Automatic Imitation in Rhythmical Actions Figure 2. Sequence of events in the automatic imitation experiment. (A) A green circle appeared when participants placed their fingers in the start location. (B) Then a picture of the to-be-pantomimed (imperative) action was shown, followed by (C) a distractor movie of the model pantomiming either the same or a different action. (D) In blocks with delayed execution, a red circle was shown for either 4 or 8 s. (E) Execution of the imperative action was cued by display of a neutral, light-grey background, which appeared at the offset of either the distractor movie or the red circle. doi:10.1371/journal.pone.0046728.g002 6. Data Analysis Mean cycle times (ms) were calculated between peak maximum kinematic positions using a customised signal processing tool within Matlab (Mathworks, Inc., Natick, MA). For both horizontal and vertical actions, the first data point taken was the peak maximum of the second movement cycle. The first cycle was not used as this additionally reflected the spatial positioning of the hand before a stable workspace was reached. Mean cycle time was calculated across all peak positions available within a 2000 ms time window across all speed conditions. This involved either two or three cycles for habitually slow actions and four or five cycles for habitually fast actions. All trials with erroneous responses (incorrect or no action) were discarded (n = 41). The two main dependent measures were the mean cycle time (ms) and the ratio (%) between slow and fast distractor trials. While the absolute difference between distractor cycle times was greater in the habitually slow actions (667 vs. 1000 ms) compared to the habitually fast actions (333 vs. 500 ms), the ratio of slow:fast distractor speeds was the same for each habitual speed (150%). For economy of exposition, we therefore restricted the analysis of the mean cycle time data to three factors of interest, and analysed the additional effects of delay and of the compatibility manipulations only for the cycle time ratios. Accordingly, the mean cycle times (ms) were analysed via a three-factorial, mixed-measures ANOVA with the two within- subjects factors distractor speed (only available for this measure) and habitual speed, and with the availability of vision as the between-subjects factor. The cycle time ratios (%) were subjected to a five-factorial mixed-measures ANOVA, with habitual speed, action type compatibility, plane compatibility, and delay as the within-subjects factors, and the availability of vision as the between-subjects factor. Subsequently, both dependent measures were analysed for the intentional imitation experiment. Finally, we contrasted automatic and intentional imitation using a five-factorial ANOVA on the cycle time ratios only, again for economy of exposition. All analyses were conducted using SPSS Statistics 19 (IBM). Where appropriate, these were adjusted for any violation of the homogeneity of variance assumption using the Greenhouse–Geisser correction. Alpha levels were set to 0.05, and effect sizes were calculated as partial eta squared values (gp2). Reaction time data were also recorded on each trial as the time taken from response-cue onset to movement onset. These data were analysed, but the effects obtained were either trivial or unpredicted, and they did not directly address the aims of this paper. Therefore, these results are not reported here. However, RTs were used to identify trials with anticipatory (,200 ms; n = 14) or omission errors (.1300 ms; n = 68), which were discarded from all analyses. In total, 2.4% of all trials recorded were removed from the analyses. PLOS ONE | www.plosone.org 5 October 2012 | Volume 7 | Issue 10 | e46728