Direction des Relations Internationales (DRI)

Programme INRIA "Equipes Associées"
 
/ INRIA "Associate Teams" Programme

 

I. DEFINITION

ASSOCIATE TEAM

CORTINA

sélection

2011

 

Equipe-Projet INRIA : CORTEX
    (in association with NEUROMATHCOMP)

Organisme étranger partenaire / Partner Institution: Universidad de Valparaiso
    (in association with Universidad de Santa-Maria)

Centre de recherche INRIA : INRIA-Nancy Grand Est
Thème INRIA :Theme 6 "Computational Medicine and Neurosciences"

Pays / Country :CHILE

 

 

Coordinateur français / French Coordinator

Coordinateur étranger / Partner Coordinator

First name, Given name

ALEXANDRE Frédéric

 PALACIOS Adrian

Position

PhD, Research Director

PhD, Professor

Home Institution
(précisez le département et/ou le laboratoire)

INRIA Nancy - Grand Est

Universidad de Valparaiso

Postal address

615 rue du jardin botanique 54600 Villers-les-Nancy

Gran Bretaña 1111, Playa Ancha, Valparaiso

Website

http://cortex.loria.fr

http://www.cnv.cl

Telephone

(+33/0) 3 83 59 20 53

(+56/32) 250 80 48

Fax



Email

frederic.alexandre@loria.fr

adrian.palacios@uv.cl


NOTA
: La proposition d'Equipe Associée comporte du Chilien plusieurs partenaires fédérés autour de l'Université de Valparaiso pour simplifier la gestion de cette EA.


La proposition en bref
/ The proposal in brief

Titre de la thématique de collaboration (en français et en anglais) / Title of the collaboration theme (in French and in English) :

  CORTINA : CORtex and reTINA modeling from an engineering and computational perspective.
                        Modélisation du Cortex et de la Rétine dans une perspective de la ingénierie et l'informatique appliquée.

Descriptif (environ 10 lignes) / Description (approximately 10 lines) :

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.


Présentation détaillée de l'Équipe Associée
Detailed presentation of the Associate Team

1. Objectifs scientifiques de la proposition / Scientific goals of the proposal (1 to 2 pages)

Description of the proposal's objectives and brief perspective regarding the state-of-the-art:

We propose to apply computational methods to model the behavior (spike response) of retinal ganglion cells in response to natural images. This last knowledge will use to further develop our artificial retina model created at the INRIA.  The results will be incorporate into real engineering applications, as new dynamical early-visual modules, for artificial vision devices.

The retina, an accessible part of the brain, is a unique model for studying how neurons code visual signals from natural scenarios. A recent review proposes that visual functions (e.g. movement, orientation, anticipatory temporal prediction, contrast), thought to be the exclusive duty of higher brain centers, are actually carried at the retina level. The anatomical and physiological segregation of visual scenes into spatial, temporal and chromatic channels begins at the retina through the action of local neural networks. However, how the precise articulation of this neural network contributes to numerical local solution at the bases of global perception remains in general a mystery.

We propose to model the complexity of behaviors find in retinal ganglion cells (the output to the brain) in front of natural images and incorporate the results into our artificial retina model. Typically, the “classical” behavior of retinal ganglion cells has been evaluated using artificial stimuli as drifting gratings or flashes. But, ganglion cells produce unexpected behavior when the input stimulus is replaced by natural images (or movies), which is what vertebrate’s eye daily see and represent the real natural early processing capacity of the eye. We revisit both the retinal neural coding information sent to the brain, and at the same time, the development of new engineering applications inspired by the understanding of such neural encoding mechanisms. We develop an innovative formalism that takes the real (natural) complexity of retinal responses into account. We also develop new dynamical early-visual modules necessary to solve visual problems task.


The scientific keys

A recent review (Gollisch & Meister 2010) shows that the retina has some functional properties (e.g. movement, orientation, anticipatory temporal prediction, and contrast detection) that were previously regarded as the exclusive duty of higher brain centers. These findings reinforce the importance and complexity of early-vision mechanisms pushing us to review our actual view of biological and artificial retinas in several ways.

At the periphery of the nervous system, sensory systems are at the boundary between physics and biology, and their molecular and cellular design produces and transports action potentials (spikes) to the brain through an intricate neural network; but is natural to ask

Natural scenes differ in their particular statistics and it is expected that an animal sensory system would try to optimally exploit such regularities (e.g. contrast / intensity). A big challenge proposed here is to include new retinal functions in artificial visual system, through bio-inspired algorithms. In this side, our teams have already developed a prototype of artificial retina that integrates some of these ideas. We expect to extend this artificial retina to new principles emerging from the study of non-standard behavior of ganglion cells. Our working hypothesis is that the deep understanding of biological solutions uses to resolve natural tasks will help the development of robust, plastics and adaptable artificial systems to be exploit in dynamically natural environment.

Scientific objective: Solving one mystery of dynamical vision.

Although computer vision and visual perception theory are now at high stage of development, with impressive outcomes and very sophisticated models, we are facing the fact that their capability compared to a natural visual system is very “rudimentary” and limited. Indeed, performing highly robust and non-trivial visio-motor or visio-perceptual tasks, in natural environment where complex visual motion are observed, is beyond the present state of the art in computer vision.

What may have been missed? One key point is that in presence of natural scenes, retina ganglion cells show qualitatively rich and unexpected behaviors, with sparse and spiky responses, and almost deterministic behaviors. For example ganglion cells respond with anticipation to visual motion pattern (e.g. immediate detection of complex spatio-temporal events), in addition to color and luminance responses. It is also well accepted that such sensor elements are tuned to natural image statistics. But, this may occur in a more operational way than actually thought, i.e. not only providing a “decomposition” of the visual input in terms of some “statistically optimal” basis, but also detecting useful statistical properties from natural images, thus providing early-vision output far beyond what is usually considered for standard cells and standard stimulus.

Innovative aspect: towards a sophisticated early-vision front-end. At the computer vision level, we claim that the classical early-vision front-ends need to be re-thought. They have to provide early-vision input/output transfer function, beyond to a simple linear spatio-temporal filter followed by a static non-linearity function. Early-vision (ganglion cells output) does not only feed high-level of cortical structures, but is also directed to pre-motor sub-systems (e.g. sub-cortical) for fast decision system (event/emergency detection, pre-attentive selection/analysis). This is especially true for embedded visual systems, able to provide significant cues during natural dynamical environments. In other words, we propose to “flatten” the classical visual architectures and propose a more sophisticated treatment at the early-vision level implementing complex non-linear processing such as sparse estimators and ICA mechanisms or non-linear variational operators, as detailed in the sequel.

Innovative aspect: considering non-standard behaviors from classic and new types of ganglion cells. The innovative aspect at the biological level will be to carrier experiments to collect data on retinal ganglion cells in responses to natural stimulus (or tasks) including eye movement and natural variation of the illuminant. We will also ask some colleagues to share with us results in retinal recording. At the computational level, we target to model and explicitly simulate retinal ganglion cells behaviors. The fact that some non-standard behaviors from ganglion cells have been neglected in the past can be due to several reasons:

(i) Only recently high-density multielectrode arrays has been use in the retina recording simultaneously from many different ganglion cells types with a full diversity of complex behavior in response to natural stimulus or task;

(ii) The wrong assumption that the majority of ganglion cells, types X and Y in mammals, are more important than the less numerous non-standard types (close to n=15 different types). In fact non-standard cells have: a larger receptive field along sparse density; and they are often silent in front of artificial stimuli.

(iii) Ganglion cells project to cortical visual areas as well to non-visual areas, where they can be used without further visual processing, playing a critical participation in species with sophisticated pre-motor behavior processing. This last issue points to a more sophisticated treatment at the early-vision level that previous thought.

Short description of the scientific tasks planned for the three years:

Expected scientific add-on: the concept of retinal module. The goal here is to achieve a better understanding in how the retina (a natural visual encoding device) works in natural conditions, which represent an extension of the work done for more classics or standard cells behavior (Wohrer and Kornprobst, 2009). We propose here to approach this topic in terms of new computational algorithms, considering the biological facts reviewed previously. As a working hypothesis we propose to disentangle the biological and computational organization of a “retina module”, which includes the function of a complete population of different types of ganglion cells, recorded from a small retina area using high density electrodes. Furthermore, we will include the understanding of how such “module” (e.g. population coding) can possible communicates with other similar brain cortical structures. The implication of such retinal modular organization (from photoreceptors to ganglions cells) will be tested and implemented in artificial visual systems.

Project outcomes: The proposed developments are going to offer new perceptual capabilities to artificial visual system. Specifically we can mention as project outcomes:

Ideally, but this is out of the scope of the present project, the complete demonstration would have included enactive vision, i.e. the integration of these new early-vision properties in sensorimotor loops. While recent research in cognitive robotics, suggests that it may be possible to exploit a direct link between embodiment and information flow, we think that at the more restrictive sensory level, a similar link between natural scenes visual flow and sensory module can be built.
To perform the previous tasks, we rely on the broad experimental and computational expertise of the project members. In the first item, we have complementary experiences in experimental (Chile) and computational (France) neuroscience and could develop together common tools. In the second item, we have a common (France and Chile) expertise in behavioral studies with an enactive perspective. Even if this topic of CORtex-reTINA visual-motor loop modeling is certainly out of the reach of a standard program of an associate team, it is an excellent topic to highlight our common and complementary expertise and also a way to progress in this domain and apply together on other external funding.

This proposal fills the need of fostering a potential source of joint collaborative scientific and technological progress. France and Chile have a tradition of historical exchanges from culture and science. However the challenge of doing science together is still pending. Until this year, all the available collaborative projects from CONICYT-CNRS-INRIA-INSERM-ECOS were for short visits and students exchange. We see now an fantastic opportunity for doing “real” joint scientific project, and we also foresee that the area of STIC will have a tremendous impact on Education, S&T generation and transfer to a variety of areas like  biomedicine, robotics and artificial intelligence.

References:

Dowling, J.E. (1987) The retina: an approachable part of the brain Personal . Harvard University Press, Cambridge, Mass. (USA).
Field, G.D., Chichilnisky, E.J. (2007) Information processing in the primate retina: Circuitry and coding. Annnual Review of Neuroscience 30:1-30.
Hemmen van, L. and Sejnowski, T.J, (eds) 2006 23 Problems in Systems Neuroscience. Oxford University Press, Inc.
Masland, R. H. and Martin, P. R. (2007) The unsolved mystery of vision. Current Biology, 17(15):R577-R582.
Segev, R., Goodhouse, J., Puchalla, J. and Berry, M.J. (2004) Recording spikes from a large fraction of the ganglion cells in a retinal patch. Nature Neuroscience 7:1154-61.
Simoncelli, E.P. and Olshausen, B.A. (2001) Natural images statistic and neural representation. Annu Rev Neuroscience 24:1193-1216.
Gollisch, T. and Meister, M. (2010) Eye smarter than scientist believed: Neural computacions in circuits of the retina. Neuron 65:150-164.
Wohrer, A. and Kornprobst, P. (2009) Virtual Retina; a biological retina model and simulator, with contrast gain control. Journal of Computational Neuroscience 26(2):219-249.

2. Présentation des partenaires / Partners presentation 

UV-CINV:  The Universidad de Valparaiso team groups members of the Faculty of Science from the area of Neuroscience, biomedicine and biostatistics. They have been working together and some of their members collaborate already with INRIA team’s fellows. The UV-CNV team is interested in the study of the sensory neural coding process and its formal computational models as well as their implementation in robotics and artificial vision devices. We work  in basic research using sensory biology (Palacios and Orio) from single to multineuronal recording in the nervous system; computational neuroscience and statistics (Guiraud, Orio, Salas); EEG and PET modelling (Chabert) and Robotic (Zagal). The UV team has several ongoing project: 1) Recording from single cells and multielectrodes in a large population of retinal neurons with the finality to study principles for neural coding 2) Developing a Robotic approach using concepts of embodiment and sensory constraint; 3) Modeling the locomotors trajectory of a rodent model for degenerative diseases (e.g. Alzheimer) were we are exploring the use of entropy and where a Bayesian model to characterize the degree of memory loses; 4) Models of diffusion magnetic resonance imaging to understand the origin of diffusion signal to providea assistance in the interpretation of diffusion MR images. The groups met regularly and have several students in co-tutelle.

In association with UV-CINV, the Universidad Técnica Federico Santa María (UTFSM), is recruiting a new researcher with a strong background in biological modeling, now involved in both computational research and industrial transfer of such outcomes. This colleague has obtained her PhD at INRIA and is now willing to build long-term collaborations between both countries.

Adrian G Palacios Vargas 51 years old, Chilean nationality, Professor Universidad de Valparaiso, 2008-2010 Visiting Researcher CORTEX INRIA and CREA Ecole Polytechnique, France
Education
Ph.D. in Neurosciences (1991) Université de Pierre et Marie Paris VI, France; 1990-1997 Postdoctoral and Associate Research Scientist, Yale U, USA.
Research domains:
Sensory systems must ultimately be understood at different biological levels, from molecular events to animal behavior seen in their natural ecological conditions. With Francisco Varela we show that Avian (Columba livia) uses ultraviolet light to shape its color vision space (Vision Research, 32:1947-1953, 1992) and we propose a theoretical framework “Ways of coloring” to this aims published in Behavioral and Brain Sciences, 15:1-74, 1992 (along 33 commentaries). At Yale I was working to establish the spectral sensitivities and kinetics response of rods and cones by recording photocurrents with suction electrodes (J Physiol (London). 471:817-829. 1993). We reported UV cones in Danio aequipinnatus, a small cyprinid related to zebrafish (Vis Neuroscien. 13:411-421. 1996, Vis Res. 38:2135-2146. 1998). Moving to the Universidad de Valparaiso in 1997 I started my own lab, focussing in visual sensory ecology from single photoreceptor, electroretinogram (ERG) and reflectance characterization from animals and their microhabitat, that are likely to be used as signals in sexual selection, recognition of conspecifics, camouflage. In retinas slices using patch-clamp, we are studying the retina neural network form by bipolar, amacrines and ganglions cells types and their participation in color vision. More recently we are recording from a population of ganglion cells using multielectrodes MEA array (64X). Furthermore, at the retinal an intricate bioelectrical neural network develop dynamically depending on the background illumination and the behavioral meaning of the task for the animal. We are using mathematical tools to model retinal neural coding. Recently, we start to work in the field of Neurobiology of Learning and Memory, using behavior, biochemistry and synaptic plasticity (LTP, LTD) approaches in Octodon degus, a rodent that during aging develop brain marks proper of Alzheimer diseases. Another area of my interest is complexity and I coordinating several multidisciplinary activities in the area of cognitive sciences at the Instituto de Sistema de Complejos de Valparaiso, Chile (www.iscv.cl). For more details see http://www.cnv.cl/palacios
Publications :

Peichl L, Chavez AE, Ocampo A, Mena W, Bozinovic F, Palacios AG (2005). Eye and Vision in the Subterranean Rodent Cururo (Spalacopus Cyanus, Octodontidae). J Comp Neurol 486:197-208.
Goles E, Palacios AG (2007) Dynamical complexity in cognitive neural networks. Biol Res 40:381-384
Delgado LM; Vielma AH; Palacios AG; Schmachtenberg O. (2009) The GABAergic system in the retina of neonate and adult Octodon degus, studied by immunohistochemistry and electroretinography J Comp Neurol. 514(5):459-472.
Schleich C, Vielma A, Palacios AG, Peichl L. (2010) The Retinal Photoreceptors of Two Subterranean Tuco-tuco Species (Rodentia, Ctenomys): Morphology, Topography and Spectral Sensitivity. In press J Comp Neurology.
Palacios AG
, Bozinovic F, Vielma A, Arrese CA, David M. Hunt DM, Peichl L (2010) Retinal Photoreceptor Arrangement, SWS1 and LWS Opsin Sequence, and Electroretinography in the South American Marsupial Thylamys elegans (Waterhouse, 1839). J Comp Neurology 518(9):1589-1602.
Author of 49 paper, participation in several divulgation activities, 101 meeting abstract, supervision 5 Postdoctoral fellows; thesis 12 graduate and 10 undergraduate. Coordinator of institutional external grants (MECESUP, Fundación Andes). Member of study sections from FONDECYT and Students Fellowships during 6 years. Member of the steering committee MECESUP2 (from Chilean Education Minister, 2006-2010). Coordinator Research grants 3 Fondecyt, 3 DIPUV, 1 NIH-FIRCA, Co-director Milenio Nucleus, coordinator PBCT ring ACT45 Coordinator of a French ECOS-CONICYT project and co-investigator in a European .project. MORPHEX. Co-investigator CNRS Neuroinformatic (2009-2010) (www.cnv.cl/palacios).

CORTEX: The goal of the research of the CORTEX team is to study the properties and capacities of distributed, numerical and adaptive automated information processing and to show that this kind of processing may allow to build "intelligent" systems, i.e. able to extract knowledge from data and to manipulate that knowledge to solve problems. More precisely, these studies rely on the elaboration and analysis of neuromimetic connectionist models, developed along two sources of inspiration, computational neuroscience and machine learning.
Working in computational neuroscience, the following objectives have been considered:
1. At the interface between the microscopic and mesoscopic levels, precise and realistic models of neurons and of their related network dynamics allow us to analyze the neural code in Spiking Neurons and Networks and to better understand the role of such neuronal characteristics as the timing of spikes and spike's assemblies, including the interplay between inhibitory and excitatory activities.
2. At the interface between mesoscopic and macroscopic scales, we model populations of neurons using diferent models of Neural Fields, in order to better understand the functioning and learning characteristics of a local circuit of neurons, seen as a high level unit of computation. This level of description allows us to study the interaction between such calculation maps, i.e., large neuronal systems, such as cerebral maps and their feedbacks, as observed in sensorimotor loops.
3. In order to remain consistent with biological and ecological characteristics, we develop embodied and Embedded Systems: From a behavioral point of view, the emerging cognition has to be situated, i.e. resulting from a real interaction in the long term with the environment.
From a computational point of view, computations have to be really distributed, with decentralized control and memory.
In order to be falsiable through the confrontation to the previous constraints, our models have to be embodied in systems (e.g. robots) that interact with their multimodal environment, and embedded in parallel architectures of computations (eg FPGA, clusters).
4. Equally important, constraints relative to the consistency with experimental data have to be considered. We devote our activity of database analysis and interpretation, on physiological signals and psychometric data recorded from the functioning brain (eg EEG, ECOG). This common work with experimental neuroscience brings us a more macroscopic view of cerebral regions implicated in Higher Level Functions and allows us to design Brain-Machine Interfaces (BMI).

  In association with CORTEX, the NEUROMATHCOMP team, regarding this calloboration, aims at stuying motion perpection models (in biological and artificial vision, considering spiking neural networks and variational and PDE-based approaches) and methods combining dynamical systems theory, statistical physics and ergodic theory allowing to classify dynamics arising in canonical neuronal networks models like integrate and fire models, including synaptic and intrinsic plasticity, spike coding, spike train statistics analysis, neural masses dynamics, with applications in vision and imaging. Furthermore, CORTEX and NEUROMATHCOMP have join their efforts to develop common software tools in these fields, which aregoing to be of primary use in this project.

Frédéric Alexandre:  45 years old, French, Director of Research 2nd class INRIA, French
Education

1997: habilitation to be a director of research, university Henri Poincaré, Nancy1: "Intelligence neuromimétique"

1990: PhD in computer science, university Henri Poincaré, Nancy1 : "Une modélisation fonctionnelle du cortex: la colonne corticale"

1986: Engineer diploma, INPL

Professional experience

2000-present: DR INRIA

1990-2000: CR INRIA

Involvement in the research community

Member (and moderator) of the Scientific Committee of the inititative NeuroComp (french community in Computational Neuroscience)

Member of the steering committee of the PIRSTEC ANR program (survey and prospective analysis in cognitive science in France)

Responsible of CogniEst, french East Network in Cognitive Science

Head of the EPI CORTEX (Computational Neuroscience) at INRIA

Publications

Kassab, R., Alexandre. F. (2009) Incremental Data-driven Learning of a Novelty Detection Model for One-Class Classification with Application to High-Dimensional Noisy Data, Machine Learning, 74(2), 191-234.

J. Vitay
, N.P. Rougier and F. Alexandre, 2005. A distributed model of visual spatial attention. in: Biomimetic Neural Learning for Intelligent Robotics. S. Wermter, G. Palm and M. Elshaw Eds. Springer, 54-72.
J.C. Sarrazin, A. Tonnelier,
F. Alexandre, 2005, A model of contextual effect on reproduced extents in recall tasks: the issue of the imputed motion hypothesis, Biological Cybernetics, 92(5), 303-315.
F. Alexandre
, 2009, Cortical basis of communication: local computation, coordination, attention. Neural Networks, 22 (2) 126-133.
J. Fix, N. Rougier, F. Alexandre, From physiological principles to computational models of the cortex, Journal of Physiology, 101, 1-3, pp. 32-39, 2007.

T
opics of research: 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

Supervision of 25 PhD students, responsible of 1 European project, 1 ANR project, 20 articles, 10 chapters, 60 international conferences.

List, for each partner, the researchers involved in the Associate Team, with a short resume of the Coordinator;

Frederic Alexandre-INRIA is a Research Senior at INRIA. He is the head of the CORTEX Research Team at INRIA Nancy Research Center. His domain of research is Computational Neuroscience: through the study of cerebral information flows, neuronal architecture and learning principles, his main question is to understand how complex intelligent behavior emerges from distributed neuronal computation. He supervised more than 25 PhD students and was implicated in several international projects, including the leadership of a European project. He is also implicated in a variety of French committees, including the NeuroComp initiative about Computational Neuroscience and the PIRSTEC survey about Cognitive Sciences and Technologies in France.

Bruno Cessac-INRIA PhD in Physic. He work as a theoretical physicist on modeling and analysis of large sized dynamical systems and especially neuronal networks dynamics. He has developed methods combining dynamical systems theory, statistical physics and ergodic theory allowing characterizing the dynamics arising in canonical neuronal networks at the microscopic (neuron dynamics) and mesoscopic level (neural masses). His expertise is crucial, in this project, regarding the use of sophisticated statistical methods. The cornerstone of the analysis performed here is his method, coming from ergodic theory, and already available at the implementation level.

Thierry Viéville-INRIA is a Researcher Senior at INRIA where he works in Computational Neurosciences, while he teaches and advices PhD students at the Nice Sophia-Antipolis University. His research interests after Computer Vision is now Computation Neurosciences, more precisely Visual Perception, Motion Analysis and Adaptive Processes. He advised more than ten PhD students and participated in several international collaborations (EEC projects) with WP responsibilities. He also helps the INRIA board regarding Scientific Culture.

Pierre Kornprobst -INRIA obtained his PhD in Mathematics 1998. Then joined the computer science department from University of Southern California (Los Angeles), working with Gérard Medioni as a CSNE (Coopérant au Service National en Entreprise) sponsored by the company MATRA Système et Information. Since 2000, he is a researcher at INRIA Sophia Antipolis, participating to several project teams and defended his Habilitation in 2007. His research interests are computational and biological vision, computational neuroscience, psychophysics, calculus of variations, nonlinear partial differential equations and numerical analysis as applied to image processing. He is the key person, in this project, regarding mathematical aspects of variational approaches, and links with other connected research projects.

-------------------------

Maria-José Escobar-Silva-UTFSM PhD in Science: Automatique et Traitement de Signals et des Images, Université de Nice-Sophia Antipolis, France. Her thesis was developed in the team Neuromathcomp, INRIA Sophia-Antipolis, on bio-inspired models for motion processing, entitled “Development of Bio-Inspired Models for Motion Estimation: Analysis and Applications”. She worked under the supervision of Pierre Kornprobst and co-supervision of Thierry Viéville, in deep links with biologists. She previously obtained the Ms. in Electronic Engineer and Electronic Engineer title in Universidad Técnica Federico Santa María, with Javier Ruiz del Solar. She is the key person, in this project, regarding biological and computational visual motion processing, at both the modeling and simulation level.

Adrian Palacios-UV-CINV (AP-CINV, (Universidad de Valparaiso (UV) Professor since 1996) PhD in Neuroscience Pierre et Marie curie Paris VI, 1990 Fellowship Foundations: Philippe and Simone & Cino del Duca, France; 1990-1997 Postdoctoral and Associate Research Scientist, Yale U. 1998 Fellow Fundacion Andes; Visiting Research-Professor: Mind/Brain Institute, Johns Hopkins, 2001 MCB Harvard U. Fellows 2003 Center for Advanced Studies in Ecology & Biodiversity (CASEB); 2008-2010 Professor and Research Visiting INRIA-Cortex and Fellow to CREA Ecole Polytecnique, France. Founder and former director of a Master and a PhD Neuroscience Programs UV. 2006 Graduate coordinator, Faculty of Science UV. With Eric Goles and others they created in 2002 the Institute for Complex Systems of Valparaiso (ISCV) Author of 45 paper, participation in several divulgation activities, 102 meeting abstract, supervision 5 Postdoctoral fellows; thesis 12 graduate and 10 undergraduate. Coordinator of several public institutional external grants (MECESUP, Fundación Andes). Member of study sections from FONDEYCT and Students Fellowships during 6 years. Actual member Steering committee MECESUP2 (from Chilean Education Minister). Coordinator of several Research grants 3 Fondecyt, 3 DIPUV, 1 NIH-FIRCA, Co-director Milenio Nucleus, Principal investigador and coordinator PBCT ring grants ACT45 Coordinator of a French ECOS-CONICYT project and co-investigator in a European project MORPHEX and CNRS-Neuroinformatic (2009-2011) proyect. (www.cnv.cl, www.iscv.cl).

Six French/Chilean colleagues are the key-person going to be involved, with their students, in the core of this collaboration. They are already engaged in long-term collaborations between both countries, are use to work as invited researcher in abroad teams, etc... However, beyond this first circle, nine other colleagues are to be quoted within the CORTINA association, because they already brought a precious expertise on the addressed topics and are willing to also get involved in this project. Our collective agreement is to have on one hand a small group intensively involved in this common work, for efficiency reasons. On the other hand, we are going to continue and amplify at the scale of the larger group all scientific events (summer schools, etc..), project outcomes, multi-disciplinary scientific discussions, etc...

Laurent Bougrain -INRIA is an associate professor at Nancy-university working on neural information processing. He is working on a top-down approach for which data analysis techniques extract properties of underlying neural activity to better understand the principles of network dynamics. He studies the spatial and temporal scales of EEG, LFP and spikes in particular, for brain-machine interfaces. He is the scientific referent for health and disability at INRIA. He is the winner of the brain-computer interface competition IV, dataset 4 on "finger flexion from ECoG". He is the international coordinator of a STIC-AmSud projet (2009-2010), Argentine et Chili (UV) on single-trial detection for brain-computer interface.


Nicolas Rougier-INRIA: is an experienced researcher at INRIA and is a member of the CORTEX Research Team at INRIA Nancy Research Center. His domain of research relates to computational neuroscience with a focus on distributed numerical adaptive computations in order to understand how cognition can emerge from such computations. He has recently supervised two PhD thesis on the computational modeling on visual attention. He has been involved in various national, European and international projects. 

Axel Hutt-INRIA is a theoretical physicist working on the synchronization of measured neural activity data and their modeling by neural population models. His work deals with continuous neuronal networks, which are extended in the spatial domain. The theoretical studies investigate and the spatio-temporal activity and networks with respect to effects of propagation delay, feedback delay and random fluctuations (noise). The investigated models consider several cell types, excitatory and inhibitory synapses and various types of spatial connectivities. He leads the CNRS NeuroInformatique project 2009-2010: "sensory transduction to perception".

---------------------------

Steren Chabert UV Universidad de Valparaíso (UV). Professor since 2005, in the Biomedical Engineering Department. Founder and director of a Master program in Biomedical Engineering, at UV (since 2009).  Director of a FONDECYT research grant, focused on diffusion MRI, of a DIPUV research grant (UV internal grants), collaborator in a CORFO Innova project, in a DIPUV, and in an international collaboration project STIC-AMsud. Author of 8 papers, 27 meeting abstracts. 8 undergraduate thesis directed. Education: 2004: Ph.D. in Biomedical Engineering from Université de Technologie de Compiegne, thesis directed by Dr. D. Lebihan in CEA, on diffusion  MRI. 2004-2005: postdoctorate fellowship from ECOS-Conycit, in Dr. P. Irarrázaval Laboratory on diffusion MRI. 2000: Master of Science in Biomedical Engineering at Washington University in St Louis, MO (USA).

Pierre Guiraud-UV is Assistant Professor Depart Statistic, UV since 2006. PhD in Theoretical Physics Universite de Provence 2004, Marseille France. 2004 -2006 Postdoctoral position in the Depart  Ing Matematica, Univ Chile, CMM Santiago de Chile. My principal line of research deals with high dimensional dynamical systems and their applications in the modelling of systems of interacting units. My PhD. thesis deals with Coupled map lattices which are lattice discrete time dynamical systems, used for instance in the modelling of chains particles, genes regulatory networks and more generally reaction diffusion systems. In  Neuroscience I am working on the dynamics of neural networks, especially integrate and fire neural networks.

Juan Cristobal Zagal-UCH PhD is on Evolutionary Robotics and on going research is on Self-Modeling with Hod Lipson at Cornell University. His research deals with questions such as How to make robots to be more resilient? How to speed up learning in robots? To answer these questions he has been working in connection with Neuroscientists like Adrian Palacios at UV and Per E. Roland at Karolinska Institute. The ideas of Enactivism that are present in this project are of particular interest for his research. Juan Cristobal has developed physics simulators for various robots. A related publication won a best paper award during the 2004 RoboCup international symposium. Juan Cristobal has designed and implemented experiments with real robots as well as the required simulation of them.

Patricio Orio-UV-CINV is Universidad de Valparaíso, professor since 2007). PhD in Molecular & Cell Biology & Neurosciences, Universidad de Chile 2004. 2005-2006 postdoctoral research at the Instituto de Neurociencias de Alicante, Spain. 2008 DIPUV (UV) Grant awarded, 2009 Fondecyt Grant awarded for initiation into research. Author or coauthor of 10 papers (4 first author) and 20 meeting abstracts. Teaching in undergraduate and PhD programs in the Universidad de Valparaíso. Current research interest: Mathematical analysis and modeling of neuronal excitability with emphasis in oscillatory phenomena and sensory encoding.

Rodrigo Salas UV: PhD current research is advocated to the development and theoretical analysis of the robustness and flexibility capabilities of the learning algorithms of artificial neural networks and neuro-fuzzy models. He is exploring biologically plausible algorithms to enhance the capabilities of current techniques. He also co-manage a Biomedical Engineering undergraduate program at the Valparaíso University, (12 professors and 250 students) thus allowing this consortium to disseminate his results also by teaching, in this structure and beyond.

For each partner, involvement of students in the proposal. Estimation of the number of students concerned and whether joint thesis supervision is expected ;

CORTEX Carolina Saavedra, Horacio Rostro-Gonzales, Thomas Girod, Maxime Rio, Wahiba Taouali, Computational Neuroscience PhD ongoing thesis work. We plan to involve two others graduate students and Master students under joint supervision.

UV-CINV
and UFSM  Claudio Elgueta, Carolina Soto, Erick Olivares, Neuroscience PhD ongoing thesis work. Luis Sanz,  Informatics PhD ongoing thesis work at the Santa María University. Nicolás Moreno Statistics Master student from University of Valparaíso.  Other studens  Jaime Oliva (Master Eng. Biomed.), Herman Zepeda (Master Eng. Biomed.), Mariela Hidalgo ((Eng. Civil Biomed.). We will involve two others graduate students under joint supervision. Two other Enginnering students Joaquin Delgadillo from the Universidad Santa Maria in Valparaiso and Diego Pardo the Universidad de Valparaiso, Biomedical Engineering will apply for an internship to complete or start a Master degree at the INRIA in 2011.

Background of the collaboration between the teams ;

For several years, there is an ongoing tradition, but somehow asymmetrical, of exchange between INRIA research labs and Chilean labs. Many Chilean students, especially in the area of Engineering, are doing (or have done) labs rotation, as well as developing their thesis work in France. Recently, a very dynamic program of internationalization of Chilean Science, with a funding increase for international programs has helped to build more balanced, human and resources exchange between both countries. Many French Scientists and Students consider now Chile as a good place for collaboration; some are actors in this project. Furthermore, since 2007, we have strengthened and developed several ongoing and past collaborations and exchanges between INRIA and Chilean researcher’s partners and students belonging to several Universities, in particular from Valparaiso. An informal, but rapidly increasing set of collaborative activities is emerging, targeting long-term team associations. For example, Frédéric Alexandre and Thierry Viéville taught in the 2008 ISCV-summer school in Valparaiso, and in the 2010  ISCV-summer school in Valparaiso, with also Laurent Bougrain and Axel Hutt, while Bruno Cessac is going to teach a course this autumn in Valpapraiso, etc... Thanks to both INRIA and CMV-UV founds. Several seminars (using video-conferences) between INRIA and labs in Valparaiso have been issued. We now have a weekly common "journal club" between Chile and France on our common subjects. In 2008, Dr. Palacios participated as a external reviewer in Adrien Worher PhD Thesis carried in the Odyssee team et INRIA. Then becomes an Associate Visitor Professor for several months at INRIA-CORTEX and CREA-Ecole Polytechnique. Two young French colleagues (Pierre Guiraud and Steren Chabert at the UV), in link with this project, have permanent positions in Valparaiso. More than 10 Chilean students have made an Internship or PhD in the INRIA teams linked with this project. Frédéric Alexandre, Laurent Bougrain, Steren Chaber and Rodrigo Salas are involved in the two years STIC-AmSud project 2009-2010 "robust single-trial evoked potential detection for brain-computer interfaces using computational intelligence techniques", including one Internship and one Ph.D. thesis in France. This geographic complementarity has also become a thematic complementarity. A main impact of this project in Chile will be to bring first class French research in mathematics, computation, robotics and its application in benefices of students and researchers from engineering, biology, experimental psychology and robotic. With reverse transfer of competence towards France.

In summary, proposal combines efforts from researchers belonging to INRIA and two related French Universities with two Chilean Universities and one Research Institute, which represents a significant opportunity to build and develop a strong collaborative STIC platform for learning, sharing, transferring and applying knowledge in divers areas of S&T with a strong benefice for higher education and the society in general. In fact, thanks to previous founds the "CORTINA team" has already started ist action, while the goal is now to make this dynamic visible and sustainable.

Links towards relevant personal webpages, laboratories, home institutions, etc

3. Impact (1 page maximum) / Impact (maximum 1 page)

Impact of the proposed collaboration.

In a nutshell, this EA is going to bring to our every day common work between Chili and France three add-on:
       1/ Provide, on the French side,  the mandatory ressources to maintain this collaboration's bundle (these links are supported for two years on Chilean resources).
       2/ Make our work more formally visible and structured, in order to apply together to common financing on our research topics, including common publications.
       3/ Allow partners to structure in the perspective of an INRIA Center of Excellence in Chili (Applied Computational Neuroscience will be a ligne to be incorporate (expected) during 2011-2012)

One outcome is going to be the organisation of common summer schools (after 2008 and 2010) with a higher visibility of the French participation.

The complementarity with respect to the other CorTexMex EA (leaded by Bernard Girau, Cortex and M.A. Arias-Estrada from Mexico) on hardware/software codesign of bio-inspired connectionist models for vision, is two-fold: the research corresponds to the dual topic of Cortex (bio-inspired systems versus computation neuroscience models) and to the work of colleagues not involved in CORTINA, except one, whose role is going to make the link between these two topics. Furthermore, despite the geographical complementarity (Mexico versus Chile), we would be pleased to embed these two collaborations in some more global coordinate actions (e.g. international conference) with ``Latin America´´, if this becomes pertinent in our field.

- the scientific objectives of participating teams;

In the area of STIC and its applications, like computational brain science and robotics are relatively scarce in Chile, in contrast to the existence of excellent engineering and computer science school. In France, INRIA and its partners, which aim at combining scientific excellence with technology transfer, can help. On the other hand, experimental brain and sensory sciences are better developed in Chilean labs, in the domains targeted here. This is the case for the retina physiology, where the CINV is in link with the worldwide best labs.

 

- the relationships between partners and their home institutions

The partners as a team in this proposal have many complementarities, from interdisciplinary fields that will facilitate the accomplishment of this application (i) a team (AP) from sensory and biophysics neuroscience team that will provide experimental data (single and multielectrodes cells recording) on retina physiology; (ii) experts (INRIA) on neural computation and population coding statistic to formalize how neural coding is created. Regarding experimental data, provided here as true entries for the interpretation and further modeling and robotic applications, we indeed will also consider some of the data, e.g. neuron biophysics properties, recollected from the literature or the present colleagues. And concentrate on the specific data set that cannot be borrowed from the literature, since obtained using new paradigms, with a strict control of the preparation and the natural stimuli, designed by us to answer particular question about temporal and spatial properties detailed previously.

On both sides, from this schematized context view, a win-win strategy emerges. In the area of STIC and its applications, like computational brain science and robotics, research teams are relatively scarce in Chile, in contrast to the existence of excellent engineering and computer science school. In France, INRIA and its partners, which aim at combining scientific excellence with technology transfer, can help. On the other hand, as mentionned before, experimental brain and sensory sciences are better developed in Chilean labs, in the domains targeted here. This is the case for the retina physiology, where ISCV and CNV are in link with the worldwide best labs. This is also the case for emerging topics in evolutionary robotics, where competences from several disciplines being aggregated.

4. Divers : néant.


II. PREVISIONS 2011 / 2011 Forecast

Programme de travail
Work programme

Description du programme scientifiquede travail (1 à 2 pages maximum)
/Description of the scientific work programme (maximum 1 to 2 pages)

An interdisciplinary platform for translation from neuroscience into bioengineering will seek convergence from experimental and analysis/models, with a fine articulation between biological inspired computation and brain neural (coding / decoding) signal processing.

Tackling modern problems in Neuroscience requires sophisticated electronic and computational equipment and provides for electronic or computer engineers and biologists in Chile and France the opportunity of new sectors of development.

As possible outcomes, we thus expect :

O1: Software modules developed under the scope of this project are going to be made available as open-source middleware (e.g., under GPL and/or CeCILL-C license). We have a precise view of the kind of software outputs: no platform, no “system” but small reusable software components that could be used from several existing platforms (e.g., C/C++, Python, Matlab) or simulators (e.g., PyNN compliant simulators such as NEURON, NEST, BRIAN).

O2: Experimental data (both from biology and simulation, but also models) is going to be made available on data-base sharing sites such as ModelDB or http://www.crcns.org .

O3: We will target clinical or industrial applications as direct outcomes of this project. Some examples are BCI (Brain Computer Interface) to aid in rehabilitation of neurological impaired patients through an active collaborative work with Robotics Lab; clinical teams.

O4: Better understanding of sensory coding may have fruitful application, especially for people with low or impaired vision, while the whole corpus of produced knowledge is going to help us to better understand the brain and some of its diseases.

The scientific work program is decomposed into 3 tasks (T1 up to T3) with a modular structure, enhancing the different interactions between them and between the teams and countries within each task.

Cortina tasks



Summarizing, each task is described as follows:


T1: Observing non-standard behavior of ganglion retinal cells, with natural image sequences.

Multielectrodes arrays (MEA) system (64 X PLEXON amplifier, National Instrument (NI625X) acquisition board (10-25 KHz) and hard drives for the storage) for field potential or spike recording is operational in the lab of CNV. MEA arrays are commercially available (Multichannel System). The retina is mounted in a perfusion camera with AMES or equivalent solution, oxygenates and maintained at 35C, under controlled light conditions. Labview homemade software (SpikeHunter) for signal acquisition, control and exportation and visualization (SpikePlay) is use. OFF line visualization, analysis, spike clustering and cross-correlograms response are done with MATLAB routines and following (Schwartz and Berry, 2008; Schwartz et al., 2007) protocols. An advantage of recording from as many 50-100 electrodes using MEA arrays, neurons is the simultaneously access to “population coding” from a complete retina ganglion cell assembly. The physiological characteristics of ganglion cells with respect to natural images stimulus, including (e.g.) contrast-intensity, color, texture, will be used to characterize properties of firings (transients, sustain) ON / OFF, size and organization of receptive fields.

The Universidad de Valparaiso is an institution with an approved animal welfare assurance (A5823-01) from the NIH (USA).  

This tasks is structured as follows :

T2: Identifying new non-linear mapping from natural images to non-standard sensor (ganglion cells) responses.

In order to better understand to which extends non-standard visual sensor responses are able to process the visual signal using still non-elucidated mechanisms, we propose to explore original non-linear local mapping from natural images using a variational approach at the mesoscopic level.

The general framework, already well-established and validated on non-trivial visual operators (such as motion perception and segmentation, visual event detection, etc) allows one to build a link between

  1. high-level specification of how the brain represents and categorizes the causes of its sensory input and

  2. related analog or spiking neural networks.

Focusing on visual processing, this computer-vision expertise allows one to show -for a rather general class of computations- how it is possible to directly rely “what is to be done'' (perceptual task) with “how to do it'' (neural network calculation). More precisely, in computer vision, efficient computation using implementations of regularization processes allow one to obtain well-defined and powerful estimations. They (i) represent what is to be done as an optimization problem, (ii) considering regularization mechanisms (implemented using so-called partial-differential-equations) and (iii) “compiling'' the related analog or spiking neural network parameters. An unbiased approximation of a so-called diffusion operator used in regularization mechanisms with a direct link between continuous formulation and the related sampled implementation is available, and spiking-mechanisms have been explored in this context (Vieville et al, 2007).

This includes non-linear local visual operators based on sparse representations (Escobar et al, 2009) and independent component analysis methods. We propose to apply this general framework in the present context in order to somehow reverse engineer the non-standard cells processing. The original framework has to be revisited in order to design well-founded mechanism to learn the proper parameters, given a set of input/output. Multi-model estimation methods are going to be used, to guarantee the estimation with a minimal number of parameters. Spike trains coding of information is going to be considered here (Cessac et al, 2009).

This modeling is not going to be a precise description of the internal retinal processes, but of its input/output relation. The key point is that we are going to be able to consider natural images sequences (and not artificial biased stimuli) as input, and thus need more sophisticated algorithms than for simple artificial stimuli.


T3: Applying statistical analysis of ganglion cells retina responses and study of underlying adaptation mechanisms.

Recent advances in multi-electrodes recording have thus brought us closer to understanding how populations of retinal ganglion cells encode visual information. By monitoring the visual responses of many ganglion cells at once, it is now possible to examine how ganglion cells act together to encode a visual scene. To attain this objective, a quantitative and statistical analysis of the ganglion cells spiking activity is required.

This issue is faced to the delicate problem of proposing and validating accurate statistical model fitting the empirical spike trains. It has been shown in (Schneidman et al, 2006; Cessac et al, 2008) that Gibbs measures constitute optimal parametric models, the estimated Gibbs potential allowing to produce population rate, correlations or synchronization pattern, providing an effective statistical tool.

Since, using the Gibbs potential framework allows us to obtain parametric estimations of spike train observables, e.g. the population rate, correlations, or synchronization pattern occurrence probability, this statistical tool appears to be a very interesting way of attaining our objective, allowing us to relate the observed spiking activity to higher scales of observation of the neuronal activity. For instance, the population spiking rate and correlation, or even higher order statistics can be measured using the previous parametric model and then integrated in mean-field mesoscopic models (Faugeras et al, 2009).

We propose to apply an open-source library (EnaS) which estimates a polynomial Gibbs potential over population spike trains and subsequently the population firing rate, correlations, higher order statistics and relative entropy (Vasquez et al, 2010).
Two types of population spike trains are studied :

The software module EnaS has been already validated at the programmatic level (functional tests). The goal here is to deal with the spike decoding mechanism, more precisely to apply the proposed estimation procedure of spike statistics in order to shed some light on the correlations between neurons in the retina. This is a key question because one hypothesis is that ganglion cells mainly act as independent encoders (Segev et al, 2004). This would have important consequences regarding computational aspects of the early-vision processing. This hypothesis contradicts in part the results of another group (Pillow et al, 2008), which has observed correlations between ganglion cells encodings. As a perspective of this work, the teams are strongly interested to attack the problem of retinal encoding of natural images. The opportunity to combine experimental recordings and the best numerical methods to analyze the data is a great advantage to attack this challenge.

The Gantt Chart is strainghtforward since all three tasks are going to be in constant interactions:

 

 

Year 1

Year 2

Year 3

 

sem 1

sem 2

sem 1

sem 2

sem 1

sem 2

T1

 

 

 

 

 

 

T2

 

 

 

 

 

 

T3

 

 

 

 

 

 

In words, T1 and T2 have already started, while T2 is going to start as soon as data analysis is going to available, while experimental work is planned for two years, data analysis and modeling for two years and a half.

References:

Cessac, B., Rostro-Gonzalez H., Vasquez J.C. and Viéville, T. (2008), Statistics of spikes trains, synaptic plasticity and Gibbs distributions, NeuroComp'08, Marseille.
Cessac, B., Paugam-Moisy H., Viéville, T. (2009), Overview of facts and issues about neural coding by spikes, J. Physiol Paris, 104, 1-2.
Escobar M.J., Masson G.S., Vieville T. and Kornprobst P. (2009). Action Recognition Using a Bio-Inspired Feedforward Spiking Network. International Journal of Computer Vision, 82-3 284-301.
Faugeras O, Touboul J, Cessac B (2009) A constructive mean field analysis of multi population neural networks with random synaptic weights and stochastic inputs” Front. Comput. Neurosci. 3:1.
Pillow W., Shlens J., Paninski L., Sher A., Litke A.M., Chichilnisky E.J. and Simoncelli E.P.(2008), Nature 454(7206), 995-999 .
Schwartz, G., and Berry, M.J., 2nd. (2008). Sophisticated temporal pattern recognition in retinal ganglion cells. J. Neurophysiol. 99, 1787–1798.
Schwartz, G., Harris, R., Shrom, D., and Berry, M.J., 2nd. (2007a). Detection and prediction of periodic patterns by the retina. Nat. Neurosci. 10, 552–554.
Schwartz, G., Taylor, S., Fisher, C., Harris, R., and Berry, M.J., 2nd. (2007b). Synchronized firing among retinal ganglion cells signals motion reversal. Neuron 55, 958–969.
Schneidman, E., Berry, M. J., Segev, R., and Bialek, W. (2006). Weak pairwise correlations imply strongly correlated network states in a neural population. Nature. 440, 1007—1012.
Segev R, Goodhouse J, Puchalla J, Berry MJ 2nd. (2004) Recording spikes from a large fraction of the ganglion cells in a retinal patch. Nat Neurosci. 7:1154-61.
Vasquez J,C, Viéville T, Cessac B (2010) Entropy-based parametric estimation of spike train statistics. J. Comp. Neuroscience (submitted).
Viéville, T., Chemla, S., and Kornprobst, P. (2007). How do high-level specifications of the brain relate to variational approaches? J Physiol Paris, 101(1-3):118-135.



Programme d'échanges avec budget prévisionnel
Exchanges schedule and estimated budget

1. Echanges / Exchanges

Incoming and outgoing exchanges planned: invitations of researchers from the partner institution in France, and missions of INRIA researchers abroad

Planned invitations and exchanges:

Year

Activity

Participantes

Subject

Outcome

Period

2011

Visio Meeting

All including students

Computational Models of Visual System

Report / Paper

Weekly

2011

Visit Chile


Summer School / Models of Visual Data / Meeting

Research / Report

3 Weeks

2011

Visit Chile


Summer School / Models of Visual Data / Meeting

Research / Report

3 Weeks

2011

Visit France


Models of Visual Data / Meeting

Research / Report

1 month

2012

Visio Meeting

All including students

Computational Models of Visual System

Report / Paper

Weekly

2012

Visit Chile


Models of Visual Data / Meeting

Research / Report

3 Weeks

2012

Visit France


Models of Visual Data and robotic implementation / Meeting

Research / Report

1 month

2013

Visio Meeting

All including students

Computational Models of Visual System

Report / Paper

Weekly

2013

Visit Chile


Models of Visual Data / Meeting

Research / Report

3 Weeks

2013

Visit France


Models of Visual Data and robotic implementation / Meeting

Research / Report

1 month

 

Status of the researchers involved (intern, PhD student, postdoctoral fellow, senior researcher, other)

 

Team

Status

Participantes

CORTEX

Senior Research

Frederic Alexandre

CORTEX

Senior Research

Thierry Vieville

Neuromathcomp

Senior Research

Bruno Cessac

Neuromathcomp

Senior Research

Pierre Kornprobst

CORTEX

Senior Research

Axel Hutt

CORTEX

Senior Research

Laurent Bougrain

CORTEX

Senior Research

Nicolas Rougier

CORTEX

Students

Carolina Saavedra

CORTEX

Students

Maxime Rio

CORTEX

Students

Wahiba Taouali

CORTEX

Students

Horacio Rostro

UV-CINV

Senior Research

Adrian Palacios

UV-Biomedica Eng

Young Faculty

Rodrigo Salas

Biomedica Eng

Young Faculty

Steren Chabert

UTFSM

Young Faculty

Maria-José Escobar

UV-Biostatistics

Young Faculty

Pierre Guiraud

UV-CINV

Young Faculty

Patricio Orio

UCH

Young Faculty

Juan Cristobal Zagal

UV-CINV

Phd Student

Claudio Elgueta

UV-CINV

Phd Student

Carolina Soto

UV-CINV

Phd Student

Erick Olivares

UFSTM

Young Engineer

Joaquin Delgadillo

UV-CINV

Biomedical Engineering Master Student

Diego Pardo

 

Scientific purpose of the exchanges planned (joint research, workshop, ...) and indicate their duration
    
Exchanges and  join  research and workshop are dedicated to both the participation to join international events (summer-schools, conferences, ..) and the works in the lab on experimental acquisition campain, where the physical presence is mandatory. All other common work is done using electronic tools, and does not require physical transportation.

Summary ofp the informations above and estimated budget

 1. ESTIMATION DES DÉPENSES EN MISSIONS INRIA VERS LE PARTENAIRE
Estimated spending for missions of INRIA researchers abroad

Nombre de personnes
Number of persons

Coût estimé
Estimated cost

Chercheurs confirmés
Senior researcher

  5

 5 x 1.2K€

Post-doctorants
Postdoctoral fellow

 néant

 

Doctorants
PhD student

 3

  3 x 1.2K€

Stagiaires
Intern

  néant

 

Autre (précisez) :
Other (detail):

  néant

 

   Total

 8

 9.6K€

 

 2. ESTIMATION DES DÉPENSES EN INVITATIONS DES PARTENAIRES
Estimated spending for invitations of Partner researchers in France

Nombre de personnes
Number of persons

Coût estimé
Estimated cost

Chercheurs confirmés
Senior researcher

 3

 3 x 2K€

Post-doctorants
Postdoctoral fellow

  1

1 x 2K€ 

Doctorants
PhD student

 

3 x 2K€ 

Stagiaires
Intern

 néant

 

Autre (précisez) :
Other (detail):

0 (see above) 

 

   Total

 7

 14K€

Note: Le calcul  se base sur 3 éléments arithmétiques simples: voyage low-cost Chili-France 1.2K€ ; séjour (en tenant compte du fait que pour réduire les coûts et renforcer le travail déquipe, plusieurs collègues sont invités de manière familiale) 100€/jour x 20 jours ; surtout la plus grande partie de nos interactions se fait en visio-conférence et avec nous outils usuels de travail collaboratif numérique, ce qui limite fortement le rapport entre le coût de transport (et impact carbone) et la bande passante de cette collaboration.

2. Cofinancement / Cofinancing

1) CNRS NeuroInformatique project 2009-2010: "sensory transduction to perception" 20.000€. INRIA CORTEX: Frédéric Alexandre, Bruno Cessac,  Laurent Bougrain, Axel Hutt (PI), Thierry Vieville; UV-CNV Chile: Adrian Palacios, Diego Cosmelli.

2) STIC AMSUD 09STIC01 project 2009-2010: "Robust single-trial evoked potential detection for brain-computer interfaces using computational intelligence techniques" 15.000€/2years. INRIA Nancy - France: Laurent Bougrain(PI), Frédéric Alexandre, Axel Hutt,  Universidad de Valparaíso - Chile: Steren Chabert, Rodrigo Salas .

If this application is successful, partner institution will also support:

4) The Universidad de Valparaiso has yearly application for Professor Exchange and Chilean graduate student can apply to CONICYT for short periods of exchange with partners labs.   

5) Up to now, the Universidad de Valparaiso has supported all different travel costs related to summer school organization and scientific travels aboard.

3. Demande budgétaire / Proposed budget

 

Commentaires

Montant

A. Coût global de la proposition (total des tableaux 1 et 2 : invitations, missions, ...)
A. Global cost of the collaboration project

 23.6K€.

B. Cofinancements utilisés (financements autres que Equipe Associée)
B. Cofinancing (other than Associate Team programme)

 3.6K€

Financement "Équipe Associée" demandé (A.-B.)
Funding from the Associate Team programme

 20K€

 

© INRIA - mise à jour le 17/09/2010