The latest DEEP-IN seminar, also a joint iTHEMS Biology seminar series, was held on June 27. The seminar featured an impressive talk by Dr. Chen Xiaowen, a postdoctoral researcher at LPENS, CNRS, France. Conducted virtually, the seminar attracted a broad audience interested in understanding collective behavior from a physics perspective.

Chen Xiaowen's talk, "Inferring Collective Behavior from Social Interactions to Population Coding," focused on the ubiquitous nature of collective behavior, from social animals to neural networks. These behaviors, encoded in interactions between individuals or cells, play critical roles in diverse biological systems. While recent advances in statistical physics have provided new insights, much of the traditional research has overlooked the temporal aspect, focusing instead on static, steady-state distributions.

Xiaowen introduced two significant advancements that address this gap by incorporating the temporal dynamics of collective behavior. The first study examined the co-localization patterns of social mice. By developing a novel inference method called generalized Glauber dynamics (GGD), the research team could capture both static and dynamic features of the data. The GGD dynamics not only explained these features effectively but also provided insights into the sociability of different mice strains through the inferred interactions.

The second part of the seminar focused on neuronal interactions in the larval zebrafish hindbrain. Although many details were left out in this part due to time constraints, Xiaowen provided a comprehensive overview of how dynamic analyses can fill the gap left by traditional static approaches and improve our understanding of neuronal interactions.

Stay tuned for more seminars and updates from the DEEP-IN events!

Reported by Lingxiao Wang

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