MD, PhD (Cantab)
Wellcome Trust Early Career Research Fellow
- PhD in Neurophysiology, University of Cambridge (Queens' College)
- MD with Economics minor, National Taiwan University (Taiwan)
My research focuses on the fundamental mechanisms of learning and decision-making. In particular, I aim to elucidate the biological foundations of reward processing and its potential to advance artificial intelligence and treatments for mental conditions. To this end, I study animal choices from nutrient-defined food options in controlled laboratory setting and record single-neuron activities during decision-making. I use decision theories from economics, psychology, ecology to formalise choice behaviour and apply advanced computational modelling and machine learning methods to uncover decision computation in single neurons and neural populations. My recent work has identified nutrients as biological sources of economic values that guide choices (PNAS, 2021) and reinforcement learning (JNeurosci, 2023). Currently, I am combining this novel nutrient-choice paradigm with cutting-edge multichannel recording and targeted neurostimulation to uncover neural decision mechanisms in broader neural circuits and develop safe and effective neuromodulation tools to restore maladaptive reward processing, which underlies many human neuropsychiatric disorders.
A neural mechanism in the human orbitofrontal cortex for preferring high-fat foods based on oral texture.
Khorisantono PA. et al, (2023), J Neurosci
Nutrient-sensitive reinforcement learning in monkeys.
Huang 黃飛揚 F-Y. and Grabenhorst F., (2023), J Neurosci
Intravenous corticosteroid treatment in adult patients with sepsis defined by the Sepsis-3 criteria: a systematic review and meta-analysis
Wu Y-P. et al, (2021)
Preferences for nutrients and sensory food qualities identify biological sources of economic values in monkeys.
Huang F-Y. et al, (2021), Proc Natl Acad Sci U S A, 118
Nutrient-sensitive reinforcement learning in monkeys
Huang F-Y. and Grabenhorst F., (2021)