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Unravelling EEG brain signals

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

"Electroencephalography (EEG) is widely used to record brain activity non-invasively. With recent advances in computer hardware and processor technology, it has been increasingly used in brain-computer interface (BCI) devices in many fields including assistive technology, neuro-marketing and gaming. EEG-based devices are relatively inexpensive and can be made wireless, portable and wearable. However despite significant progress made in EEG analysis methodologies, the interpretation of EEG time series is still difficult, in the sense that we are unable to associate precisely the positive and negative deflections in EEG recordings to the underlying neural mechanisms such as neural excitation and inhibition.
The aim of this project is to understand how sensory evoked potentials recorded by EEG are related to synaptic activities underlying their generation. These synaptic activities, or local field potentials (LFPs), can be recorded invasively via a multichannel microelectrode. Using a rodent model, we conducted electrophysiological experiments and collected concurrent and co-localised EEG and LFP data across different age groups. We also developed a simple neural model linking LFP recordings to synaptic excitation and inhibition. This project will use advanced signal processing techniques combined with mathematical modelling approach to establish the link between EEG recordings and multichannel LFP recordings, with the goal of relating the positive and negative deflections in EEG to the synaptic mechanism. This would allow us to interpret EEG signals more precisely, and offer the opportunity to use our mind to control evoked brain signals in a specific manner. The outcome of the project will have a direct impact on the interpretation of EEG signals and the wide range of potential applications in medical diagnosis, artificial intelligence, BCI and brain sciences. For potential applicants who would like to discuss further details of the project, please contact Prof Ying Zheng via email at: .


Funding Notes

Eligibility requirements: Applicants should have a Bachelor’s (at least 2.1 or equivalent) or Master’s degree in Science, Bio-Engineering, Medicine or a strongly related discipline.

References

"1. ZHENG, Y., LUO, J. J., HARRIS, S., KENNERLEY, A., BERWICK, J., BILLINGS, S. A. & MAYHEW, J. 2012. Balanced excitation and inhibition: Model based analysis of local field potentials. Neuroimage, 63, 81-94.
2. BRUYNS-HAYLETT, M., LUO, J., KENNERLEY, A. J., HARRIS, S., BOORMAN, L., MILNE, E., VAUTRELLE, N., HAYASHI, Y., WHALLEY, B. J., JONES, M., BERWICK, J., RIERA, J. & ZHENG, Y. 2017. The neurogenesis of P1 and N1: A concurrent EEG/LFP study. NeuroImage, 146, 575-588.
3. KANG, S., BRUYNS-HAYLETT, M., HAYASHI, Y. & ZHENG, Y. 2017. Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent. Journal of Visualized Experiments : JoVE, 56447."

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