The Importance of Planning in Motor Learning

Cortical Patterns Shift from Sequence Feature Separation during Planning to Integration during Motor Execution

Performing sequences of movements from memory and adapting them to changing task demands is a hallmark of skilled human behavior, from handwriting to playing a musical instrument. Prior studies showed a fine-grained tuning of cortical primary motor, premotor, and parietal regions to motor sequences: from the low-level specification of individual movements to high-level sequence features, such as sequence order and timing. However, it is not known how tuning in these regions unfolds dynamically across planning and execution. To address this, we trained 24 healthy right-handed human participants (14 females, 10 males) to produce four five-element finger press sequences with a particular finger order and timing structure in a delayed sequence production paradigm entirely from memory. Local cortical fMRI patterns during preparation and production phases were extracted from separate No-Go and Go trials, respectively, to tease out activity related to these perimovement phases. During sequence planning, premotor and parietal areas increased tuning to movement order or timing, regardless of their combinations. In contrast, patterns reflecting the unique integration of sequence features emerged in these regions during execution only, alongside timing-specific tuning in the ventral premotor, supplementary motor, and superior parietal areas. This was in line with the participants' behavioral transfer of trained timing, but not of order to new sequence feature combinations. Our findings suggest a general informational state shift from high-level feature separation to low-level feature integration within cortical regions for movement execution. Recompiling sequence features trial-by-trial during planning may enable flexible last-minute adjustment before movement initiation.SIGNIFICANCE STATEMENT Musicians and athletes can modify the timing and order of movements in a sequence trial-by-trial, allowing for a vast repertoire of flexible behaviors. How does the brain put together these high-level sequence features into an integrated whole? We found that, trial-by-trial, the control of sequence features undergoes a state shift from separation during planning to integration during execution across a network of motor-related cortical areas. These findings have implications for understanding the hierarchical control of skilled movement sequences, as well as how information in brain areas unfolds across planning and execution.

Competitive state of movements during planning predicts sequence performance

Humans can learn and produce skilled movement sequences from memory, yet the nature of sequence planning is not well understood. Previous computational and neurophysiological work suggests that movements in a sequence are planned as parallel graded activations and selected for output through competition. However, the relevance of this planning pattern to sequence production fluency and accuracy, as opposed to the temporal structure of sequences, is unclear. To resolve this question, we assessed the relative availability of constituent movements behaviorally during the preparation of motor sequences from memory. In three separate multisession experiments, healthy participants were trained to retrieve and produce four-element finger press sequences with particular timing according to an abstract sequence cue. We evaluated reaction time (RT) and error rate as markers of movement availability to constituent movement probes. Our results demonstrate that longer preparation time produces more pronounced differences in availability between adjacent sequence elements, whereas no effect was found for sequence speed or temporal grouping. Further, participants with larger position-dependent differences in movement availability tended to initiate correct sequences faster and with a higher temporal accuracy. Our results suggest that competitive preactivation is established gradually during sequence planning and predicts sequence skill, rather than the temporal structure of the motor sequence.NEW & NOTEWORTHY Sequence planning is an integral part of motor sequence control. Here, we demonstrate that the competitive state of sequential movements during sequence planning can be read out behaviorally through movement probes. We show that position-dependent differences in movement availability during planning reflect sequence preparedness and skill but not the timing of the planned sequence. Behavioral access to the preparatory state of movements may serve as a marker of sequence planning capacity.

Corticocortical Systems Underlying High-Order Motor Control

Cortical networks are characterized by the origin, destination, and reciprocity of their connections, as well as by the diameter, conduction velocity, and synaptic efficacy of their axons. The network formed by parietal and frontal areas lies at the core of cognitive-motor control because the outflow of parietofrontal signaling is conveyed to the subcortical centers and spinal cord through different parallel pathways, whose orchestration determines, not only when and how movements will be generated, but also the nature of forthcoming actions. Despite intensive studies over the last 50 years, the role of corticocortical connections in motor control and the principles whereby selected cortical networks are recruited by different task demands remain elusive. Furthermore, the synaptic integration of different cortical signals, their modulation by transthalamic loops, and the effects of conduction delays remain challenging questions that must be tackled to understand the dynamical aspects of parietofrontal operations. In this article, we evaluate results from nonhuman primate and selected rodent experiments to offer a viewpoint on how corticocortical systems contribute to learning and producing skilled actions. Addressing this subject is not only of scientific interest but also essential for interpreting the devastating consequences for motor control of lesions at different nodes of this integrated circuit. In humans, the study of corticocortical motor networks is currently based on MRI-related methods, such as resting-state connectivity and diffusion tract-tracing, which both need to be contrasted with histological studies in nonhuman primates.

Sequence learning is driven by improvements in motor planning

The ability to perform complex sequences of movements quickly and accurately is critical for many motor skills. Although training improves performance in a large variety of motor sequence tasks, the precise mechanisms behind such improvements are poorly understood. Here we investigated the contribution of single-action selection, sequence preplanning, online planning, and motor execution to performance in a discrete sequence production task. Five visually presented numbers cued a sequence of five finger presses, which had to be executed as quickly and accurately as possible. To study how sequence planning influenced sequence production, we manipulated the amount of time that participants were given to prepare each sequence by using a forced-response paradigm. Over 4 days, participants were trained on 10 sequences and tested on 80 novel sequences. Our results revealed that participants became faster in selecting individual finger presses. They also preplanned three or four sequence items into the future, and the speed of preplanning improved for trained, but not for untrained, sequences. Because preplanning capacity remained limited, the remaining sequence elements had to be planned online during sequence execution, a process that also improved with sequence-specific training. Overall, our results support the view that motor sequence learning effects are best characterized by improvements in planning processes that occur both before and concurrently with motor execution. NEW & NOTEWORTHY Complex skills often require the production of sequential movements. Although practice improves performance, it remains unclear how these improvements are achieved. Our findings show that learning effects in a sequence production task can be attributed to an enhanced ability to plan upcoming movements. These results shed new light on planning processes in the context of movement sequences and have important implications for our understanding of the neural mechanisms that underlie skill acquisition.