Junheng Li

Junheng Li

Project title: Investigation of the falling asleep brain dynamics and its closed-loop augmentation strategy
Supervisor: Dr Nir Grossman
Location: Level 5, Burlington Danes Building, Hammersmith Campus, Du Cane Road, W12 0NN

About Me

I am a PhD student in the Grossman lab in the Department of Brain Sciences at Imperial College London. I graduated from Xidian University in 2017, and then received an MSc with distinction from Imperial in 2018, specialising in engineering and signal processing. Now, I am very eagerly applying my engineering expertise into the neuroscience research, looking to better understand brain signals and machine learning techniques.

Publications

  • Schreglmann S, Wang D, Peach R, Li J, Zhang X, Latorre A, Rhodes E, Panella E, Boyden E, Barahona M, Santaniello S, Bhatia K, Rothwell J, Grossman N. (2021). Non-invasive amelioration of essential tremor via phase-locked disruption of its temporal coherence, Nature Communications, Vol: 12, ISSN: 2041-1723
  • Vinao-Carl M, Gal-Shohet Y, Rhodes E, Li J, Hampshire A, Sharp D, & Grossman N. (2024). Just a phase? Causal probing reveals spurious phasic dependence of sustained attention. NeuroImage,285, 120477.
  • Tang J, Huang H, Muirhead R, Zhou Y, Li J, DeFelice J, Kopanitsa M, Serneels L, Davey K, Tilley B, Gentleman S, Matthews P, Associations of amyloid-β oligomers and plaques with neuropathology in the AppNL-G-Fmouse, Brain Communications, 2024. 

Qualifications

  • 2014-2017: BEng. in Telecommunications Engineering, Xidian University
  • 2017-2018: MSc in Communications and Signal Processing (Distinction), Imperial College London

Research Interests

My PhD focuses on using novel feature-based signal processing technique combined with machine learning to better understand brain signals and exploring mechanisms. Specifically, we are trying to use neuro-modulation techniques to intervene brain activities and facilitate restorative sleep in dementia patients. Novel feature-based analysis approach will be implemented in such brain activity analysis (normally spatio-temporal EEG), and machine learning algorithms are used to find out mechanisms in neuro-intervention, which in turn directs us to optimise the stimulation for better outcomes.

Conferences

  • Presentation in ECR day at Connectome 2021: "The brain dynamics during falling asleep"
  • Poster presentation at Computational Neuroscience Society (CNS) conference 2023

Contact details

Email: junheng.li17@imperial.ac.uk