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  3. Picower Special Seminar with Sangyu Xu "Contextualized Phenovectors Reveal a Drosophila Serotonergic Circuit Controlling Satiety"
Picower Special Seminar with Sangyu Xu "Contextualized Phenovectors Reveal a Drosophila Serotonergic Circuit Controlling Satiety"
The Picower Institute for Learning and Memory

Picower Special Seminar with Sangyu Xu "Contextualized Phenovectors Reveal a Drosophila Serotonergic Circuit Controlling Satiety"

Add to CalendarAmerica/New_YorkPicower Special Seminar with Sangyu Xu "Contextualized Phenovectors Reveal a Drosophila Serotonergic Circuit Controlling Satiety"10/14/2026 4:00 pm10/14/2026 5:00 pmBuilding 46,Picower Seminar Room (46-3310, Third Fl of MIT Building 46)
October 14, 2026
4:00 pm - 5:00 pm
Location
Building 46,Picower Seminar Room (46-3310, Third Fl of MIT Building 46)
Contact
bgreeno@mit.edu
    Description

    Picower Special Seminar with Sangyu Xu, PhD

    • Speaker: Sangyu Xu, PhD, Duke-NUS Medical School, Singapore (The Neuroscience and Behavioural Disorders Programme)

    • Date: Wednesday, October 14, 2026

    • Time: 4:00pm

    • Location: Picower Seminar Room (46-3310, Third Floor of MIT Building 46)

    • Please note that this seminar is in person only

     

    Talk Title: Contextualized Phenovectors Reveal a Drosophila Serotonergic Circuit Controlling Satiety

     

    Abstract: How do we know when an intervention has truly changed an internal state, rather than simply moved a convenient metric? My work develops measurement and benchmarking methods for this problem, specifically in neural circuits supporting feeding behavior. I’ll discuss contextualized ethomics (DESTRA), a framework for testing whether a circuit perturbation reproduces a coherent natural state transition, such as the shift between hunger and satiety, across the behavioral profile rather than a single readout. This reframes what counts as evidence for a manipulation to have “worked”: not whether one variable moved in the expected direction, but whether the resulting phenovector wholistically resembles the biological state we intended to reproduce.

     

    I’ll connect this to a broader theme in my work: that understanding biological change requires us not only to ask whether an effect is present, but to quantify its magnitude and uncertainty as well. This perspective also motivated my work on DABEST, an estimation-statistics framework recently published.

     

    Bio: Sangyu Xu is a computational behavioral scientist studying how internal states, such as hunger, satiety, and attention, shape behavior and can be inferred from behavioral and physiological measurements. Her work spans neuromodulation, decision-making, and estimation statistics. She is a Senior Research Fellow in Adam Claridge-Chang’s lab at Duke-NUS Medical School and earned her PhD in Susumu Tonegawa’s lab at MIT.

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