Motor Imagery May Incorporate Trial-to-Trial Error

ABSTRACT

The authors tested for 1/f noise in motor imagery (MI). Participants pointed and imagined pointing to a single target (Experiment 1), to targets of varied size (Experiment 2), and switched between pointing and grasping (Experiment 3). Experiment 1 showed comparable patterns of serial correlation in actual and imagined movement. Experiment 2 suggested increased correlation for MI and performance with increased task difficulty, perhaps reflecting adaptation to a more complex environment. Experiment 3 suggested a parallel decrease in correlation with task switching, perhaps reflecting discontinuity of mental set. Although present results do not conclusively reveal 1/f fluctuation, the emergent patterns suggest that MI could incorporate trial-to-trial error across a range of constraints.

Keywords:

• 1/f noise
• ARFIMA
• fractal
• motor imagery
• simulation

Notes

^aDifferent from 0.50, or white noise.

^bWithin the range of 1/f noise, where d was different from 0.

^cARFIMA model preferred for only 1 time series.

^aARFIMA model preferred for only 1 time series.

^aDifferent from 0.50, or white noise.

^bWithin the range of 1/f noise, where d was different from 0.

^cARFIMA model preferred for only 1 time series.

^aARFIMA model preferred for only 1 time series.

^aDifferent from 0.50, or white noise.

^bWithin the range of 1/f noise, where d was different from 0.

^cARFIMA model preferred for only 1 time series.

^aARFIMA model preferred for only 1 time series.

1. Others, however, have suggested that an extension of Vorberg and Wing's (1996) linear phase correction model may explain the increased correlation in syncopated tapping (see Delignieres, Torre, & Lemoine, 2009).

2. A lack of differences in variability further supports the notion of functional equivalence between MI and performance, verifying that (similar to MT) overall timing variation in MI and performance is comparable and that changes in correlation are less likely the result of fundamental differences in timing error.

3. It is important to note that this threshold is a recommendation and depends on the criterion used (e.g., the suggested threshold is 70% using Akaike's [1973] information criterion). Nonetheless, some have suggested that BIC provides better estimates in ARFIMA modeling (Torre et al., 2007).

4. We acknowledge the possibility that practice in each experiment may have served as a type of training, perhaps affecting both MI and performance. We also note, however, the likelihood that prior to the present study, participants would have already acquired significant experience in simulating and performing such everyday tasks (i.e., pointing and grasping).