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Research Group:

Brain Computer Interface for Therapy

Sources of Funding:

  • Medical Research Council (MRC)
  • Wellcome Trust ISSF
  • Rostrees Trust

Other Affiliations:

MRC Brain Network Dynamics Unit


Huiling studied Control Engineering at Beijing University of Aeronautics and Astronautics, and was awarded Undergraduate Academic Excellence Scholarship for four years (1996-2000). In 2003, she came to the University of Oxford with an Oxford Overseas Research Scholarship and China Oxford Scholarship. After completing her D.Phil. in Engineering Sciences at the University of Oxford in Dec 2006, Huiling studied Psychology with Open University and was awarded BSc in Psychology with Honours (1st class).

Huiling Tan

University Research Lecturer;

  • Principal Investigator

Developing Brain Computer Interfaces to improve quality of life for people with neurological disorders

Research Summary

Huiling’s recent research focuses the role of the basal ganglia in motor control and motor learning, and how information important for motor control and motor learning is represented, processed and transmitted in different networks of the brain, including the motor cortex and the basal ganglia. Her recent work has revealed how frequency-specific oscillations in the local field potentials (LFP) recorded from the basal ganglia contribute to encoding gripping force, motor effort and other movement related information. She is also interested in how malfunction of these oscillations can lead to symptoms in different movement disorders, in particular, Parkinson’s disease. This will allow for the design of novel neuromodulation strategies to interact with pathological brain activities for better treatment of symptoms.

The overarching aim of Huiling’s research is to use these arising insights in a brain-machine interface (BMI) context to improve the quality of life for the neurologically impaired. With this, she aim to translate the neuroscience and engineering knowledge into clinical therapies in order to recover function and ameliorate symptoms, whilst at the same time answering to fundamental neuroscience questions.


Thanks to the close collaboration we have established with functional neurosurgery teams, we have enjoyed the rare opportunity to record local field potentials from the deep brain structures, such as the basal ganglia, in human patients with movement disorders who have undergone the surgery for Deep Brain Stimulation. We will continue to freely share those data in order to support open science and reproducibility in neuroscience. Examples are:

STN activity during stopping of rhythmic finger tapping

STN LFPs and simultaneous cortical EEGs during joystick movements 

STN LFPs from Parkinson's patients during stepping in place

Recent publications

More publications