Behavioural data analysis

Metrics for learning

We have previously shown that such opposing force fields can be learned concurrently if each is associated with a different motor plan (see Chapter 2, Sheahan et al. (2016)). Therefore, concurrent adaptation can serve as an indicator of motor planning. That is, if participants adapt to two opposing force fields concurrently, we can infer that each movement is executed under a distinct motor plan, that is, movements are planned as cohesive follow-throughs.

Conversely, elemental motor planning will cause each movement to the central target to be executed under the same plan for both opposing fields, and will therefore result in full interference.

Two metrics were used to evaluate learning from exposure to force fields. We analysed MPE on movements originating from all starting locations and adaptation on channel trials originating from just the 0^◦starting location. We evaluated adaptation only on movements that were associated with force field perturbations. These metrics were obtained using the same analysis methods as described in Chapter 2. We averaged MPE for each subject over 8 consecutive field trials, and adaptation corresponding to the same epoch, measured only on the channel trials which were nominally associated with a force field. Learning within a group was assessed using a within-subjects repeated-measures ANOVA with a fixed effect of epoch, to compare adaptation between the average of the pre-exposure blocks and adaptation corresponding to the final 48 exposure trials (approximately 6 blocks). Similarly, we also assessed the aftereffects, calculated as the difference in MPE between the average of the pre-exposure blocks and the first two blocks of post-exposure.

To compare learning between groups, we performed a mixed-effects ANOVA on the adapta-tion data, as assessed on just those trials which were nominally associated with a force field, and using a fixed effect of epoch (same two epochs of trials, pre-exposure vs late exposure), a fixed effect of group, and a random effect of participants, as in Chapters 2 and 3. We explored differences between groups post-hoc using reduced mixed-effects ANOVAs of a similar structure but with pairs of groups.

Central target dwell times

A measure of chunking which is common in the literature is the time between the end of one movement and the start of the next in a motor sequence (Rosenbaum et al., 1983; Sakai et al., 2003; Verwey, 1996; Verwey and Dronkert, 1996; Wymbs et al., 2012). That is longer dwell times are associated with movements which form part of separate chunks and shorter dwell times for movements which are part of the same chunk. Motor chunking was therefore assessed using the time between successive movements within a trial. For each participant this was calculated as the time between entering and leaving the central target on follow-through movements which were not artificially constrained by channel trials. We call this the dwell time, and calculated it using follow-through null trials in the final 40 trials of the pre-exposure phase (corresponding to approximately 4 blocks) to assess chunking under null field dynamics for each trial set. We performed a one-way ANOVA on these pre-exposure phase dwell times, using a fixed effect of group and a random effect of participant, to compare our model predictions of chunking against baseline behavioural differences between groups.

We subsequently evaluated how chunking of follow-through movements changed across the experiment for the four groups by performing a mixed-effects ANOVA of dwell-times as the response variable, using a within-subjects fixed effect of epoch (three levels: pre-exposure trials, the first 40 trials during the exposure phase and the final 40 trials during the exposure phase), a between-subjects fixed effect of group (4 levels, one for each group) and a random effect of participant. Within-subjects differences were explored post-hoc across groups with reduced mixed-effects ANOVAs of similar structure but with two levels of epoch.

Movement initiation times

As response times have been shown to scale with navigational plan complexity (Balaguer et al., 2016), and the depth of planning shown to reduce when response times are restricted (Keramati et al., 2016), we additionally used movement initiation times as a measure of

planning complexity. This was assessed from the go cue to the time the hand exited the start position.

We first assessed how baseline movement initiation times differed across the groups using a one-way ANOVA, with a between-subjects fixed effect of group and a random effect of participants, as for dwell-times. We subsequently assessed how movement initiation times changed across the experiment for the different groups with a mixed-effects ANOVA, using a fixed effect of group, a fixed effect of epoch (using the same three trial epochs as for the dwell time assessments) and a random effect of participants. In our experiments, the same movements are repeated hundreds of times and so response (movement initiation) times may decrease with learning, or may become at least partly habitual (Haith and Krakauer, 2018;

Hardwick et al., 2017b). To separate generic decreases in response time from changes in chunking behaviour across the experiment, we evaluated the difference between response times on central target-only trials (which can only be planned as a single movement), and response times on follow-through trials (which may be planned as far as the central target, when planned elementally, or as a full follow-through movements requiring more planning depth). We assessed how these differences in movement initiation times for different trials changed across the experiment with a similarly structured mixed-effects ANOVA, again with a fixed effect of epoch with three levels consisting of the same three epochs as previously (pre-exposure, early exposure and late exposure), a random effect of participants and a fixed effect of group, this time with only the three groups that performed both follow-through and centre-only movements (Groups 2, 3 and 4).

Correlations in chunking when dynamics changed

We subsequently evaluated whether pre-exposure null field chunking scaffolded chunking in curl fields by assessing the correlation between the participants’ mean dwell times in the pre-exposure (final 40 trials) and early exposure (first 40 trials) epochs.

To assess whether baseline (pre-exposure phase) chunking of follow-through movements were correlated with subsequent opposing force field adaptation across all trial sets, we assessed the correlation between participants’ dwell times during the final 4 blocks of the pre-exposure phase with the final adaptation across the final 4 blocks in the exposure phase.