Dynamic interplay between standard and non-standard retinal pathways in the early thalamocortical visual system : A modeling studydécembre 2014 Directeur(s) de thèse : Frédéric ALEXANDRE and Thierry VIEVILLE Résumé de thèse
Understanding the behavior of the retino-thalamo-cortico-collicular (i.e. early) visual system in a natural images situation is of utmost importance to understand what further happens in the brain. To understand these behaviors, neuroscientists have looked at the standard Parvocellular and Magnocellular pathways for decades. However, there is also the non-standard Koniocellular pathway, which plays an important modulating role in the local, global, and intermingled processing carried out to achieve such behaviors.
Particularly, the standard motion analysis carried out by the Magno pathway is alternated with rapid reactions, like fleeing or approaching to specic motions, which are hard-wired in the Konio pathway. In addition, studying a fixation task in a real situation, e.g., when a predator slowly approaches its prey, not only involves a motion mechanism, but also requires the use of the Parvo pathway, analyzing, at least, the image contrast. Here, we study in a bio-inspired computational neural model how these pathways can be modeled with a minimal set of parameters, in order to provide robust numerical results when doing a real task. This model is based upon an important study to integrate biological elements about the architecture of the circuits, the time constants and the operating characteristics of the different neurons.
Our results show that our model, despite operating via local computations, globally shows a good network behavior in terms of space and time, and allows to analyze and propose interpretations to the interplay between thalamus and cortex. At a more macroscopic scale, the behaviors emerging from the model are reproducible and can be qualitatively compared to human-made fixation measurements. This is also true when using natural images, where just a few parameters are slightly modified, keeping the qualitatively human-like results. Robustness results show that the precise values of the parameters are not critical, but their order of magnitude matters. Numerical instability occurs only after a 100% variation of a parameter. We thus can conclude that such a reduced systemic approach is able to represent attentional shifts using natural images, while also being algorithmically robust. This study gives us as well a possible interpretation about the role of the Konio pathway, while at the same time allowing us to participate in the debate between low and high-roads in the attentional and emotional streams. Nevertheless, other information, such as color, is also present in the early visual system, and should be addressed together with more complex cortical mechanisms in a sequel of this work.