Motivation

We believe that the deficits in imitation observed following fronto-parietal or callosal brain lesions, such as apraxia, can be very instructive on the neural and cognitive principles underlying normal imitation. Following this rational, we have developed a neurocomputational model of imitation that reproduces the statistics of callosal apraxia errors. Ideally, we would like to: a) reproduce not only the statistics, but also the exact nature of apraxic errors and b) validate our model against a new set of experimental data. This has led us to conduct neuropsychological experiments of apraxia ourselves, in collaboration with the Geneva University Hospital (HUG) through the Laboratory of Cognitive Neuroscience (LNCO) and the "Service de Neuropsychologie et de Neuroréhabilitation" of the Centre Hospitalier Universitaire Vaudois (CHUV).

MRI image of an apraxic patient with a large left posterior parietal lesion.

Apraxia

Apraxia is generally defined as the inability to perform voluntary movements that cannot be explained by elementary motor, sensory or cognitive deficits (not caused by weakness, ataxia, akinesia, deafferentation, inattention to commands or poor comprehension), meaning that is a deficit at the level of the sensory-motor transformations. Apraxia has uncovered many selective deficits and dissociations in gesture production and imitation such as: impaired transitive (with objects) and preserved intransitive movements, isolated impairment of meaningful gestures, defective imitation of meaningless gestures contrasted with preserved performance of meaningful gestures to verbal command or imitation as well as dissociation in imitation of hand vs. finger configurations. These deficits were reviewed in (Petreska et al., Progress in Brain Research, 07)

Motion Study

We have replicated Goldenberg’s seminal study of imitation of meaningless gestures with apraxic patients (Goldenberg et al, Neuropsychologia, 01; described in more detail here) with 4 parietal patients. In order to provide quantitative data of the affected variables, we have extended Goldenberg’s experiment by recording the hand posture and kinematics of arm motion with motion sensors (see Figure on the right).

Results

We have analyzed the spatial and temporal abnormalities in the kinematics of apraxic imitative movements and we have compared them with those of normal subjects. We considered the hand and joint angles trajectories, their principal components, speed and acceleration profiles, joint angles phase analysis and timing, inter-subject and inter-trial variability, etc... An example is given below. Whereas the patient's reaching movement is not impaired per se, one can observe a lot of variability and hesitations in the patient's imitative movement and the need for the patient to execute the imitation in two phases. We have also assessed the error systematicity, which was very high meaning that the apraxic errors were consistent across trials, arguing for a specific underlying deficit.

Left, trajectories of an apraxic patient's imitative movements, the color represents the speed of the movement. Right, we show the patient's (in red) and control subject's (in blue) shoulder flexion-extension joint angle trajectories. Note that the patient hesitates a lot, giving rise to abnormal multi-peaked kinematics. The trajectories were normalized in time, the patient's execution time was significantly longer.

Example of the stimulus to imitate and the patient’s response in the experimental condition.

Applications

In order to be able to compare our neurocomputational model's predictions with the kinematic data we have collected, we have developed a dynamic model for reaching that generates naturally curved human movements.

Related Software

We have developed a very user-friendly software that synchronises the neuropsychological experiment's task instructions and stimuli presentation with the recording of data from Xsens motion sensors and 5Dt data gloves. The software also walks the user through a calibration procedure. If you are interested in this software, shown below, please contact Biljana Petreska.

Interface of the software developed for conducting the experiment and recording data from motion sensors and data gloves.