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Visuomotor learning in immersive 3D virtual reality in Parkinson’s disease and in aging

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Abstract

Successful adaptation to novel sensorimotor contexts critically depends on efficient sensory processing and integration mechanisms, particularly those required to combine visual and proprioceptive inputs. If the basal ganglia are a critical part of specialized circuits that adapt motor behavior to new sensorimotor contexts, then patients who are suffering from basal ganglia dysfunction, as in Parkinson’s disease should show sensorimotor learning impairments. However, this issue has been under-explored. We tested the ability of 8 patients with Parkinson’s disease (PD), off medication, ten healthy elderly subjects and ten healthy young adults to reach to a remembered 3D location presented in an immersive virtual environment. A multi-phase learning paradigm was used having four conditions: baseline, initial learning, reversal learning and aftereffect. In initial learning, the computer altered the position of a simulated arm endpoint used for movement feedback by shifting its apparent location diagonally, requiring thereby both horizontal and vertical compensations. This visual distortion forced subjects to learn new coordinations between what they saw in the virtual environment and the actual position of their limbs, which they had to derive from proprioceptive information (or efference copy). In reversal learning, the sign of the distortion was reversed. Both elderly subjects and PD patients showed learning phase-dependent difficulties. First, elderly controls were slower than young subjects when learning both dimensions of the initial biaxial discordance. However, their performance improved during reversal learning and as a result elderly and young controls showed similar adaptation rates during reversal learning. Second, in striking contrast to healthy elderly subjects, PD patients were more profoundly impaired during the reversal phase of learning. PD patients were able to learn the initial biaxial discordance but were on average slower than age-matched controls in adapting to the horizontal component of the biaxial discordance. More importantly, when the biaxial discordance was reversed, PD patients were unable to make appropriate movement corrections. Therefore, they showed significantly degraded learning indices relative to age-matched controls for both dimensions of the biaxial discordance. Together, these results suggest that the ability to adapt to a sudden biaxial visuomotor discordance applied in three-dimensional space declines in normal aging and Parkinson disease. Furthermore, the presence of learning rate differences in the PD patients relative to age-matched controls supports an important contribution of basal ganglia-related circuits in learning novel visuomotor coordinations, particularly those in which subjects must learn to adapt to sensorimotor contingencies that were reversed from those just learned.

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Notes

  1. An eleventh elderly subject was run, but his data were excluded since analysis revealed that his spatial errors fell well outside those of all other elderly control subjects; they were greater than two standard deviations from the mean

  2. The number of trials tested is different for the initial learning (20 trials) and the reversal learning phases (15 trials). To compare more directly performance indices between the two learning phases, we also performed statistical analyses on the learning phases using only the first 15 trials. For instance, we evaluated the variability indexes and the adaptation magnitude scores on trials 10–15 of initial learning as was done for reversal learning. Similar results were obtained as when using all 20 trials of initial learning. The adaptation score for the horizontal component of the initial biaxial discordance was similar in all three subject groups (F (2,25) = 0.285; P > 0.05) as was the level of trial-to-trial variability (F (2,25) = 0.012; P > 0.05). Also, there was a significant between group difference in the adaptation magnitude score for the vertical component of the initial discordance (F (2,25) = 8.49; P < 0.05). Young and elderly controls showed a similar level of adaptation (P > 0.05), while PD patients showed significantly smaller adaptation magnitude score (P < 0.025). In a similar manner, we performed the ANOVAs on constant errors for trials 1–15 of initial learning. Again, these analyses confirmed results found when trials 1–20 were analyzed

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Acknowledgments

This research was supported in part by an FRSQ and CIHR Postdoctoral Fellowship to JM and by NIH Grant 7 R01 NS36449 to UCSD (HP).

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Authors and Affiliations

  1. Département de kinésiolgie, Université de Montréal, 2100, boul. Édouard-Montpetit, bureau 8225, H3T 1J4, Montreal, QC, Canada

    Julie Messier

  2. Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA

    David Jack

  3. Institute for Neural Computation, University of California, San Diego, CA, USA

    Howard Poizner

  4. Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA

    Sergei Adamovich

  5. Department of Neurology, UMDNJ/Robert Wood Johnson Medical School, Piscataway, NJ, USA

    Wayne Hening & Jacob Sage

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  1. Julie Messier
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  2. Sergei Adamovich
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  3. David Jack
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  4. Wayne Hening
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  5. Jacob Sage
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  6. Howard Poizner
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Correspondence to Julie Messier.

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Messier, J., Adamovich, S., Jack, D. et al. Visuomotor learning in immersive 3D virtual reality in Parkinson’s disease and in aging. Exp Brain Res 179, 457–474 (2007). https://doi.org/10.1007/s00221-006-0802-2

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