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SUMMARY:Poster Flash Talks Group A: Graph-based method for reconstruction 
  of neuronal networks - Philippe Aymard (CNRS - Ecole Normale Superieure P
 aris)
DTSTART:20251202T144500Z
DTEND:20251202T145000Z
UID:TALK240988@talks.cam.ac.uk
DESCRIPTION:Connected networks are central to neurobiology\, and reconstru
 cting them is key to understanding the computational principles of the bra
 in. Modern recording technologies&mdash\;calcium imaging\, Neuropixels\, a
 nd large-scale electrophysiology&mdash\;now generate massive neuronal data
 sets\, creating a need for robust\, interpretable graph-based analysis too
 ls. We present a simple graph reconstruction framework [1] enhanced by a d
 ata-driven adaptive thresholding method derived from statistics. Using str
 ongly connected components\, we extract functionally relevant sub-networks
 \, and we characterize their topology through Markovian statistics [2\,3].
  Applied to volumetric calcium imaging data [4]\, our approach reveals sub
 -networks whose activity patterns suggest their role as fundamental comput
 ational units of the brain.\n[1] Aymard\, P.\, Boffi J-C.\, Asari H.\, Pre
 vedel R.\, Holcman D. Column-Like Subnetwork Reconstruction in Motor Corte
 x &nbsp\;from Graph-Based 3D High-Density Two-Photon Calcium Imaging doi: 
 https://doi.org/10.1101/2025.06.17.660119. [2] Karlin\, S.\, and Taylor\, 
 H. (1981). A Second Course in Stochastic Processes. vol. 2. Elsevier Scien
 ce.[3] Boyd\, S.\, Diaconis\, P.\, and Xiao\, L. (2004). Fastest mixing ma
 rkov chain on a graph. SIAM Review 46.[4] Prevedel\, R.\, Verhoef\, A.\, P
 ern&iacute\;a-Andrade\, A. et al. Fast volumetric calcium imaging across m
 ultiple cortical layers using sculpted light. Nat Methods 13.&nbsp\;
LOCATION:Seminar Room 1\, Newton Institute
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