Rhythms Synchronization Effects on Cognition during Listening to Quranic Recitation


  • Ismail Samhani Faculty of Medicine, Universiti Sultan Zainal Abidin (UniSZA) Medical Campus, 20400 Kuala Terengganu, Terengganu, Malaysia
  • Mohammed Faruque Reza Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kota Bharu, Kelantan, Malaysia
  • Mohd Hanifah Jusoh Department of Orthopaedics, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kota Bharu, Kelantan, Malaysia
  • Hafizan Juahir East Coast Environmental Research Institute (ESERI), Universiti Sultan Zainal Abidin (UniSZA) Gong Badak Campus, 21300 Kuala Nerus, Terengganu, Malaysia




Acoustic stimulation, Al-Quran, Brain oscillations, Cognitive neuroscience, Multivariate analysis, Signal analysis.


Sound has rhythms that can interact with human brain rhythms. The interaction may improve human cognition through neuronal synchronization. However, research on the synchronization effects of listening to the Holy Quran remains elusive. This study aimed to learn the potential synchronous effects of Quranic listening in beta frequency through electroencephalographic oscillatory dataset. Subjects were listening to Fatihah Chapter, Arabic News and Rest in random sequence. Data were pre-processed followed by neuroimaging analysis using BESA Research 6.1. Repeated Measures ANOVA and Agglomerative Hierarchical Clustering (AHC) algorithm were applied to elucidate the significantly different EEG electrode channels compared to Rest and their clusters. Results showed that Beta rhythms synchronization with the Fatihah Chapter is associated with verbal fluency, academic performance, social interaction, inhibitory function, movement planning, self-motivation, self-management and reactivation of sensory features of memory trace as highly activated cluster, followed by working memory, language processing and decision making as medially activated cluster; and tune recognition and visual mental imagery as low activated neural circuits cluster during listening to the Fatihah Chapter.


Aron, A. R., Robbins, T. W., & Poldrack, R. A. (4 C.E.). Inhibition and the right inferior frontal cortex. Trends in Cognitive Sciences, 8(4), 170–177. https://doi.org/https://doi.org/10.1016/j.tics.2004.02.010.

Azhar, S. C., Aris, A. Z., Yusoff, M. K., Ramli, M. F., & Juahir, H. (2015). Classification of river water quality using multivariate analysis. Procedia Environmental Sciences, 30, 79–84. https://doi.org/https://doi.org/10.1016/j.proenv.2015.10.014.

Bartolo, R., & Merchant, H. (2015). Oscillations are linked to the initiation of sensory-cued movement sequences and the internal guidance of regular. The Journal of Neuroscience, 35(11), 4635–4640. https://doi.org/10.1523/JNEUROSCI.4570-14.2015.

Boly, M., Laureys, S., Schabus, M., Marrelec, G., Benali, H., Pelegrini-Issac, M., Doyon, J., Maquet, P., & Perlbarg, V. (2012). Hierarchical clustering of brain activity during human nonrapid eye movement sleep. PNAS, 109(15), 5856–5861. https://doi.org/10.1073/pnas.1111133109.

Brodziak, A. (2013). A current model of neural circuitry active in forming mental images. Medical Science Monitor, 19(December 2013), 1146–1158. https://doi.org/10.12659/MSM.889587.

Chen, J. L., Penhune, V. B., & Zatorre, R. J. (2008). Moving on Time: Brain Network for Auditory-Motor Synchronization is Modulated by Rhythm Complexity and Musical Training. Journal of Cognitive Neuroscience, 20, 226–239.

Chochon, F., Cohen, L., Moortele, P. F. va. de, & S. Dehaene. (1999). Differential contributions of the left and right inferior parietal lobules to number processing. Journal of Cognitive Neuroscience, 11(6), 617–630.

Craik, A., He, Y., & Contreras-Vidal, J. L. (2019). Deep learning for electroencephalogram (EEG) classification tasks: A review. Journal of Neural Engineering, 16.

de Borst, A. W., Sack, A. T., Jansma, B. M., Esposito, F., de Martino, F., Valente, G., Roebroeck, A., di Salle, F., Goebel, R., & Formisano, E. (2012). Integration of "what" and "where" in frontal cortex during visual imagery of scenes. NeuroImage, 60(1), 47–58. https://doi.org/https://doi.org/10.1016/j.neuroimage.2011.12.005.

Edagawa, K., & Kawasaki, M. (2017). Beta phase synchronization in the frontal-temporal-cerebellar network during auditory-to-motor rhythm learning. Nature Publishing Group, February, 1–9. https://doi.org/10.1038/srep42721.

Engel, A. K., & Fries, P. (2010). Beta-band oscillations – signalling the status quo? 20(2), 156–165.

Fink, A., & Benedek, M. (2014). Neuroscience and Biobehavioral Reviews EEG alpha power and creative ideation ଝ. Neuroscience and Biobehavioral Reviews, 44, 111–123. https://doi.org/10.1016/j.neubiorev.2012.12.002.

Forina, M., Armanino, C., & Raggio, V. (2002). Clustering with dendrograms on interpretation variables. Analytica Chimica Acta, 454(1), 13–19. https://doi.org/https://doi.org/10.1016/S0003-2670(01)01517-3.

Fujioka, T., Trainor, L. J., Large, E. W., & Ross, B. (2012). Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. 32(5), 1791–1802. https://doi.org/10.1523/JNEUROSCI.4107-11.2012.

Giraud, A., & Poeppel, D. (2015). Cortical oscillations and speech processing: emerging computational principles and operations. Nature Neuroscience, 15(4), 511–517. https://doi.org/10.1038/nn.3063.Cortical.

Groussard, M., Viader, F., Landeau, B., Desgranges, B., Eustache, F., & Platel, H. (2009). Neural correlates underlying musical semantic memory. Annals of the New York Academy of Sciences, 1169, 278–281. https://doi.org/10.1111/j.1749-6632.2009.04784.x.

Hampshire, A., Chamberlain, S. R., Monti, M. M., Duncan, J., & Owen, A. M. (2010). The role of the right inferior frontal gyrus: inhibition and attentional control. NeuroImage, 50(3), 1313–1319. https://doi.org/10.1016/j.neuroimage.2009.12.109.

Hanslmayr, S., Volberg, G., Wimber, M., Raabe, M., Greenlee, M. W., & Bauml, K.-H. T. (2011). The Relationship between Brain Oscillations and BOLD Signal during Memory Formation: A Combined EEG-fMRI Study. Journal of Neuroscience, 31(44), 15674–15680. https://doi.org/10.1523/JNEUROSCI.3140-11.2011.

Hanslmayr, Simon, Staresina, B. P., & Bowman, H. (2016). Oscillations and Episodic Memory: Addressing the Synchronization/Desynchronization Conundrum. Trends in Neurosciences Elsevier Ltd. 39(1), 16–25. https://doi.org/10.1016/j.tins.2015.11.004.

Hanslmayr, Simon, Staudigl, T., & Fellner, M.-C. (2012). Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis. Frontiers in Human Neuroscience, 6(April), 74. https://doi.org/10.3389/fnhum.2012.00074.

Hughes, L. E., Rittman, T., Regenthal, R., Robbins, T. W., & Rowe, J. B. (2015). Improving response inhibition systems in frontotemporal dementia with citalopram. Brain, 138(7), 1961–1975. https://doi.org/10.1093/brain/awv133.

Hussain, S., Madi, E. N., Iqbal, N., Botmart, T., Karaca, Y., & Mohammed, W. W. (2021). Fractional dynamics of vector-borne infection with sexual transmission rate and vaccination. Mathematics, 9(23), 1–22. https://doi.org/10.3390/math9233118.

Hussain, S., Madi, E. N., Khan, H., Etemad, S., Rezapour, S., Sitthiwirattham, T., & Patanarapeelert, N. (2021). Investigation of the stochastic modeling of covid-19 with environmental noise from the analytical and numerical point of view. Mathematics, 9(23). https://doi.org/10.3390/math9233122.

Ishak, I., Rahman, S. A., Ibrahim, F. W., Khair, N. M., Warif, N. M. A., Harun, D., Ghazali, A. H., Ariffin, F., Din, N. C., Mohamad, S., Mastor, K. A., Haneefa, M. H. M., Ismail, S. (2021). the impact of quran memorization on psychological and health well-being. Review of Internatioanl Geographical Education, 11(8), 337-344. DOI: 10.48047/rigeo.11.08.33.

Ismail, A., Ibrahim, M. S., Ismail, S., Aziz, A. A., Yusoff, H. M., Mokhtar, M., Juahir H. (2022). Development of COVID-19 health-risk screening system for COVID-19 health-risk assessment and self-evaluation (CHaSe) tool among the university students and staff during movement control order (MCO). Network Modeling Analysis in Health Informatics and Bioinformatics, 11( 21). https://doi.org/10.1007/s13721-022-003573.

Ismail, S., Jusoh, M. H., Juahir, H., Idris, Z., & Reza, M. F. (2022). Activation of mental imagery neural network revealed during listening to Fatihah Chapter; a neuroimaging study. Bangladesh Journal of Medical Science, 21(3), 710–716. https://doi.org/https://doi.org/10.3329/bjms.v21i3.59589.

Jain, A., & Dubes, R. (1988). Algorithms for Clustering Data. Prentice Hall, Inc.

Joundi, R. A., Jenkinson, N., Brittain, J.-S., Aziz, T. Z., & Brown, P. (2012). Driving Oscillatory Activity in the Human Cortex Enhances Motor Performance. Current Biology, 22(5), 403–407.

Kamiński, J., Brzezicka, A., Gola, M., & Wróbel, A. (2012). Beta band oscillations engagement in human alertness process. International Journal of Psychophysiology, 85(1), 125–128. https://doi.org/https://doi.org/10.1016/j.ijpsycho.2011.11.006.

Klem, G. H., Lüders, H. O., Jasper, H. H., & Elger, C. (1999). The ten-twenty electrode system of the International Federation. In G. Deuschl & A. Eisen (Eds.). Recommendations for the Practice of Clinical Neurophysiology: Guidelines of the International Federation of Clinical Physiology (EEG Suppl. 52) (pp. 3–6). Elsevier Science B.V.

Komaru, Y., Yoshida, T., Hamasaki, Y., Nangaku, M., & Doi, K. (2020). Hierarchical Clustering Analysis for Predicting 1-Year Mortality After Starting Hemodialysis. Kidney International Reports, 5(8), 1188–1195. https://doi.org/10.1016/j.ekir.2020.05.007.

Konishi, S. (2011). Frontal lobes and inhibitory function. Brain Nerve, 63(12), 1346–1351.

Massart, D. L., & Kaufman, L. (1983). The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis. John Wiley & Sons.

McKenna, J. E. (2003). An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis. Environmental Modelling & Software, 18(2), 205–220. https://doi.org/doi:10.1016/S1364- 8152(02)00094-4.

Hashim, Z. I. M., Ismail, S., Husain, R., Omar, S. H. S., & Mohamad, N. (2018). an application of healing verses (as-syifa verses) as therapy approach to reduce stress in drug addiction. International Journal of Civil Engineering and Technology, 9(9), 165-173.

O'Reilly, C., Godbout, J., Carrier, J., & Lina, J.-M. (2015). Combining time-frequency and spatial information for the detection of sleep spindles. Frontiers in Human Neuroscience, 9(February), 1–14. https://doi.org/10.3389/fnhum.2015.00070.

Otto, M. (1998). Multivariate Methods. In R. Kellner, J. Mermet, M. Otto, & H. Widmer (Eds.). Analytical Chemistry (p. 916). Wiley-VCH.

Patterson, R. D., Uppenkamp, S., Johnsrude, I. S., & Griffiths, T. D. (2002). The processing of temporal pitch and melody information in auditory cortex. Neuron, 36, 1–10. https://doi.org/10.1016/S0896-6273(02)01060-7.

Pfurtscheller, G., & Berghold, A. (1989). Patterns of cortical activation during planning of voluntary movement. Electroencephalography and Clinical Neurophysiology, 72(3), 250–258. https://doi.org/https://doi.org/10.1016/0013-4694(89)90250-2.

Pfurtscheller, G., & Lopes, F. H. (1999). Event-related EEG / MEG synchronization and desynchronization : basic principles. Clinical Neurophysiology, 110, 1842–1857. https://doi.org/10.1016/S1388-2457(99)00141-8.

Plakke, B., Romanski, L. M., & Petkov, C. I. (2014). Auditory connections and functions of prefrontal cortex. 8(July), 1–13. https://doi.org/10.3389/fnins.2014.00199.

Platel, H. (1997). The structural components of music perception. A functional anatomical study. Brain, 120(2), 229–243. https://doi.org/10.1093/brain/120.2.229.

Reedijk, S. A., Bolders, A., & Hommel, B. (2013). The impact of binaural beats on creativity. Frontiers in Human Neuroscience, 7(November), 1–7. https://doi.org/10.3389/fnhum.2013.00786.

Reybrouck, M., Vuust, P., Brattico, E., Reybrouck, M., Vuust, P., & Brattico, E. (2018). Music and brain plasticity: how sounds trigger neurogenerative adaptations. In Neuroplasticity - Insights of Neural Reorganization (pp. 85–103).

Rosdan, R. M., Awang, W. S. W. & Ismail, S. (2022). Affinity Degree as Ranking Method. International Journal of Advanced Computer Sciences and Applications (IJACSA), 13(2), 403-410.

Sameiro-barbosa, C. M., & Geiser, E. (2016). Sensory Entrainment Mechanisms in Auditory Perception : Neural Synchronization Cortico-Striatal Activation. 10(August), 1–8. https://doi.org/10.3389/fnins.2016.00361.

Samhani, I., & Reza, M. F. (2017). Auditory Elicitation of Event Related Desynchronization Reveals the Neuronal Mechanism during Listening to Sura Fatiha Recitation. Research Journal of Pharmacy and Technology, 10(12), 4488–4550.

Samhani, I., Begum, T., Juahir, H., Idris, Z., Abdullah, J. M. and Reza, F. (2019). Psychoacoustical effects of brain oscillations during listening to Fatihah Chapter. Bangladesh Journal of Medical Sciences.

Samhani, I., Husain, R., Begum, T., Juahir, H., Idris, Z., Abdullah, J.M. and Reza, F. (2018). Attentional process during listening to Quantitative Quranic Verses (Fatihah Chapter) associated with memory, speech and emotion. Asian Journal of Medicine and Biomedicine, 2(1), 1-9.

Samhani, I., Juahir, H., Idris, Z., and Reza, F. (2019). Potential of quantitative Electroencephalography (qEEG) in measuring cognitive and psychoacoustical effects of The Fatihah Chapter acoustic stimulation. QURANICA. International Journal of Quranic Research, 11(2).

Sikka, R., Cuddy, L. L., Johnsrude, I. S., & Vanstone, A. D. (2015). An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults. Frontiers in Neuroscience, 9(OCT), 1–10. https://doi.org/10.3389/fnins.2015.00356.

Song, S., Zou, Z., Song, H., Wang, Y., Uquillas, F. d. O., Wang, H., & Chen, H. (2016). Romantic love is associated with enhanced inhibitory control in an emotional stop-signal task. Frontiers in Psychology, 7(OCT), 1–10. https://doi.org/10.3389/fpsyg.2016.01574.

Stenner, M.-P., Dürschmid, S., Rutledge, R. B., Zaehle, T., Schmitt, F. C., Kaufmann, J., Voges, J., Heinze, H.-J., Dolan, R. J., & Schoenfeld, M. A. (2016). Perimovement decrease of alpha/beta oscillations in the human nucleus accumbens. Journal of Neurophysiology, 116(4), 1663–1672.

Usman, U. N., Toriman, M. E., Juahir, H., Abdullahi, M. G., Rabiu, A. A., & Isiyaka, H. (2014). Assessment of groundwater quality using multivariate statistical techniques in Terengganu. Science and Technology, 4(3), 42–49. https://doi.org/10.5923/j.scit.20140403.02.

Wagner, J., Solis-escalante, T., Scherer, R., Neuper, C., & Daniel, P. (2014). It' s how you get there : walking down a virtual alley activates premotor and parietal areas. Frontiers in Human Neuroscience, 8(February), 1–11. https://doi.org/10.3389/fnhum.2014.00093.

Wagner, J., TeodoroSolis-Escalante, Grieshofer, P., Neupera, C., Müller-Putz, G., & Scherera, R. (2012). Level of participation in robotic-assisted treadmill walking modulates midline sensorimotor EEG rhythms in able-bodied subjects. NeuroImage, 63(3), 1023–1211.

Waldhauser, G. T., Johansson, M., & Hanslmayr, S. (2012). Alpha / Beta Oscillations Indicate Inhibition of Interfering Visual Memories. 32(6), 1953–1961. https://doi.org/10.1523/JNEUROSCI.4201-11.2012.

Zainuddin, N. F., Omar, A. H., Zulkapri, I., Jamaludin, M. N., & Miswan, M. S. (2017). Brainwave biomarkers of brain activity, physiology and biomechanics in cycling performance. Malaysian Journal of Fundamental and Applied Sciences, 13(4–2), 533–539. https://doi.org/10.11113/mjfas.v13n4-2.840.

Zimmermann, J. F., Moscovitch, M., & Alain, C. (2016). Attending to auditory memory. Brain Research, 1640(April 2016), 208–221. https://doi.org/10.1016/j.brainres.2015.11.032.