During movement planning, brain activity within parietofrontal networks encodes information about upcoming actions that can be driven either externally (e.g., by a sensory cue) or internally (i.e., by a choice/decision). Here we used multivariate pattern analysis (MVPA) of fMRI data to distinguish between areas that represent (1) abstract movement plans that generalize across the way in which these were driven, (2) internally driven movement plans, or (3) externally driven movement plans. In a delayed-movement paradigm, human volunteers were asked to plan and execute three types of nonvisually guided right-handed reaching movements toward a central target object: using a precision grip, a power grip, or touching the object without hand preshaping. On separate blocks of trials, movements were either instructed via color cues (Instructed condition), or chosen by the participant (Free-Choice condition). Using ROI-based and whole-brain searchlight-based MVPA, we found abstract representations of planned movements that generalize across the way these movements are selected (internally vs externally driven) in parietal cortex, dorsal premotor cortex, and primary motor cortex contralateral to the acting hand. In addition, we revealed representations specific for internally driven movement plans in contralateral ventral premotor cortex, dorsolateral prefrontal cortex, supramarginal gyrus, and in ipsilateral posterior parietotemporal regions, suggesting that these regions are recruited during movement selection. Finally, we observed representations of externally driven movement plans in bilateral supplementary motor cortex and a similar trend in presupplementary motor cortex, suggesting a role in stimulus-response mapping.

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.

Motor planning plays a critical role in producing fast and accurate movement. Yet, the neural processes that occur in human primary motor and somatosensory cortex during planning, and how they relate to those during movement execution, remain poorly understood. Here we used 7T functional magnetic resonance imaging (fMRI) and a delayed movement paradigm to study single finger movement planning and execution. The inclusion of no-go trials and variable delays allowed us to separate what are typically overlapping planning and execution brain responses. Although our univariate results show widespread deactivation during finger planning, multivariate pattern analysis revealed finger-specific activity patterns in contralateral primary somatosensory cortex (S1), which predicted the planned finger action. Surprisingly, these activity patterns were as informative as those found in contralateral primary motor cortex (M1). Control analyses ruled out the possibility that the detected information was an artifact of subthreshold movements during the preparatory delay. Furthermore, we observed that finger-specific activity patterns during planning were highly correlated to those during execution. These findings reveal that motor planning activates the specific S1 and M1 circuits that are engaged during the execution of a finger press, while activity in both regions is overall suppressed. We propose that preparatory states in S1 may improve movement control through changes in sensory processing or via direct influence of spinal motor neurons.

Action understanding requires a many-to-one mapping of perceived input onto abstract representations that generalize across concrete features. It is debated whether such abstract action concepts are encoded in ventral premotor cortex (PMv; motor hypothesis) or, alternatively, are represented in lateral occipitotemporal cortex (LOTC; cognitive hypothesis). We used fMRI-based multivoxel pattern analysis to decode observed actions at concrete and abstract, object-independent levels of representation. Participants observed videos of 2 actions involving 2 different objects, using either an explicit or implicit task with respect to conceptual action processing. We decoded concrete action representations by training and testing a classifier to discriminate between actions within each object category. To identify abstract action representations, we trained the classifier to discriminate actions in one object and tested the classifier on actions performed on the other object, and vice versa. Region-of-interest and searchlight analyses revealed decoding in LOTC at both concrete and abstract levels during both tasks, whereas decoding in PMv was restricted to the concrete level during the explicit task. In right inferior parietal cortex, decoding was significant for the abstract level during the explicit task. Our findings are incompatible with the motor hypothesis, but support the cognitive hypothesis of action understanding.

Motor planning plays a critical role in producing fast and accurate movement. Yet, the neural processes that occur in human primary motor and somatosensory cortex during planning, and how they relate to those during movement execution, remain poorly understood. Here we used 7T functional magnetic resonance imaging (fMRI) and a delayed movement paradigm to study single finger movement planning and execution. The inclusion of no-go trials and variable delays allowed us to separate what are typically overlapping planning and execution brain responses. Although our univariate results show widespread deactivation during finger planning, multivariate pattern analysis revealed finger-specific activity patterns in contralateral primary somatosensory cortex (S1), which predicted the planned finger movements. Surprisingly, these activity patterns were similarly strong to those found in contralateral primary motor cortex (M1). Control analyses ruled out the possibility that the detected information was an artifact of subthreshold movements during the preparatory delay. Furthermore, we observed that finger-specific activity patterns during planning were highly correlated to those during movement execution. These findings reveal that motor planning activates the specific S1 and M1 circuits that are engaged during the execution of a finger movement – while activity in S1 and M1 is overall suppressed. We propose that preparatory states in S1 may improve movement control through changes in sensory processing or via direct influence of spinal motor neurons.Significance statementMotor planning is important for good motor performance, yet it is unclear which neural processes underlie the preparation of the nervous system for an upcoming movement. Using high-resolution functional neuroimaging, we investigated how the planning of finger movements changes the activity state in primary motor (M1) and somatosensory (S1) cortex, and how brain responses during planning and execution relate to each other. We show that planning leads to finger-specific activation in both M1 and S1, which is highly similar to the finger-specific activity patterns elicited during movement execution. Our findings suggest that even S1 is being specifically prepared for an upcoming movement, either to actively contribute to the outflowing motor command or to enable movement-specific sensory gating.