Skip to main content
  • Poster presentation
  • Open access
  • Published:

Neurocomputational modeling of imitation deficits

Introduction

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.

References

  1. Petreska B, Adriani M, Blanke O, Billard AG: Apraxia. A review. From Action to Cognition. Progress in Brain Research. Edited by: von Hofsten C. 2007, 164: 61-83.

    Chapter  Google Scholar 

  2. Goldenberg G, Laimgruber K, Hermsdörfer J: Imitation of gestures by disconnected hemispheres. Neuropsychologia. 2001, 39: 1432-1443.

    Article  CAS  PubMed  Google Scholar 

  3. Petreska B, Billard AG: A neurocomputational model of an imitation deficit following brain lesion. Proceedings of 16th International Conference on Artificial Neural Networks (ICANN06) LNCS. 2006, 4131: 770-779.

    Google Scholar 

  4. Decety J, Grèzes J, Costes N, Perani D, Procyk E, Grassi F, Jeannerod M, Fazio F: Brain activity during observation of actions: influence of action content and subject's strategy. Brain. 1997, 120: 1763-1777.

    Article  PubMed  Google Scholar 

  5. Mühlau M, Hermsdörfer J, Goldenberg G, Wohlschläger AM, Castrop F, Stahl R, Röttinger M, Erhard P, Haslinger B, Ceballos-Baumanna AO, et al: Left inferior parietal dominance in gesture imitation: an fMRI study. Neuropsychologia. 2005, 43: 1086-98.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work has been supported by the Sport and Rehabilitation Engineering Program EPFL.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Biljana Petreska.

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Petreska, B., Billard, A.G. Neurocomputational modeling of imitation deficits. BMC Neurosci 9 (Suppl 1), P76 (2008). https://doi.org/10.1186/1471-2202-9-S1-P76

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/1471-2202-9-S1-P76

Keywords