Rong Gong

How does the brain learn from changes within the body and use past experiences to anticipate physiological needs and guide future behavior? Traditionally, neuroscience has focused on how the brain learns from external sensory information, such as sights and sounds, and feedback in the form of rewards and punishments. Yet, from an evolutionary perspective, sensing and regulating the body's internal state is a far more ancient and highly conserved capacity. Internal signals related to hunger, thirst, nutrient availability, and visceral activity not only convey information about the body's current physiological state but also provide essential signals for learning. Rather than simply monitoring and regulating the body, the brain continuously learns from it, builds predictions about future physiological needs, and proactively adjusts behavior.

Consider a fascinating yet fundamental phenomenon: How can an animal sometimes learn, from a single feeding experience, whether a food is nutritious or potentially harmful, and subsequently seek it out or avoid it? The taste of food is perceived immediately, yet its nutritional benefits or adverse physiological consequences may not become apparent until minutes or even hours later. How does the brain associate these delayed internal signals with an earlier feeding experience and transform them into lasting memories? Even more remarkably, certain forms of interoceptive learning are exceptionally efficient and persistent, with a single experience sometimes sufficient to shape behavior over the long term. Does such rapid and enduring learning rely on specialized neural population dynamics, circuit architectures, or mechanisms of plasticity? Does interoceptive learning follow principles that differ from those underlying classical learning driven by external sensory cues? Furthermore, our subjective experiences of internal states, such as hunger, do not always directly correspond to peripheral physiological measures, such as blood glucose levels. Could interoceptive learning and memory also shape how we perceive our internal bodily states, or even alter how physiological needs are translated into behavioral motivation?

Our laboratory uses feeding behavior and appetite regulation in mice as primary experimental models to investigate these questions. By integrating in vivo neural recording and manipulation, circuit dissection, molecular approaches, and computational analysis, we focus on three interconnected research questions:

1. Interoceptive Learning and Memory: How does the brain learn from internal bodily signals, form memories of food value, and use these memories to guide future decisions? Does interoceptive learning rely on distinct neural population dynamics, computational principles, and plasticity mechanisms that set it apart from classical learning driven by external sensory information?

2. Brain–Body Communication and Predictive Regulation: How do learning and memory shape the perception of internal bodily states and coordinate interactions between the brain and peripheral organs to proactively regulate behavior and physiology?

3. Disease Mechanisms: How do disruptions in interoceptive learning and memory alter appetite and the perception of bodily states, and contribute to eating disorders, metabolic dysfunction, and psychiatric conditions?

Our ultimate goal extends beyond understanding how the brain regulates appetite. By using feeding as a model of a fundamental survival behavior, we seek to uncover the neural principles by which the brain learns from the body, generates predictions about physiological needs, and coordinates perception, behavior, and bodily functions. We hope this work will expand existing theories of learning and memory while offering new perspectives on obesity, anorexia nervosa, and related psychiatric and metabolic disorders.

2012    Special Postdoctoral Fellowship provided by the Tsinghua-Peking University Center for Life Sciences, Beijing, China

2011    The Excellent Graduated Student Fellowship, National Institute of Biological Science, Beijing, China

1. Yang X, Yan W, Lu W, Wang R, Li D, Wang Z, Han H, Yang X, Yang M, Han X, Song R, Lu Y, Chen G, Gong R. A sync state in the midbrain dopamine network for interoceptive nutrient learning. Neuron. 2026 Jul 22:S0896-6273(26)00531-3. doi: 10.1016/j.neuron.2026.07.002. Epub ahead of print. PMID: 42486089.

2. Zhong S, Zhang X, Gao X, Li Z, Huang L, Guo Q, Gong R, Ren J, Luo M, Lin R. Ultrabright chemical labeling enables rapid neural connectivity profiling in large tissue samples. Neuron. 2025 Nov 19;113(22):3741-3757.e11. doi: 10.1016/j.neuron.2025.08.022. Epub 2025 Sep 18. PMID: 40972576.

3. Tang L, Wang J, Ding J., Sun J, Chen X, Shen Q, Song R, Cao P, Gong R, Xu F, Ge W, Sun W, Zhao H, Wu J.  Curved light sheet microscopy for centimetre-scale cleared tissue imaging. Nat. Photon. 19, 577–584 (2025). https://doi.org/10.1038/s41566-025-01659-4

4. Zhu Z, Gong R, Rodriguez V, Quach KT, Chen X, Sternson SM. Hedonic eating is controlled by dopamine neurons that oppose GLP-1R satiety. Science. 2025 Mar 28;387(6741):eadt0773. doi: 10.1126/science.adt0773. Epub 2025 Mar 28. PMID: 40146831; PMCID: PMC12009138.

5. Yang X, Yan W, Gong R. Holistic inside and outside: The impact of food taste on ARC^AGRP neuron activity in feeding regulation. Neuron. 2024 Oct 9;112(19):3228-3230. doi: 10.1016/j.neuron.2024.09.011. PMID: 39389011.

6. Gong R, Xu S, Hermundstad A, Yu Y, Sternson SM. Hindbrain Double-Negative Feedback Mediates Palatability-Guided Food and Water Consumption. Cell. 2020 Sep 17;182(6):1589-1605.e22. doi: 10.1016/j.cell.2020.07.031. Epub 2020 Aug 24. PMID: 32841600.

7. Betley JN, Xu S, Cao ZFH, Gong R, Magnus CJ, Yu Y, Sternson SM. Neurons for hunger and thirst transmit a negative-valence teaching signal. Nature. 2015 May 14;521(7551):180-185. doi: 10.1038/nature14416. Epub 2015 Apr 27. PMID: 25915020; PMCID: PMC4567040.

8. Gong R^*, Ding C^*, Hu J^*, Lu Y, Liu F, Mann E, Xu F, Cohen MB, Luo M. Role for the membrane receptor guanylyl cyclase-C in attention deficiency and hyperactive behavior. Science. 2011 Sep 16;333(6049):1642-6. doi: 10.1126/science.1207675. Epub 2011 Aug 11. PMID: 21835979. (* equal contribution)