Abstract
In ageing society, it is not only that we need better care and treatment to maintain the quality of life of elderly population but also need better ways to strengthen the development of our children so that we could live in a healthy ageing society. This study proposed a framework for human learning ability study by using multimodal neuroimaging through simultaneous EEG/fNIRS measurement and neuroinformatics to understand target learning ability in laboratory and using portable EEG device to monitor real-time brain state for evaluating the learning/teaching methods introduced for improving the target learning ability in learning environment. By incorporating neuroscience approach in both laboratory and learning environment, not only scientific findings from neuroscience studies could give implications to educators to improve students’ learning, but also the developed learning/teaching methods could be assessed their effectiveness in classroom practice. This framework may help contribute in bridging the gap between neuroscience and education, which is the aim of educational neuroscience. Toward smart education, the proposed conceptual framework deploys truly brain-based learning/teaching approach to enhance students’ learning to better acquire the knowledge and cognitive skills.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Oblinger, D., Oblinger, J.: Is it age or it: first steps toward understanding the net generation. Educating the Net Generation. EDUCAUSE (2005)
Moore, S., Barrett, T.: New Approaches to Problem-based Learning: Revitalising Your Practice in Higher Education. Routledge, New York (2010)
Kaewkamnerdpong, B.: Problem-based learning approach for bio-inspired artificial intelligence: a case study. In: Proceedings of International Consortium for Educational Development (ICED), pp. 327–330, Bangkok, Thailand, 23-25 July 2012
Neuroscience and Education: Issues and Opportunities. Teaching and Learning Research Programme, The Economic and Social Research Council (2007)
Shibasaki, H.: Human brain mapping: hemodynamic response and electrophysiology. Clin. Neurophysiol. 119, 731–743 (2008)
Shibasaki, H., Ikeda, A., Nagamine, T.: Use of magnetoencephalography in the presurgical evaluation of epilepsy patients. Clin. Neurophysiol. 118, 1438–1448 (2007)
Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A.: Neuro-physiological investigation of the basis of the fMRI signal. Nature 412, 150–157 (2001)
Devor, A., Ulbert, I., Dunn, A.K., Narayanan, S.N., Jones, S.R., Andermann, M.L., Boas, D.A., Dale, A.M.: Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity. Proc. Natl. Acad. Sci. U.S.A. 102, 3822–3827 (2005)
Arthurs, O.J., Boniface, S.J.: How well do we understand the neural origins of the fMRI BOLD signal? TRENDS Neuroscience. 25, 27–31 (2002)
Arthurs, O.J., Boniface, S.J.: What aspect of the fMRI BOLD signal best reflects the underlying electrophysiology in human somatosensory cortex. Clin. Neurophysiol. 114, 1203–1209 (2003)
Arthurs, O.J., Donovan, T., Spiegelhalter, D.J., Pickard, J.D., Boniface, S.J.: Intracortically distributed neurovascular coupling relationships within and between human somatosensory cortices. Cereb. Cortex 17, 661–668 (2007)
Dennis, N.A., Cabeza, R.: Age-related dedifferentiation of learning systems: an fMRI study of implicit and explicit learning. Neurobiol. Aging 32, 2318.e17–2318.e30 (2011)
Hammer, A., Tempelmann, C., Münte, T.F.: Recognition of face-name associations after errorless and errorful learning: an fMRI study. BMC Neurosci. 14, 30 (2013)
Weiskopf, N.: Real-time fMRI and its application to neurofeedback. NeuroImage 62, 682–692 (2012)
Seghier, M.L., Hüppi, P.S.: The role of functional magnetic resonance imaging in the study of brain development, injury, and recovery in the newborn. Semin. Perinatol. 34, 79–86 (2010)
Wallois, F., Patil, A., Héberlé, C., Grebe, R.: EEG-NIRS in epilepsy in children and neonates. Neurophysiol. Clin./Clin. Neurophysiol. 40, 281–292 (2010)
Wallois, F., Mahmoudzadeh, M., Patil, A., Grebe, R.: Usefulness of simultaneous EEG–NIRS recording in language studies. Brain Lang. 121, 110–123 (2012)
Machado, A., Lina, J.M., Tremblay, J., Lassonde, M., Nguyen, D.K., Lesage, F., Grova, C.: Detection of hemodynamic responses to epileptic activity using simultaneous Electro-EncephaloGraphy (EEG)/Near Infra Red Spectroscopy (NIRS) acquisitions. NeuroImage 56, 114–125 (2011)
Fazli, S., Mehnert, J., Steinbrink, J., Curio, G., Villringer, A., Müller, K.R., Blankertz, B.: Enhanced performance by a hybrid NIRS–EEG brain computer interface. NeuroImage 59, 519–529 (2012)
Yoo, J.J., Hinds, O., Ofen, N., Thompson, T.W., Whitfield-Gabrieli, S., Triantafyllou, C., Gabrieli, J.D.E.: When the brain is prepared to learn: enhancing human learning using real-time fMRI. NeuroImage 59, 846–852 (2012)
Angsuwatanakul, T., Iramina, K., Keawkamnerdpong, B.: Multi-scale sample entropy as a feature for working memory study. In: The Seventh Biomedical Engineering International Conference (BMEiCON), pp. 1–5, Fukuoka, Japan, 26–28 Nov 2014
Angsuwatanakul, T., Iramina, K., Keawkamnerdpong, B.: Brain complexity analysis of functional near infrared spectroscopy for working memory study. In: The Eighth Biomedical Engineering International Conference (BMEiCON), pp. 1–5, Pattaya, Thailand, 25–27 Nov 2015
Acknowledgements
The author is grateful for all financial supports for research projects conducted with this framework including (1) MRG5680144 by Thailand Research Fund, Office of the Higher Education Commission, and King Mongkut’s University of Technology Thonburi, (2) Hitachi Research Fellowship HSF-R136 by Hitachi Scholarship, the Hitachi Global Foundation, and (3) Research Strengthening Project of the Faculty of Engineering, King Mongkut’s University of Technology Thonburi.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Kaewkamnerdpong, B. (2016). A Framework for Human Learning Ability Study Using Simultaneous EEG/fNIRS and Portable EEG for Learning and Teaching Development. In: Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and e-Learning 2016. Smart Innovation, Systems and Technologies, vol 59. Springer, Cham. https://doi.org/10.1007/978-3-319-39690-3_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-39690-3_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39689-7
Online ISBN: 978-3-319-39690-3
eBook Packages: EngineeringEngineering (R0)