Presentation Team AVA
Coordinators : Solène Kalénine & Laurent Madelain
The AVA team focuses on exploring a functional approach of vision, the relations between perception and action, and the role of reinforcement in behavioral changes. Research topics encompass behavioral, cognitive and brain mechanisms. Applications relate to the digital domain (cognitive technologies, virtual reality, etc.) and neuropsychology.
Methodologies: quantifying response times and choices, eye movements, fNIRS, EEG, EMG, EDA, motion capture, static and dynamic virtual reality, force platform, computational modeling, neural networks.
Populations: healthy adults, patients with neurological or psychopathological disorders, children with typical and atypical development, older adults
Coordinators : Laurent Madelain (Pr, ULille) & Solène Kalénine (CR, CNRS)
Researchers : Jérôme Alessandri (MCF, ULille), Angela Bartolo (Pr, ULille), Cédrick Bonnet (CR, CNRS), Yann Coello (Pr, ULille),Yvonne Delevoye (Pr, ULille), Murielle Garcin (Pr, ULille), Jeremie Jozefowiez (MCF, ULille), Solène Kalénine (CR, CNRS), Françoise Lefèvre (MCF, ULille), Laurent Madelain (Pr, ULille), Tatjana Nazir (DR, CNRS), Arthur Prével (MCF, ULille), Vinca Rivière (Pr, ULille), Clémence Roger (MCF, ULille), Bilge Sayim (CR, CNRS), Yannick Wamain (MCF, ULille)
PhD Student : Maria-Isabel Casso Echalar, Baptiste Chopin, Fabrizia Gallo, Robin Gigandet, Angela Gomes Tomaz, Lilas Haddad, Yann-Romain Kechabia, Clémence Lelaumier, Manon Lenain, Lucie Lenglart, Miao Li, Maxime Martel, Faouzia Millequant Gourari, Raphaelle Radenne, Luc Virlet, Dandan Yu
PAST: Sabrina Hassaïni, Joëlle Nuchadee
Post-doctorant: Bing Li
ATER: Fabrizia Gallo
Associate members : Justine Blampain (psychologue Hôpital Provo de Roubaix), Mauraine Carlier (privé)
Associate EC : Yannick Miossec (MCF, ULille)
Personnels sur contrat de recherche: Mélen Guillaume
Themes of study
Research conducted on the functional representation of space highlights the existence of different neural networks for the manual action space (peripersonal space) and for the whole-body navigation space (extrapersonal space). We study the neural bases of peripersonal space representation and its role in the cognitive mechanisms underlying perceptual categorization, symbolic processing and social interactions. In the general framework of embodied cognition theories, we also aim at specifying the complex relations between action and object representations. Finally, we examine the neural and psychophysiological bases of communicative and object-directed actions.
We could not fully process all of the visual information available at once. Instead, vision relies on actively selecting and prioritizing parts of the visual field. This active vision can be nicely evidenced in the laboratory by studying visual crowding, in which the visual perception of a target object in peripheral vision is affected by the presence of nearby distractors. Research on ocular motor behaviors, and in particular saccadic eye movements, is also of importance for unraveling the functional approach of vision. Saccades are characterized by a great plasticity that is studied in the context of reinforcement learning.
The functional approach of motor control stands on the hypothesis that motor behaviors are regulated by bio-mechanical constraints but also by the cognitive ability to select and simulate specific goals in order to optimize performance. We examine the interactions between vision, posture, and cognition through models of upright balance regulation in the context of various visual tasks. Moreover, we propose to further develop a theoretical model of motor control that integrates temporal dynamics in internal loops. Mechanisms of cognitive control are also deeply studied to better understand decision-making and error regulation in motor responses.
Theories of learning assume that the functional organization of the environment is critical for learning new behaviors. Our research aims at clarifying the conditions under which organisms may use relations between events in order to draw a formal description of the mechanisms underlying learning. One of our main scientific challenges is to highlight the variables involved in the development of novel behaviors. We also study the relative effect of reinforcement contingencies, instructions and experimenter expectations.