2011.09 – 2016.07, Ph.D. in Biochemistry and Molecular Biology, Peking University & National Institute of Biological Sciences, Beijing
2006.09 – 2010.06, B.S. in Biology Technology, Nankai University

2024.08 – present, Professor, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
2021.06 – present, Assistant Investigator, Chinese Institute for Brain Research, Beijing
2016.07 – 2021.05, Postdoctoral Fellow, NIDA-IRP, National Institutes of Health
2010.10 – 2011.08, Technician, National Institute of Biological Sciences, Beijing

Our group uses rats and mice as model organisms to study the neural basis of associative learning and decision-making. Specifically, we aim to understand, at the level of systems neuroscience, how the brain constructs associations between events in complex environments and organizes, maintains, updates, and generalizes these learned associations based on experience and current needs, thereby making predictions and guiding choice behaviors. To address these questions, we employ an integrative approach that includes various Pavlovian and operant tasks along with a suite of neuroscience tools, including multichannel in vivo electrophysiology, single- and two-photon imaging, widefield imaging, optogenetics, chemogenetics, neuropharmacology, statistical analysis, machine learning, and computational modeling. Through observing, manipulating, and modeling neuronal activities, we explore the information coding and computational principles of population neurons in regions such as the prefrontal cortex and hippocampus and how they work together to support complex and flexible associative learning, memory, and decision-making behaviors.

*First authors

#Corresponding author

1. Lin, H., & Zhou, J#. Hippocampal and orbitofrontal neurons contribute to complementary aspects of associative structure. Nat Commun, 2024, 15, 5283.

2. Ma, F., Zhang, L., & Zhou, J#. Event-specific and persistent representations for contextual states in orbitofrontal neurons. Curr Biol, 2024, 34(5), 1023-1033.

3. Song, W., Liu, X., Huang, H., Wu, Y., Tang, Z., Wang, J., Ma, F., Zhou, J., & Zhang, M#. A frequency-division transceiver for long-range neural signal recording from multiple subjects. IEEE JSSC, 2024, 59(3), 923-934.

4. Zong, W#., Zhou, J., Gardner, M. P. H., Costa, K. M., Zhang, Z., & Schoenbaum, G#. Schema cell formation in orbitofrontal cortex is suppressed by hippocampal output. bioRxiv, 2023, 539307.

5. Bruch, S#., McClure, P., Zhou, J., Schoenbaum G. & Pereira F#. Validating the representational space of deep reinforcement learning models of behavior with neural data. bioRxiv, 2021, 448556.

6. Zhou, J#., Gardner, M. P., & Schoenbaum, G#. Is the core function of orbitofrontal cortex to signal values or make predictions? Curr Opin Behav Sci, 2021, 41, 1-9.

7. Zhou, J#., Zong, W., Jia, C., Gardner, M.P.H., & Schoenbaum, G#. Prospective representations in rat orbitofrontal ensembles. Behav Neurosci, 2021, 135 (4), 518–527.

8. Zhou, J#., Jia, C., Montesinos-Cartagena, M., Gardner, M.P.H., Zong, W., & Schoenbaum, G#. Evolving schema representations in orbitofrontal ensembles during learning. Nature, 2021, 590, 606–611.

10. Gardner, M#., Sanchez, D., Conroy, J.S., Wikenheiser, A., Zhou, J., & Schoenbaum, G#. Processing in lateral orbitofrontal cortex is required to estimate subjective preference during initial, but not established, economic choice. Neuron, 2020, 108, 1-12.

11. Gardner, M#, Conroy, J., Sanchez, D., Zhou, J., & Schoenbaum, G#. Real-time value integration during economic choice is regulated by orbitofrontal cortex. Curr Biol, 2019, 29(24), 4315-4322.

12. Zhou, J#., Montesinos-Cartagena, M., Wikenheiser, A., Gardner, M., Niv, Y., & Schoenbaum, G#. Complementary task structure representations in hippocampus and orbitofrontal cortex during an odor sequence task. Curr Biol, 2019, 29(20), 3402-3409.

13. Zhou, J#., Gardner, M., Stalnaker, T., Ramus, S., Wikenheiser, A., Niv, Y., & Schoenbaum, G#. Rat orbitofrontal ensemble activity contains multiplexed but dissociable representations of value and task structure in an odor sequence task. Curr Biol, 2019, 29(6), 897-907. (F1000 recommended)

14. Wang, D., Li, Y., Feng, Q., Guo, Q., Zhou, J., & Luo, M#. Learning shapes the aversion and reward responses of lateral habenula neurons. eLife, 2017, 6, e23045.

15. Zhang, J., Tan, L., Ren, Y., Liang, J., Lin, R., Feng, Q., Zhou, J., Hu, F., Ren, J., Wei, C., Yu, T., Zhuang, Y., Bettler, B., Wang, F., & Luo, M#. Presynaptic excitation via GABA B receptors in habenula cholinergic neurons regulates fear memory expression. Cell, 2016, 166(3), 716-728.

16. Li, Y., Zhong, W., Wang, D., Feng, Q., Liu, Z., Zhou, J., Jia, C., Hu, F., Zeng, J., Guo, Q., Fu, L., & Luo, M#. Serotonin neurons in the dorsal raphe nucleus encode reward signals. Nat Commun, 2016, 7.

17. Guo, Q*., Zhou, J*., Feng, Q., Lin, R., Luo Q., Zeng S., Luo, M#., & Fu, L#. Multi-channel fiber photometry for population neuronal activity recording. Biomed Opt Express, 2015, 6(10), 3919-3931.

18. Luo M#., Zhou J., & Liu Z. Reward processing by the dorsal raphe nucleus: 5-HT and beyond. Learn Mem, 2015, 22: 452-460.

19. Zhou, J., Jia, C., Feng, Q., Bao, J., & Luo, M#. Prospective coding of dorsal raphe reward signals by the orbitofrontal cortex. J Neurosci, 2015, 35(6), 2717-2730.

20. Liu, Z*., Zhou, J*., Li, Y., Hu, F., Lu, Y., Ma, M., Feng, Q., Zhang, J., Wang, D., Zeng, J., Bao, J., Kim, J., Chen, Z., Mestikawy, S., & Luo, M#. Dorsal raphe neurons signal reward through 5-HT and glutamate. Neuron, 2014, 81(6), 1360-1374. (F1000 recommended).

21. Zhan, C*#., Zhou, J*., Feng, Q., Zhang, J. E., Lin, S., Bao, J., Wu, P., & Luo, M#. Acute and long-term suppression of feeding behavior by POMC neurons in the brainstem and hypothalamus, respectively. J Neurosci, 2013, 33(8), 3624-3632. (F1000 recommended).

Full publication list: https://scholar.google.com/citations?user=ZQD-fmcAAAAJ