I study how structure defines function in the brain. More specifically, I am interested in understanding how neural networks are assembled to carry out their functions. Investigating the relationship between brain structure and function should enable us to build machines that can mimic human behaviors.
At present, I have several ongoing projects:
Several high-resolution (30-µm cubic in volume) serial EM datasets have been fully annotated and are currently being analyzed. This project aims to establish a data-driven framework that extracts latent features from biological big data and creates computational models based on empirical constraints acquired from the data to make predictions about mitochondria morphology.
By mapping and comparing the fully reconstructed synaptic inputs of cortical pyramidal neurons in brain tissue of a Shank3 knock-out mouse with that of a wild-type mouse, this project aims to provide detailed information about how the numbers or strengths or distributions or ratio of excitatory and inhibitory synapses altered in a mouse model of autism.
Over the past three years, I have been working on the reconstruction of two medium-sized SEM dataset (100x100x100 µm^3 for each) acquired from L2/3 of rat V1. These datasets contain hundreds of neurons from various types. I am still working on refining the dense segmentations. The fully segmented datasets will be released and made open-access early next year (2022).
Central Pattern Generators (CPGs) are ubiquitous and regulate a diverse set of rhythmic behaviors. I am interested in one such system underlying the neural control of breathing. This current project aims to reconstruct the complete wiring diagram of the mammalian respiratory CPG network at the level of individual synaptic connections.
In collaboration with the Yuste Lab at Columbia
In collaboration with the Pfister Lab at Harvard SEAS