My current research is focus on the biological mechanisms and computational principles underlying the adaptation and inforamtion encoding of the single nuron and neural networks by conducting both physiology experiments and mathematical modeling. My recent research interests can be mainly divided into the following topics:

1. Neural design principles underlying contrast adaptation.

2. The coding properties of visual neurons to long-term correlation in the natural signals.

3. The role of the synchronized spiking activities in the information encoding.

4. The role of synaptic noise in the neural information processing (Stochastic Resonance and Coherence Resonance mechanisms).

5. The dynamical properties of single neuron and network.

 

I am intrigued by the biological mechanisms and computational principles the brain uses to transform the physical world into the spiking patterns of neurons. The following topics have my great attention and interests: (1) how do the natural signals be efficiently represented by the different levels of cortical neurons? (2) how to decode the spiking patterns from multiple units so that we can read memory or the internal state of the brain? (3) learning process induced adaptation, synaptic plasticity and experience-modified response properties. (4) the neural circuits and mechanisms for spike-timing dependent plasticity, Long-Term Potentiation (LTP) and Long-Term Depression (LTD). (5) How do sensory information or experience be transformed and consolidated into short-term or long-term memory.