Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session R01: Learning without NeuronsInvited Live
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Sponsoring Units: DBIO Chair: Arvind Murugan, University of Chicago Room: 01 |
Thursday, March 18, 2021 8:00AM - 8:36AM Live |
R01.00001: Processing information by flow: the smart slime mold Physarum Invited Speaker: Karen Alim Simple organisms manage to thrive in complex environments. Propagating and remembering information about the environment is key to take decisions. The network-shaped slime mold Physarum polycephalum excels as a giant unicellular eukaryote being even able to solve optimization problems despite the lack of a nervous system. To uncover how Physarum accomplishes these tasks we combine experimental observations of the organism’s response to nutrients with theoretical modelling of network adaptation and fluid flows pervading the network. We find that flows are the mean to propagate information about the location of a nutrient source. Information that is subsequently memorized in the pattern of thicker and smaller tubes of the network’s architecture. As the pattern of tube size determines organism behavior such as migration direction, these memories are forming the basis for behavioral decisions. |
Thursday, March 18, 2021 8:36AM - 9:12AM Live |
R01.00002: Learning in Physical Networks:
From Machine Learning to Learning Machines Invited Speaker: Menachem Stern Materials and machines are often designed with particular goals in mind, so that they exhibit desired responses to given forces or constraints. Here we explore an alternative approach, namely physical learning. In this paradigm, the network physically adapts to applied forces, obtaining a desired function. Crucially, learning is facilitated by physically plausible learning rules, requiring only local responses and no explicit information about the desired functionality. |
Thursday, March 18, 2021 9:12AM - 9:48AM Live |
R01.00003: Prediction and learning in immune repertoires Invited Speaker: Aleksandra Walczak
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Thursday, March 18, 2021 9:48AM - 10:24AM Live |
R01.00004: Evolutionary principles of protein structure and function Invited Speaker: Rama Ranganathan Proteins can fold spontaneously into well-defined three-dimensional structures and can carry out complex biochemical reactions such as binding, catalysis, and long-range information transfer. The precision required for these properties is achieved while also preserving evolvability – the capacity to adapt in response to fluctuating selection pressures in the environment. What is the basic design of proteins that supports all of these properties? Recent work suggests that rather than direct physical analysis, statistical analysis of genome sequences provides a powerful and general approach to this problem. Using different methodologies, this approach has revealed both direct structural contacts as well as collective functional modes within protein structures. In this talk, I will present new approaches for probing the physical mechanisms implied by the evolution-based models and present ideas for how such mechanisms are constrained by the dynamics of the evolutionary process. This work represents a step towards a theory for the physics of proteins that is consistent with evolution. |
Thursday, March 18, 2021 10:24AM - 11:00AM On Demand |
R01.00005: How ecosystems and gene regulatory networks can learn? Invited Speaker: Eörs Szathmáry Both evolution and learning are known to produce (sometimes spectacular) adaptive solutions. One can rightfully ask whether these processes might share some common features, and whether they can help each other, possibly in the form of one being a "subroutine" in the other and vice versa. |
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