Event type: Seminar
Events
Alexander Petroff
(Clark University)
Magnetotactic Bacteria Optimally Navigate Pore Networks
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Magnetotactic bacteria swim along geomagnetic field lines to navigate the pore spaces of water-saturated sediment. To understand the physical basis for efficient navigation in confined geometries, we observe the motion of Multicellular Magnetotactic Bacteria through an artificial pore space under an applied magnetic field. Magnetotaxis is fastest when bacteria swim a distance of order the pore size in the time required to align with the applied field. A model---in which bacteria deterministically align with the magnetic field and randomly scatter off boundaries---predicts the non-monotonic relationship between the drift velocity and applied magnetic field and the value of the maximum drift velocity. A comparison of diverse MTB shows that the magnetic moments, swimming speeds, and hydrodynamic mobilities of different species covary such that the average speed of magnetotaxis for each species is close to optimal for its natural environment.
Fernando Pascoal Dos Santos
(University of Amsterdam)
The complexity of human cooperation under indirect reciprocity
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Indirect reciprocity is a key mechanism to understand the evolution of cooperation among unrelated individuals. It involves reputations and complex information processing, arising from social interactions. By helping someone, individuals may improve their reputation, which may be shared in a population and change the predisposition of others to reciprocate in the future. The reputation of individuals depends, in turn, on social norms that define a good or bad action, offering a mathematically appealing way of studying the evolution of moral systems. Over the years, theoretical and empirical research has unveiled many features of cooperation under IR, exploring norms with varying degrees of complexity and information requirements. Often, however, it is assumed that reputations spread for free, and individuals can adopt arbitrarily complex norms and strategies. In this presentation, I will discuss a way to quantify the complexity of norms and strategies in indirect reciprocity and the challenges introduced by complex rules and costly reputation sharing. We will observe that cooperation can prevail with simple norms and costly reputation sharing, provided that individuals can anticipate the reporting intentions of their opponents. I will conclude by discussing future research directions and the prospects of applying mathematical biology methods to design prosocial artificial systems.
Anita Layton
(University of Waterloo)
His and Her Mathematical Models of Physiological Systems
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Imagine someone having a heart attack. Do you visualize the dramatic Hollywood portrayal of a heart attack, in which a man collapses, grabbing his chest in agony? Even though heart disease is the leading killer of women worldwide, the misconception that heart disease is a men’s disease has persisted. A dangerous misconceptions and risks women ignoring their own symptoms. Gender biases and false impressions are by no means limited to heart attack symptoms. Such prejudices exist throughout our healthcare system, from scientific research to disease diagnosis and treatment strategies. A goal of our research program is to address this gender equity, by identifying and disseminating insights into sex differences in health and disease, using computational modeling tools.
Marte Julie Sætra
(Simula Research Laboratory)
Computational modeling of ion concentration dynamics in brain tissue
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Over the past decades, computational neuroscientists have developed ever more sophisticated and morphologically complex neuron models. Most of these models assume that the intra- and extracellular ion concentrations remain constant over the simulated period and thus do not account for concentration-dependent effects on neuronal firing properties. Of the models that do incorporate ion concentration dynamics, few account for the electrodiffusive nature of intra- and extracellular ion transport. In this talk, I will present the first multicompartmental neuron model that accounts for ion concentration dynamics in a biophysically consistent manner [1]. I will also show how electrodiffusive modeling of neurons and glial cells can be used to explore the genesis of slow potentials in the brain [2].
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https://mathbio.sas.upenn.edu/event_listing_type/seminar/page/2/
https://mathbio.sas.upenn.edu/event_listing_type/seminar/
