those in the JG group went for 30 min JG every day at 5.30 am.
Data extraction
Mathematics Anxiety Rating ScaleRevised (MARSR), CCAQ, digit span test and STROOP test were given at baseline, and after the 7day VM and YB workshops were completed.
Data analysis
The data were analyzed using SPSS 17.0 (Seattle, Washington, United States). Due to small group size, nonparametric tests were used: Mann–Whitney test for intergroup comparisons and Wilcoxon test for within group prepost comparisons.
Results   
There were no baseline differences between the three groups in all the variables studied except offtask thoughts for the JG Group, for which the baseline score was significantly different from other two groups (P < 0.05).
Results for the three groups, YB, VM, and JG, were as follows:
Math anxiety Rating Scale
VM group showed significant prepost differences in TMA (pre 57.85 ± 14.43; post 46.08 ± 14.38; P < 0.01), LMA (pre 34.69 ± 8; post 29 ± 9.23; P < 0.05), and EMA (pre 23.15 ± 7.8; post 17.08 ± 6.22; P < 0.01) [Table 1].  Table 1: Mathematics Anxiety Rating ScaleRevised: Mean±standard deviation
Click here to view 
Yoga group showed significant differences in MARSR in prepost measures. Of the two subsets, EMA was significantly different between prepost measures (pre 20.85 ± 7.35; post 17.15 ± 4.38, P < 0.05), but not LMA; TMA was still significantly lowered (pre 51 ± 14.3; post 46.92 ± 12.63, P < 0.05) [Table 1].
JG group showed no significant differences between prepost measures [Table 1].
Comparisons of prepost differences between the three groups: LMA and TMA differences between Yoga pranayama and VM groups were significant (P < 0.05) [Table 1]; this could have been due to lower pre values in yoga group. In contrast, the JG group was not significantly different in any of the three parameters from either of the other groups [Table 1].
STROOP test
VM group showed significant difference in color score (pre 61.23 ± 7.44; post 66.85 ± 10.64; P < 0.05) and color word (pre 34.15 ± 7.45; post 43.92 ± 9.06; P < 0.001). Prepost differences in means of color word were not significant [Table 2].
YB showed significant difference in color word test of the STROOP test (pre 35.46 ± 5.98; post 40.85 ± 7.89; P < 0.005) [Table 2].
In JG group, significance was observed in word score (pre 86.58 ± 13.27; post 93.5 ± 12.38; P < 0.05) and color word (pre 31.33 ± 6.4; post 39.92 ± 9.03; P < 0.05) [Table 2].
No significant difference was observed between three groups on the STROOP test.
Children's Cognitive Assessment Questionnaire
VM group showed highly significant difference in prepost values of OFFT (pre: 6.08 ± 1.61; post: 2.62 ± 2.66; P < 0.001) [Table 3].  Table 3: Children's Cognitive Assessment Questionnaire: Mean±standard deviation
Click here to view 
YB Group showed significant improvement in lowering NSE (pre: 2.77 ± 2.01; post: 1 ± 1; P < 0.01) and OFFT (pre: 5.54 ± 2.57; post: 3.38 ± 2.36; P < 0.01) [Table 3].
JG group also showed significant difference in prepost values of OFFT (pre: 7.42 ± 2.91; post: 5.92 ± 2.35; P < 0.05) [Table 3].
Prepost differences analyses between the three groups suggest that YB and JG were significantly different in NSE (YB: −1.77 ± 1.83; JG: 0.67 ± 1.44; P < 0.05) [Table 3].
Digit span test
All the three groups performed equally in forward and backward digit span tests [Table 4].
Discussion   
This paper reports comparative effects of three interventions on math anxiety by MARSR; cognitive flexibility and selective attention by the STROOP test; selfdefeating and selfenhancing thoughts by CCAQ; and working memory by the digit span test. All three interventions appeared to influence the various measured parameters, to varying degrees.
Math anxiety with its two subscales, learning math anxiety, and evaluation math anxiety is the primary variable. VM brought the most benefit for math anxiety levels, followed by YB [Figure 2]. JG did not reduce Math anxiety levels to any significant extent. Why the VM group received the most benefit compared to the other groups is obvious: it directly enhances math problemsolving skills bringing confidence to students concerned about math ability.  Figure 2: Comparison of math anxiety prepost differences between Yoga breathing, Vedic mathematics, and Jogging groups: Prepost differences of all three math anxiety score: Learning math anxiety, evaluation math anxiety, and total math anxiety, between all three groups, i.e., Yoga breathing, Vedic mathematics, and Jogging. Vedic mathematics group showed greater reduction in math anxiety, followed by Yoga breathing group. Standard deviations are shown by error bars
Click here to view 
The VM group also showed the greatest improvement on the STROOP test [Figure 3]. The JG group's initial values were lower than those of the other two groups on word score, and its final (post) value did not even reach the prevalues of the other two groups [Table 2] and [Figure 3]. These measurements seem confusing and require further investigation.  Figure 3: Comparison of STROOP prepost differences scores between Yoga breathing, Vedic mathematics, and Jogging groups: Comparison of prepost differences of all three parameters of STROOP test score: Word score, color score, and color word score, between all the three groups, i.e., Yoga breathing, Vedic mathematics, and Jogging. Vedic mathematics group showed greater increase in color and color word scores. Jogging group showed maximum increase in word score. Standard deviations are shown by error bars
Click here to view 
Scores on the CCAQ test measuring selfdefeating and selfenhancing thoughts improved most for the Yoga group followed by the VM group [Figure 4]. The JG group's initial negative evaluation increased but not significantly [Table 3].  Figure 4: Comparison of Children's Cognitive Assessment Questionnaire prepost differences scores between Yoga breathing, Vedic mathematics, and Jogging groups: Compare the prepost differences of all four parameters of Children's Cognitive Assessment Questionnaire, between all the three groups, i.e., Yoga breathing, Vedic mathematics, and Jogging. Vedic mathematics group showed greater reduction in Offtask thoughts, followed by Yoga breathing group. Yoga breathing was observed to have greater reduction in negative evaluation and maximum increase in positive evaluations. Standard deviations are shown by error bars
Click here to view 
The digit span test, which measures working memory and focused attention,^{[31]} did not show significant change after any intervention, nor between any pair of groups [Figure 5]. This result may be due to low sample size and the short intervention period. It needs further investigation.  Figure 5: Comparison of digit span prepost differences scores between Yoga breathing, Vedic mathematics, and Jogging groups: Comparison of digit span prepost differences: forward and backward span, between all the three groups, i.e., Yoga breathing, Vedic mathematics, and Jogging. Standard deviations are shown by error bars
Click here to view 
Overall, VM tended to show greater results than the other interventions on all parameters. VM offers different possible strategies of mental calculation in smaller numbers of steps, bringing “a feelgood factor” to solving lengthy problems. Its methods promote pattern recognition in math,^{[32]} introducing a fun element, possibly by stimulating “feel good” neurotransmitters release (dopamine, serotonin, and an array of endorphins).^{[33]} Improvement in working memory, and reduction in math anxiety result.
YB practices, including repetitive chanting of A, U, M, OM, and generating a humming sound in Shambhavi Mudra, may stimulate the brain, eventually yielding stronger pattern recognition.^{[34]} They may also stimulate the dopamine and endorphin system.^{[35]} Cognitive flexibility, creativity, and reaction to cognitive stress and math anxiety all improve slightly.
Yogic breathing brought greater improvements in CCAQ than the other interventions, strengthens the impact of Yoga in decreasing stress and improving selfconcept and selfesteem,^{[36]} which may lead to greater selfconfidence, and result in better performance.^{[37]} This may also lead to reduction in math anxiety.
The combined effect of these practices may therefore be of value in managing math anxiety and enhancing cognitive skills. The study brings a new understanding of VM and may introduce a new domain for its application. It also offers reasons for including VM and Pranayama, individually or together, in the school curriculum.
Strength of the study
Observed improvements in working memory, math anxiety, and focused attention, resulting from learning VM are new, as are those produced by practicing pranayamṃ
Limitation
As a pilot study, the sample size was too small to draw any strong conclusions. The intervention of 1 week is not enough make results conclusive.
Further research
Followup studies with larger group sizes are called for – one such has recently been accepted for publication;^{[38]} also studies investigating mechanisms behind the observed changes.
Conclusion   
The VM and YB modules were found useful in decreasing math anxiety, selfdefeating thoughts and improving cognitive flexibility and selfenhancing thoughts in school children. Increasing sample size and intervention time may help generate stronger conclusions, and thus provide the grounds for implementing both techniques in school curriculṃ
Acknowledgment
We would like to thank Sri Sai Angels School for providing subjects, place, and equipment to carry out the study. We would like to acknowledge Mr. Manjunath BS for technical support during data collection.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References   
1.  Meece JL, Wigfield A, Eccles JS. Predictors of math anxiety and its influence on young adolescents' course enrollment intentions and performance in mathematics. J Educ Psychol 1990;82:6070. 
2.  Ashcraft MH, Krause Jṃ Working memory, math performance, and math anxiety. Psychon Bull Rev 2007;14:2438. 
3.  Ashcraft MH, Kirk EP. The relationships among working memory, math anxiety, and performance. J Exp Psychol Gen 2001;130:22437. 
4.  Sherman BF, Wither DP. Mathematics anxiety and mathematics achievement. Math Educ Res J 2003;15:13850. 
5.  Ramirez G, Gunderson EA, Levine SC, Beilock SL. Math anxiety, working memory, and math achievement in early elementary school. J Cogn Dev 2013;14:187202. 
6.  Ahmed W, Minnaert A, Kuyper H, Werf G. Reciprocal relationships between math selfconcept and math anxiety. Learn Individ Differ 2012;22:3859. 
7.  Morsanyi K, Busdraghi C, Primi C. Mathematical anxiety is linked to reduced cognitive reflection: A potential road from discomfort in the mathematics classroom to susceptibility to biases. Behav Brain Funct 2014;10:31. 
8.  
9.  Iossi L. Strategies for reducing math anxiety in postsecondary students. In: Nielsen SM, Plakhotnik MS, editors. Proceedings of the Sixth Annual College of Education Research Conference: Urban and International Education Section. Miami: Florida International University; 2007. p. 305. 
10.  Tirthaji Maharaja BK, Agrawala VS. Vedic Mathematics. Delhi: Motilal Banarsidass; 1992. 
11.  Smitha S. Enriching school mathematics education with ancient Indian treasure of vedic algorithms – Application of vedic “Anurupyena” method. Int J Informative Futuristic Res 2014;1:21824. 
12.  Williams K. Vedic Mathematics Teacher's Manual. Revised Edition. Castle Douglas, Scotland: Inspiration Books; 2009. 
13.  Ziatdinov R, Musa S. Rapid mental computation system as a tool for algorithmic thinking of elementary school students development. Eur Res 2012;25:110510. 
14.  Chidgupkar PD, Karad MT. The implementation of vedic algorithms in digital signal processing. Glob J Eng Educ 2004;8:27. 
15.  Panda SK, Das R, Sahoo TR. VLSI implementation of vedic multiplier using Urdhva – Tiryakbhyam sutra in VHDL environment: A novelty. IOSR J VLSI Signal Process 2015;5:1724. 
16.  Anjana S, Pradeep C, Samuel P. Synthesize of high speed floatingpoint multipliers based on vedic mathematics. Procedia Comput Sci 2015;46:1294302. 
17.  Chunduri VS, Lakshmi GS, Prasad MJ. Design and implementation of multiplier using KCM and vedic mathematics by using reversible adder. Int J Mod Eng Res 2013;3:323041. 
18.  Brown RP, Gerbarg PL. Yoga breathing, meditation, and longevity. Ann N Y Acad Sci 2009;1172:5462. 
19.  Gupta N, Khera S, Vempati RP, Sharma R, Bijlani RL. Effect of yoga based lifestyle intervention on state and trait anxiety. Indian J Physiol Pharmacol 2006;50:417. 
20.  Naveen KV, Nagarathna R, Nagendra HR, Telles S. Yoga breathing through a particular nostril increases spatial memory scores without lateralized effects. Psychol Rep 1997;81:55561. 
21.  Nagendra HR. Pranayamṃ Bangalore: Swami Vivekananda Yoga Prakashana; 2005. 
22.  Sharma VK, Rajajeyakumar M, Velkumary S, Subramanian SK, Bhavanani AB, Madanmohan, et al. Effect of fast and slow pranayama practice on cognitive functions in healthy volunteers. J Clin Diagn Res 2014;8:103. 
23.  
24.  Plake BS, Parker CS. The development and validation of a revised version of the mathematics anxiety rating scale. Educ Psychol Meas 1982;42:5517. 
25.  Richardson FC, Suinn RM. The mathematics anxiety rating scale: Psychometric datṃ J Couns Psychol 1972;19:5514. 
26.  Gualtieri CT, Johnson LG. Reliability and validity of a computerized neurocognitive test battery, CNS Vital Signs. Arch Clin Neuropsychol 2006;21:62343. 
27.  Stroop JR. Studies of interference in serial verbal reactions. J Exp Psychol 1935;18:64362. 
28.  Woods DL, Kishiyamaa MM, Lund EW, Herron TJ, Edwards B, Poliva O, et al. Improving digit span assessment of shortterm verbal memory. J Clin Exp Neuropsychol 2011;33:10111. 
29.  Zatz S, Chassin L. Cognitions of testanxious children. J Consult Clin Psychol 1983;51:52634. 
30.  Draine S. Inquisit [Computer Software]. Ver. 4. Seattle, WA: Millisecond Software; 1998. 
31.  Rosenthal EN, Riccio CA, Gsanger KM, Jarratt KP. Digit span components as predictors of attention problems and executive functioning in children. Arch Clin Neuropsychol 2006;21:1319. 
32.  Kellman PJ, Massey CM, Son JY. Perceptual learning modules in mathematics: Enhancing students' pattern recognition, structure extraction, and fluency. Top Cogn Sci 2010;2:285305. 
33.  
34.  Subbalakshmi NK, Saxena SK, Urmimala, D'Souza UJ. Immediate effect of nadishodhana pranayama on some selected parameters of cardiovascular, pulmonary and higher functions of brain. Thai J Physiol Sci 2004;18:106. 
35.  Mohandas E. Neurobiology of spirituality. Mens Sana Monogr 2008;6:6380. [ PUBMED] [Full text] 
36.  Deshpande S, Nagendra HR, Nagarathna R. A randomized control trial of the effect of yoga on Gunas (personality) and self esteem in normal healthy volunteers. Int J Yoga 2009;2:1321. [ PUBMED] [Full text] 
37.  Feltz DL. Selfconfidence and sports performance. Exerc Sport Sci Rev 1988;16:42357. 
38.  Shastri VV, Hankey A, Sharma B, Patra S. Investigation of yoga pranayama and vedic mathematics on mindfulness, aggression and emotion regulation. Int J Yoga 2017;4:1623. 
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3], [Table 4]
