First International Workshop on the Shapes of Brain Dynamics

Complex Systems Institute Paris, June 18, 2010


"When we think a given thought, then the meaning of this thought is expressed in the shape of the corresponding neurophysiological process." —Bernhard Riemann

This workshop focuses on the observation, measure and modeling of the "shapes" of complex spatiotemporal phenomena in large populations of neurons. It aims to contribute to a view of the brain as a "pattern formation machine" generating dynamical states composed of myriads of bioelectrical signals, at multiple mesoscopic levels from 10^3 to 10^9 units (between cortical columns and areas). Dynamical structures of neural activity constitute a prototypical example of emergent collective behaviors observed in nature, such as bird flocking or insect colonies. Such systems exhibit multistability, phase transitions, a wide diversity of trajectories and, of particular interest here, "morphogenetic" abilities. In addition, the special features of "neuron flocking" reside in its precise spatiotemporal relationships on the ms time scale and its complex underlying network structure. We propose here to explore various geometric, topological, statistical and computational approaches that can describe the dynamics of collective neural shape formation, in physical space or phase space.

Confirmed invited speakers

  • Walter J. Freeman (keynote) – Division of Neurobiology, University of California, Berkeley
  • Daniel Bennequin – Geometry & Dynamics Team, Université Paris Diderot, Paris
  • Alain Destexhe – Neuroscience, Information & Complexity Research Unit (UNIC), CNRS Gif-Sur-Yvette
  • Cyril Monier – Neuroscience, Information & Complexity Research Unit (UNIC), CNRS Gif-Sur-Yvette
  • Jean Petitot – Research Center in Applied Epistemology (CREA), Ecole Polytechnique, Paris
  • Carl van Vreeswijk – Laboratory of Neurophysics and Physiology, Université Paris Descartes, Paris

Download workshop's program
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The foundational thesis of cognitive science is that the mind relies on internal dynamical "states", "regimes" or "representations" that correspond to (or are triggered by) states of the external world. It operates by creating, assembling and transforming these entities, both under the influence of external stimuli and the constraints of its internal architecture. Can we characterize the structure of these complex objects of neural activity? What are the adaptation, integration, and learning rules that shape their dynamics? How are they endogenously sustained and reproduced by the neuronal substrate even in the absence of external perturbation?

  • In neurobiology, or "neurodynamics", the convergence of multi-electrode recordings, brain imaging techniques and increased computing power has revealed a great diversity of possible, and plausible, spatiotemporal regimes of activity in large cell populations—synchronization and phase locking, delayed correlations and traveling waves, rhythms and chaos. It has populated the mesoscopic levels of brain dynamics with a zoology of emergent theoretical objects such as synfire chains, cortical songs, polychronous groups, a/synchronous ir/regular ongoing activity, chaotic attractors, etc.

  • In mathematics, since Riemann, the search for a correspondence between the worlds of "shapes" and "dynamics", i.e., between geometry and function, has continuously questioned the foundations of mathematics and has given birth to topology and algebraic geometry. As a result, it created new concepts and generic invariants that could offer a unified description of biological shapes/structures in relation with their function/dynamics. For instance, the application of ergodic and hyperbolic systems theories to neuronal dynamics have unraveled deep relations between the generic characteristics of flows and neuronal adaptation-plasticity mechanisms. Such tools allow us to organize and quantify the complexity of biological systems in a meaningful way, avoiding oversimplification.

It is the ambition of this workshop to present current experimental results and theoretical models able to measure and characterize the neural patterns of activity through geometric, topological, statistical and computational approaches.

For more information, see the Call for Abstracts and Program. To submit an abstract and/or register to this no-fee workshop, please fill out the Submission & Registration form. If you have comments or questions, feel free to contact the organizers. Thank you for your interest.

Contributors to this page: Pierre Baudot , webmaster and Rene Doursat .
Page last modified on Monday 14 June, 2010 12:01:15 by Pierre Baudot.