Object recognition, Deep learning neural network, Functional brain imaging, Electrophysiology
Bao’s laboratory will focus on the exploration of the neural mechanism of high-level visual cognition, such as object recognition, scene categorization and contour segmentation. The lab will combine electrophysiological recordings, functional brain imaging, micro electrical stimulation, and psychophysics methods to study human and non-human primate’s visual systems across different levels. To build the mathematic model of the visual function of the primate brain, different kinds of tools, including deep learning network, will be applied with the collected data.
1. Bao, P., She, L., McGill, M. & Tsao, D.Y. A map of object space in primate inferotemporal cortex. Nature (2020). https://doi.org/10.1038/s41586-020-2350-5
2. Bao, P., & Tsao, D. Y. (2018). Representation of multiple objects in macaque category-selective areas. Nature communications, 9(1), 1774.
3. Chang, L., Bao, P., & Tsao, D. Y. (2017). The representation of colored objects in macaque color patches. Nature communications, 8(1), 2064.
4. Olman, C. A., Bao, P., Engel, S. A., Grant, A. N., Purington, C., Qiu, C., ... & Tjan, B. S. (2016). Hemifield columns co-opt ocular dominance column structure in human achiasma. NeuroImage.
5. Bao, P., Purington, C. J., & Tjan , B. S. (2015). Using an achiasmic human visual system to quantify the relationship between the fMRI BOLD signal and neural response. eLife, e09600. http://doi.org/10.7554/ eLife.09600
6. Kwon, M*., Bao, P*., Millin, R., & Tjan, B. S. (2014). Radial-tangential anisotropy of crowding in the early visual areas. Journal of Neurophysiology, 112(10), 2413-2422.