Mauricio Girardi-Schappo
Federal University of Santa Catarina (UFSC), Brazil

Title: Neural adaptation and spatial learning: from navigation to the dentate gyrus

Abstract: Adaptive neural networks are involved in various brain functions, from sensory perception to memory and spatial navigation. In this presentation, we will discuss how neural adaptability influences spatial learning on three levels: in the behavior of mice in a navigation task, in the activity of place cells in the dentate gyrus (DG), and in the encoding of information in a DG-inspired neural network. We will show that mice can learn the position of a target and build a cognitive map using only path integration. In addition, we will also show that the excitatory cells of the DG have a highly adaptive firing threshold, allowing for synergistic encoding of stimuli. This adaptation favors the differentiation of similar stimuli through firing patterns in the network, instead of exclusively depending on the average firing rate, as classically expected. This suggests that neural adaptation is fundamental for the flexibility and efficiency of spatial processing in the brain and must be a key mechanism for memory formation by the hippocampus.

Pablo A. Marquet
Pontificia Universidad Catolica de Chile, Chile & The Santa Fe Institute, USA

Title: The emergence, maintenance, and dynamics of biodiversity

Abstract: The question for the emergence, maintenance, and dynamics of biodiversity are at the core of biology in general, and ecology and evolution in particular. During my career I have worked on these three questions and came to realize not only their non-independence but their interaction and the existence of some common themes. In this talk I will try to connect these three questions and show their commonalities. I will highlight, with the help of simple adaptive dynamics models, diffusion theory, super-statistical mechanics metaphors and noncommutative algebraic approaches, the existence of some important first principles that could be useful towards developing  a coherent theory of biodiversity rooted in birth-death processes, symmetry (neutrality), niche construction, and noncommutativity.

Title: Challenges in simulating whole virus particles and some initiatives to address in the South

Abstract: Recent advances in specialized software and computing power have made it technically feasible to simulate large molecular assemblies, though these simulations remain computationally expensive. Coarse-grained (CG) modeling approaches address this challenge by reducing molecular complexity and computational demands while maintaining essential physical and chemical interactions between molecules. This makes virus simulations more practical for research teams without access to extensive supercomputing facilities.

Nevertheless, preparing and executing molecular dynamics simulations of systems containing millions of components demands expertise in molecular modeling, editing, and visualization. Additionally, critical decisions regarding computational setup, simulation engine selection, and force field parameters that govern intermolecular interactions require careful consideration to achieve realistic representations of viral systems at both fully atomistic and CG scales.

This work presents an overview of current obstacles in whole virus particle simulation, examining how the SIRAH force field can help overcome these challenges through its CG and multiscale simulation capabilities.

Title: Brain dynamics: data analysis and numerical simulation of neuronal circuits

Abstract: The brain is one of the best examples of a complex, out-of-equilibrium system studied by science. Understanding how the brain processes information during cognitive tasks remains a fundamental challenge in neuroscience. Significant advances have been made in recent years in understanding brain dynamics and connectivity using tools from nonlinear dynamics, statistical analysis, and complex networks. The applications of this knowledge range from improved diagnosis of neurodegenerative diseases and neurological disorders to technological advancements such as brain-machine interfaces for biomechanical control. This talk will present examples of how physics can be applied to study the nervous system, focusing on both dynamical system modeling and the analysis of electrophysiological data. Neuronal population models that reproduce phenomena observed in brain signals from humans and other animals, such as oscillations, synchronization, bistability, and phase diversity, will be discussed. Additionally, the talk will cover methods for comparing model dynamics with experimental data using measures of entropy and complexity, in light of recent results on the maximization of complexity near criticality and the characterization of different cortical states.

Title: Scale invariance in the physics of life

Abstract: Organisms come in a wide range of sizes and behaviors span a wide range of time scales.  There are classical scaling relations, such as the power-law dependence of metabolism on body mass, but it is not clear if these are rules of thumb or more exact statements.  In many areas of physics, scale invariance was the clue pointing to deep theoretical ideas.  I will explore three examples in the physics of biological systems—patterns of gene expression in the early fly embryo, dynamics in a network of 1000+ neurons, and the walking behavior of flies—where scaling relations are precise in the second decimal place.  Most of the discussion will be phenomenological, in the hope of generating discussion.