Qinggong Tang
Associate Professor of Biomedical Engineering (CBN Associate)Stephenson Research & Technology Center 1160F
405-325-6246
qtang at ou dot edu
https://www.ou.edu/coe/sbme/people
Ph.D., Biomedical Engineering - University of Maryland, 2017Research:
Dr. Tang’s research mainly focuses on the development of novel optical imaging techniques for functional brain imaging.
The first project in our lab is about deep brain imaging. Most current optical imaging setups involving CCD cameras can only provide two-dimensional information and are limited to surface areas such as the cerebral cortex. In order to access subcortical structures or even deep brain structures (e.g., the thalamus), we have designed a fluorescence endoscope system, based on a gradient-index (GRIN) rod lens, and performed voltage-sensitive dye imaging (VSDi) to visualize neural activity evoked in the thalamic barreloids by deflection of a single whisker or several whiskers in living mice. We are able to obtain functional maps in the thalamus and study corticothalamic feedback.
We also investigate 3D neural activities in cortex, since the neocortex can be divided into distinct layers containing various classes of neurons, and each of them contributes differently to cortical computation. We have developed a time-resolved fluorescence laminar optical tomography (FLOT) system for fast three-dimensional mesoscopic imaging. After a single mouse whisker is deflected, we can image the 3D neural activities evoked in the primary sensory cortex in different layers, with 5 ms temporal resolution. This imaging method can help to study dynamic neural activities in different parts of the cortex in 3D and provide some support to the hypothesis of spiral-like dynamic patterns of neural networks. We are investigating the layer-specific interaction between sensory and motor cortices.
Selected Publications:
Islam, W. Abdoli, N., Alam, T. E., Jones, M., Mutembei, B.M., Yan, F., and Tang, Q. (2024) A neoteric feature extraction technique to predict the survival of gastric cancer patients. Diagnostics. 14:954.
Yan, F., Mutembei, B., Valerio, T., Gunay, G., Ha, J., Zhang, Q., Wang, C., Mercyshalinie, E. R. S., Alhajeri, Z. A., Zhang, F., Dockery, L. E., Li, X., Liu, R., Dhanasekaran, D. N., Acar, H., Chen, W. R., and Tang, Q. (2024) Optical coherence tomography for multicellular tumor spheroid category recognition and drug screening classification via multi-spatial-superficial-parameter and machine learning. Biomed. Opt. Express 15: 2014-2047.
Yan, F., Alhajeri, Z., Nyul-Toth, A., Wang, C., Zhang, Q., Mercyshalinie, E., DelFavero, J., Ahire, C., Mutembei, B., Tarantini, S., Csiszar, A., and Tang, Q. (2024) Dimension-based quantification of aging-associated cerebral microvasculature determined by optical coherence tomography and two-photon microscopy. J. Biophotonics 2024. e202300409
Yan, F., Wang, C., Yan, Y., Zhang, Q., Yu, Z., Patel, S. G., Fung, K.-M., and Tang, Q. (2023) Polarization-sensitive optical coherence tomography for renal tumor detection in ex vivo human kidneys. Opt Lasers Eng 173:107900.
Wang, Y. Liu, P. Calle, X. Li, R. Liu, Q. Zhang, F. Yan, K.-m. Fung, A.K. Conner, S. Chen, C. Pan, and Q. Tang. (2023) Enhancing epidural needle guidance using a polarization-sensitive optical coherence tomography probe with convolutional neural networks. J. Biophotonics. e202300330.
He, Y., Li, K., Li, W., Qiu, Y., Li, D., Wang, C., Tang, Q., and Li, Z. (2023) Polarization coherency matrix tomography. Biophotonics
16:e202300093.
Ahire, A., Nyul-Toth, J., DelFavero, R., Gulej, J. A., Faakye, S. A., Tarantini, T., Kiss, A., Kuan-Celarier, P., Balasubramanian, A., Ungvari, A., Tarantini, R., Nagaraja, F., Yan, Q., Tang, P., Mukli, T., Csipo, A., Yabluchanskiy, J., Campisi, A., Ungvari, Z., and Csiszar, A. (2023) Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and ensemble deep learning. Aging Cell: e13832
Yan, J. H., Ha, Y., Yan, S.B., Ton, C., Wang, B., Mutembei, Z. A., Alhajeri, A. F., McNiel, A. J., Keddissi, Q., Zhang, M., Jayaraman, D. N., Dhanasekaran, Q., and Tang, Q. (2022) Optical Coherence Tomography of Tumor Spheroids Identifies Candidates for Drug Repurposing in Ovarian Cancer. IEEE Transactions on Biomedical Engineering, doi: 10.1109/TBME.2022.3231835.
Wang, C., Calle, P., Reynolds, J., Ton, S., Zhang, Z., Yan, F., Donaldson, A., Ladymon, A., Roberts, P., Armendi, A., Fung, K., Shettar, S., Pan, C., and Tang, Q. (2022) Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and ensemble deep learning. Sci Rep 12: 9057.
Wang, C., Reynolds, J., Calle, P., Ladymon, A., Yan, F., Yan, Y., Ton, S., Fung, K., Patel, S., Yu, Z., Pan, C., and Tang, Q. (2022) Computer-aided Veress needle guidance using endoscopic optical coherence tomography and convolutional neural network. J. Biophotonics e202100347. [Featured on journal cover]