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Plasticity Without Genetic Change - Bioelectric Embryos & Synthetic Proto-Organisms

Institute for Pure & Applied Mathematics (IPAM) via YouTube

Overview

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Explore a cutting-edge lecture on structural and functional plasticity in biological systems without genetic changes. Delve into the fascinating world of bioelectric embryos and synthetic proto-organisms as presented by Michael Levin from Tufts University. Discover how embryogenesis and regeneration adapt to environmental perturbations, challenging traditional notions of morphogenetic control and evolution. Learn about AI-driven reconfiguration of embryonic tissues leading to novel organisms with unprecedented collective behaviors, such as kinematic self-replication. Examine how these findings blur the lines between genotype and phenotype, brain and body, and tape and machine. Gain insights into bioelectric encoding of anatomical patterns, the role of somatic electrical activity in morphogenetic decision-making, and the development of quantitative, predictive multiscale machine learning models for biological systems. Explore the potential biomedical applications and the creation of synthetic morphologies, including the groundbreaking Xenobots.

Syllabus

Intro
Knowledge Gaps: prediction
The State of the Art
Where is Anatomical Pattern Specified?
Same anatomy, despite perturbations
Somatic electrical activity is the cognitive medium of morphogenetic decision-making
Writing High-level Setpoints into Cellular CI
Endogenous membrane voltage pattern is crucial for Xenopus embryonic brain patterning
Re-writing Target Morphology
Bioelectrically-Encoded Pattern Memory
An organism's genome sets its Target Morphology, doesn't it?
Developing Quantitative, Predictive Multiscale
Machine Learning for Model Discovery
Cell Collectives can pursue Target Morphologies other than their Genomic Default
Biomedical Applications
Synthetic Morphology: probing the creativity of cellular collective intelligence
Xenobots - a novel proto-organism

Taught by

Institute for Pure & Applied Mathematics (IPAM)

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