Skip to main content

A Framework for Human Learning Ability Study Using Simultaneous EEG/fNIRS and Portable EEG for Learning and Teaching Development

  • Conference paper
  • First Online:
Smart Education and e-Learning 2016

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 59))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Oblinger, D., Oblinger, J.: Is it age or it: first steps toward understanding the net generation. Educating the Net Generation. EDUCAUSE (2005)

    Google Scholar 

  2. Moore, S., Barrett, T.: New Approaches to Problem-based Learning: Revitalising Your Practice in Higher Education. Routledge, New York (2010)

    Google Scholar 

  3. 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

    Google Scholar 

  4. Neuroscience and Education: Issues and Opportunities. Teaching and Learning Research Programme, The Economic and Social Research Council (2007)

    Google Scholar 

  5. Shibasaki, H.: Human brain mapping: hemodynamic response and electrophysiology. Clin. Neurophysiol. 119, 731–743 (2008)

    Article  Google Scholar 

  6. Shibasaki, H., Ikeda, A., Nagamine, T.: Use of magnetoencephalography in the presurgical evaluation of epilepsy patients. Clin. Neurophysiol. 118, 1438–1448 (2007)

    Article  Google Scholar 

  7. 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)

    Article  Google Scholar 

  8. 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)

    Article  Google Scholar 

  9. 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)

    Article  Google Scholar 

  10. 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)

    Article  Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. 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)

    Google Scholar 

  13. 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)

    Article  Google Scholar 

  14. Weiskopf, N.: Real-time fMRI and its application to neurofeedback. NeuroImage 62, 682–692 (2012)

    Article  Google Scholar 

  15. 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)

    Article  Google Scholar 

  16. Wallois, F., Patil, A., Héberlé, C., Grebe, R.: EEG-NIRS in epilepsy in children and neonates. Neurophysiol. Clin./Clin. Neurophysiol. 40, 281–292 (2010)

    Article  Google Scholar 

  17. Wallois, F., Mahmoudzadeh, M., Patil, A., Grebe, R.: Usefulness of simultaneous EEG–NIRS recording in language studies. Brain Lang. 121, 110–123 (2012)

    Article  Google Scholar 

  18. 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)

    Article  Google Scholar 

  19. 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)

    Article  Google Scholar 

  20. 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)

    Article  Google Scholar 

  21. 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

    Google Scholar 

  22. 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

    Google Scholar 

Download references

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

Authors

Corresponding author

Correspondence to Boonserm Kaewkamnerdpong .

Editor information

Editors and Affiliations

Rights and permissions

Reprints 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)

Publish with us

Policies and ethics