Confirmed workshops at CNS*2003

University Miquel Hernández, 8-9 July 2003

  • Unifying Neural Coding, Computation and Dynamics (Tutorial) C. H. Anderson (Washington University, St. Louis, USA) and C. Eliasmith (University of Waterloo, Waterloo, Canada).

    Tutorial covering material in the book Neural Engineering: Computation, Representation and Dynamics in Neurobiological Systems (MIT Press). [details].

  • Comparative perspectives on sensory coding. M. Maravall, R. Peterson, M. Diamond (SISSA, Trieste, Italy) and S. Panzeri (UMIST, Manchester, UK).

    In recent years there has been substantial progress in rigorous and quantitative studies of sensory coding. Principles relating to the role of spike timing, population coding, redundancy reduction and adaptation have been elucidated in particular systems: invertebrate and vertebrate, and from sensory periphery to mammalian neocortex. However, results obtained with particular systems and stimulus designs raise the question of which general principles of neural coding transcend individual sensory modalities and species.

    The aim of this workshop is therefore to take an explicitly comparative perspective. By presenting work from a wide range of systems and modalities, we hope to facilitate fruitful discussion of this fundamental issue. Do neuronal spike trains in different modalities employ similar information-bearing elements? Are there common rules for the precision and content of spike timing? Are there general principles for designing efficient test stimuli? Does adaptation to changes in stimulus statistics operate similarly in different modalities? Finally, are common features of sensory codes reflected in analogous common features of the neuronal structures that underlie them -and conversely, do common structures imply similar coding schemes?

    More information is available here.

  • Advances in activity-dependent plasticity. P. Munro (University of Pittsburgh, Pittsburgh, USA).

    The major goals of the workshop are:

    1. To review current experimental results on spike-timing-dependent synaptic plasticity and related effects.
    2. To discuss models and mechanisms for this form of synaptic plasticity.
    3. To explore the relationship of STDP with other approaches
    4. To reconcile the rate-based and spike-based plasticity data with a unified theoretical framework (very optimistic!).

  • Computational Models of Active Maintenance in Prefrontal Cortex D. Noelle, Vanderbilt University, Nashville, USA.

    This workshop will bring together leading researchers interested in formally characterizing the mechanisms which allow circuits in prefrontal cortex to actively maintain task relevant information over a delay, with a particular focus on the role of the dopamine system in proposed computational models. Higher level models which make contact with measures of cognitive performance will be discussed alongside lower level models which make contact with detailed physiological data. A list of speakers and other details is available here.

  • Constraints in Neural Systems Design A. Dmitrov (Montana State University, Bozeman, USA). Described here.

  • Cortical Models and Psychophysics C. W. Eurich and U. A. Ernst (Universitaet Bremen, Bremen, Germany).

    Psychophysical experiments are a widespread tool to investigate the sensory performance of animals or human observers and may allow to infer properties of the underlying brain processes. For example, masking experiments operating on the brink of the spatial and temporal resolution of the visual system yield constraints on neural signal processing, and the perception of ambiguous figures elucidates dynamical properties of neural systems. In this workshop, we want to discuss cortical models for psychophysical phenomena and the role which the combination of psychophysics and modelling plays for an understanding of the brain processes underlying perception and cognition.

    We want to address the following questions:

    1. What types of models are necessary and sufficient to describe psychophysical phenomena?
    2. What mechanisms can be identified on the neural or network level to account for psychophysical phenomena?
    3. In how far do results from psychophysical experiments constrain cortex models? Are additional data (electrophysiological, fMRI, EEG, ...) necessary to yield an understanding of the neural basis of psychophysical effects?
    4. Which observations cannot be explained to-date, and pose a challenge for the modelling studies?
    More details here.

  • Complexity and Criticality in Networks D. R. Chialvo (University of California, Los Angeles, USA).

    This workshop discusses recent attempts of using approaches inspired on the physics of non-equilibrium systems to analyze complex dynamics in brain networks. Self-organized criticality (SOC) is suggested to be a robust mechanism by which complex dynamics can emerge from the interaction of very large number of nonlinear elements. This behavior is the tendency of large systems to evolve spontaneously towards a critical state, i.e. a state that presents long-range correlations in both space and time. Systems at the critical state are highly susceptible, optimizing information transfer and adaptation. More details here.

  • Nonlinear spatio-temporal neural dynamics - Experiments and Theoretical Models P. Andras (Newcastle Univeristy, Newcastle, UK), Robert Kozma (University of Memphis, Memphis, USA), Peter Erdi (Kalamazoo College, Kalamazoo, USA & KFKI, Budapest, Hungary) and David DeMaris (IBM Microelectronics, Austin, USA)

    Nonlinear spatio-temporal dynamics of information processing in biological and computational neural systems have attracted a lot of attention in recent years. Recent experimental studies in fMRI and in high-resolution EEG and MEG measurements indicated the potential of combining the advantages of various methods to achieve fine spatial and temporal resolution. An increasing segment of neural network research is devoted to computational models based on the identified biological principles, like pulse-coupled neural networks, spiking neurons, oscillatory and chaotic neural networks. These methods have been successfully applied to interpret a range of experimental findings. The goal of this special session is to create a forum for researchers in this exciting research area, to exchange ideas and to discuss recent developments, and also to outline perspectives for future activities.

    More information is available here.

  • Attention: Theory and Mechanism Barak A. Pearlmutter and Santiago Jaramillo (NUI Maynooth, Ireland) Described here.

  • Assessing New Structure-Function Relationships by Computational Neuroscience Models: What Conventions to Break? T. Wennekers (Ruhr University, Bochum, Germany) and F. Sommer (Redwood Neuroscience Institute, Menlo Park, USA).

  • Visibility, Brightness, Shape, and their Relationship to the Neural Code S. Martinez-Conde and S. L. Macknik (University College, London, UK).

    This tutorial will highlight studies of the underlying neural code of visibility and brightness perception, and its entangled relationship with, surprisingly, the fundamental neural basis of primary shape perception. These studies used a combination of experimental methods in primates and humans (psychophysical, electrophysiological, and optical imaging), and computational modeling.