A Neurocomputational Model of an Imitation Deficit following Brain Lesion

This paper investigates the neural mechanisms of visuo-motor imitation in humans through convergent evidence from neuroscience. In particular, we consider a deficit in imitation following callosal brain lesion, based on the rational that looking at how imitation is impaired can unveil its underlying neural principles. We ground the functional architecture and information flow of our model in brain imaging studies and use findings from monkey brain neurophysiological studies to drive the choice of implementation of our processing modules. Our neural model of visuo-motor imitation is based on self-organizing maps with associated activities. Patterns of impairment of the model, realized by adding uncertainty in the transfer of information between the networks, account for the scores found in a clinical examination of imitation (Goldenberg et al, 01). The model also allows several interesting predictions.

A Neurocomputational Model of Impaired Imitation

Aude Billard, Biljana Petreska von Ritter-Zahony

This abstract addresses the question of human imitation through convergent evidence from neuroscience, using tools from machine learning. In particular, we consider a deficit in imitation of meaningless gestures (i.e., hand postures relative to the head) following callosal brain lesion (i.e., disconnected hemispheres). We base our work on the rational that looking at how imitation in apraxic patients is impaired can unveil its underlying neural principles. We ground the functional architecture and information flow of our model in brain imaging studies. Finally findings from monkey brain neurophysiological studies drive the choice of implementation of our processing modules. Our neurocomputational model of visuo-motor imitation is based on selforganizing maps receiving sensory input (i.e., visual, tactile or proprioceptive) with associated activities [1]. We train the connections between the maps with anti-hebbian learning to account for the transformations required to translate the observation of the visual stimulus to imitate to the corresponding tactile and proprioceptive information that will guide the imitative gesture. Patterns of impairment of the model, realized by adding uncertainty in the transfer of information between the networks, reproduce the deficits found in a clinical examination of visuo-motor imitation of meaningless gestures [2]. The model makes hypotheses on the type of representation used and the neural mechanisms underlying human visuo-motor imitation. The model also helps to gain more understanding in the occurrence and nature of imitation errors in patients with brain lesions.

2006

Neurocomputational modeling of imitation deficits

Aude Billard, Biljana Petreska von Ritter-Zahony

We are interested in the question of human imitation and we address this through convergent evidence from neuroscience. The rationale of our work is that the nature of imitation deficits following brain lesion can unveil some of the neural and computational principles underlying normal imitation. In particular, we consider how imitation of meaningless gestures (i.e., hand postures relative to the head) is impaired in apraxia [1], i.e., an inability to perform voluntary movements that cannot be explained by elementary motor, sensory or cognitive deficits. We have first considered a clinical study of visuo-motor imitation of meaningless gestures in an apraxic patient with damage to the corpus callosum [2]. Interestingly the patient made different errors depending on the visual field of presentation of the stimulus and the hand used, with preserved imitation only in the right visual field – right hand condition. These observations brought us to consider modeling of the information pathway across the two hemispheres and the type of connectivity impairment which would account for them. We have thus developed a leaky integrator neurocomputational model of the neural representations of different sensory information (e.g., visual, tactile or proprioceptive) and reciprocal nonlinear transformations necessary to perform the imitation task [3]. The sensory representations in our model are self-organizing maps whose interconnections are trained with anti-hebbian learning. The information flow and implementation details of the model are consistent with evidence from brain imaging and neurophysiological studies [4,5]. To simulate callosal apraxia, we added uncertainty in the transfer of information between sensory representations localized in different hemispheres, successfully reproducing the results found in [3]. To summarize, our model makes hypotheses on the type of neural representations used and the computational mechanisms underlying human visuo-motor imitation and could possibly help to gain more understanding in the occurrence and nature of imitation errors in patients with brain lesions. In addition, to further test and validate the model against human motion experimental data, we conduct, in collaboration with the Geneva University Hospital (HUG) and Vaud University Hospital Center (CHUV), kinematic studies with brain damaged adults specifically disabled in gesture imitation.

2008

Neural Modeling of Imitation Deficits

Aude Billard, Olaf Blanke, Biljana Petreska von Ritter-Zahony

This abstract addresses the question of human imitation through convergent evidence from neuroscience. We look at deficits in imitation following brain lesion, such as apraxia. We believe that looking at how imitation is impaired can unveil its underlying principles. We also take inspiration from numerous brain imaging studies to ground the functional architecture and information flow of our model. In the end we will use findings from monkey brain neurophysiological studies to implement the details of our processing modules. We aim at developing a model of visuo-motor imitation using tools from neural networks and dynamical systems. The model should account for some of the behaviors observed in faulty imitation. At this stage we have implemented a somatotopically organized neural network with probabilistically impaired transfer of information that simulates lesions at the level of the parietal cortex (a brain center for sensorimotor integration). To validate the model against human motion experimental data, we conduct, in collaboration with the Geneva University Hospital (HUG), kinematic studies with brain damaged adults specifically disabled in gesture imitation. The model will motivate the realization of computer-based rehabilitation tools.

2006

Neurocomputational modeling of imitation deficits

Aude Billard, Biljana Petreska von Ritter-Zahony

2008