From Cortex project

Projects: Cortina

UV-CINV, Universidad ValparaisoCORTEX - INRIA NANCY
UTFSM, Universidad Técnica Federico Santa MaríaNEUROMATHCOMP - INRIA SOPHIA

The Associate team CORTINA ran from 2011 to 2013. Mid-2012, the members of the EPI Cortex principally involved in Cortina moved to Bordeaux to create the new EPI Mnemosyne. Consequently,this webpage, associated to the Cortex EPI, reports on the activities of Cortina in 2011 and 2012. The activities of 2013 are reported on this webpage, associated to the Mnemosyne EPI.


Scientific Activities
Collaborative activities
Related projects
Future activities
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Keywords : Computational Neurosciences, cortex modeling, cerebral models of architecture and learning in the visual system, distributed computation, machine learning, artificial intelligence, memory, learning and reasoning, cognitive science
Keywords : brain-machine interface, machine learning, visuo-motor system
Keywords : Dynamical systems, statistical physics, modelling and analysing neural networks, spike train statistics
Keywords: neural field, population coding, mathematical analysis
Keywords : models of vision (retina, perception of the movement, salience, recognition of images and actions), mathematical frameworks (approaches by EDP, neuronal fields)
Keywords: dynamic neural fields, self-orgnization, cognition, attention
Keywords : Artificial/biological motion perception, event-based neural assembly computation, variational parametric estimation
Keywords : sensory biology, retina, multielectrodes, neural coding
Keywords : computational neuroscience, biological vision, motion perception, spiking neural networks, natural image analysis
Keywords : Magnetic Resonance Imaging, more specifically diffusion MRI and functional MRI & Medical Image Processing
Keywords : Large-sized dynamic systems, nondifferentiable dynamic systems, dynamic symbolic system, chaos, entropy, modeling
Keywords : Conductance based modeling, neuronal excitability, cold sensory transduction, channel noise and variability
Keywords : Machine Learning, Pattern Recognition, Computational Intelligence, Data Mining
Keywords : Artificial Vision, Robotic
Keywords : Cognitive Science



  • Mauricio Cerda Villablanca CORTEX PhD (now postdoc in Santiago)
  • Hassan Nasser NeuroMathComp PhD
  • Vivien Robinet NeuroMathComp (Post-doc, now assistant professor)
  • Carolina Saavedra CORTEX PhD
  • Wahiba Taouali CORTEX PhD
  • Carlos Carvajal, CORTEX PhD
  • Rodrigo Coffre, NEUROMATHCOMP PhD


  • Catherine Fuentealba, UTSFM
  • Luis Caceres, UTFSM
  • Cristóbal Nettle, UTFSM
  • Gabriel Urrutia, UTFSM
  • Pedro Toledo, UTFSM
  • Sebastián Sáez, UTFSM
  • Aland Astudillo, UV-CINV, UTFSM
  • Claudia Salazar, UV-CINV
  • Joaquin Araya, UV-CINV
  • Danilo Pezo, UV-CINV
  • Erick Olivares, Doctorado en Ciencias, mención Neurociencia, UV-CINV
  • Miguel Piñeiro, Doctorado en Ciencias, mención Neurociencia, UV-CINV
  • Jose Maria Hurtado, Phd UCSD USA, Postdoctoral Fellow, UV-CINV
  • Alvaro Ardiles, PhD UV, Postdoctoral Fellow, UV-CINV
  • Cesar Ravello, UCH, Research Assistant


Much progress has been made in the last decades in understanding the basic organization and function of the nervous system in general. Contributions to this end have come from various domains including computational neuroscience and numerical science of the information in general. The goal of this associate team is to combine our complementary expertise, from experimental biology and mathematical models (U de Valparaiso and U Federico Santa-Maria) to computational neuroscience (CORTEX and NEUROMATHCOMP), in order to develop common tools for the analysis and formalization of neural coding and related sensory-motor loops. Recording and modeling spike trains from the retina neural network, an accessible part of the brain, is a difficult task that our partnership can address, what constitute an excellent and unique opportunity to work together sharing our experience and to focus in developing computational tools for methodological innovations. To understand How the neural spike coding from natural image sequences works we are addressing the following issues: How visual signals are coded at earlier steps in the case of natural vision? What are their functions? What are the computational “coding” principles explaining (in artificial or biological system) the statistical properties of natural images? We wish to advance our actual knowledge in natural and artificial visual signals processing and apply it to the field of education; to foster better capacities for learning and memory; sensory prosthesis design, to will help unpaired sensory persons to sense the world and physical rehabilitation, among others. In the context of the cooperation between the INRIA and Chile our methodology and questions are transversal and can be used and potentiated several field and applications.



We can also mention that this latter paper has obtained a good visibility at the national and international levels, eg:


We mention here new projects (on the same collaborative ground or not) on close scientific domains, the existence of which is partly due to our focus on the domain, particularly within CORTINA:



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Page last modified on October 03, 2013, at 12:24 PM