Assistant Professor
Department of Neuroscience
Baylor College of Medicine
Houston, TX, US
Assistant Professor
Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital
Houston, Texas, United States


Advanced Training from University Of Virginia
BMed from Zhejiang University School Of Medicine
PhD from Uniformed Services University Of The Health Sciences

Professional Interests

  • Dissecting the cortical microcircuit in health and disease; connectopathies in epilepsy and autism-spectrum disorders

Professional Statement

Each brain region contains distinct neuronal cell types with characteristic morphological features, electrophysiological properties and gene expression profiles, and these different types of neurons are wired in a specific manner to form a functional microcircuit. A mechanistic understanding of the workings of the normal and pathological brain requires identifying all of the constituent cell types, mapping their interconnections and determining their functions.

Our Laboratory at the Baylor College of Medicine and Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital focuses on two related questions regarding cortical microcircuit: (1) how different cortical cell types connect each other to form a normal, functional circuit? and (2) how stereotypical wiring principles among distinct cell types are impacted by distinct neuropsychiatric conditions. To this end, we developed and employ a multi-disciplinary approach that includes multi-cell patching (up to 12 simultaneous patching) in brain slices, detailed morphological recovery, single-cell RNA sequencing of patched cells (Patch-seq), optogenetic techniques, machine learning, and sophisticated mouse genetic models. Using this integrated approach, we perform unbiased, multi-modal profiling of the individual neurons in the cortical microcircuit, including their electrophysiology, morphology, transcriptome and connections, in order to decipher the comprehensive blueprint of the cortical microcircuit at the level of cell types and connections. We also use in vivo whole cell recordings, two-photon Ca2+ imaging and behavioral assays to explore cell-type specific roles in the information processing of intact brains. Our ultimate goal is to reverse-engineer cortical microcircuit by revealing its essential building blocks and the specific functional role each constituent performs.

Once we decipher the canonical circuit blueprint in normal heathy brain, we further use this knowledge as a template to reveal aberrant connections between specific cell types (connectopathies) underlying distinct neuropsychiatric disorders, including epilepsy, autism-spectrum disorders (ASD) and schizophrenia. Extensive research has been done to probe these disorders at genetic/molecular, macro-scale, and behavior level. However, at the meso-scale level, how each neuropsychiatric condition impacts the circuit blueprint are still being elucidated. In addition, within each disorder, there are distinct etiologies that share a similar symptomatology and EEG signature, raising the possibility that different etiologies induce the same circuit wiring deficits that result in the same phenotypes. To explore if there is a stereotypical circuit wiring deficit underlying absence epilepsy despite disparate molecular lesions, we use two mouse models of absence epilepsy, stargazer and tottering, which harbor distinct monogenic mutations but have the same epileptic phenotype. We perform an unbiased, large-scale microcircuit analysis on both models at the level of cell types and connections to reveal detailed circuit blueprint change as a function of genotype. Similarly, we are using different mouse models of ASD, including Angelman syndrome and Rett syndrome, to examine if there are stereotypical wiring abnormalities across different ASDs. Identifying the stereotypical circuit deficits for a specific type of neuropsychiatric diseases paves the way for more universal, circuit-based cell-type specific interventions for these diseases.

Selected Publications


Single-cell RNA sequencing