TNC Neurocolloquium - MPI Lecture - Srinivas Turaga

“Modeling the fruit fly brain and body” Thursday, April 11th, at 16:15 (CEST).

The TNC presents the MPI Lecture:

Speaker: Srinivas Turaga (HHMI Janelia Research Campus)

Title: Modeling the fruit fly brain and body

Host: Peter Dayan (Max Planck Institute for Biological Cybernetics, Tübingen)

Location: Lecture Hall HNO (Hals-Nasen-Ohren-Klinik), Elfriede-Aulhorn-Str. 5, Tübingen and online. Please contact silke.dutz@medizin.uni-tuebingen.de for the zoom login details.

Afterwards, there will be a Get Together at the HNO Lecture Hall with drinks and Butterbrezeln for everybody to enjoy.

Abstract: Through recent advances in microscopy, we now have an unprecedented view of the brain and body of the fruit fly Drosophila melanogaster. We now know the connectivity at single neuron resolution across the whole brain. How do we translate these new measurements into a deeper understanding of how the brain processes sensory information and produces behavior? I will describe two computational efforts to model the brain and the body of the fruit fly. First, I will describe a new modeling method which makes highly accurate predictions of neural activity in the fly visual system as measured in the living brain, using only measurements of its connectivity from a dead brain [1], joint work with Jakob Macke. Second, I will describe a whole body physics simulation of the fruit fly which can accurately reproduce its locomotion behaviors, both flight and walking [2], joint work with Google DeepMind.

[1] Lappalainen JK, Tschopp FD, Prakhya S, McGill M, Nern A, Shinomiya K, Takemura Sy, Gruntman E, Macke JH, and Turaga SC. Connectome-constrained deep mechanistic networks predict neural responses across the fly visual system at single-neuron resolution. bioRxiv, 2023.
https://www.biorxiv.org/content/10.1101/2023.03.11.532232
[2] Vaxenburg R, Siwanowicz I, Merel J, Robie AA, Morrow C, Novati G, Stefanidi Z, Card GM, Reiser MB, Botvinick MM, Branson KM, Tassa† Y, and Turaga† SC. Whole-body simulation of realistic fruit fly loco- motion with deep reinforcement learning. bioRxiv, 2024.
https://www.biorxiv.org/content/10.1101/2024.03.11.584515

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