Advertisement

Brain Imaging and Behavior

, Volume 12, Issue 5, pp 1363–1378 | Cite as

Action, observation or imitation of virtual hand movement affect differently regions of the mirror neuron system and the default mode network

  • Nabila BrihmatEmail author
  • Mohamed Tarri
  • Yann Quidé
  • Ketty Anglio
  • Bernard Pavard
  • Evelyne Castel-Lacanal
  • David Gasq
  • Xavier De Boissezon
  • Philippe Marque
  • Isabelle Loubinoux
Original Research
  • 438 Downloads

Abstract

Virtual reality (VR)-based paradigms use visual stimuli that can modulate visuo-motor networks leading to the stimulation of brain circuits. The aims of this study were to compare the changes in blood-oxygenation level dependent (BOLD) signal when watching and imitating moving real (RH) and virtual hands (VH) in 11 healthy participants (HP). No differences were found between the observation of RH or VH making this VR-based experiment a promising tool for rehabilitation protocols. VH-imitation involved more the ventral premotor cortex (vPMC) as part of the mirror neuron system (MNS) compared to execution and VH-observation conditions. The dorsal-anterior Precuneus (da-Pcu) as part of the Precuneus/posterior Cingulate Cortex (Pcu/pCC) complex, a key node of the Default Mode Network (DMN), was also less deactivated and therefore more involved. These results may reflect the dual visuo-motor roles for the vPMC and the implication of the da-Pcu in the reallocation of attentional and neural resources for bimodal task management. The ventral Pcu/pCC was deactivated regardless of the condition confirming its role in self-reference processes. Imitation of VH stimuli can then modulate the activation of specific areas including those belonging to the MNS and the DMN.

Keywords

Mirror Neuron System Precuneus/posterior Cingulate Cortex complex Imitation Virtual Reality Functional magnetic resonance imaging Healthy Participants 

Abbreviations

VR

Virtual Reality

VE

Virtual environment

VH

Virtual Hand

RH

Real Hand

HP

Healthy participants

fMRI

Functional magnetic resonance imaging

BOLD

Blood oxygenation level dependent

MNS

Mirror neuron system

DMN

Default mode network

AON

Action observation network

PET

Positron emission tomography

S1M1

Sensorimotor cortex

SMA

Supplementary motor area

PMC

Premotor cortex

dPMC

Dorsal premotor cortex

vPMC

Ventral premotor cortex

SPL

Superior parietal lobule

IPL

Inferior parietal lobule

EBA

Extrastriate body area

FFA

Fusiform face area

ANOVA

Analysis of variance

PCU

Precuneus

da-Pcu

Dorsal anterior precuneus

BA7m

Medial part of Brodman area 7

Pcu/pCC complex

Precuneus / posterior cingulate cortex complex

midCC

Midcingulate cortex

EXE

Execution of a wrist extension movement

OBS

Observation of a virtual (OBS-VH) or a real hand (OBS-RH) movement

IMI

Imitation of a virtual wrist extension movement

Notes

Acknowledgements

The authors thank all the volunteers for their participation in the study, the IRIT for their help in designing the protocol, Alice Lefriec for English editing and finally Thomas Nichols for his help and valuable advices on using the SnPM toolbox. We would like to acknowledge that one of the authors, Yann Quide is now affiliated to the School of Psychiatry, University of New South Wales, Randwick, NSW, Australia and the Neuroscience Research Australia, Randwick, NSW, Australia.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Compliance with Ethical Standards

Conflict of interest

All the authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in this study.

References

  1. Adamovich, S. V., August, K., Merians, A., & Tunik, E. (2009). A virtual reality-based system integrated with fmri to study neural mechanisms of action observation-execution: a proof of concept study. Restorative Neurology and Neuroscience, 27(3), 209–223.  https://doi.org/10.3233/RNN-2009-0471.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Addis, D. R., Wong, A. T., & Schacter, D. L. (2007). Remembering the past and imagining the future: common and distinct neural substrates during event construction and elaboration. Neuropsychologia, 45(7), 13631377.  https://doi.org/10.1016/j.neuropsychologia.2006.10.016.
  3. August, K., Lewis, J. A., Chandar, G., Biswal, B., & Adamovich, S. (2006). Fmri Analysis of Neural Mechanisms Underlying Rehabilitation in Virtual Reality: Activating Secondary Motor Areas, pp. 3692–3695.Google Scholar
  4. Bagce, H. F., Saleh, S., Adamovich, S. V., & Tunik, E. (2012). Visuomotor gain distortion alters online motor performance and enhances primary motor cortex excitability in patients with stroke. Neuromodulation : Journal of the International Neuromodulation Society, 15(4), 361–366.  https://doi.org/10.1111/j.1525-1403.2012.00467.x.
  5. Baque, E., Sakzewski, L., Barber, L., & Boyd, R. N. (2016). Systematic review of physiotherapy interventions to improve gross motor capacity and performance in children and adolescents with an acquired brain injury. Brain Injury, 30(8), 948–959.  https://doi.org/10.3109/02699052.2016.1147079.CrossRefPubMedGoogle Scholar
  6. Bekrater-Bodmann, R., Foell, J., & Kamping, S. (2011). The importance of ventral premotor cortex for body ownership processing. Journal of Neuroscience, 31(26), 9443–9444.  https://doi.org/10.1523/JNEUROSCI.2302-11.2011.CrossRefPubMedGoogle Scholar
  7. Binkofski, F., & Buccino, G. (2006). The role of ventral premotor cortex in action execution and action understanding. Journal of Physiology Paris, 99(4–6), 396–405.  https://doi.org/10.1016/j.jphysparis.2006.03.005.CrossRefGoogle Scholar
  8. Buccino, G. (2014). Action observation treatment: a novel tool in neurorehabilitation. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1644), 20130185–20130185.  https://doi.org/10.1098/rstb.2013.0185.CrossRefGoogle Scholar
  9. Buccino, G., Binkofski, F., Fink, G. R., Fadiga, L., Fogassi, L., Gallese, V., Seitz, R. J., Zilles, K., Rizzolatt, G., & Freund, H. J. (2001). European Journal of Neurosciences, 13, 400–404.Google Scholar
  10. Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124(1), 1–38.  https://doi.org/10.1196/annals.1440.011.CrossRefPubMedGoogle Scholar
  11. Buckner, R. L., & Carroll, D. C. (2007). Self-projection and the brain. Trends in Cognitive Sciences, 11(2), 49–57.  https://doi.org/10.1016/j.tics.2006.11.004.CrossRefPubMedGoogle Scholar
  12. Caspers, S., Zilles, K., Laird, A. R., & Eickhoff, S. B. (2010). NeuroImage ALE meta-analysis of action observation and imitation in the human brain. NeuroImage, 50(3), 1148–1167.  https://doi.org/10.1016/j.neuroimage.2009.12.112.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Cauda, F., Geminiani, G., D’Agata, F., Sacco, K., Duca, S., Bagshaw, A. P., & Cavanna, A. E. (2010). Functional connectivity of the posteromedial cortex. PLoS ONE, 5(9), 1–11.  https://doi.org/10.1371/journal.pone.0013107.CrossRefGoogle Scholar
  14. Cavanna, A. E. (2006). The precuneus: a review of its functional anatomy and behavioural correlates. Brain, 129(3), 564–583.  https://doi.org/10.1093/brain/awl004.CrossRefPubMedGoogle Scholar
  15. Chiang, T.-C., Liang, K.-C., Chen, J.-H., Hsieh, C.-H., & Huang, Y.-A. (2013). Brain deactivation in the outperformance in bimodal tasks: an fMRI study. PLoS ONE, 8(10), e77408.  https://doi.org/10.1371/journal.pone.0077408.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Clark, I., & Dumas, G. (2015). Toward a neural basis for peer-interaction: What makes peer-learning tick? Frontiers in Psychology, 6(28), 1–12.  https://doi.org/10.3389/fpsyg.2015.00028.CrossRefGoogle Scholar
  17. Davare, M. (2006). Dissociating the role of ventral and dorsal premotor cortex in precision grasping. Journal of Neuroscience, 26(8), 2260–2268.  https://doi.org/10.1523/JNEUROSCI.3386-05.2006.CrossRefPubMedGoogle Scholar
  18. Dayan, E., Sella, I., Mukovskiy, A., Douek, Y., Giese, M. A., Malach, R., & Flash, T. (2016). The default mode network differentiates biological from non-biological motion. Cerebral Cortex, 26(1), 234–245.  https://doi.org/10.1093/cercor/bhu199.CrossRefPubMedGoogle Scholar
  19. Dehaene, S., & Changeux, J.-P. (2011). Experimental and theoretical approaches to conscious processing. Neuron, 70(2), 200–227.  https://doi.org/10.1016/j.neuron.2011.03.018.CrossRefPubMedGoogle Scholar
  20. Dien, J. (2009). A tale of two recognition systems: Implications of the fusiform face area and the visual word form area for lateralized object recognition models. Neuropsychologia, 47(1), 1–16.  https://doi.org/10.1016/j.neuropsychologia.2008.08.024.CrossRefPubMedGoogle Scholar
  21. Dushanova, J., & Donoghue, J. (2010). Neurons in primary motor cortex engaged during action observation. European Journal of Neuroscience, 31(2), 386–398.  https://doi.org/10.1111/j.1460-9568.2009.07067.x.CrossRefPubMedGoogle Scholar
  22. Enzinger, C., Dawes, H., Johansen-Berg, H., Wade, D., Bogdanovic, M., Collett, J., Guy, C., Udo, K., Ropele, S., Fazekas, F., & Matthews, P. M. (2009). Brain activity changes associated with treadmill training: after stroke. Stroke, 40(7), 2460–2467.  https://doi.org/10.1161/STROKEAHA.109.550053.CrossRefPubMedGoogle Scholar
  23. Fabbri-Destro, M., & Rizzolatti, G. (2008). Mirror neurons and mirror systems in monkeys and humans. Physiology (Bethesda, Md.), 23(38), 171–179.  https://doi.org/10.1152/physiol.00004.2008.CrossRefGoogle Scholar
  24. Fadiga, L., Fogassi, L., Pavesi, G., Rizzolatti, G., & Neurologica, C. (1995). Motor facilitation during action observation: a magnetic stimulation study. Neurophysiology, 73(6).Google Scholar
  25. Ferraina, S., Johnson, P. B., Garasto, M. R., Battaglia-Mayer, a, Ercolani, L., Bianchi, L., Lacquaniti, L., & Caminiti, R. (1997). Combination of hand and gaze signals during reaching: activity in parietal area 7 m of the monkey. Journal of Neurophysiology, 77(2), 1034–1038.CrossRefGoogle Scholar
  26. Fransson, P., & Marrelec, G. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: evidence from a partial correlation network analysis. NeuroImage, 42(3), 1178–1184.  https://doi.org/10.1016/j.neuroimage.2008.05.059.CrossRefPubMedGoogle Scholar
  27. Gallese, V., Fadiga, L., Fogassi, L., & Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119(2), 593–609.  https://doi.org/10.1093/brain/119.2.593.CrossRefPubMedGoogle Scholar
  28. Gatica-Rojas, V., & Méndez-Rebolledo, G. (2014). Virtual reality interface devices in the reorganization of neural networks in the brain of patients with neurological diseases. Neural Regeneration Research, 9(8), 888–896.  https://doi.org/10.4103/1673-5374.131612.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Jeannerod, M. (1994). The representing brain: Neural correlates of motor intention and imagery. Behavioral and Brain Sciences, 17(2), 187.  https://doi.org/10.1017/S0140525X00034026.CrossRefGoogle Scholar
  30. Jeannerod, M. (2001). Neural simulation of action: a unifying mechanism for motor cognition. NeuroImage, 14(1), S103–S109.  https://doi.org/10.1006/nimg.2001.0832.CrossRefPubMedGoogle Scholar
  31. Leech, R., & Sharp, D. J. (2014). The role of the posterior cingulate cortex in cognition and disease. Brain, 137(1), 12–32.  https://doi.org/10.1093/brain/awt162.CrossRefPubMedGoogle Scholar
  32. Mager, R., Stefani, O., Angehrn, I., Mueller-Spahn, F., Bekiaris, E., Wiederhold, B. K., Sulzenbacher, H., & Bullinger, A. H. (2005). Neurophysiological age differences during task-performance in a stereoscopic virtual environment. Applied Psychophysiology Biofeedback, 30(3), 233–238.  https://doi.org/10.1007/s10484-005-6380-4.CrossRefPubMedGoogle Scholar
  33. Modroño, C., Navarrete, G., Rodríguez-Hernández, A. F., & González-Mora, J. L. (2013). Activation of the human mirror neuron system during the observation of the manipulation of virtual tools in the absence of a visible effector limb. Neuroscience Letters, 555, 220–224.  https://doi.org/10.1016/j.neulet.2013.09.044.CrossRefPubMedGoogle Scholar
  34. Molnar-Szakacs, I., & Uddin, L. Q. (2013). Self-processing and the default mode network: interactions with the mirror neuron system. Frontiers in Human Neuroscience, 7, 571.  https://doi.org/10.3389/fnhum.2013.00571.
  35. Mueller, C., Luehrs, M., Baecke, S., Adolf, D., Luetzkendorf, R., Luchtmann, M., & Bernarding, J. (2012). Building virtual reality fMRI paradigms : A framework for presenting immersive virtual environments. Journal of Neuroscience Methods, 209(2), 290–298.  https://doi.org/10.1016/j.jneumeth.2012.06.025.CrossRefPubMedGoogle Scholar
  36. Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46–59.  https://doi.org/10.1002/hbm.20131.CrossRefPubMedGoogle Scholar
  37. Parvizi, J., Van Hoesen, G. W., Buckwalter, J., & Damasio, A. (2006). Neural connections of the posteromedial cortex in the macaque. Proceedings of the National Academy of Sciences of the United States of America, 103(5), 1563–8.  https://doi.org/10.1073/pnas.0507729103.CrossRefPubMedPubMedCentralGoogle Scholar
  38. Perani, D., Fazio, F., Borghese, N. A., Tettamanti, M., Ferrari, S., Decety, J., & Gilardi, M. C. (2001). Different brain correlates for watching real and virtual hand actions. NeuroImage, 14(3), 749–58.  https://doi.org/10.1006/nimg.2001.0872.CrossRefPubMedGoogle Scholar
  39. Plata Bello, J., Modroño, C., Marcano, F., & González-Mora, J. L. (2015). Mapping the mirror neuron system in neurosurgery. World Neurosurgery, 84(6), 2077.e5–2077.e10.  https://doi.org/10.1016/j.wneu.2015.07.059.CrossRefGoogle Scholar
  40. Proffitt, R., Lange, B., Chen, C., & Winstein, C. (2015). A comparison of older adults’ subjective experience with virtual and real environments during dynamic balance activities. Journal of Aging and Physical Activity, 23(1), 24–33.  https://doi.org/10.1123/japa.2013-0126.CrossRefPubMedGoogle Scholar
  41. Riva, G., Castelnuovo, G., & Mantovani, F. (2006). Transformation of flow in rehabilitation: the role of advanced communication technologies. Behavior Research Methods, 38(2), 237–244.  https://doi.org/10.3758/BF03192775.CrossRefPubMedGoogle Scholar
  42. Rizzolatti, G., & Craighero, L. (2004). the Mirror-Neuron System. Annual Review of Neuroscience, 27(1), 169–192.  https://doi.org/10.1146/annurev.neuro.27.070203.144230.CrossRefPubMedGoogle Scholar
  43. Sajonz, B., Kahnt, T., Margulies, D. S., Park, S. Q., Wittmann, A., Stoy, M., Ströhle, A., Heinz, A., Northoff, G., & Bermpohl, F. (2010). Delineating self-referential processing from episodic memory retrieval: Common and dissociable networks. NeuroImage, 50(4), 1606–1617.  https://doi.org/10.1016/j.neuroimage.2010.01.087.CrossRefPubMedGoogle Scholar
  44. Salomon, R., Levy, D. R., & Malach, R. (2014). Deconstructing the default: cortical subdivision of the default mode/intrinsic system during self-related processing. Human Brain Mapping, 35(4), 1491–1502.  https://doi.org/10.1002/hbm.22268.CrossRefPubMedGoogle Scholar
  45. Schubotz, R. I., & von Cramon, D. Y. (2001). Functional organization of the lateral premotor cortex: fMRI reveals different regions activated by anticipation of object properties, location and speed. Cognitive Brain Research, 11, 97–112.CrossRefGoogle Scholar
  46. Sgandurra, G., Ferrari, A., Cossu, G., Guzzetta, A., Biagi, L., Tosetti, M., Fogassi, L., & Cioni, G. (2011). Upper limb children action-observation training (UP-CAT): a randomised controlled trial in hemiplegic cerebral palsy. BMC Neurology, 11(1), 80.  https://doi.org/10.1186/1471-2377-11-80.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Spreng, R. N., & Grady, C. L. (2010). Patterns of brain activity supporting autobiographical memory, prospection, and theory of mind, and their relationship to the default mode network. Journal of Cognitive Neuroscience, 22, 1112–1123.  https://doi.org/10.1162/jocn.2009.21282.CrossRefPubMedGoogle Scholar
  48. Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2008). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis. Journal of Cognitive Neuroscience, 21(3), 489–510.  https://doi.org/10.1162/jocn.2008.21029.CrossRefGoogle Scholar
  49. Taillade, M., N’Kaoua, B., & Sauzéon, H. (2016). Age-related differences and cognitive correlates of self-reported and direct navigation performance: the effect of real and virtual test conditions manipulation. Frontiers in Psychology, 6(2034), 1–12.  https://doi.org/10.3389/fpsyg.2015.02034.CrossRefGoogle Scholar
  50. Takeuchi, H., Taki, Y., Nouchi, R., Sekiguchi, A., Hashizume, H., Sassa, Y., Kotozaki, Y., Miyauchi, C. M., Yokoyama, R., Iizuka, K., Nakagawa, S., Nagasa, T., Kunitoki, K., & Kawashima, R. (2014). Association between resting-state functional connectivity and empathizing/systemizing. NeuroImage, 99, 312–322.  https://doi.org/10.1016/j.neuroimage.2014.05.031.CrossRefPubMedGoogle Scholar
  51. Tomassini, V., Jbabdi, S., Klein, J. C., Behrens, T. E. J., Pozzilli, C., Matthews, P. M., Rushworth, M. F. S., & Johansen-Berg, H. (2007). Diffusion-weighted imaging tractography-based parcellation of the human lateral premotor cortex identifies dorsal and ventral subregions with anatomical and functional specializations. Journal of Neuroscience, 27(38), 10259–10269.  https://doi.org/10.1523/JNEUROSCI.2144-07.2007.CrossRefPubMedGoogle Scholar
  52. Treserras, S., Boulanouar, K., Conchou, F., Simonetta-Moreau, M., Berry, I., Celsis, P., Chollet, F., & Loubinoux, I. (2009). Transition from rest to movement: brain correlates revealed by functional connectivity. NeuroImage, 48(1), 207–216.  https://doi.org/10.1016/j.neuroimage.2009.06.016.CrossRefPubMedGoogle Scholar
  53. Uddin, L. Q., Kaplan, J. T., Molnar-Szakacs, I., Zaidel, E., & Iacoboni, M. (2005). Self-face recognition activates a frontoparietal “mirror” network in the right hemisphere: an event-related fMRI study. NeuroImage, 25(3), 926–935.  https://doi.org/10.1016/j.neuroimage.2004.12.018.CrossRefPubMedGoogle Scholar
  54. Wiener, J., Kmecova, H., & de Condappa, O. (2012). Route repetition and route retracing: Effects of cognitive aging. Frontiers in Aging Neuroscience, 4(7), 1–7.  https://doi.org/10.3389/fnagi.2012.00007.CrossRefGoogle Scholar
  55. Willems, R. M., Peelen, M. V., & Hagoort, P. (2010). Cerebral lateralization of face-selective and body-selective visual areas depends on handedness. Cerebral Cortex, 20(7), 1719–1725.  https://doi.org/10.1093/cercor/bhp234.CrossRefPubMedGoogle Scholar
  56. Wise, S. P., Moody, S. L., Blomstrom, K. J., & Mitz, A. R. (1998). Changes in motor cortical activity during visuomotor adaptation. Experimental Brain Research, 121(3), 285–299.  https://doi.org/10.1007/s002210050462.CrossRefPubMedGoogle Scholar
  57. Xiao, X., Lin, Q., Lo, W. L., Mao, Y. R., Shi, X. C., Cates, R. S., Zhou, S. F., Huang, D. F., & Li, L. (2017). Cerebral reorganization in subacute stroke survivors after virtual reality-based training: a preliminary study. Behavioural Neurology. 2017.  https://doi.org/10.1155/2017/6261479.
  58. Yeshurun, Y., Swanson, S., Simony, E., Chen, J., Lazaridi, C., Honey, C. J., & Hasson, U. (2017). Same story, different story. Psychological Science, 28(3), 307–319.  https://doi.org/10.1177/0956797616682029.CrossRefPubMedPubMedCentralGoogle Scholar
  59. Zeller, D., Gross, C., Bartsch, A., Johansen-Berg, H., & Classen, J. (2011). Ventral premotor cortex may be required for dynamic changes in the feeling of limb ownership: a lesion study. Journal of Neuroscience, 31(13), 4852–4857.  https://doi.org/10.1523/JNEUROSCI.5154-0.2011.CrossRefPubMedGoogle Scholar
  60. Zhang, K., Wang, H., Dong, G., Wang, M., Zhang, J., Zhang, H., Meng, W., & Du, X. (2016). Neural activation during imitation with or without performance feedback: an fMRI study. Neuroscience Letters, 629, 202–207.  https://doi.org/10.1016/j.neulet.2016.07.015.CrossRefPubMedGoogle Scholar
  61. Zhang, S., & Li, C. R. (2012). Functional connectivity mapping of the human precuneus by resting state fMRI. Neuroimage, 59(4), 3548–3562.  https://doi.org/10.1016/j.neuroimage.2011.11.023.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017
corrected publication December/2017

Authors and Affiliations

  • Nabila Brihmat
    • 1
    Email author
  • Mohamed Tarri
    • 1
  • Yann Quidé
    • 1
  • Ketty Anglio
    • 2
  • Bernard Pavard
    • 3
  • Evelyne Castel-Lacanal
    • 1
    • 2
  • David Gasq
    • 1
    • 2
  • Xavier De Boissezon
    • 1
    • 2
  • Philippe Marque
    • 1
    • 2
  • Isabelle Loubinoux
    • 1
  1. 1.ToNIC, Toulouse NeuroImaging CenterUniversité de Toulouse, Inserm, UPSToulouseFrance
  2. 2.Department of Rehabilitation and Physical Medicine, Pôle NeurosciencesCentre Hospitalier Universitaire de Toulouse CHUToulouseFrance
  3. 3.Informatic Research Institute of Toulouse, IRITUniversité de Toulouse, CNRS, UPSToulouseFrance

Personalised recommendations