Reverse engineering Hydra
Computational Neuroscience, Biomechanics, Neuroscience and seminar by Prof Adrienne Fairhall, University of Washington
Hosted by SWC Symposium
Friday 16:50–18:00 London (GMT+1)
Recording available
Abstract
Hydra is an extraordinary creature. Continuously replacing itself, it can live indefinitely, performing a stable repertoire of reasonably sophisticated behaviors. This remarkable stability under plasticity may be due to the uniform nature of its nervous system, which consists of two apparently noncommunicating nerve net layers. We use modeling to understand the role of active muscles and biomechanics interact with neural activity to shape Hydra behaviour. We will discuss our findings and thoughts on how this simple nervous system may self-organize to produce purposeful behavior.
Topics
Related seminars
- Video · 57 min · Apr 8, 2020Kanaka Rajan, Icahn School of Medicine at Mount Sinai
Nature over Nurture: Functional neuronal circuits emerge in the absence of developmental activity
Video · Apr 5, 2023Dániel L. Barabási, Engert lab, MCB Harvard UniversityNeural manifolds for the stable control of movement
Video · Apr 29, 2020Sara Solla, Northwestern University
More from SWC Symposium
All talksPhysical Computation in Insect Swarms
Video · Oct 8, 2021Orit PelegCollective Construction in Natural and Artificial Swarms
Video · Oct 8, 2021Justin WerfelTuning dumb neurons to task processing - via homeostasis
Video · Oct 8, 2021Viola PriesemannSwarms for people
Video · Oct 8, 2021Sabine Hauert
More with Adrienne Fairhall
All their workReconciling Diverse Experimental Findings on Inhibitory Tuning in the Mouse Visual Cortex
ePoster · Sep 29, 2024Bernstein Conference 2024Variability, maintenance and learning in birdsong
Seminar · Video · 45 min · Mar 31, 2021van Vreeswijk TNSReverse engineering neural control of movement in Hydra
Seminar · Oct 7, 2020Systems NeuroecologyThe Learning Salon
Seminar · Video · Sep 11, 2020Learning Salon
Upcoming in Computational Neuroscience
All seminarsLearning to Oscillate: Hebbian Plasticity Imprints Limit Cycles in Neural Networks
Nov 4, 2026Pierfrancesco Urbani