Tan Group
The Tan Group is based at the Nuffield Department of Clinical Neurosciences, University of Oxford.
Research Themes
Targeting motor learning & execution
Our prior work revealed the important role of beta reduction and post-movement beta rebound in the sensorimotor cortex and the STN for motor execution and learning, respectively. In Parkinson’s disease, impaired beta modulation disrupts these functions. We aim to use adaptive DBS to modulate beta oscillations to improve motor symptoms in PD.
Understanding & Engineering sleeping brain
Our recent work has identified pathological activities in the STN LFPs underlying specific symptoms of sleep disorders in PD. We will test the hypothesis that tailored aDBS protocols, designed to suppress pathological oscillations while preserving physiological rhythms during sleep, will improve the treatment of sleep disturbances in PD.
Physiomarkers
Our previous work contributed to the identification of beta in STN LFPs as a physiomarker for bradykinesia and rigidity in PD. Recently, we showed that stimulation-induced resonant activity (ERNA) in STN LFPs reliably reflects arousal and sleep stages. We will study ERNA as a physiomarker for automated DBS programming and adaptive DBS feedback.
Tools (devices, software, algorithms)
We proposed a hardware design that synchronizes sampling with stimulation pulses, preventing artifact capture while preserving continuous LFP recording. We aim to create next-generation bi-directional neural interfaces with superior artifact rejection, fast processing, and flexible control for testing advanced stimulation protocols in humans.
Approaches
Empirical Neuroscience
We use an empirical neuroscience approach by recording electrophysiological signals (LFPs, EEG, EMG and etc) from human patients and healthy participants during motor and cognitive tasks. This enables us to examine how neural oscillations support movement and cognition, and how these processes are disrupted in movement disorders.
Experimental Medicine
We record electrophysiological signals from patients undergoing treatments such as dopaminergic medication and high-frequency DBS. This enables us to investigate how these interventions modulate neural oscillations and how such changes relate to symptom improvement, advancing our understanding of disease pathophysiology and treatment mechanisms.
Biomedical Engineering
We aim to create next-generation bi-directional neural interfaces with superior artifact rejection, fast processing, and flexible control for testing advanced stimulation protocols in humans. We also applying more advanced control algorithms, such as model predictive control, in aDBS.
