Brain Disorders Related to The Learning Process
DOI:
https://doi.org/10.61455/sicopus.v4i01.386Keywords:
brain disorders, learning processes, learning difficulties, cognitive function, educational neuroscienceAbstract
Objective: The purpose of this study is to deeply understand the role of the brain in the learning process, as well as identify various types of brain disorders that impact students' cognitive abilities. In addition, this study also aims to examine how certain neurological disorders, such as dyslexia, Minimal Brain Dysfunction, dyscalculia, and attention deficit hyperactivity disorder, affect students' academic performance and daily life. This research is expected to provide a neuroscientific perspective in designing learning strategies that are more inclusive and responsive to specific learning needs. Theoretical framework: The theoretical framework is based on the neuroscience approach of education, specifically the concepts of brain plasticity, the function of the hemispheres, and the role of the central nervous system in learning. Literature review: The literature review covers brain development and function, as well as various disorders such as dyslexia, DMO, ADHD, and dyscalculia, which have a direct impact on learning ability. Methods: This study uses a descriptive qualitative method with a literature review approach. The data was analyzed using content analysis from various scientific literature sources. Results: The results of the study show that brain function has a very important role in supporting the learning process. Connections between neurons are formed through experience and appropriate stimuli, while disturbances in brain structure or function can cause various difficulties in the learning process. Disorders such as Minimal Brain Dysfunction, dyslexia, dyscalculia, and attention deficit hyperactivity disorder significantly affect concentration, memory, and the ability to read, write, and count in school-age children. In addition, the dominance of left-brain or right-brain function also affects a person's learning style, so learning strategies need to be adjusted to the cognitive tendencies of each student. Implications: The results of this study encourage the importance of understanding neuroscience in education so that learning strategies can be adjusted to the neurological condition of students. Novelty: The novelty of this research lies in the integration of neuroscience and Islamic educational approaches in understanding and dealing with learning disorders holistically and empathically.
References
D. Yao et al., “A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity,” IEEE Trans. Med. Imaging, vol. 40, no. 4, pp. 1279–1289, 2021, https://doi.org/10.1109/TMI.2021.3051604.
P. Muralidharan, M. Prasanth, K. N. Jiji, and S. Gejalakshmi, “Ameliorative effect of hydroalcoholic extract of Caryota urens (Arecaceae) on streptozotocin-induced Alzheimer’s model in mice,” Drug Invent. Today, no. 1, pp. 201–205, 2019, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081670749&partnerID=40&md5=8dc797a08132d35f993f843e03e9002d
A. Z. Ibrahim, P. Prakash, V. Sakthivel, and P. Prabu, “Integrated Approach of Brain Disorder Analysis by Using Deep Learning Based on DNA Sequence,” Comput. Syst. Sci. Eng., vol. 45, no. 3, pp. 2447–2460, 2023, https://doi.org/10.32604/csse.2023.030134.
E. Grinman, I. Espadas, and S. V. Puthanveettil, “Emerging roles for long noncoding RNAs in learning, memory and associated disorders,” Neurobiol. Learn. Mem., vol. 163, 2019, https://doi.org/10.1016/j.nlm.2019.107034.
C. Sakurada, H. Mizoguchi, T. Komatsu, S. Sakurada, and T. Sakurada, Neuropeptide degradation related to the expression of the physiological action of neuropeptides. CRC Press, 2012. https://doi.org/10.1201/b12279.
P. Chu Sin Chung and B. L. Kieffer, “Delta opioid receptors in brain function and diseases,” Pharmacology and Therapeutics, vol. 140, no. 1. Elsevier Inc., pp. 112–120, 2013. https://doi.org/10.1016/j.pharmthera.2013.06.003.
S. Pei, Y. Wang, Z. Lv, and C. Zhang, “Transformer Based Multi-view Learning for Interagting Static and Dynamic Complementarity of Brain Function,” in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, R. B.D., T. I., S. G., and M. N.B., Eds., Institute of Electrical and Electronics Engineers Inc., 2025. https://doi.org/10.1109/ICASSP49660.2025.10887907.
L. Shiels, P. Majmundar, A. Zywot, J. Sobotka, C. S. M. Lau, and T. O. Jalonen, “Medical student attitudes and educational interventions to prevent neurophobia: A longitudinal study,” BMC Med. Educ., vol. 17, no. 1, 2017, https://doi.org/10.1186/s12909-017-1055-4.
P. Zhong, R. Cheng, and X. Tang, “Utilizing average symmetrical surface distance in active shape modeling for subcortical surface generation with slow-fast learning,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 230–233. https://doi.org/10.1109/EMBC48229.2022.9871829.
J. A. Rathner and M. A. Schier, “How we teach: Generalizable education research: The impact of flipped classroom andragogy on student assessment performance and perception of learning experience in two advanced physiology subjects,” Adv. Physiol. Educ., vol. 44, no. 1, pp. 80–92, 2020, https://doi.org/10.1152/ADVAN.00125.2019.
M. I. Garcia-Planas and M. V. Garcia-Camba, “Control theory tools for best understanding brain Learning Disorders,” in Proceedings - 2022 7th International Conference on Mathematics and Computers in Sciences and Industry, MCSI 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 96–100. https://doi.org/10.1109/MCSI55933.2022.00022.
S. Sandrone and K. N. Alavian, “Threshold Concepts in Neuroscience: Identification Challenges, Educational Opportunities and Recommendations for Practice,” Front. Educ., vol. 5, 2021, https://doi.org/10.3389/feduc.2020.540307.
A. Y. L. Li and H. Carvalho, “Active learning in neuroscience: A manipulative to simulate visual field defects,” Adv. Physiol. Educ., vol. 40, no. 4, pp. 462–464, 2016, https://doi.org/10.1152/advan.00071.2016.
E. O. Sanya, O. E. Ayodele, and T. O. Olanrewaju, “Interest in neurology during medical clerkship in three Nigerian medical schools,” BMC Med. Educ., vol. 10, no. 1, 2010, https://doi.org/10.1186/1472-6920-10-36.
B. Trappler, “Integrated problem-based learning in the neuroscience curriculum - The SUNY Downstate experience,” BMC Med. Educ., vol. 6, 2006, https://doi.org/10.1186/1472-6920-6-47.
S. Jaberzadeh and F. A. Mansouri, “Short-term research projects in cognitive neuroscience for undergraduate students: a contingency plan to maintain quality teaching during the COVID-19 pandemic,” Adv. Physiol. Educ., vol. 45, no. 2, pp. 376–383, 2021, https://doi.org/10.1152/advan.00012.2021.
K. Foray, W. Zhou, J. Fitzgerald, P. G. Gianferrara, and W. M. Joiner, “Applied Motor Noise Affects Specific Learning Mechanisms during Short-Term Adaptation to Novel Movement Dynamics,” eNeuro, vol. 12, no. 1, 2025, https://doi.org/10.1523/ENEURO.0100-24.2024.
W. Yin, L. Li, and F. X. Wu, “Deep learning for brain disorder diagnosis based on fMRI images,” Neurocomputing, vol. 469, pp. 332–345, 2022, https://doi.org/10.1016/j.neucom.2020.05.113.
M. T. Bianchi, V. Caviness, and S. S. Cash, Network approaches to diseases of the brain. Bentham Science Publishers Ltd., 2012. https://doi.org/10.2174/97816080501781120101.
E. Adeli-Mosabbeb, K. H. Thung, L. An, F. Shi, and D. Shen, “Robust feature-sample linear discriminant analysis for brain disorders diagnosis,” in Advances in Neural Information Processing Systems, C. C., L. D.D., G. R., L. N.D., and S. M., Eds., Neural information processing systems foundation, 2015, pp. 658–666. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84965153630&partnerID=40&md5=82379c84c77483fa3f1ec223359bf51e
Y. Zong, Q. Zuo, M. K. P. Ng, B. Lei, and S. Wang, “A New Brain Network Construction Paradigm for Brain Disorder via Diffusion-Based Graph Contrastive Learning,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 46, no. 12, pp. 10389–10403, 2024, https://doi.org/10.1109/TPAMI.2024.3442811.
O. Alshorman, M. Masadeh, A. Alzyoud, M. B. Bin Heyat, and Rishipal, “The effects of emotional stress on learning and memory cognitive function: An EEG review study in education,” in Proceedings of the International Conference on e-Learning, ICEL, Academic Conferences and Publishing International Limited, 2020, pp. 177–182. https://doi.org/10.1109/econf51404.2020.9385468.
Y. X. Luo, Y. X. Xue, H. W. Shen, and L. Lu, “Role of amygdala in drug memory,” Neurobiol. Learn. Mem., vol. 105, pp. 159–173, 2013, https://doi.org/10.1016/j.nlm.2013.06.017.
D. Zare et al., “Inhibition of protease-activated receptor 1 (PAR1) ameliorates cognitive performance and synaptic plasticity impairments in animal model of Alzheimer’s disease,” Psychopharmacology (Berl), vol. 238, no. 6, pp. 1645–1656, 2021, https://doi.org/10.1007/s00213-021-05798-8.
M. Mulyadi, “Penelitian Kuantitatif Dan Kualitatif Serta Pemikiran Dasar Menggabungkannya,” J. Stud. Komun. dan Media, vol. 15, no. 1, p. 128, 2013, https://doi.org/10.31445/jskm.2011.150106.
A. Sholikhah, “Statistik Deskriptif Dalam Penelitian Kualitatif,” KOMUNIKA J. Dakwah dan Komun., vol. 10, no. 2, pp. 342–362, 2016, https://doi.org/10.24090/komunika.v10i2.953.
A. A. Mekarisce, “Teknik Pemeriksaan Keabsahan Data pada Penelitian Kualitatif di Bidang Kesehatan Masyarakat,” JJurnal Ilm. Kesehat. Masy. Media Komun. Komunitas Kesehat. Masy., vol. 12, no. 3, pp. 145–151, 2020, https://doi.org/10.52022/jikm.v12i3.102.
E. D. Pinheiro, J. R. Sato, R. da S. S. Junior, C. Barreto, and A. Y. A. Oku, “Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children’s educational robotics activities,” Trends Neurosci. Educ., vol. 36, 2024, https://doi.org/10.1016/j.tine.2024.100234.
J. H. Abraini, C. Bouquet, F. Joulia, M. Nicolas, and B. Kriem, “Cognitive performance during a simulated climb of Mount Everest: Implications for brain function and central adaptive processes under chronic hypoxic stress,” Pflugers Arch. Eur. J. Physiol., vol. 436, no. 4, pp. 553–559, 1998, https://doi.org/10.1007/s004240050671.
M. R. Ramis et al., Neuroprotection induced by catechins in aging. Elsevier, 2024. https://doi.org/10.1016/B978-0-443-23763-8.00031-2.
A. L. T. Tadielo, P. M. Sosa, and P. B. Mello-Carpes, “Physiology faculty and student contributions to schoolteacher training in neuroscience: innovations during the COVID-19 pandemic,” Adv. Physiol. Educ., vol. 46, no. 4, pp. 606–614, 2022, https://doi.org/10.1152/advan.00045.2022.
J. Pellinen et al., “Engagement in online cognitive testing with the Cogstate brief battery among a multinational cohort of people with focal epilepsy,” Epilepsy Behav., vol. 159, 2024, https://doi.org/10.1016/j.yebeh.2024.109953.
C. A. Harris et al., “Neurorobotics Workshop for High School Students Promotes Competence and Confidence in Computational Neuroscience,” Front. Neurorobot., vol. 14, 2020, https://doi.org/10.3389/fnbot.2020.00006.
M. Joyce and D. Siever, “Audio-visual entrainment program as a treatment for behavior disorders in a school setting,” J. Neurother., vol. 4, no. 2, pp. 9–25, 2000, https://doi.org/10.1300/J184v04n02_04.
D. T. Nguyen, S. Ryu, M. N. I. Qureshi, M. Choi, K. H. Lee, and B. Lee, “Hybrid multivariate pattern analysis combined with extreme learning machine for Alzheimer’s dementia diagnosis using multi-measure rs-fMRI spatial patterns,” PLoS One, vol. 14, no. 2, 2019, https://doi.org/10.1371/journal.pone.0212582.
B. Garcia-Zapirain, I. de la Torre Díez, and M. López-Coronado, “Dual System for Enhancing Cognitive Abilities of Children with ADHD Using Leap Motion and eye-Tracking Technologies,” J. Med. Syst., vol. 41, no. 7, 2017, https://doi.org/10.1007/s10916-017-0757-9.
N. A. Khan, S. A. Waheeb, A. Riaz, and X. Shang, “A three-stage teacher, student neural networks and sequential feed forward selection-based feature selection approach for the classification of autism spectrum disorder,” Brain Sci., vol. 10, no. 10, pp. 1–22, 2020, https://doi.org/10.3390/brainsci10100754.
S. Cherrier, P. Y. Le Roux, F. M. Gerard, G. Wattelez, and O. Galy, “Impact of a neuroscience intervention (NeuroStratE) on the school performance of high school students: Academic achievement, self-knowledge and autonomy through a metacognitive approach,” Trends Neurosci. Educ., vol. 18, 2020, https://doi.org/10.1016/j.tine.2020.100125.
A. E. Smith, F. der Weduwen, T. Powell, and G. Doherty, “The practical skills passport: a co-curricular program to enhance lab skills confidence in undergraduate neuroscience and biology students,” Adv. Physiol. Educ., vol. 49, no. 3, pp. 696–703, 2025, https://doi.org/10.1152/advan.00204.2024.
B. H. S. Das Neves, V. Á. Martini, M. de Freitas Fantti, and P. B. Mello-Carpes, “Long-term impact of neuroscience outreach interventions on elementary students’ knowledge,” Adv. Physiol. Educ., vol. 48, no. 2, pp. 147–154, 2024, https://doi.org/10.1152/advan.00028.2023.
R. E. A. Elgheit and N. Nashat, “Bringing theory to life: integrating case-based learning in applied physiology for undergraduate physiotherapy education,” BMC Med. Educ., vol. 25, no. 1, 2025, https://doi.org/10.1186/s12909-025-06725-7.
S. R. Goyette and J. DeLuca, “A semester-long student-directed research project involving enzyme immunoassay: Appropriate for immunology, endocrinology, or neuroscience courses,” CBE Life Sci. Educ., vol. 6, no. 4, pp. 332–342, 2007, https://doi.org/10.1187/cbe.07-01-0001.
S. Justus, K. Simmers, K. Arnold, and I. Davidesco, “Translating neuroscience research to practice through grassroots professional learning communities,” Trends Neurosci. Educ., vol. 37, 2024, https://doi.org/10.1016/j.tine.2024.100243.
S. Sandrone and I. Ntonia, “Exploring the identity development of the budding neuroscientist at postgraduate level: a mixed-method study with perspectives from alumni and academics,” BMC Med. Educ., vol. 22, no. 1, 2022, https://doi.org/10.1186/s12909-022-03758-0.






