CORTEX International Meeting 2013Published on April 22, 2013
LabEx CORTEX is organising an International Conference in Lyon next June....
Cortical Networks for Cognitive Interaction
A fundamental aspect of human cognition is the adaptive capability it provides which allows the individual to interact in a novel and compositional manner with objects and other individuals in the surrounding space. These capabilities rely on perceptual processing, the integration of multimodal signals and the construction of multidimensional representations that can link high level processing from vision, action perception, speech and language, and cooperative interaction. Our previous research has addressed sensory-motor integration and higher cognition including spatial integration and language comprehension through a variety of methods including human functional imagery and clinical neuroscience, neural network simulation and robotics. This has lead us to an understanding of certain canonical principals of the cortico-striatal system in sequence learning and language, and an understanding of how distinct cortical processes for sensory-motor integration operate at different time-scales in the construction of a coherent representation of space, towards a general model of integrated perceptual processing. These studies have provided the basis for our implementation of robotic systems capable of vision and language based interaction with humans, including the ability to learn new cooperative behaviours in real time. One of the crucial issues that has emerged in this research is the realization that the nature of internal representations will be determined by the physiological structure of the system and its direct link with the nervous system, thus bringing us towards the “embodied cognition” stance. In this context we will develop a “hybrid” embodied cognitive system for a humanoid robot, the “iCub”.
| Peter Ford Dominey || |
Peter Ford Dominey is a Research Director with the CNRS in Lyon France. He completed the BA at Cornell University in 1984 in cognitive psychology and artificial intelligence. In 1989 and 1993 respectively he obtained the M.Sc. and Ph.D. in computer science from the University of Southern California, developing neural network models of sensorimotor sequence learning, including the first simulations of the role of dopamine in sensorimotor associative learning. From ...
| Jean-David Boucher PHD Student|| |
The goal of my Phd is to create a programm for a human-robot intercation (HRI).The main characteristics of it are:* The robot has to learn via the interaction with the user.* The user is a naive personn, no computer science knowledge is necessary.* The robot has to create new representations for each behavior.* The user can reuse these representations.* The interaction has to be as fluently as possible.In order to achieve this aim, I don't adopt a classical AI point of view but rather "developmental ...
| Guillaume Gibert || |
| Xavier Hinaut || |
His research explores brain mechanisms of complex sequence processing, focusing on language syntactic comprehension. He is interested in using Recurrent Neural Networks to model these processes and investigating how such models can be used in developmental robotics.Xavier Hinaut received an M.S. in Computer Science from the University of Technology of Compiègne, France in 2008 and an M.S. in Cognitive Science from the Ecole Pratrique des Hautes Etudes, France ...
| Anne-Lise Jouen Student|| |
| Mehdi Khamassi || |
Medhi Khamassi was a post-doc fellow in the team of Peter Ford Dominey and Emmanuel Procyk. His work aimed at proposing a computational model of the dorsolateral prefrontal and anterior cingulate cortices' involvement in the exploration-exploitation trade-off during visuo-motor sequences learning. He completed a Master Degree in Cognitive Science at University of pierre et Marie Curie in 2003, and another Master Degree in Computer Science and Engineering at CNAM-ENSIIE ...
| Stephane Lallee || |
As a member of Dominey's Team, I work on improving how robots can cooperate with humans.
How can we modelise the cooperation ability, what is the goal of an action or a task and how to understand it ? These are some questions which I try to answer. My main approach is to define and use neural network based models in order to mimic various cognitives functions.
By linking all these models to a high level model of cognition, I hope to be able to build the ground of a new theory ...
| Carol Madden-Lombardi || |
My program of research
brings together principles from the strong tradition of cognitive
the emerging framework of embodied cognition, and pioneering work in
robotics to better understand how we comprehend described events. Our
employs a methodical approach in which (1) the behavior in question is
characterized, (2) the mechanisms that implement that behavior are
(3) this knowledge is used to create an artificial system (derived ...
| Maxime Petit || |
| Jocelyne Ventre-Dominey || |
Jocelyne Ventre-Dominey is Senior Researcher at INSERM-U846 in Lyon, France.
She received her PhD at University Claude Bernard in Lyon
in 1982 studying the implication of cortex in visual vestibular functions in
the cat and macaque. During her thesis, she described for the first time the
role of the posterior cerebral cortex in vestibular function and its anatomical
correlates as direct projections from cortex to the vestibular nuclei. During
her 2 years ...
Selected Publications of Team members : |
Dominey PF, Inui T, Hoen M (2008) Neural network processing of natural language: II. Towards a unified model of cortico-striatal function in learning sentence comprehension and non-linguistic sequencing. Brain and Language. Available on line 5 october 08 download
Ventre-Dominey J, Vallee B. (2007) Vestibular integration in human cerebral cortex contributes to spatial remapping. Neuropsychologia 45(2):435-9. download
Dominey PF, Mallet A, Yoshida E (2007) Progress in Programming the HRP-2 Humanoid Using spoken Language Proceedings of IEEE/RAS Int. Conf. Robotics & Auton. Systems download
Hoen M, Deprez V, Dominey PF (2007) Do you agree? Electrophysiological characterization of online agreement checking during the comprehension of correct French passive sentences. Journal of Neurolinguistics, 20, 395-421 download
Hoen M, Pachot-Clouard M, Segebarth C, Dominey PF (2006) When Broca experiences the Janus syndrome: an ER-fMRI study comparing sentence comprehension and cognitive sequence processing. Cortex 42:605-23. download
Ventre-Dominey J, Bailly A, Lavenne F, Lebars D, Mollion H, Costes N, Dominey PF. (2005) Double dissociation in neural correlates of visual working memory: a PET study. Cogn Brain Res 25(3):747-59 download
Dominey PF, Boucher JD (2005) Learning to talk about events from narrated video in the construction grammar framework Artificial Intelligence 167 (2005) 31–61 download
Zwaan RA, Madden CJ. (2004) Updating situation models. J Exp Psychol Learn Mem Cogn 30(1):283-8; discussion 289-91. download
Madden CJ, Zwaan RA. (2003) How does verb aspect constrain event representations? Mem Cognit 31(5):663-72 download
Dominey PF, Hoen M, Blanc JM, Lelekov-Boissard T (2003) Neurological basis of language and sequential cognition: Evidence from Simulation, Aphasia and ERP Studies Brain and Language 86(2):207-25 download
Hoen M, Golembiowski M, Guyot E, Deprez V, Caplan D, Dominey PF (2003) Non-linguistic cognitive sequence training improves syntactic comprehension in agrammatic aphasics Neuroreport, 14, 495-9 download
Ventre-Dominey J, Dominey PF, Broussolle E. (2002) Dissociable processing of temporal structure in repetitive eye-hand movements in Parkinson’s disease. Neurospychologia 40(8):1407-18 download
Neimer J, Eskiizmirliler S, Ventre-Dominey J, Darlot C, Luyat M, Gresty MA, Ohlmann T. (2001) Trains with a view to sickness. Curr Biol 11(14):R549-50. download
Dominey PF, Ramus F (2000) Neural network processing of natural language: I. Sensitivity to serial, temporal and abstract structure of language in the infant. Lang Cogn Processes, 15(1):87-127 download
Procyk E, Dominey PF, Amiez C, Joseph J-P (2000) The effects of sequence structure and reward schedule on serial reaction time learning in the monkey Cogn Brain Res 9(3):239-48 download