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Applying functional near-infrared spectroscopy (fNIRS) in educational research: a systematic review

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Abstract

Functional near-infrared spectroscopy (fNIRS) has been applied in educational studies during the past decade, arousing tremendous attention, but lack of a systematic review, which prompted this paper to fill the gap. A systematic search with snowball approach identified 99 peer-reviewed journal papers for in-depth content analysis. The findings revealed that considerable attention was devoted to cognitive domain, while a discernible void was observed in the affective domain, accounting for a mere 10.1% of articles. Most participants were aged between 7 and 11 years old, while the adolescents were not sufficiently investigated. Most studies on infants investigated the temporal region, which showed the great potential of fNIRS exploring language function in the younger age group. More wearable or wireless fNIRS devices applied in education suggested its practicability of cognitive evaluation in physical education and skilled training. Finally, this paper proposed potential prospects for future trends adopting fNIRS in education research (e.g., learning science in real educational context, facilitating brain science in early education, learning analytics based on multi-modal data fusion).

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Data Availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

References

  • Antonenko, P. D., van Gog, T., & Paas, F. (2014). Implications of Neuroimaging for Educational Research. In Handbook of Research on Educational Communications and Technology: Fourth Edition (Issue January, pp. 51–63). Springer. https://doi.org/10.1007/978-1-4614-3185-5.

  • Artemenko, C., Coldea, A., Soltanlou, M., Dresler, T., Nuerk, H. C., & Ehlis, A. C. (2018a). The neural circuits of number and letter copying: An fNIRS study. Experimental Brain Research, 236(4), 1129–1138. https://doi.org/10.1007/s00221-018-5204-8

    Article  PubMed  Google Scholar 

  • Artemenko, C., Soltanlou, M., Dresler, T., Ehlis, A. C., & Nuerk, H. C. (2018b). The neural correlates of arithmetic difficulty depend on mathematical ability: Evidence from combined fNIRS and ERP. Brain Structure and Function, 223(6), 2561–2574. https://doi.org/10.1007/s00429-018-1618-0

    Article  PubMed  Google Scholar 

  • Artemenko, C., Soltanlou, M., Bieck, S. M., Ehlis, A. C., Dresler, T., & Nuerk, H. C. (2019). Individual differences in math ability determine neurocognitive processing of arithmetic complexity: A combined fNIRS-EEG study. Frontiers in Human Neuroscience, 13(July), 1–13. https://doi.org/10.3389/fnhum.2019.00227.

    Article  Google Scholar 

  • Asgher, U., Khan, M. J., Asif Nizami, M. H., Khalil, K., Ahmad, R., Ayaz, Y., & Naseer, N. (2021). Motor Training using Mental workload (MWL) with an Assistive Soft Exoskeleton System: A functional Near-Infrared spectroscopy (fNIRS) study for brain–machine interface (BMI). Frontiers in Neurorobotics, 15(March), 1–20. https://doi.org/10.3389/fnbot.2021.605751.

    Article  Google Scholar 

  • Ayaz, H., Shewokis, P. A., Bunce, S., Izzetoglu, K., Willems, B., & Onaral, B. (2012). Optical brain monitoring for operator training and mental workload assessment. Neuroimage, 59(1), 36–47. https://doi.org/10.1016/j.neuroimage.2011.06.023.

    Article  PubMed  Google Scholar 

  • Badampudi, D., Wohlin, C., & Petersen, K. (2015). Experiences from using snowballing and database searches in systematic literature studies. ACM International Conference Proceeding Series, 27–29. https://doi.org/10.1145/2745802.2745818.

  • Beauchamp, M. S., Beurlot, M. R., Fava, E., Nath, A. R., Parikh, N. A., Saad, Z. S., Bortfeld, H., & Oghalai, J. S. (2011). The developmental trajectory of brain-scalp distance from birth through childhood: Implications for functional neuroimaging. Plos One, 6(9), 1–9. https://doi.org/10.1371/journal.pone.0024981.

    Article  Google Scholar 

  • Benavides-Varela, S., & Gervain, J. (2017). Learning word order at birth: A NIRS study. Developmental Cognitive Neuroscience, 25, 198–208. https://doi.org/10.1016/j.dcn.2017.03.003.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956a). Handbook I: Cognitive domain. David McKay.

  • Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956b). The classification of Educational Goals. Taxonomy of Educational Objectives, 62–197.

  • Blumenfeld, R. S., & Ranganath, C. (2007). Prefrontal cortex and long-term memory encoding: An integrative review of findings from neuropsychology and neuroimaging. The Neuroscientist: A Review Journal Bringing Neurobiology, Neurology And Psychiatry, 13(3), 280–291. https://doi.org/10.1177/1073858407299290.

    Article  PubMed  Google Scholar 

  • Brink, T. T., Urton, K., Held, D., Kirilina, E., Hofmann, M. J., Klann-Delius, G., Jacobs, A. M., & Kuchinke, L. (2011). The role of orbitofrontal cortex in processing empathy stories in 4to 8-year-old children. Frontiers in Psychology, 2(APR), 1–16. https://doi.org/10.3389/fpsyg.2011.00080.

    Article  Google Scholar 

  • Burgess, P. W. (2014). Serial versus concurrent multitasking: From lab to life. In I. J. Fawcett, E. F. Risko, & A. Kingstone (Eds.), The handbook of attention (pp. 443–462). MIT Press.

  • Chong, J. S., Chan, Y. L., Ebenezer, E. G. M., Chen, H. Y., Kiguchi, M., Lu, C. K., & Tang, T. B. (2020). fNIRS-based functional connectivity estimation using semi-metric analysis to study decision making by nursing students and registered nurses. Scientific Reports, 10(1), 1–12. https://doi.org/10.1038/s41598-020-79053-z.

    Article  Google Scholar 

  • Da Barreto, S. F., Zimeo Morais, C., Vanzella, G. A., P., & Sato, J. R. (2020). Combining the intersubject correlation analysis and the multivariate distance matrix regression to evaluate associations between fNIRS signals and behavioral data from ecological experiments. Experimental Brain Research, 238(10), 2399–2408. https://doi.org/10.1007/s00221-020-05895-8.

    Article  Google Scholar 

  • de Roever, I., Bale, G., Mitra, S., Meek, J., Robertson, N. J., & Tachtsidis, I. (2018). Investigation of the pattern of the hemodynamic response as measured by functional near-infrared spectroscopy (fNIRS) studies in newborns, less than a month old: A systematic review. Frontiers in Human Neuroscience, 12(October), https://doi.org/10.3389/fnhum.2018.00371.

  • Delİce, A. (2001). The sampling issues in quantitative research. Educational Sciences: Theory & Practices, 10(4), 2001–2019.

    Google Scholar 

  • Dybvik, H., & Steinert, M. (2021). Real-world fNIRS brain activity measurements during. Brain Sciences, 11(6), 742.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fairchild, G., Hagan, C. C., Walsh, N. D., Passamonti, L., Calder, A. J., & Goodyer, I. M. (2013). Brain structure abnormalities in adolescent girls with conduct disorder. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54(1), 86–95. https://doi.org/10.1111/j.1469-7610.2012.02617.x.

    Article  PubMed  Google Scholar 

  • Felizardo, K. R., Mendes, E., Kalinowski, M., Souza, É. F., & Vijaykumar, N. L. (2016). Using Forward Snowballing to update Systematic Reviews in Software Engineering. International Symposium on Empirical Software Engineering and Measurement, 08-09-Sept. https://doi.org/10.1145/2961111.2962630.

  • Ferreri, L., Bigand, E., Bard, P., & Bugaiska, A. (2015). The Influence of Music on Prefrontal Cortex during Episodic Encoding and Retrieval of Verbal Information: A Multichannel fNIRS Study. Behavioural Neurology, 2015. https://doi.org/10.1155/2015/707625.

  • Ferry, A. L., Fló, A., Brusini, P., Cattarossi, L., Macagno, F., Nespor, M., & Mehler, J. (2016). On the edge of language acquisition: Inherent constraints on encoding multisyllabic sequences in the neonate brain. Developmental Science, 19(3), 488–503. https://doi.org/10.1111/desc.12323.

    Article  PubMed  Google Scholar 

  • Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3).

  • Frijda, N. H., & Scherer, K. R. (2009). Emotion definitions (psychological perspectives). The Oxford Companion to Emotion and the Affective Sciences, 142–144.

  • Groba, A., De Houwer, A., Obrig, H., & Rossi, S. (2019). Bilingual and monolingual first language acquisition experience differentially shapes children’s property term learning: Evidence from behavioral and neurophysiological measures. Brain Sciences, 9(2), 1–28. https://doi.org/10.3390/brainsci9020040.

    Article  Google Scholar 

  • Gross, J. J. (1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2(3), 271–299. https://doi.org/10.1037/1089-2680.2.3.271.

    Article  Google Scholar 

  • Hallez, H., Vanrumste, B., Grech, R., Muscat, J., De Clercq, W., Vergult, A., D’Asseler, Y., Camilleri, K. P., Fabri, S. G., Van Huffel, S., & Lemahieu, I. (2007). Review on solving the forward problem in EEG source analysis. Journal of NeuroEngineering and Rehabilitation, 4, https://doi.org/10.1186/1743-0003-4-46.

  • Harrow, A. J. (1972). A taxonomy of the Psychomotor Domain: A guide for developing behavioral objectives. Physical Therapy, 54(9), 1031–1032.

    Google Scholar 

  • He, Y., Wang, M. Y., Li, D., & Yuan, Z. (2017). Optical mapping of brain activation during the English to Chinese and Chinese to English sight translation. Biomedical Optics Express, 8(12), 5399. https://doi.org/10.1364/boe.8.005399.

    Article  PubMed  PubMed Central  Google Scholar 

  • Herold, F., Wiegel, P., Scholkmann, F., & Müller, N. (2018). Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise–Cognition Science: A systematic, methodology-focused review. Journal of Clinical Medicine, 7(12), 466. https://doi.org/10.3390/jcm7120466.

    Article  PubMed  PubMed Central  Google Scholar 

  • Homae, F., Watanabe, H., Nakano, T., & Taga, G. (2011). Large-scale brain networks underlying language acquisition in early infancy. Frontiers in Psychology, 2(MAY), 1–14. https://doi.org/10.3389/fpsyg.2011.00093.

    Article  Google Scholar 

  • Homae, F., Watanabe, H., & Taga, G. (2014). The neural substrates of infant speech perception. Language Learning, 64(SUPPL.2), 6–26. https://doi.org/10.1111/lang.12076.

    Article  Google Scholar 

  • Howell-munson, A., Sonmez, D., Walker, E., & Solovey, E. (2021). Preliminary steps towards detection of proactive and reactive control states during learning with fNIRS brain signals. 1–10.

  • Hu, Z., Liu, G., Dong, Q., & Niu, H. (2020). Applications of resting-state fNIRS in the developing brain: A review from the Connectome Perspective. Frontiers in Neuroscience, 14(June), 1–12. https://doi.org/10.3389/fnins.2020.00476.

    Article  Google Scholar 

  • Huebner, T., Vloet, T. D., Marx, I., Konrad, K., Fink, G. R., Herpertz, S. C., & Herpertz-Dahlmann, B. (2008). Morphometric brain abnormalities in boys with conduct disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 47(5), 540–547. https://doi.org/10.1097/CHI.0b013e3181676545.

    Article  PubMed  Google Scholar 

  • Jasińska, K. K., Berens, M. S., Kovelman, I., & Petitto, L. A. (2017). Bilingualism yields language-specific plasticity in left hemisphere’s circuitry for learning to read in young children. Neuropsychologia, 98(November 2016), 34–45. https://doi.org/10.1016/j.neuropsychologia.2016.11.018.

  • John T. Bruer. (1997). Education and the brain: A Brige Too Far. Educational Researcher, 26(8), 4–16.

    Article  Google Scholar 

  • Kerr, J., Molloy, C., Reddy, P., Shewokis, P. A., & Izzetoglu, K. (2021). Individual Differences in fNIRS Measures of Cognitive Workload During a UAS Mission. In Augmented Cognition (pp. 49–62). Springer International Publishing. https://doi.org/10.1007/978-3-030-78114-9_4.

  • Kersey, A. J., & Emberson, L. L. (2017). Tracing trajectories of audio-visual learning in the infant brain. Developmental Science, 20(6), 1–13. https://doi.org/10.1111/desc.12480.

    Article  Google Scholar 

  • Kleinginna, P. R., & Kleinginna, A. M. (1981). A categorized list of motivation definitions, with a suggestion for a consensual definition. Motivation and Emotion, 5(3), 263–291. https://doi.org/10.1007/BF00993889.

    Article  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Kruesi, M. J. P., Casanova, M. F., Mannheim, G., & Johnson-Bilder, A. (2004). Reduced temporal lobe volume in early onset conduct disorder. Psychiatry Research, 132(1), 1–11. https://doi.org/10.1016/j.pscychresns.2004.07.002.

    Article  PubMed  Google Scholar 

  • Lai, C. Y. Y., Ho, C. S. H., Lim, C. R., & Ho, R. C. M. (2017). Functional near-infrared spectroscopy in psychiatry. BJPsych Advances, 23(5), 324–330. https://doi.org/10.1192/apt.bp.115.015610.

    Article  Google Scholar 

  • Lawrence, R. J., Wiggins, I. M., Hodgson, J. C., & Hartley, D. E. H. (2021). Evaluating cortical responses to speech in children: A functional near-infrared spectroscopy (fNIRS) study. Hearing Research, 401, 108155. https://doi.org/10.1016/j.heares.2020.108155.

    Article  PubMed  PubMed Central  Google Scholar 

  • León-Carrión, J., Izzetoglu, M., Izzetoglu, K., Martín-Rodríguez, J. F., Damas-López, J., Martin, J.M. B. y., & Domínguez-Morales, M. R. (2010). Efficient learning produces spontaneous neural repetition suppression in prefrontal cortex. Behavioural Brain Research, 208(2), 502–508. https://doi.org/10.1016/j.bbr.2009.12.026.

  • Li, C., Ding, K., Zhang, M., Zhang, L., Zhou, J., & Yu, D. (2020a). Effect of Picture-Book Reading with Additive Audio on Bilingual Preschoolers’ Prefrontal activation: A naturalistic functional Near-Infrared Spectroscopy Study. Frontiers in Psychology, 11(August), 1–13. https://doi.org/10.3389/fpsyg.2020a.01939

    Article  Google Scholar 

  • Li, H., Hsueh, Y., Yu, H., & Kitzmann, K. M. (2020b). Viewing fantastical events in animated television shows: Immediate Effects on chinese preschoolers’ executive function. Frontiers in Psychology, 11(December), 1–14. https://doi.org/10.3389/fpsyg.2020b.583174

    Article  Google Scholar 

  • Mareschal, D., Butterworth, B., & Tolmie, A. (2013). Educational Neuroscience. Wiley. https://books.google.co.jp/books?id=daILAQAAQBAJ.

  • Martín-Loeches, M., Casado, P., Hernández-Tamames, J. A., & Álvarez-Linera, J. (2008). Brain activation in discourse comprehension: A 3t fMRI study. Neuroimage, 41(2), 614–622. https://doi.org/10.1016/j.neuroimage.2008.02.047.

    Article  PubMed  Google Scholar 

  • Mauri, M., Grazioli, S., Crippa, A., Bacchetta, A., Pozzoli, U., Bertella, S., Gatti, E., Maggioni, E., Rosi, E., Diwadkar, V., Brambilla, P., Molteni, M., & Nobile, M. (2020). Hemodynamic and behavioral peculiarities in response to emotional stimuli in children with attention deficit hyperactivity disorder: An fNIRS study. Journal of Affective Disorders, 277(August), 671–680. https://doi.org/10.1016/j.jad.2020.08.064.

    Article  PubMed  Google Scholar 

  • May, L., Byers-Heinlein, K., Gervain, J., & Werker, J. F. (2011). Language and the newborn brain: Does prenatal language experience shape the neonate neural response to speech? Frontiers in Psychology, 2(SEP), 1–9. https://doi.org/10.3389/fpsyg.2011.00222.

    Article  Google Scholar 

  • Mayberg, H. S., Liotti, M., Brannan, S. K., McGinnis, S., Mahurin, R. K., Jerabek, P. A., Silva, J. A., Tekell, J. L., Martin, C. C., Lancaster, J. L., & Fox, P. T. (2013). Reciprocal limbic-cortical function and negative mood: Converging PET findings in depression and normal sadness. Depression: The Science of Mental Health, 6(May), 245–253. https://doi.org/10.1176/ajp.156.5.675.

    Article  Google Scholar 

  • Mckay, C., Wijeakumar, S., Rafetseder, E., & Lee, Y. (2021). Disentangling Age and Schooling Effects on Inhibitory Control Development: An fNIRS Investigation. 1–44.

  • Niu, H., Li, H., Sun, L., Su, Y., Huang, J., & Song, Y. (2014). Visual Learning Alters the Spontaneous Activity of the Resting Human Brain: An fNIRS Study. BioMed Research International, 2014. https://doi.org/10.1155/2014/631425.

  • Obrig, H., Mock, J., Stephan, F., Richter, M., Vignotto, M., & Rossi, S. (2017). Impact of associative word learning on phonotactic processing in 6-month-old infants: A combined EEG and fNIRS study. Developmental Cognitive Neuroscience, 25, 185–197. https://doi.org/10.1016/j.dcn.2016.09.001.

    Article  PubMed  Google Scholar 

  • Paquette, N., Lassonde, M., Vannasing, P., Tremblay, J., González-Frankenberger, B., Florea, O., Béland, R., Lepore, F., & Gallagher, A. (2015). Developmental patterns of expressive language hemispheric lateralization in children, adolescents and adults using functional near-infrared spectroscopy. Neuropsychologia, 68, 117–125. https://doi.org/10.1016/j.neuropsychologia.2015.01.007.

    Article  PubMed  Google Scholar 

  • Peng, C., & Hou, X. (2021). Applications of functional near-infrared spectroscopy (fNIRS) in neonates. Neuroscience Research, 170, 18–23. https://doi.org/10.1016/j.neures.2020.11.003.

    Article  PubMed  Google Scholar 

  • Perlman, S. B., Huppert, T. J., & Luna, B. (2016). Functional Near-Infrared Spectroscopy evidence for development of Prefrontal Engagement in Working Memory in Early through Middle Childhood. Cerebral Cortex, 26(6), 2790–2799. https://doi.org/10.1093/cercor/bhv139.

    Article  PubMed  Google Scholar 

  • Pessoa, L. (2008). On the relationship between emotion and cognition. Nature Reviews Neuroscience, 9, 148–158. https://doi.org/10.1007/978-3-030-65072-8_13.

    Article  PubMed  Google Scholar 

  • Petitto, L. A., Berens, M. S., Kovelman, I., Dubins, M. H., Jasinska, K., & Shalinsky, M. (2012). The “Perceptual Wedge Hypothesis” as the basis for bilingual babies’ phonetic processing advantage: New insights from fNIRS brain imaging. Brain and Language, 121(2), 130–143. https://doi.org/10.1016/j.bandl.2011.05.003.

    Article  PubMed  Google Scholar 

  • Pinti, P., Aichelburg, C., Gilbert, S., Hamilton, A., Hirsch, J., Burgess, P., & Tachtsidis, I. (2018). A review on the Use of Wearable Functional Near-Infrared Spectroscopy in naturalistic environments. Japanese Psychological Research, 60(4), 347–373. https://doi.org/10.1111/jpr.12206.

    Article  PubMed  Google Scholar 

  • Rossi, S., Gugler, M. F., Rungger, M., Galvan, O., Zorowka, P. G., & Seebacher, J. (2020). How the brain understands spoken and sung sentences. Brain Sciences, 10(1), 36. https://doi.org/10.3390/brainsci10010036.

    Article  PubMed  PubMed Central  Google Scholar 

  • Rueckert, L., & Grafman, J. (1998). Sustained attention deficits in patients with lesions of posterior cortex. Neuropsychologia, 36(7), 653–660. https://doi.org/10.1016/S0028-3932(97)00150-4.

    Article  PubMed  Google Scholar 

  • Sakurada, T., Hirai, M., & Watanabe, E. (2019). Individual optimal attentional strategy during implicit motor learning boosts frontoparietal neural processing efficiency: A functional near-infrared spectroscopy study. Brain and Behavior, 9(1), 1–13. https://doi.org/10.1002/brb3.1183.

    Article  Google Scholar 

  • Sala, S. D., & Anderson, M. (2012). Neuroscience in Education: The good, the bad, and the ugly. OUP Oxford. https://books.google.co.jp/books?id=pFE5UCaFwEQC.

  • Scholkmann, F., Kleiser, S., Metz, A. J., Zimmermann, R., Mata Pavia, J., Wolf, U., & Wolf, M. (2014). A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage, 85, 6–27. https://doi.org/10.1016/J.NEUROIMAGE.2013.05.004.

    Article  PubMed  Google Scholar 

  • Seidel, O., Carius, D., Kenville, R., & Ragert, P. (2017). Motor learning in a complex balance task and associated neuroplasticity: A comparison between endurance athletes and nonathletes. Journal of Neurophysiology, 118(3), 1849–1860. https://doi.org/10.1152/jn.00419.2017.

    Article  PubMed  PubMed Central  Google Scholar 

  • Shewokis, P. A., Shariff, F. U., Liu, Y., Ayaz, H., Castellanos, A., & Lind, D. S. (2017). Acquisition, retention and transfer of simulated laparoscopic tasks using fNIR and a contextual interference paradigm. American Journal of Surgery, 213(2), 336–345. https://doi.org/10.1016/j.amjsurg.2016.11.043.

    Article  PubMed  Google Scholar 

  • Soltanlou, M., Artemenko, C., Dresler, T., Haeussinger, F. B., Fallgatter, A. J., Ehlis, A. C., & Nuerk, H. C. (2017). Increased arithmetic complexity is associated with domain-general but not domain-specific magnitude processing in children: A simultaneous fNIRS-EEG study. Cognitive Affective and Behavioral Neuroscience, 17(4), 724–736. https://doi.org/10.3758/s13415-017-0508-x.

    Article  Google Scholar 

  • Soltanlou, M., Sitnikova, M. A., Nuerk, H. C. C., & Dresler, T. (2018). Applications of functional near-infrared spectroscopy (fNIRS) in studying cognitive development: The case of mathematics and language. Frontiers in Psychology, 9(APR), https://doi.org/10.3389/fpsyg.2018.00277.

  • Sterzer, P., Stadler, C., Poustka, F., & Kleinschmidt, A. (2007). A structural neural deficit in adolescents with conduct disorder and its association with lack of empathy. Neuroimage, 37(1), 335–342. https://doi.org/10.1016/j.neuroimage.2007.04.043.

    Article  PubMed  Google Scholar 

  • Sugiura, L., Hata, M., Matsuba-Kurita, H., Uga, M., Tsuzuki, D., Dan, I., Hagiwara, H., & Homae, F. (2018). Explicit performance in girls and implicit processing in boys: A simultaneous fNIRS–ERP study on second language syntactic learning in young adolescents. Frontiers in Human Neuroscience, 12(March), 1–19. https://doi.org/10.3389/fnhum.2018.00062.

    Article  Google Scholar 

  • Tak, S., & Ye, J. C. (2014). Statistical analysis of fNIRS data: A comprehensive review. Neuroimage, 85, 72–91. https://doi.org/10.1016/J.NEUROIMAGE.2013.06.016.

    Article  PubMed  Google Scholar 

  • Takeuchi, N., Mori, T., Suzukamo, Y., & Izumi, S. I. (2019). Activity of Prefrontal Cortex in Teachers and students during teaching of an insight problem. Mind Brain and Education, 13(3), 167–175. https://doi.org/10.1111/mbe.12207.

    Article  Google Scholar 

  • Tang, T. B., Chong, J. S., Kiguchi, M., Funane, T., & Lu, C. K. (2021). Detection of emotional sensitivity using fNIRS based dynamic functional connectivity. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 894–904. https://doi.org/10.1109/TNSRE.2021.3078460.

    Article  PubMed  Google Scholar 

  • Telkemeyer, S., Rossi, S., Nierhaus, T., Steinbrink, J., Obrig, H., & Wartenburger, I. (2011). Acoustic processing of temporally modulated sounds in infants: Evidence from a combined near-infrared spectroscopy and EEG study. Frontiers in Psychology, 2(APR), 1–14. https://doi.org/10.3389/fpsyg.2011.00062.

    Article  Google Scholar 

  • Tianran, H., & Buwei, Y. (2014). The application of functional near infrared spectroscopy in cognitive neuroscience. International Journal of Anesthesiology and Resuscitation|Int J Anesth Resus, 35(10), 932–935.

    Google Scholar 

  • Uysal, M. P. (2016). Evaluation of learning environments for object-oriented programming: Measuring cognitive load with a novel measurement technique. Interactive Learning Environments, 24(7), 1590–1609. https://doi.org/10.1080/10494820.2015.1041400.

    Article  Google Scholar 

  • Wilcox, T., & Biondi, M. (2015). fNIRS in the developmental sciences. Wiley Interdisciplinary Reviews: Cognitive Science, 6(3), 263–283. https://doi.org/10.1002/wcs.1343.

    Article  PubMed  Google Scholar 

  • Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. ACM International Conference Proceeding Series. https://doi.org/10.1145/2601248.2601268.

  • Wohlin, C. (2016). Second-generation systematic literature studies using snowballing. ACM International Conference Proceeding Series, 01-03-June, 3–8. https://doi.org/10.1145/2915970.2916006.

  • Wohlin, C., Kalinowski, M., Romero Felizardo, K., & Mendes, E. (2022). Successful combination of database search and snowballing for identification of primary studies in systematic literature studies. Information and Software Technology, 147(March), 106908. https://doi.org/10.1016/j.infsof.2022.106908.

    Article  Google Scholar 

  • Wolfe, J. M., Horowitz, T. S., Van Wert, M. J., Kenner, N. M., Place, S. S., & Kibbi, N. (2007). Low target prevalence is a stubborn source of errors in visual search tasks. Journal of Experimental Psychology General, 136(4), 623–638. https://doi.org/10.1037/0096-3445.136.4.623.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wood, A. G., Harvey, A. S., Wellard, R. M., Abbott, D. F., Anderson, V., Kean, M., Saling, M. M., & Jackson, G. D. (2004). Language cortex activation in normal children. Neurology, 63(6), https://doi.org/10.1212/01.WNL.0000140707.61952.CA. 1035 LP – 1044.

  • Yang, Y., Li, Y., Wang, X., Liu, N., Jiang, K., Zhang, S., & Qiu, J. (2021). Cognitive inhibition mediates the relationship between ESL listening proficiency and English spoken word segmentation in Chinese learners: A functional near-infrared spectroscopy (fNIRS) study. Journal of Neurolinguistics, 59(October 2020), 100987. https://doi.org/10.1016/j.jneuroling.2021.100987.

  • Yeung, M. K. (2021). An optical window into brain function in children and adolescents: A systematic review of functional near-infrared spectroscopy studies: fNIRS in developmental cognitive neuroscience. NeuroImage, 227(December 2020), 117672. https://doi.org/10.1016/j.neuroimage.2020.117672.

  • Yeung, M. K., & Chan, A. S. (2021). A systematic review of the application of Functional Near-InfraredSpectroscopy to the study of cerebral hemodynamics in healthy aging. Neuropsychology Review, 31(1), 139–166. https://doi.org/10.1007/s11065-020-09455-3.

    Article  PubMed  Google Scholar 

  • Ying, Z. (2014). Foundations of Experimantal Psychology. In Peking University Press (3rd ed.).

  • Zhan, Z., Wu, J., Mei, H., Wu, Q., & Fong, P. S. W. (2020). Individual difference on reading ability tested by eye-tracking: From perspective of gender. Interactive Technology and Smart Education, 17(3), 267–283.

    Article  Google Scholar 

  • Zhang, F., & Roeyers, H. (2019). Exploring brain functions in autism spectrum disorder: A systematic review on functional near-infrared spectroscopy (fNIRS) studies. International Journal of Psychophysiology, 137(August 2018), 41–53. https://doi.org/10.1016/j.ijpsycho.2019.01.003.

  • Zhao, H., Li, X., Karolis, V., Feng, Y., Niu, H., & Butterworth, B. (2019). Arithmetic learning modifies the functional connectivity of the fronto-parietal network. Cortex; A Journal Devoted To The Study Of The Nervous System And Behavior, 111, 51–62. https://doi.org/10.1016/j.cortex.2018.07.016.

    Article  PubMed  Google Scholar 

  • Zhao, H., Zhang, T., Cheng, T., Chen, C., Zhai, Y., Liang, X., Cheng, N., Long, Y., Li, Y., & Wang, Z. (2023). Neurocomputational mechanisms of young children’s observational learning of delayed gratification. Cerebral Cortex, 33(10), 6063–6076.

    Article  PubMed  Google Scholar 

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Funding

This research was financially supported by the National Natural Science Foundation in China (62277018; 62237001), the Ministry of Education in China Project of Humanities and Social Sciences (22YJC880106), the Major Project of Social Science in South China Normal University (ZDPY2208), the Degree and graduate education Reform research project in Guangdong (2023JGXM046).

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The idea was proposed by [Zehui Zhan] performed the literature search. [Qinchen Yang] has conducted the paper coding, data analysis, and drafted the paper. [Lixia Luo] and [Xia Zhang] also implemented the paper coding. [Zehui Zhan] and [Qinchen Yang] finally revised the work.

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Correspondence to Zehui Zhan.

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Zhan, Z., Yang, Q., Luo, L. et al. Applying functional near-infrared spectroscopy (fNIRS) in educational research: a systematic review. Curr Psychol 43, 9676–9691 (2024). https://doi.org/10.1007/s12144-023-05094-y

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