Pengaruh Perkembangan Otak pada Kemampuan Kognitif dan Perilaku dari Masa Infansi hingga Dewasa
Tinjauan Terkini
Keywords:
kognitif, perkembangan, perilaku, otakAbstract
Perkembangan otak dalam rentang usia dari masa infansi hingga dewasa memegang peran kunci dalam membentuk kompleksitas kemampuan kognitif dan perilaku individu. Sebagai pusat kendali sistem saraf, otak mengalami transformasi yang signifikan, membentuk dasar yang kuat untuk fungsi-fungsi kognitif seperti pemecahan masalah, belajar, dan adaptasi terhadap lingkungan sosial. Artikel ini bertujuan untuk memberikan kontribusi pada pemahaman yang lebih holistik tentang kompleksitas interaksi perkembangan antara otak dan kemampuan kognitif serta perilaku dari masa infansi hingga dewasa, mencerminkan urgensi pemahaman ini seiring dengan terus berkembangnya pengetahuan di bidang neurosains dan psikologi perkembangan.
Downloads
References
Antonenko, D., Külzow, N., Sousa, A., Prehn, K., Grittner, U., & Flöel, A. (2018). Neuronal and behavioral effects of multi-day brain stimulation and memory training. Neurobiology of Aging, 61, 245–254. https://doi.org/10.1016/j.neurobiolaging.2017.09.017
Antonucci, T. C., Ajrouch, K. J., & Birditt, K. S. (2013). The convoy model: Explaining social relations from a multidisciplinary perspective. The Gerontologist, 54(1), 82–92. https://doi.org/10.1093/geront/gnt118
Baird, A. A., Gruber, S. A., Fein, D. A., Maas, L. C., Steingard, R. J., Renshaw, P. F., & Cohen, B. M. (1999). Functional magnetic resonance imaging of facial affect recognition in children and adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 38(2), 195–199. https://doi.org/10.1097/00004583-199902000-00019
Belleville, S., Clément, F., Mellah, S., Gilbert, B., Fontaine, F., & Gauthier, S. (2011). Training-related brain plasticity in subjects at risk of developing alzheimer’s disease. Brain, 134(6), 1623–1634. https://doi.org/10.1093/brain/awr037
Belsky, J. (2016). The differential susceptibility hypothesis. JAMA Pediatrics, 170(4), 321. https://doi.org/10.1001/jamapediatrics.2015.4263
Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review, 28(1), 62–77. https://doi.org/10.1016/j.dr.2007.08.003
Deoni, S. C., O’Muircheartaigh, J., Elison, J. T., Walker, L., Doernberg, E., Waskiewicz, N., Dirks, H., Piryatinsky, I., Dean, D. C., & Jumbe, N. L. (2014). White matter maturation profiles through early childhood predict general cognitive ability. Brain Structure and Function, 221(2), 1189–1203. https://doi.org/10.1007/s00429-014-0947-x
Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64(1), 135–168. https://doi.org/10.1146/annurev-psych-113011-143750
Diamond, A. (2020). The early development of executive functions. In Executive Function in Preschool-Age Children (pp. 11-29). Routledge.
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Changes in grey matter induced by training. Nature, 427(6972), 311–312. https://doi.org/10.1038/427311a
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., Schatzberg, A. F., Sudheimer, K., Keller, J., Mayberg, H. S., Gunning, F. M., Alexopoulos, G. S., Fox, M. D., Pascual-Leone, A., Voss, H. U., … Liston, C. (2016). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, 23(1), 28–38. https://doi.org/10.1038/nm.4246
Erickson, K. I., Voss, M. W., Prakash, R. S., Basak, C., Szabo, A., Chaddock, L., Kim, J. S., Heo, S., Alves, H., White, S. M., Wojcicki, T. R., Mailey, E., Vieira, V. J., Martin, S. A., Pence, B. D., Woods, J. A., McAuley, E., & Kramer, A. F. (2011). Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences, 108(7), 3017–3022. https://doi.org/10.1073/pnas.1015950108
Ernst, M., Pine, D. S., & Hardin, M. (2005). Triadic model of the neurobiology of motivated behavior in adolescence. Psychological Medicine, 36(3), 299–312. https://doi.org/10.1017/s0033291705005891
Forbes, E. E., & Dahl, R. E. (2010). Pubertal development and behavior: Hormonal activation of social and motivational tendencies. Brain and Cognition, 72(1), 66–72. https://doi.org/10.1016/j.bandc.2009.10.007
Gauthier, S., Reisberg, B., Zaudig, M., Petersen, R. C., Ritchie, K., Broich, K., Belleville, S., Brodaty, H., Bennett, D., Chertkow, H., Cummings, J. L., de Leon, M., Feldman, H., Ganguli, M., Hampel, H., Scheltens, P., Tierney, M. C., Whitehouse, P., & Winblad, B. (2006). Mild cognitive impairment. The Lancet, 367(9518), 1262–1270. https://doi.org/10.1016/s0140-6736(06)68542-5
Ghetti, S., & Bunge, S. A. (2012). Neural changes underlying the development of episodic memory during middle childhood. Developmental Cognitive Neuroscience, 2(4), 381–395. https://doi.org/10.1016/j.dcn.2012.05.002
Giedd, J. N. (2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Sciences, 1021(1), 77–85. https://doi.org/10.1196/annals.1308.009
Gogtay, N., & Thompson, P. M. (2010). Mapping gray matter development: Implications for typical development and vulnerability to psychopathology. Brain and Cognition, 72(1), 6–15. https://doi.org/10.1016/j.bandc.2009.08.009
Isaacs, E. B., Gadian, D. G., Sabatini, S., Chong, W. K., Quinn, B. T., Fischl, B. R., & Lucas, A. (2008). The effect of early human diet on caudate volumes and IQ. Pediatric Research, 63(3), 308–314. https://doi.org/10.1203/pdr.0b013e318163a271
Jansen, K., & Kiefer, S. M. (2020). Understanding brain development: Investing in young adolescents’ cognitive and social-emotional development. Middle School Journal, 51(4), 18–25. https://doi.org/10.1080/00940771.2020.1787749
Karunanayaka, P. R., Holland, S. K., Schmithorst, V. J., Solodkin, A., Chen, E. E., Szaflarski, J. P., & Plante, E. (2007). Age-related connectivity changes in fmri data from children listening to stories. NeuroImage, 34(1), 349–360. https://doi.org/10.1016/j.neuroimage.2006.08.028
Knudsen, E. I. (2004). Sensitive periods in the development of the brain and behavior. Journal of Cognitive Neuroscience, 16(8), 1412–1425. https://doi.org/10.1162/0898929042304796
Lindenberger, U., & Ghisletta, P. (2009). Cognitive and sensory declines in old age: Gauging the evidence for a common cause. Psychology and Aging, 24(1), 1–16. https://doi.org/10.1037/a0014986
Luby, J. L., Barch, D. M., Belden, A., Gaffrey, M. S., Tillman, R., Babb, C., Nishino, T., Suzuki, H., & Botteron, K. N. (2012). Maternal support in early childhood predicts larger hippocampal volumes at school age. Proceedings of the National Academy of Sciences, 109(8), 2854–2859. https://doi.org/10.1073/pnas.1118003109
Luby, J., Belden, A., Botteron, K., Marrus, N., Harms, M. P., Babb, C., Nishino, T., & Barch, D. (2013). The effects of poverty on childhood brain development. JAMA Pediatrics, 167(12), 1135. https://doi.org/10.1001/jamapediatrics.2013.3139
Lövdén, M., Bäckman, L., Lindenberger, U., Schaefer, S., & Schmiedek, F. (2010). A theoretical framework for the study of adult cognitive plasticity. Psychological Bulletin, 136(4), 659–676. https://doi.org/10.1037/a0020080
McEwen, B. S., & Morrison, J. H. (2013). The brain on stress: Vulnerability and plasticity of the prefrontal cortex over the life course. Neuron, 79(1), 16–29. https://doi.org/10.1016/j.neuron.2013.06.028
Mulder, H., Verhagen, J., Van der Ven, S. H., Slot, P. L., & Leseman, P. P. (2017). Early executive function at age two predicts emergent mathematics and literacy at age five. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.01706
Nyberg, L., Lövdén, M., Riklund, K., Lindenberger, U., & Bäckman, L. (2012). Memory aging and brain maintenance. Trends in Cognitive Sciences, 16(5), 292–305. https://doi.org/10.1016/j.tics.2012.04.005
Olulade, O. A., Seydell-Greenwald, A., Chambers, C. E., Turkeltaub, P. E., Dromerick, A. W., Berl, M. M., Gaillard, W. D., & Newport, E. L. (2020). The neural basis of language development: Changes in lateralization over age. Proceedings of the National Academy of Sciences, 117(38), 23477–23483. https://doi.org/10.1073/pnas.1905590117
Paré, G., & Kitsiou, S. (2017). Methods for Literature Reviews. In F. Lau & C. Kuziemsky (Eds.), Handbook of eHealth Evaluation: An Evidence-based Approach. University of Victoria. Diunduh dari https://www.ncbi.nlm.nih.gov/books/NBK481583/ tanggal 2 Oktober 2023
Poldrack, R. A., & Packard, M. G. (2003). Competition among multiple memory systems: Converging evidence from Animal and Human Brain Studies. Neuropsychologia, 41(3), 245–251. https://doi.org/10.1016/s0028-3932(02)00157-4
Rosenberg-Lee, M., Chang, T. T., Young, C. B., Wu, S., & Menon, V. (2011). Functional dissociations between four basic arithmetic operations in the human posterior parietal cortex: A cytoarchitectonic mapping study. Neuropsychologia, 49(9), 2592–2608. https://doi.org/10.1016/j.neuropsychologia.2011.04.035
Saygin, Z. M., Norton, E. S., Osher, D. E., Beach, S. D., Cyr, A. B., Ozernov-Palchik, O., Yendiki, A., Fischl, B., Gaab, N., & Gabrieli, J. D. E. (2013). Tracking the roots of reading ability: White matter volume and integrity correlate with phonological awareness in prereading and early-reading Kindergarten Children. The Journal of Neuroscience, 33(33), 13251–13258. https://doi.org/10.1523/jneurosci.4383-12.2013
Schlegel, A. A., Rudelson, J. J., & Tse, P. U. (2012). White matter structure changes as adults learn a second language. Journal of Cognitive Neuroscience, 24(8), 1664–1670. https://doi.org/10.1162/jocn_a_00240
Skeide, M. A., & Friederici, A. D. (2016). The ontogeny of the cortical language network. Nature Reviews Neuroscience, 17(5), 323–332. https://doi.org/10.1038/nrn.2016.23
Tottenham, N., & Galván, A. (2016). Stress and the adolescent brain. Neuroscience & Biobehavioral Reviews, 70, 217–227. https://doi.org/10.1016/j.neubiorev.2016.07.030
Utevsky, A. V., Smith, D. V., & Huettel, S. A. (2014). Precuneus is a functional core of the default-mode network. The Journal of Neuroscience, 34(3), 932–940. https://doi.org/10.1523/jneurosci.4227-13.2014
Walker, M. P., & Stickgold, R. (2004). Sleep-dependent learning and memory consolidation. Neuron, 44(1), 121–133. https://doi.org/10.1016/j.neuron.2004.08.031
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Ivana Nur Intishar

This work is licensed under a Creative Commons Attribution 4.0 International License.
License and Copyright Agreement
- Authors retain copyright and other proprietary rights related to the article.
- Authors retain the right and are permitted to use the substance of the article in their own future works, including lectures and books.
- Authors grant the journal the right of first publication with the work simultaneously licensed under Creative Commons Attribution License (CC BY 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post or self-archive their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
