Electronic Thesis and Dissertation Repository

Degree

Master of Science

Program

Neuroscience

Supervisor

Jorn Diedrichsen

2nd Supervisor

Andrew Pruszynski

Co-Supervisor

Abstract

Many everyday skills involve the production of complex sequences of movements. However, the dynamics of the interplay between action selection and execution processes in sequential movements is poorly understood.Here, we set out to investigate the extent to which information regarding upcoming actions is utilized by the motor system to preplan into the future and furthermore, how this ability is influenced by learning. We designed a finger sequence taskwhere participants were shown only a fixed number of upcoming cues regarding future presses in every trial (viewing window, W). W varied between 1 (next digit revealed with pressing the current digit – classical discrete sequence production task, DSP) to full view of the sequence. Each participant underwent 5 sessions of training. Our results clearly indicate that participants selected and prepared multiple actions into the future. On day 1, when the effect of practice is minimal, participants performed significantly slower for window sizes 1 and 2, compared to a fully visible sequence. This suggests that information regarding up to 2 digits ahead was used to preplan upcoming actions. Furthermore, our results show that for larger window sizes, performance benefits from practice to a higher extent compared to smaller window sizes. This suggests that in addition to more efficient stimulus-to-response mapping, a large part of sequence-nonspecific learning is explained by using in-advance information more effectively. This claim is supported by the fact that the span of preplanning, i.e. the preplanning horizon size increased from 2 digits ahead in the early phase of learning to 4 digits ahead in the late learning phase. Finally, we show that the observations of this study can be successfully modelled using a relatively simple race model of action selection, with the ability to preplan multiple actions into the future in parallel with action execution.

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