Introduction to Research

The ultimate goal of neuroscience research is to deeply understand how the brain performs computations, in order to construct or repair an intelligent entity equivalent to the brain. The main obstacle to this goal is that the brain contains a vast number of basic computing units—neurons; moreover, these units can communicate through complex long-distance connections, forming an enormous potential for combinations—so much so that the number of possible combinations of neurons in a small fish’s brain far exceeds the total number of atoms likely present in the universe! This complexity is the source of the brain's extraordinary capabilities, surpassing any other type of biological organ. As a result, brain science inevitably becomes a cutting-edge interdisciplinary field that must integrate techniques and methods from multiple disciplines to unravel its mysteries. Our laboratory is committed to developing this interdisciplinary research paradigm, exploring neuroscience questions to discover profound neural principles, and training a new generation of scholars who can thrive in interdisciplinary research.

Research Strategy

Our strategy adopts a complex systems science perspective to analyze multidimensional information about structure, function, and molecules at the whole-brain scale, revealing the patterns of interaction between different brain regions and between cells. Complex systems science has shown its significant value in fields such as climate, electrical networks, and social networks, explaining the principles of self-organization and emergence through nonlinear processes. This field's research contributions were recognized with the 2021 Nobel Prize in Physics. Such a research perspective is crucial for explaining how the brain operates, where the key lies in the acquisition of high-quality biological data and its effective integration with theoretical methods.

Research Subject

Under this framework, we use zebrafish, which allow for observation of all neural activities across the entire brain, as our research subjects to establish a whole-brain, single-cell resolution research system. This system includes a specially designed optical microscope for whole-brain imaging, fluorescent probes for live imaging, behavior paradigms integrated with virtual reality, and appropriate data analysis methods. Our research has been published in top-tier journals like Cell, Nature Neuroscience, Neuron, and eLife, placing us at the forefront of international research.

Scientific Questions

In the process of sensory-motor transduction, we analyze the activity of excitatory and inhibitory neurons across the whole brain, while also monitoring neurotransmitter systems such as dopamine, serotonin, and norepinephrine. With this comprehensive neural data, we focus on: (1) What are the fundamental principles of how the brain encodes sensory information across multiple modalities and types? (2) What is the whole-brain model that maintains sensory information and generates decision-making? (3) What are the whole-brain mechanisms that modify cognition and states through behavior feedback during active exploration?

Furthermore, we also apply our methods to broader and more complex systems, such as interactions between the nervous system and the enteric nervous system.

In addition, we closely cooperate with our center's zebrafish whole-brain neural connectivity atlas platform to integrate the brain's structure and function. By analyzing complete data, we decipher the underlying architecture and information processing mechanisms of brain networks. Our ultimate goal is to reveal the neural mechanisms of flexibility and robustness in visuo-motor transduction based on whole-brain neural connectivity structures and dynamics, driving a paradigm shift in brain science research from localized to holistic studies.

When these research goals are truly realized, a clear indicator will be our ability to integrate all our discoveries about structure and function into a virtual intelligent agent. This agent will be able to simulate the behavior of real fish and possess the ability to survive in unknown environments. Moreover, given sufficient resources and virtual life conditions, this agent will also be able to evolve over time, developing more complex and sophisticated strategies for intelligence. Further, when the body of this virtual fish is replaced with that of another species, it will be able to adapt and learn, thriving in new environments and different bodily conditions, demonstrating remarkable adaptability. Lab webpage: www.mulab.org