Abstract

Attention-based learning tasks of modern classrooms require processing of information in working memory. Not much is known about the cognitive processes operating during these tasks. To gain an understanding of the processes that support cognitive functions like learning, we have monitored the activity of the brain waves emanating from the frontal lobes region of a group of high school students working on a series of conceptually-linked tasks using a commercially available electroencephalographic (EEG) headband. Analysis of the EEG recordings revealed an increase in the relative power of gamma and beta as students worked through the tasks, suggesting that they were adding items in the working memory, retaining them, retrieving and reading them out for either use in the tasks or disposal. Remarkably, a decrease in alpha activity indicated that students seem to be attenuating the inhibition of distracting images retrieved from memory to make a larger pool of words available for solving the word puzzle. Such cognitive processing probably increased the load in the working memory as indicated by reduction in theta activity. Lastly, the students increased wakeful attention and alertness by lowering the delta activity. These results provide new insights into the cognitive functions operating during attention-based classroom learning tasks.

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References

• Baddeley, A. D. (2003). Working memory: looking back and looking forward. Nature Reviews Neuroscience, 4(10), 829–839. https://doi.org/10.1038/nrn1201
• Bollimunta, A., Mo, J., Schroeder, C. E., & Ding, M. (2011). Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. The Journal of Neuroscience, 31(13), 4935–4943. https://doi.org/10.1523/jneurosci.5580-10.2011
• Bruner, J. S. (1961). The Act of Discovery. Harvard Educational Review, 31, 21–32.
• Bruner, J. S., & Bruner, U. P. J. (1966). Toward a theory of ınstruction. Harvard University Press.
• Brzezicka, A., Kamiński, J., Reed, C. M., Chung, J. M., Mamelak, A. N., & Rutishauser, U. (2019). Working memory load-related theta power decreases in dorsolateral prefrontal cortex predict individual differences in performance. Journal of Cognitive Neuroscience, 31(9), 1290–1307. https://doi.org/10.1162/jocn_a_01417
• Chafee, M. V., & Crowe, D. A. (2017). Implicit and explicit learning mechanisms meet in monkey prefrontal cortex. Neuron, 96(2), 256-258. https://doi.org/10.1016/j.neuron.2017.09.049
• Colgin, L. L. (2013). Mechanisms and functions of theta rhythms. Annual Review of Neuroscience, 36(1), 295–312. https://doi.org/10.1146/annurev-neuro-062012-170330
• Constantinople, C. M., & Bruno, R. M. (2011). Effects and mechanisms of wakefulness on local cortical networks. Neuron, 69(6), 1061–1068. https://doi.org/10.1016/j.neuron.2011.02.040
• Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1), 87–114. https://doi.org/10.1017/s0140525x01003922
• Eichenbaum, H. (1999). Conscious awareness, memory and the hippocampus. Nature Neuroscience, 2(9), 775–776. https://doi.org/10.1038/12137
• Fernández, T., Harmony, T., Rodriguez, M. H., Bernal, J., Silva, J. R. H., Reyes, A., & Marosi, E. (1995). EEG activation patterns during the performance of tasks involving different components of mental calculation. Electroencephalography and Clinical Neurophysiology, 94(3), 175–182. https://doi.org/10.1016/0013-4694(94)00262-j
• Foxe, J. J., & Snyder, A. C. (2011). The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Frontiers in Psychology, 2, 154. https://doi.org/10.3389/fpsyg.2011.00154
• Palacios-García, I., Silva, J. R., Villena-González, M., Campos-Arteaga, G., Artigas-Vergara, C., Luarte, N., Rodríguez, E. B., & Bosman, C. A. (2021). Increase in beta power reflects attentional top-down modulation after psychosocial stress induction. Frontiers in Human Neuroscience, 15 630813. https://doi.org/10.3389/fnhum.2021.630813
• Gärtner, M., Grimm, S., & Bajbouj, M. (2015). Frontal midline theta oscillations during mental arithmetic: effects of stress. Frontiers in Behavioral Neuroscience, 9, 96. https://doi.org/10.3389/fnbeh.2015.00096
• Gentner, D., & Gentner, D. R. (1983). Flowing waters or teeming crowds: Mental models of electricity. In D. Gentner & A. L. Stevens (Eds.), Mental models (pp. 99-129). Lawrence Erlbaum Associates.
• Harmony, T. (2013). The functional significance of delta oscillations in cognitive processing. Frontiers in Integrative Neuroscience, 7, 83. https://doi.org/10.3389/fnint.2013.00083
• Hashimoto, H., Hasegawa, Y., Araki, T., Sugata, H., Yanagisawa, T., Yorifuji, S. & Hirata, M. (2017). Non-invasive detection of language-related prefrontal high gamma band activity with beamforming MEG. Scientific Reports 7, 14262-14270. DOI: https://doi.org/10.1038/s41598-017-14452-3
• Howard, M. W., Rizzuto, D. S., Caplan, J. B., Madsen, J. R., Lisman, J., Aschenbrenner-Scheibe, R., ... & Kahana, M. J. (2003). Gamma oscillations correlate with working memory load in humans. Cerebral cortex, 13(12), 1369-1374. https://doi.org/10.1093/cercor/bhg084
• Hsieh, L. T., & Ranganath, C. (2014). Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval. NeuroImage, 85, 721–729. https://doi.org/10.1016/j.neuroimage.2013.08.003
• Huang, Y., Cheng, Y., Cheng, S., & Chen, Y. Y. (2020). Exploring the correlation between attention and cognitive load through association rule mining by using a brainwave sensing headband. IEEE Access, 8, 38880–38891. https://doi.org/10.1109/access.2020.2975054
• Jaiswal, S., Tsai, S. Y., Juan, C. H., Muggleton, N. G., & Liang, W. (2019). Low delta and high alpha power are associated with better conflict control and working memory in high mindfulness, low anxiety individuals. Social Cognitive and Affective Neuroscience, 14(6), 645–655. https://doi.org/10.1093/scan/nsz038
• Johnson, J. A., Sutterer, D., Acheson, D. J., Lewis-Peacock, J. A., & Postle, B. R. (2011). Increased alpha-band power during the retention of shapes and shape-location associations in visual short-term memory. Frontiers in Psychology, 2, 128. https://doi.org/10.3389/fpsyg.2011.00128
• Klimesch, W., Doppelmayr, M., Schimke, H., & Ripper, B. (1997). Theta synchronization and alpha desynchronization in a memory task. Psychophysiology, 34(2), 169–176. https://doi.org/10.1111/j.1469-8986.1997.tb02128.x
• Locke, J. (1948). An essay concerning human understanding, 1690. In W. Dennis (Ed.), Readings in the history of psychology (pp. 55–68). Appleton-Century-Crofts. https://doi.org/10.1037/11304-008
• Lundqvist, M., Herman, P., Warden, M. R., Brincat, S. L., & Miller, E. K. (2018). Gamma and beta bursts during working memory readout suggest roles in its volitional control. Nature Communications, 9(1), 494. https://doi.org/10.1038/s41467-017-02791-8
• Neely, J. H. (1977). Semantic priming and retrieval from lexical memory: Roles of inhibitionless spreading activation and limited-capacity attention. Journal of Experimental Psychology, 106(3), 226–254. https://doi.org/10.1037/0096-3445.106.3.226
• Minteer, S. D., Liang, Z., He, B., Zhao, C., Yao, W., Xu, G., Xie, J., & Cui, L. (2019). Attention-controlled assistive wrist rehabilitation using a low-cost EEG sensor. IEEE Sensors Journal, 19(15), 6497–6507. https://doi.org/10.1109/jsen.2019.2910318
• Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390(6657), 279–281. https://doi.org/10.1038/36846
• Oby, E. R., Golub, M. D., Hennig, J. A., Degenhart, A. D., Tyler-Kabara, E. C., Yu, B. M., Chase, S. M., & Batista, A. P. (2019). New neural activity patterns emerge with long-term learning. Proceedings of the National Academy of Sciences of the United States of America, 116(30), 15210–15215. https://doi.org/10.1073/pnas.1820296116
• Piaget, J. (2013). The construction of reality in the child. Routledge. https://doi.org/10.4324/9781315009650
• Pina, J. E., Bodner, M., & Ermentrout, G. B. (2018). Oscillations in working memory and neural binding: A mechanism for multiple memories and their interactions. PLOS Computational Biology, 14(11), e1006517. https://doi.org/10.1371/journal.pcbi.1006517
• Pinson, A., Xing, L., Namba, T., Kalebic, N., Peters, J., Oegema, C. E., Traikov, S., Reppe, K., Riesenberg, S., Maricic, T., Derihaci, R., Wimberger, P., Pääbo, S., & Huttner, W. B. (2022). Human TKTL1 implies greater neurogenesis in frontal neocortex of modern humans than Neanderthals. Science, 377(6611). https://doi.org/10.1126/science.abl6422
• Reber, P. J., & Squire, L. R. (1994). Parallel brain systems for learning with and without awareness. Learning & Memory, 1(4), 217–229. https://doi.org/10.1101/lm.1.4.217
• Schmidt, R. L., Ruiz, M. T., Kilavik, B. E., Lundqvist, M., Starr, P. A., & Aron, A. R. (2019). Beta oscillations in working memory, executive control of movement and thought, and sensorimotor function. The Journal of Neuroscience, 39(42), 8231–8238. https://doi.org/10.1523/jneurosci.1163-19.2019
• Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66. https://doi.org/10.1037/0033-295x.84.1.1
• Schneider, W., & Fisk, A. D. (1982). Concurrent automatic and controlled visual search: Can processing occur without resource cost? Journal of Experimental Psychology: Learning, Memory and Cognition, 8(4), 261–278. https://doi.org/10.1037/0278-7393.8.4.261
• Singer, W. (1993). Synchronization of cortical activity and its putative role in information processing and learning. Annual Review of Physiology, 55(1), 349–374. https://doi.org/10.1146/annurev.ph.55.030193.002025
• Skinner, B. (1974). About Behaviorism. Vintage.
• Steriade, M., McCormick, D. A., & Sejnowski, T. J. (1993). Thalamocortical oscillations in the sleeping and aroused brain. Science, 262(5134), 679–685. https://doi.org/10.1126/science.8235588
• Todd, J., & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature, 428(6984), 751–754. https://doi.org/10.1038/nature02466
• Uzun, S., & Şen, N. (2023). The effects of a STEM-based intervention on middle school students science achievement and learning motivation. Journal of Pedagogical Research, 7(1), 228-242. https://doi.org/10.33902/jpr.202319315
• Vogel, E. K., Woodman, G. F., & Luck, S. J. (2001). Storage of features, conjunctions, and objects in visual working memory. Journal of Experimental Psychology: Human Perception and Performance, 27(1), 92–114. https://doi.org/10.1037/0096-1523.27.1.92
• Vygotsky, L. S. (1978). Mind in society: Development of higher psychological processes. Harvard University Press. https://doi.org/10.2307/j.ctvjf9vz4
• Woods, D. R. (1987). How might I teach problem solving. New Directions for Teaching and Learning, 30, 55–71.
• Yin, J., & Yuan, Q. (2015). Structural homeostasis in the nervous system: a balancing act for wiring plasticity and stability. Frontiers in Cellular Neuroscience, 8, 439. https://doi.org/10.3389/fncel.2014.00439
• Zhang, Y., Zhang, Y., Cai, P., Luo, H., & Fang, F. (2019). The causal role of α-oscillations in feature binding. Proceedings of the National Academy of Sciences of the United States of America, 116(34), 17023–17028. https://doi.org/10.1073/pnas.1904160116

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