Practical information: 

The workshop is a full-day event, taking place from 9:00 until 17:00.

The location of the workshop is De Brug, Roeterseiland campus, Nieuwe Achtergracht 127, Amsterdam.

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Registration:

Please register through this form.

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Tentative shedule:

09:00-09:25: Walk-in

09.25-09.30: Opening remarks

 

09:30-10:15: Speaker 1

10:15-11:00: Speaker 2

11:00-11:30: Coffee break

11:30-12:15: Speaker 3

 

12:15-13:45: Lunch break

 

13:45-14:30: Speaker 4

14:30-15:15: Speaker 5

15:15-15:45: Coffee break

15:45-16:30: Speaker 6

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Professor Constantino Tsallis: Along the Boltzmann-Gibbs-von Neumann-Shannon legacy – Nonadditive entropies

Boltzmann-Gibbs (BG) statistical mechanics is, together with Newton, Einstein and quantum mechanics as 
well as Maxwell electromagnetism, one of the pillars of contemporary theoretical physics. As well known,
this magnificent theory, grounded on the BG additive entropic functional, satisfactorily handles, along more
than 150 years, a plethora of physical phenomena. It fails, however, when relevant space-time correlations
are strictly long-ranged, meaning typically that correlation momenta are not finite at all orders. To overcome
such limitations, a generalized statistical mechanics is possible grounded on nonadditive entropic
functionals. This enlarged theory, first proposed in 1988, has been successfully applied to diverse natural,
technological and social complex systems. Moreover, it implies that the BG entropy is sufficient but not
necessary for preserving the Legendre structure of classical thermodynamics. We will briefly present the
foundations of this generalized theory, as well as applications in low- and high-energy physics, cosmology, granular matter, 
nonlinear dynamical systems, economics, engineering, medical (e.g., EEGs and deep brain microelectrode) and computational sciences, among others.

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Professor Thierry Mora: Modeling correlations in neural and behavioral systems

I will cover two separate topics - collective social behavior in groups of mice, and population coding by retinal neurons - but which both lend themselves to the tools of statistical mechanics to describe how collective behaviour emerges from interactions between individual units. I will describe how to infer these interactions directly from data, and explore their implication for function: for social cohesiveness in social groups, and for visual acuity in the case of retinal coding.

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Dr. Fleur Zeldenrust: From structure to function: Heterogeneity in the brain

 

The brain is a unique system, in that its dynamics have a clear function: making its owner respond to the world around it. In order to perform this function, the brain continuously processes information. How do the dynamics of neurons and networks result in information processing? The physical structure of the brain (its ‘hardware’) shapes this information processing and vice versa: the computations needed for information processing (the ‘software’) are adapted to the physical structure of the hardware. Here, I will discuss this relationship between information processing and neural properties on different levels, from single neurons to networks, and from different perspectives, from single cell electrophysiology to network modelling. In particular, I will focus on heterogeneity: the fact that neurons in the brain are not identical, but show a wide variety of properties. Recently, we showed that this neural diversity itself is not static: it depends on for instance input characteristics and on neuromodulatory state. How does this heterogeneity influence the dynamics and information processing of neural networks? Is this a dial the brain can use to adapt to the requirements of different tasks? I will discuss our latest analysis of experimental data on the heterogeneity of cell properties and how this influences network dynamics and performance in different tasks using different types of network simulations.

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Professor Iain D. Couzin: Ring Attractor Criticality Explains Accurate and Flexible Decision-Making Across Species

As animals run, swim, or fly through the world, they constantly decide where to eat, where to hide, and with whom to associate. Movement both results from these decisions and shapes how options are perceived, represented, and evaluated by changing the spatial relationships among them. I will present an integrated theoretical and experimental framework, grounded in neurobiological principles, that links spatial search and decision-making to ring attractor networks encoding bearings to social and asocial objects. In the absence of salient cues, these networks can occupy distinct search regimes in which excitatory dynamics generate structured trajectories such as zigzags and loops, while inhibitory, noise-driven dynamics generate correlated random walks and run-and-tumble motion, including Lévy-like walks. Cue loss or active inhibition can spontaneously produce spirals and expanding loops as goal-directed activity weakens. Together, these results reveal a reciprocal relationship between neural dynamics and movement. Sufficiently strong, spatially localized cues can instead shift the network into a decision-making regime. As movement changes the geometry of the options, the network resolves multi-option choices through a succession of abrupt, critical binary decisions until only one remains. Using immersive volumetric virtual reality (VR), I will demonstrate this process in fruit flies, ants, desert locusts, and schooling juvenile zebrafish, including decisions involving up to three options and both stationary and moving targets. Theory shows that the mechanism generalizes to any number of options and also predicts that near each critical transition, an animal should become briefly hypersensitive to differences that would otherwise be too small to detect. VR experiments designed to test this prediction reveal that geometric criticality allows animals to be both maximally discriminating and maximally flexible, increasing accuracy while preserving the ability to switch to a better option if conditions change. Finally, I will show how these principles extend to collectives, where individuals act as sensory inputs to one another’s navigational networks, allowing coordinated motion such as fish schooling to emerge directly from those circuits without explicit alignment mechanisms or additional interaction rules.

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