Modeling the neural correlates of imitation from a neuropsychological perspective
Imitation is a fundamental mechanism by which humans learn and understand the actions of others. This thesis addresses the low-level neural mechanisms underlying the imitation of meaningless gestures, using tools from computational neuroscience. We investigate how the human brain perceives these gestures and translates them into appropriate motor commands. In addition, we take a relatively unexplored neuropsychological perspective, which looks at imitation following a brain lesion. The analysis of how imitation breaks down in apraxia, a complex disorder of voluntary movement, enables us to reverse engineer brain function through the identification of those building blocks that are preserved. To better understand the phenomenon of apraxia, we develop a neurocomputational model of imitation that proposes potential neuroanatomical correlates, such as the flow of information across the two brain hemispheres. The model accounts for the pattern of errors observed in apraxic patients with disconnected brain hemispheres. To validate the predictions of our model, we further analyze the experimental errors and uncover a goal-dissociation, where a goal is defined as the spatial relation between two body parts. The experimental observations suggest that the imitation deficit in apraxia arises from an incorrect coordination between the reproductions of multiple goals. A prediction of this hypothesis was validated on three apraxic patients. The collected body of kinematic and neuropsychological data allowed us to refine our neurocomputational model of imitation, and to propose a biologically plausible mathematical model for the execution stage of the imitation. The model controls movement by following nonlinear dynamics, and precisely reproduces both the spatial and temporal aspects of unconstrained and natural three-dimensional reaching movements. Importantly, the model is stable and robust against external perturbations. Overall, our computational models and neuropsychological experiments contribute to a better understanding of how the brain performs the imitation of meaningless gestures; that is, by first decomposing the gesture into imitation goals, and then reproducing these goals through the association of different sensory modalities.
Keywords: computational neuroscience ; nonlinear dynamical systems ; imitation of meaningless gestures ; apraxia ; brain lesion ; human motor control ; reaching movements ; neurosciences computationnelles ; systèmes non-linéaires dynamiques ; imitation de gestes sans signification ; apraxie ; lésion cérébrale ; contrôle moteur humain ; mouvements d'atteinteThèse École polytechnique fédérale de Lausanne EPFL, n° 4577 (2009)
Programme doctoral Systèmes de production et Robotique
Faculté des sciences et techniques de l'ingénieur
Institut de microtechnique
Laboratoire d'algorithmes et systèmes d'apprentissage
Record created on 2009-11-09, modified on 2016-08-08