2016 - 2020 Ph.D. Computational Neuroscience University College London
2013 - 2016 M.S. Cognitive Neuroscience Beijing Normal University

2021 - present Principal Investigator Beijing Normal University (BNU)
2021 - present Honorary Research Associate University College London
2020 - 2021 Postdoc University of Oxford

The Yunzhe Liu Lab explores the fundamental brain mechanisms that drive human intelligence. We are especially interested in how the brain builds internal representations of the world during offline periods such as rest and sleep. This hidden neural activity is crucial because it enables truly flexible human behaviour, empowering us with zero-shot generalisation and efficient on-task planning when we face completely new situations.
Artificial intelligence (AI) sits at the very core of our approach. We weave advanced neural encoding and decoding models through every stage of our work. By applying these AI tools to complex brain data, we uncover profound insights and seamlessly bridge the gap between basic neuroscience and clinical practice.
Ultimately, we translate these discoveries into life-changing treatments for neuropsychiatric patients. We use our AI-driven models to develop intelligent brain-computer interfaces and guide targeted neuromodulation. Our overarching goal is to pioneer precision therapies utilising both non-invasive approaches like transcranial ultrasound stimulation (TUS) and invasive techniques such as deep brain stimulation (DBS) and stereo-electroencephalography (sEEG).

1. Qu, Y., Ou, J., Pang, L., Wu, S., Luo, Y., Behrens, T., & Liu, Y*. (2026). Development of non-spatial grid-like neural codes tracks inference and intelligence. Cell (accepted)

2. He, L., Wang, X., Zhang, J., Xiao, Z., Hu, X., Schwartenbeck, P., Bakermans, J., Behrens, T., & Liu, Y*. (2026). Human hippocampal ripples coordinate planning sequences and compositional representation in neocortex. Nature Neuroscience (accepted)

3. Zhou, X., Wang, X., Hu, X., Wang, H., Zhang, J., Yu, Q., Xu, J., Xiao, Z., He. L., & Liu, Y*. (2026). Human hippocampal ripples prioritise model-based learning. Neuron (accepted)

4. Chen, Z., Zheng, H., Zhou, J., Zheng, L., Lin, P., Wang, H., Busche, M., Behrens, T., Dolan, R., & Liu, Y*. (2026). Interpreting Human Sleep Activity Through Neural Contrastive Learning. Neuron (accepted)

5. Xiao, Z., Wang, X., Zhang, J., Ou, J., He, L., Qu, Y., Hu, X., Behrens, T., & Liu, Y*. (2025). Human hippocampal ripples predict the alignment of experience to a grid-like schema. Neuron, 113(21), 3661-3672.

6.Yu, Q., Luo, Y., Dolan, R., Ou, J., Huang, C., Wang, H., Xiao, Z., & Liu, Y*. (2025). Trait anxiety is associated with reduced reward-related replay at rest. Nature Communications, 16(1), 7975.

7.Lyu, B., Qin, L., Wang, X., Ou, J., Nour, M., D, N., Gao, J.-H., & Liu, Y*. (2025). Building hierarchically nested structure by rapid neural sequences. Proceedings of the National Academy of Sciences, 122(50), e2507417122.

8.Zhang, J., Ou, J., & Liu, Y*. (2025). Replay and Ripples in Humans. Annual Review of Neuroscience, 48, 65–84.

9.Wei, T., Zhou, J., Wang, Z., Liu, X., Mi, Y., Zhao, Y., Xing, Y., Zhao, B., Zhou, S., Liu, Y., Liu, Y*., & Tang, Y*. (2025). Coupled sleep rhythm disruption predicts cognitive decline in Alzheimer’s disease. Science Bulletin, 70(9), 1491-1503.

10.Huang, Q., Xiao, Z., Yu, Q., Luo, Y., Xu, J., Qu, Y., Dolan, R., Behrens, T., & Liu, Y*. (2024). Replay-triggered brain-wide activation in humans. Nature Communications, 15(1), 7185.

11.Schwartenbeck, P., Baram, A., Liu, Y., Mark, S., Muller, T., Dolan, R., Botvinick, M., Kurth-Nelson, Z., & Behrens, T. (2023). Generative replay underlies compositional inference in the hippocampal-prefrontal circuit. Cell, 186(22), 4885-4897.e7.

12.Liu, Y*., Nour, M., Schuck, N. W., Behrens, T. E. J., & Dolan, R. J. (2022). Decoding cognition from spontaneous neural activity. Nature Reviews Neuroscience, 23(4), 204–214.

13.Liu, Y.*, Mattar, M., Behrens, T. E., Daw, N., Dolan, R.J. (2021) Experience replay is associated with efficient nonlocal learning. Science, 372(6544).

14.Nour, M. ^#, Liu, Y. ^#, Arumuham, A., Kurth-Nelson, Z., Dolan, R. (2021) Impaired neural replay of inferred relational structure in schizophrenia. Cell, 184(16), 4315-4328.

15.Higgins, C. ^#, Liu, Y.^#, Vidaurre, D, Kurth-Nelson, Z., Dolan, R. J., Behrens, T. E., Woolrich, M (2021) Replay bursts coincide with activation of the default mode and parietal alpha network. Neuron, 109(5), 882-893.

16.Wise, T. ^#, Liu, Y. ^#, Chowdhury, F., & Dolan, R. J. (2021). Model-based aversive learning in humans is supported by preferential task state reactivation. Science Advances, eabf9616.

17.Liu, Y.*, Dolan, R. J., Higgins, C., Penagos, H., Woolrich, M., Ólafsdóttir, H. F., Barry, C., Kurth-Nelson, Z., Behrens, T. E. (2021) Temporally delayed linear modelling (TDLM) measures replay in both animals and humans. ELife, 10: e66917.

18.Wimmer, G. E. ^#, Liu, Y. ^#, Vehar, N., Behrens, T. E., Dolan, R. J. (2020) Episodic memory retrieval success is associated with rapid replay of episode content. Nature Neuroscience, 1-9.

19.Liu, Y.*, Dolan, R. J., Kurth-Nelson, Z., Behrens, T. E. (2019) Human replay spontaneously reorganises experience. Cell, 178(3), 640-652.

20.Liu, Y., Lin, W., Li, W., Wang, X., Pan, X., Yan, X., Rutledge, R. Ma, Y. (2019) Oxytocin modulates social value representations in the amygdala. Nature Neuroscience, 22(4), 633.

21.Liu, Y., Lin, W., Liu, C., Wu, J., Luo, Y., Bayley, P., Qin, S. (2016) Memory consolidation reconfigures neural pathways involved in the suppression of emotional memories. Nature Communications, 7, 13375.

 # co-first; * corresponding author