Yves Burnod

Publications (2)3.64 Total impact

• Source

  Available from: Christine Schiltz

  Article: Is there continuity between categorical and coordinate spatial relations coding? Evidence from a grid/no-grid working memory paradigm.

  Romain Martin, Claude Houssemand, Christine Schiltz, Yves Burnod, Frédéric Alexandre
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  ABSTRACT: We ask the question whether the coding of categorical versus coordinate spatial relations depends on different neural networks showing hemispheric specialization or whether there is continuity between these two coding types. The 'continuous spatial coding' hypothesis would mean that the two coding types rely essentially on the same neural network consisting of more general-purpose processes, such as visuo-spatial attention, but with a different weighting of these general processes depending on exact task requirements. With event-related fMRI, we have studied right-handed male subjects performing a grid/no-grid visuo-spatial working memory task inducing categorical and coordinate spatial relations coding. Our data support the 'continuous spatial coding' hypothesis, indicating that, while based on the same fronto-parieto-occipital neural network than categorical spatial relations coding, the coding of coordinate spatial relations relies more heavily on attentional and executive processes, which could induce hemispheric differences similar to those described in the literature. The results also show that visuo-spatial working memory consists of a short-term posterior store with a capacity of up to three elements in the parietal and extrastriate cortices. This store depends on the presence of a visible space categorization and thus can be used for the coding of categorical spatial relations. When no visible space categorization is given or when more than three elements have to be coded, additional attentional and executive processes are recruited, mainly located in the dorso-lateral prefrontal cortex.
  Neuropsychologia 02/2008; 46(2):576-94. · 3.64 Impact Factor
• Article: The cortical column: A new processing unit for multilayered networks

  Frédéric Alexandre, Frédéric Guyot, Jean-Paul Haton, Yves Burnod
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  ABSTRACT: We propose in this paper a new connectionist unit that matches a biological model of the cortical column. The architectural and functional characteristics of this unit have been designed in the simplest manner in order to simulate human-like reasoning, and to be as similar as possible to the main known features of real intracortical networks. We use a new type of learning rule which can easily take into account goal-oriented combinations of actions in behavioral programs. These learning rules are both simple and biologically plausible. We show in this paper that such units can be used in multilayered networks to perform pattern recognition, with feedback connections effecting an attentive gating of sensory information flow. Computer simulations were performed to assess the ability of a multilayered network made of these biologically inspired units to perform standard speech and visual recognition. Such simulations show levels of performance equivalent to the best currently available connectionist networks for typical human-like problems, with very fast learning and recognition processes. Furthermore, this type of “cortical” unit can be used in more general multilayered networks with units controlling different types of external processing, in order to learn programs of actions which may be included in the process of recognition.
  Neural Networks. 01/1991;