Rong Gong

Neural Mechanism of Adaptive Consumption Behavior

Consumption behaviors are essential to life. In higher life-forms with appetite control, rather than being the so-called “innate behaviors”, feeding is much more adaptive. It often entails many learning components and reveals unanticipated complexity. Under such contexts, the consumption decision in feeding depends on the interactions between the nervous system, body, and environment. Therefore, under neural constraints, both external and internal elements determine what to eat, how much to eat and how often to eat. These elements often include not only hunger or satiety sensation but also perception to the food-related cues, internal references from previous consumption experiences and so on. Meanwhile, in modern society, our environment abounds with more and more high-palatable, high-calorie food, which dramatically shape our consumption habit: tasty food, food-related cues or memory of yummy food often easily drive to excessive food intake. Overexaggerating of food or food-associative cue perception has become one of the major contributors to obesity or obesity-related metabolic diseases in modern society, such as type II diabetes. The skewed adaptive consumption behavior is tightly linked to our current consumption experiences. And understanding the neuronal mechanism of it is important to set up the guideline towards healthy eating, fighting against obesity or obesity-related metabolic diseases. Based on that, our lab current focuses are (but not limited to) the following questions:

1. How does palatable food or beverage drive to excess intake beyond the metabolic need? How are the palatable information encoded in brain and how does it determine meal size mechanistically? How are palatable information involved in food-based learning and memory? And how does these learning components determine our food selection and preferences?

2. How are the reward properties of food transferred to food-associative external cues, for example, food advertisements and fast-food restaurants?  How do these food-associative cues finally drive to overconsumption?

3. Any chances to reverse overconsumption habit driven by palatable food or food-associative cues/contexts? What are the molecular and neural circuit models of reversal?

Regulation of physiological states on other cognitive functions

Sensorimotor transformation in brain is not an optical flow process. Instead, sensory perception often integrates organisms’ internal state information, which incorporates organisms’ physiological states, such as homeostatic states or emotional states, and internal references derived from the previous experiences. It has been widely appreciated that physiological states set the “ground rules” for diverse behaviors. They have great impact on the development of internal references and can regulate sensorimotor transformation process in multiple ways. For example, perception of hunger or thirst is the fundamental basis of divergent behaviors in face of the same sensory inputs, one of the major contributors to flexible behaviors. In the past decades, knowledge has gained regarding to how our brain monitors physiological states and orchestrates need-motivated behaviors important for survival. However, we know little of how these physiological states, such as hunger or thirst, regulate other cognitive behaviors. For example, how does hunger/thirst configurate the neural dynamics during sensorimotor transformation and directly change the route of behavior output? How does hunger/thirst influence learning and memory process, and thereby indirectly change behavior in face of the same sensory perception? Using mice as a model, we are also interested in the role that physiological states play in flexible behaviors and focus on its impact on other cognitive functions. We aim to specifically ask these questions:

1. How does hunger change our gustatory perception? What are the underlying molecular and neuronal circuit models?

2. How does energy surfeit or shortage regulate long-term or short-term memory? Would they determine the subjective valence of memory? What is the optimized energy state for quick learning?

Our lab will combine spatial transcriptomics, neural dynamics, neural circuit study and behavior decomposition to address the above questions in molecular, cellular and circuitry levels.

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. 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, 333, 1642-1646 (* equal contribution).

2. 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.

3. Gong R, Xu S, Hermundstad AM, Yu Y, Sternson SM. Hindbrain double-negative feedback mediates palatability-guided food and water consumption. Cell, 2020 September 17; 182, 1-17.