Keynotes
From SCWiki
There will be five keynote speakers during the workshop. Confirmed speakers are indicated below. Title, abstract and material about the keynotes will be soon available.
Contents |
Prof. Kevin Passino
Prof. Kevin Passino is currently a Professor of Electrical and Computer Engineering at Ohio State University. He has published over 100 papers and five books.
Talk: Honey Bee Swarm Cognition
See also the Workshop Material page.
Prof. Gustavo Deco
Prof. Dr. phil. Dr. rer. nat. habil. Gustavo Deco is Research Professor at the Institucio Catalana de Recerca i Estudis Avanats and Full Professsor (Catedrático) at the Pompeu Fabra University (Barcelona). He studied Physics at the National University of Rosario (Argentina) where he received his diploma degree in Theoretical Atomic Physics. In 1987, he received his Ph.D. degree in Physics for his thesis on Relativistic Atomic Collisions. In 1987, he was a post doctoral fellow at the University of Bordeaux in France. In the period from 1988 to 1990, he obtained a post doctoral position of the Alexander von Humboldt Foundation at the University of Giessen in Germany. From 1990 to 2003, he has been with the Neural Computing Section at the Siemens Corporate Research Center in Munich, Germany, where he led the Computational Neuroscience Group. In 1997, he obtained his habilitation (maximal academical degree in Germany) in Computer Science (Dr. rer. nat. habil.) at the Technical University of Munich for his thesis on Neural Learning. In 2001, he received his PhD in Psychology (Dr. phil.) for his thesis on Visual Attention at the Ludwig-Maximilian-University of Munich. Since 2001 he is Invited Professor at the Ludwig-Maximilian-University of Munich, and McDonnell-Pew Visiting Fellow of the Centre for Cognitive Neuroscience at the University of Oxford. In 2001 he was awarded the international price of Siemens "Inventor of the Year" for his contribution in statistical learning, models of visual perception, and fMRI based diagnosis of neuropsychiatric diseases. He has published three books, more than 133 papers in International Journals, 215 papers in International Conferences and 25 book chapters. He has also 52 patents in Europe, USA, Canada and Japan. His books include:
1) An Information-Theoretic Approach to Neural Computation. G. Deco and D. Obradovic, Springer Verlag,, New York 1996.
2) Information Dynamics: Foundations and Applications. G. Deco and B. Schürmann, Springer Verlag, New York, 2000.
3) Computational Neuroscience of Vision. E. Rolls and G. Deco, Oxford University Press, Oxford, 2001.
Talk: Stochastic dynamics as a principle of brain function
Abstract: The relatively random spiking times of individual neurons is a source of noise in the brain. We show that in a finite-sized cortical attractor network, this can be an advantage, for it leads to
probabilistic behavior that is advantageous in decision-making, by preventing deadlock, and is important in signal detectability. We show how computations can be performed through stochastic dynamical effects, including the role of noise in enabling probabilistic jumping across barriers in the energy landscape describing the flow of the dynamics in attractor networks. The results obtained in neurophysiological studies of decision-making and signal detectability are modelled by the stochastical neurodynamics of integrate-and-fire networks of neurons with probabilistic neuronal spiking. We describe how these stochastic neurodynamical effects can be analyzed, and their importance in many aspects of brain function, including decision-making, memory recall, short-term memory, and attention.
Prof. Jean-Louis Deneubourg
Prof. Jean-Louis Deneubourg - Université Libre de Bruxelles
Talk: Collective Intelligence and Elementary Chemistry
Prof. Gregor Schöner
Prof. Gregor Schöner - Ruhr-Universität-Bochum
Talk: Swarm cognition: analogies with pattern formation and neuronal dynamics and their limitations
Dr. James Marshall
Dr. James Marshall - University of Bristol, UK
Talk: Colony-Level Cognition: Optimal Decision-Making Structures in Brains and Social Insect Colonies
Abstract: What is 'colony-level cognition', or 'swarm cognition'? 'Collective intelligence' and 'swarm intelligence' have been established areas of research for two decades; these rest on the self-organisation of simple autonomous individuals to achieve some adaptive behaviour at the level of the collective, but apart from these general principles there is little in common between different studies in these areas. In contrast, I will argue that 'colony-level cognition' is different in that it is concerned with finding deep parallels between how cognition functions in different systems at different levels of biological complexity. I will illustrate this by means of an example: it is now understood how binary decision-making in certain areas of the primate brain, such as the visual cortex, may actually achieve the statistically optimal strategy for compromising decision-speed with decision-accuracy, the Sequential Probability Ratio Test. I will show how simplified models from the literature of collective social insect behaviour during nest-site selection may also be analysed, by adapting techniques from theoretical neuroscience, and an optimality hypothesis for social insect behaviour proposed.
See also the Workshop Material page.
