Real-World NeuroImaging Research and BCI:

Chair: Prof. Nancy LAW, Professor, Faculty of Education, The University of Hong Kong

The past twenty years have witnessed remarkable advances in both fundamental neuroscience research and next-generation neurotechnologies. Nonetheless, nearly all brain imaging research to date has required participants to remain nearly motionless and perform improvised stimulus-response experiments while their brain activity is recorded within a well-controlled laboratory setting. It has been argued that fundamental differences between laboratory-based and naturalistic human behavior may exist. It remains unclear how well the current knowledge of human brain function translates into the highly dynamic real world [1]. Therefore, there is a need to study the brain in ecologically valid environments in order to truly understand how the human brain functions to optimally control behavior in face of ever-changing physical and cognitive circumstances. This talk will focus on recent progress in real-world neuroimaging and Brain-Computer Interfaces that leverages innovations advanced by our groups at University of California San Diego and National Chiao Tung University [2-4].  This talk will also explore the effects of real-life stressors (e.g. sleep quality and stress) on the EEG activities in the classroom and other real-world environments. [5-7].

[References]

1. McDowell K, Lin C-T., Oie K.S., Jung T-P., Gordon S., Whitaker K.W., Li S-Y., Lu S-W., Hairston W-D., Real-World Neuroimaging Technologies,” IEEE Access, 1:131-49, 2013.
2. Siddharth, S., Jung, T-P., Sejnowski, T.J. “How about taking a Low-cost Multimodal Bio-sensing and Eye-gaze Tracking System into the “Wild”? Proceedings of the 38th International IEEE EMBS conference, 2016.
3. Liao, L-D., Lin, C-T.,  McDowell, K., Wickenden, A. E., Gramann, K., Jung, T-P. Ko, L-W., Chang, J-Y. Biosensor Technologies for Augmented Brain-Computer Interfaces in the Next Decades, Proceedings of the IEEE, 100:1553-66, 2012.
4. Zao, J.K., Gan,T-T., You, C-K., Rodríguez_Méndez, S.C., Chung, C-E., Wang, Y-T., Mullen, T., Kothe, C., Yu, C., Hsiao, C-T., Chu, S., Shieh, C-K., Jung, T-P., Pervasive Brain Monitoring and Data Sharing based on Multi-tier Distributed Computing and Linked Data Technology, Frontiers in Human Neuroscience, 2014 Jun 3;8:370. doi: 10.3389/fnhum.2014.00370.
5. Chen, S.-C., She, H.-C., Chuang, M.-H., Wu, J.-Y., Tsai, J.-L., Jung, T.-P. Eye movements predict students' computer-based assessment performance of physics concepts in different presentation modalities, Computers & Education, 74: 61–72, 2014.
6. Chou, W.C., She, H. C., Lai, K., Gramann, K., & Jung, T. P. Temporal Dynamics and Cortical Networks Engaged in Biological Concepts Encoding. Journal of Neuroscience and Neuroengineering, 3(1), 21–35, 2014.
7. Ko, L-W., Komarov, O., Hairston, W.D., Jung, T-P., and Lin, C-T., Sustained Attention in Real Classroom Settings: An EEG Study, Frontiers in Human Neuroscience, 11:article 388, 2017.