Dr. Tang’s research interests focus on experience-dependent effects on brain circuits, behavior, subjective experiences, and mental health. Early adverse experiences are associated with many psychiatric and personality disorders. To investigate their connections, Dr. Tang’s group integrate approaches from artificial intelligence, structural biology, bioengineering, developmental biology, neuroscience, and psychology/psychiatry. A major limitation to brain research is the inability to access all molecular and cellular components of the brain rapidly and comprehensively. To facilitate this, Dr. Tang’s group is developing generalizable strategies to generating conditionally stable nanobodies, which can be applied as sensors to detect and manipulate desired molecules and cell populations. Dr. Tang’s group aims to apply these tools in mice to study the neural and behavioral mechanisms underlying the action learning process. This research integrates state-of-the-art technologies such as wireless inertial sensors,  optogenetics, miniscope imaging, fiber photometry and neuropixel recordings in a closed loop system to rigorously investigate how mice home in on the right actions for reward. To overcome limitations of animal models for studying subjective repertoires of individuals, Dr. Tang’s group is applying AI to model psychological structures. The group looks to integrate these multi-level approaches in the understanding of rigid learning patterns (autism, OCD, etc.) and experience-associated psychiatric (PTSD, Borderline Personality Disorders, etc.) disorders.

Education

B.Sc. Honors in Biochemistry at University of British Columbia (2007), M.Sc. in Cell and Developmental Biology at University of British Columbia (2009), Ph.D. in Genetics at Harvard University (2015).

Neurobiology course, Marine Biological Laboratory, Woods Hole, USA (2014)

Methods in Computational Neuroscience course, Marine Biological Laboratory, Woods Hole, USA (2016)

Publications

Action Learning

Tang JCY, Paixao V, Carvalho F, Silva A, Klaus A, da Silva JA, Costa RM. Dynamic behaviour restructuring mediates dopamine-dependent credit assignment. Nature. 2024 Feb;626(7999):583-592. doi: 10.1038/s41586-023-06941-5. Epub 2023 Dec 13. PMID: 38092040; PMCID: PMC10866702.

Bioengineering

Papers

Dingus JG, Tang JCY, Amamoto R, Wallick GK, Cepko CL. A general approach for stabilizing nanobodies for intracellular expression. Elife. 2022 Nov 23;11:e68253. doi: 10.7554/eLife.68253. PMID: 36416528; PMCID: PMC9683787.

Tang JC, Drokhlyansky E, Etemad B, Rudolph S, Guo B, Wang S, Ellis EG, Li JZ, Cepko CL. Detection and manipulation of live antigen-expressing cells using conditionally stable nanobodies. Elife. 2016 May 20;5:e15312. doi: 10.7554/eLife.15312. PMID: 27205882; PMCID: PMC4922844.

Tang JC, Rudolph S, Dhande OS, Abraira VE, Choi S, Lapan SW, Drew IR, Drokhlyansky E, Huberman AD, Regehr WG, Cepko CL. Cell type-specific manipulation with GFP-dependent Cre recombinase. Nat Neurosci. 2015 Sep;18(9):1334-41. doi: 10.1038/nn.4081. Epub 2015 Aug 10. PMID: 26258682; PMCID: PMC4839275.

Tang JC, Szikra T, Kozorovitskiy Y, Teixiera M, Sabatini BL, Roska B, Cepko CL. A nanobody-based system using fluorescent proteins as scaffolds for cell-specific gene manipulation. Cell. 2013 Aug 15;154(4):928-39. doi: 10.1016/j.cell.2013.07.021. PMID: 23953120; PMCID: PMC4096992.

Book Chapter

Tang JCY, Rudolph S, Cepko CL. Viral Delivery of GFP-Dependent Recombinases to the Mouse Brain. Methods Mol Biol. 2017;1642:109-126. doi: 10.1007/978-1-4939-7169-5_8. PMID: 28815497.

Developmental Neuroscience

Berndt AJ, Tang JC, Ridyard MS, Lian T, Keatings K, Allan DW. Gene Regulatory Mechanisms Underlying the Spatial and Temporal Regulation of Target-Dependent Gene Expression in Drosophila Neurons. PLoS Genet. 2015 Dec 29;11(12):e1005754. doi: 10.1371/journal.pgen.1005754. PMID: 26713626; PMCID: PMC4694770.

Castellanos MC, Tang JC, Allan DW. Female-biased dimorphism underlies a female-specific role for post-embryonic Ilp7 neurons in Drosophila fertility. Development. 2013 Sep;140(18):3915-26. doi: 10.1242/dev.094714. PMID: 23981656; PMCID: PMC3915572.