Event Schedule

Sitabhra Sinha

Nonlinearity and Pattern Formation [Part 2]

Tea Break

Hareesh J.

Nonlinearity and Pattern Formation [Part 3]

Soling Zimik

Statistical Physics of Collective Phenomena [part 2]

Phase Transitions in the Ising Model

Lunch Break

Soling Zimik

Statistical Physics of Collective Phenomena [part 3]

Tutorial on the Ising Model

Tea Break

V. Sasidevan

Game Theory for Beginners [Part 3]

Group Project Discussion

V. Sasidevan

Game Theory for Beginners [Part 4]

Tea Break

Sitabhra Sinha

Evolutionary Games and Adaptive Dynamics [Part 1]

Sitabhra Sinha

Evolutionary Games and Adaptive Dynamics [Part 2]

Lunch Break

Shakti N. Menon

Crowds in Motion: Herding, Flocking, Swarming [Part 1]

Thirteen Ways of Looking at a Boid, or: A Walk for a Walk's Sake

Tea Break

Rainer Klages [online talk]

Modelling the movements of organisms: Movement ecology meets active particles and anomalous diffusion

Organisms living at very different spatio-temporal scales, from migrating in the microworld to foraging across the earth, display random-looking movement paths. Understanding these complex patterns by constructing mathematical models from data provides a fundamental challenge. In this talk I review fundamental stochastic models for understanding movement data, like (correlated) random walks, (generalised) Langevin equations and active Brownian particles. On this basis experimental data for the movement paths of foraging sea turtles, migrating cells and bumblee flights is analysed. For all three examples generalised overdamped Langevin equations are constructed from data revealing active and anomalous diffusive properties. I then put forward a generalised underdamped Langevin equation for modelling organismic movements, which blends key ingredients of the three fields of movement ecology, active particles and anomalous diffusion. I illustrate the application of this equation for constructing a stochastic model of bumblebee flights from experimental data and outline its theoretical foundation.

Group Project Discussion

Sitabhra Sinha

Evolutionary Games and Adaptive Dynamics [Part 3]

Tea Break

Shakti N. Menon

Crowds in Motion: Herding, Flocking, Swarming [Part 2]

The Shape of Flocks to Come: Modelling Collective Motion

Hareesh J.

Networks: Structure, Dynamics and Function [Part 1]

Lunch Break

Sanjay P. Sane

Collective Construction Behavior in Mound-Building Termites

Tea Break

P. Varuni

Group Project Discussion

Shakti N. Menon

Crowds in Motion: Herding, Flocking, Swarming [Part 3]

Soft Machines: Collective Motion at the Micro-Scale

Tea Break

Shakti N. Menon

Crowds in Motion: Herding, Flocking, Swarming [Part 4]

Something in the Air: The Physics of Crowds

Hareesh J.

Networks: Structure, Dynamics and Function [Part 2]

Lunch Break

Hareesh J.

Networks: Structure, Dynamics and Function [Part 3]

Tea Break

Ana Amador [online]

Emergent low-dimensional oscillatory dynamics in neural networks coding for birdsong

Oscillatory dynamics and rhythmic pattern generation are fundamental features of many nonlinear systems out of equilibrium. A central challenge across disciplines is to understand how such low-dimensional dynamics emerge from high-dimensional, strongly coupled networks.

In this talk, I will present birdsong production as a biological model system to investigate the emergence of rhythmic oscillations from complex neural networks. Specifically, I will show neurophysiological recordings obtained in our lab during song production. Using machine learning techniques to uncover concise underlying structure in the data, we identified a low-dimensional representation of the neural recordings by analyzing the latent modes of an autoencoder neural network. Our results show that, despite the high dimensionality of the underlying neural network, song production is governed by a small number of dynamical variables exhibiting robust oscillatory structure. These findings highlight general mechanisms of dimensionality reduction and rhythm generation in complex.

This work illustrates how interdisciplinary approaches combining neuroscience and nonlinear dynamics, can provide insight into universal principles underlying oscillations and dynamic instabilities in biological networks

Group Project Discussion

Kavita Isvaran

Tea Break

Vishwesha Guttal

Vishwesha Guttal

Lunch Break

Supreet Saini

Tea Break

Anupama Sharma

Collective Resistance in Spatially Structured Microbial Communities

Antibiotic resistance in microbial populations is often studied in well-mixed environments, despite the fact that most natural microbial communities are spatially structured. In this talk, I will discuss how spatial organization can alter the dynamics of antibiotic resistance during microbial range expansion. I will also highlight how local interactions between resistant and sensitive cells can give rise to collective survival under antibiotic stress.

Group Project Discussion

Supreet Saini

Tea Break

Supreet Saini

Jitesh Jhawar

Lunch Break

Annagiri Sumana

Tea Break

Ramray Bhat

Group Project Discussion

Jitesh Jhawar

Tea Break

Jitesh Jhawar

Anuradha Bhat

Lunch Break

Annagiri Sumana

Tea Break

Ramray Bhat

Group Project Discussion

Viraj Torsekar

Tea Break

Anuradha Bhat

Manjari Jain

Lunch Break

Amitabh Joshi

Re-examining the role of heritability in explaining selection responses

Heritability is typically treated as a unitary concept in evolutionary genetics, depicted as a quantity ranging between zero and one that can be estimated through the ratio of additive genetic to phenotypic variance, or by offspring parent phenotypic regression, or as the ratio of selection response to selection differential. However, these three heritabilities are distinct, and converge only under very restrictive conditions. Two of them are not even constrained to lie between zero and one. I will discuss what exactly these three heritabilities are, when they do or do not coincide, and some implications for widely-held beliefs in evolution such as Sewall Wright's misplaced insistence that Fisher's Fundamental Theorem implies that populations can not move downhill on an adaptive landscape under the influence of selection. I will show that even for a simple one-locus two-allele model of viability selection - if we relax only the assumption that the previous generation underwent random mating - heritability exceeds one, or is negative, for large parts of the genotypic frequency simplex. These imply, respectively, that heredity can also amplify the mean fitness gains of selection, or move populations downhill on the fitness landscape from one generation to the next, in addition to playing its canonical role of slightly reducing the fitness gains through selection due to a return to Hardy-Weinberg frequencies upon reproduction. The canonical role of heredity actually manifests itself only in a small part of the genotypic frequency simplex, around the Hardy-Weinberg parabola.

Tea Break

Lukas Eigentler [online talk]

Variation in resource quality causes maintenance of individual variation in a competitive trait

When competitive traits are costly, negative frequency-dependence can maintain genetic variance. Most theoretical studies examining this question assume binary polymorphisms, yet most trait variation in wild populations is continuous. In this talk I show results obtained through an individual based model that propose that continuous trait variation can result from continuous variation in resource quality. Moreover, I highlight that the shape of the resource distribution determines whether or not temporal fluctuations in trait values occur. Finally, I show some preliminary results from a corresponding PDE model, whose bifurcation structure provides more insight into the conditions leading to polymorphisms.

Anindya Sinha

Tea Break

Manjari Jain

Mrinal Kanti Pal

Lunch Break

P. Varuni

Tea Break

Amitabh Joshi

Twenty-eight years of experimental (and theoretical) population dynamics in the lab

Fruitflies of the genus Drosophila have been used extensively as model systems in genetics, development, evolution and population ecology for almost a century. A detailed understanding of the ecology of Drosophila cultures, and the major factors playing a role in regulating population size in a density-dependent manner, together with detailed species-specific modelling of population growth, has led to substantial enhancement of our understanding in many areas at the interface of population ecology and evolution over the past two decades in our laboratory. Here, I provide a “big-picture” overview of this body of work on the importance of interactions between local dynamics and dispersal, the context-specific nature of the relationship between the constancy and persistence aspects of population stability, and the many nuances of density-dependent selection and the evolution of competitive ability and population stability. I also briefly describe how these studies came about, and how they are interlinked, so that the historical and technical reasons for why these advances were possible with the Drosophila system become clear.

Group Project Presentations

Tea Break

Group Project Presentations

Group Project Presentations

Lunch Break

Group Project Presentations

Tea Break

Closing Session