RESEARCH AREAS
Social interactions between individuals and among groups are a hallmark of human society and are critical to the physical and mental health of a wide variety of species including humans. The central goal of our lab is to study general principles of how social behavior is regulated in the brain. We take a multi-disciplinary approach and uses a variety of experimental and computational technologies across molecular, circuit, and behavioral levels. We study how neural circuits regulate social behavioral decisions within a single brain as well as how emergent inter-brain neural properties arise from social interactions between individuals.
1. Neural circuits underlying social behavioral decisions (within a single brain)
Social behaviors among conspecifics, either conflictive or cooperative, are exhibited by all animal species. Social interactions involve active detection of various social cues and selection of appropriate social decisions. We are interested in studying how social sensory information is processed and integrated in the brain and how different social behavioral decisions are selected and modulated in neural circuits.
General review:
Chen P, Hong W. Neural circuit mechanisms of social behavior. Neuron 2018.
Representation of conspecific sex during social interaction
Kingsbury L, Huang S, Raam T, Ye LS, Wei D, Hu RK, Ye L, Hong W. Cortical representations of conspecific sex shape social behavior Neuron 2020.
Neural mechanisms underlying parenting behavior
Chen PB, Hu RK, Wu YE, Pan L, Huang S, Micevych PE, Hong W. Sexually dimorphic control of parenting behavior by the medial amygdala. Cell 2019.
Neural mechanisms underlying aggressive behavior
Hong W, Kim DW, Anderson DJ. Antagonistic control of social versus repetitive self-grooming behaviors by separable amygdala neuronal subsets. Cell 2014.
2. Emergent inter-brain properties in a multi-brain neural system (across brains)
Social interaction can be seen as a dynamic feedback loop that dynamically shapes behavior, shared cognitive states, and social relationships across individual agents. A fuller understanding of the social brain requires a description of how the neural dynamics across coupled brains are linked and how they coevolve over time. We study social decisions and emergent inter-brain neural properties in a multi-brain framework that considers social interaction as an integrated network of neural systems.
General review
Kingsbury L, Hong W. A multi-brain framework for social interaction. Trends in Neurosciences 2020.
Inter-brain neural synchrony across brains of socially interacting mice
Kingsbury L, Huang S, Wang J, Gu K, Golshani P, Wu YE, Hong W. Correlated neural activity and encoding of behavior across brains of socially interacting animals. Cell 2019.
General review
Kingsbury L, Hong W. A multi-brain framework for social interaction. Trends in Neurosciences 2020.
Inter-brain neural synchrony across brains of socially interacting mice
Kingsbury L, Huang S, Wang J, Gu K, Golshani P, Wu YE, Hong W. Correlated neural activity and encoding of behavior across brains of socially interacting animals. Cell 2019.
3. Molecular and behavioral tools for studying social behavior
Act-seq: a single-cell sequencing approach to identify active neuronal populations
Wu YE, Pan L, Zuo Y, Li X, Hong W. Detecting Activated Cell Populations Using Single-Cell RNA-Seq. Neuron 2017.
Using depth sensing and machine learning to track and analyze social behavior
Hong W, Kennedy A, Burgos-Artizzu XP, Zelikowsky M, Navonne SG, Perona P, Anderson DJ. Automated Measurement of Mouse Social Behaviors Using Depth Sensing, Video Tracking, and Machine Learning. Proc. Natl. Acad. Sci. USA. 2015.
Wu YE, Pan L, Zuo Y, Li X, Hong W. Detecting Activated Cell Populations Using Single-Cell RNA-Seq. Neuron 2017.
Using depth sensing and machine learning to track and analyze social behavior
Hong W, Kennedy A, Burgos-Artizzu XP, Zelikowsky M, Navonne SG, Perona P, Anderson DJ. Automated Measurement of Mouse Social Behaviors Using Depth Sensing, Video Tracking, and Machine Learning. Proc. Natl. Acad. Sci. USA. 2015.