Interaction of temporal and ordinal representations in movement sequences

C-SMB 2.0: Integrating over 25 years of motor sequencing research with the Discrete Sequence Production task

An exhaustive review is reported of over 25 years of research with the Discrete Sequence Production (DSP) task as reported in well over 100 articles. In line with the increasing call for theory development, this culminates into proposing the second version of the Cognitive framework of Sequential Motor Behavior (C-SMB 2.0), which brings together known models from cognitive psychology, cognitive neuroscience, and motor learning. This processing framework accounts for the many different behavioral results obtained with the DSP task and unveils important properties of the cognitive system. C-SMB 2.0 assumes that a versatile central processor (CP) develops multimodal, central-symbolic representations of short motor segments by repeatedly storing the elements of these segments in short-term memory (STM). Independently, the repeated processing by modality-specific perceptual and motor processors (PPs and MPs) and by the CP when executing sequences gradually associates successively used representations at each processing level. The high dependency of these representations on active context information allows for the rapid serial activation of the sequence elements as well as for the executive control of tasks as a whole. Speculations are eventually offered as to how the various cognitive processes could plausibly find their neural underpinnings within the intricate networks of the brain.

Goal-Dependent Use of Temporal Regularities to Orient Attention under Spatial and Action Uncertainty

The temporal regularities in our environments support the proactive dynamic anticipation of relevant events. In visual attention, one important outstanding question is whether temporal predictions must be linked to predictions about spatial locations or motor plans to facilitate behaviour. To test this, we developed a task for manipulating temporal expectations and task relevance of visual stimuli appearing within rapidly presented streams, while stimulus location and responding hand remained uncertain. Differently coloured stimuli appeared in one of two concurrent (left and right) streams with distinct temporal probability structures. Targets were defined by colour on a trial-by-trial basis and appeared equiprobably in either stream, requiring a localisation response. Across two experiments, participants were faster and more accurate at detecting temporally predictable targets compared to temporally unpredictable targets. We conclude that temporal expectations learned incidentally from temporal regularities can be called upon flexibly in a goal-driven manner to guide behaviour. Moreover, we show that visual temporal attention can facilitate performance in the absence of concomitant spatial or motor expectations in dynamically unfolding contexts.

Learning to pause: Fidelity of and biases in the developmental acquisition of gaps in the communicative signals of a songbird

The temporal organization of sounds used in social contexts can provide information about signal function and evoke varying responses in listeners (receivers). For example, music is a universal and learned human behavior that is characterized by different rhythms and tempos that can evoke disparate responses in listeners. Similarly, birdsong is a social behavior in songbirds that is learned during critical periods in development and used to evoke physiological and behavioral responses in receivers. Recent investigations have begun to reveal the breadth of universal patterns in birdsong and their similarities to common patterns in speech and music, but relatively little is known about the degree to which biological predispositions and developmental experiences interact to shape the temporal patterning of birdsong. Here, we investigated how biological predispositions modulate the acquisition and production of an important temporal feature of birdsong, namely the duration of silent pauses ("gaps") between vocal elements ("syllables"). Through analyses of semi-naturally raised and experimentally tutored zebra finches, we observed that juvenile zebra finches imitate the durations of the silent gaps in their tutor's song. Further, when juveniles were experimentally tutored with stimuli containing a wide range of gap durations, we observed biases in the prevalence and stereotypy of gap durations. Together, these studies demonstrate how biological predispositions and developmental experiences differently affect distinct temporal features of birdsong and highlight similarities in developmental plasticity across birdsong, speech, and music. RESEARCH HIGHLIGHTS: The temporal organization of learned acoustic patterns can be similar across human cultures and across species, suggesting biological predispositions in acquisition. We studied how biological predispositions and developmental experiences affect an important temporal feature of birdsong, namely the duration of silent intervals between vocal elements ("gaps"). Semi-naturally and experimentally tutored zebra finches imitated the durations of gaps in their tutor's song and displayed some biases in the learning and production of gap durations and in gap variability. These findings in the zebra finch provide parallels with the acquisition of temporal features of speech and music in humans.

Task-irrelevant auditory metre shapes visuomotor sequential learning

The ability to learn and reproduce sequences is fundamental to every-day life, and deficits in sequential learning are associated with developmental disorders such as specific language impairment. Individual differences in sequential learning are usually investigated using the serial reaction time task (SRTT), wherein a participant responds to a series of regularly timed, seemingly random visual cues that in fact follow a repeating deterministic structure. Although manipulating inter-cue interval timing has been shown to adversely affect sequential learning, the role of metre (the patterning of salience across time) remains unexplored within the regularly timed, visual SRTT. The current experiment consists of an SRTT adapted to include task-irrelevant auditory rhythms conferring a sense of metre. We predicted that (1) participants' (n = 41) reaction times would reflect the auditory metric structure; (2) that disrupting the correspondence between the learned visual sequence and auditory metre would impede performance; and (3) that individual differences in sensitivity to rhythm would predict the magnitude of these effects. Altering the relationship via a phase shift between the trained visual sequence and auditory metre slowed reaction times. Sensitivity to rhythm was predictive of reaction times over all. In an exploratory analysis, we, moreover, found that approximately half of participants made systematically different responses to visual cues on the basis of the cues' position within the auditory metre. We demonstrate the influence of auditory temporal structures on visuomotor sequential learning in a widely used task where metre and timing are rarely considered. The current results indicate sensitivity to metre as a possible latent factor underpinning individual differences in SRTT performance.

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.

Default mode and dorsal attention network involvement in visually guided motor sequence learning

Motor sequence learning (MSL) paradigms are often used to investigate the neural processes underlying the acquisition of complex motor skills. Behavioral and neuroimaging studies have indicated an early stage in which spatial learning is prominent and a late stage of automatized performance after multiple training periods. Functional magnetic resonance imaging (fMRI) studies yielded both decreased and increased activations of the sensorimotor and association areas. However, task-negative and task-positive intrinsic connectivity networks (ICNs), the default mode (DMN) and dorsal attention (DAN) networks involved in governing attention demands during various task conditions were not specifically addressed in most studies. In the present fMRI study, a visually guided MSL (VMSL) task was used for bringing roles of visuospatial and motor attention into foreground in order to investigate the role of attention-related ICNs in MSL. Seventeen healthy, right-handed participants completed training and test sessions of VMSL during fMRI on the 1st day. Then, after daily training for three consecutive days outside the scanner, they were re-tested during the 5th day's scanning session. When test session after early learning period was compared with training session, activation decrease was observed in the occipito-temporal fusiform cortex, while task-related suppression of DMN was reduced. Reduced deactivation after early learning was correlated with decreased error rates. After late learning stage we observed activation decreases in bilateral superior parietal lobules of task-positive DAN, dorsal precunei, and cerebellum. Reduced activity in left posterior parietal and right cerebellar regions were correlated with gains in speed, error rate, respectively. This dissociation in activity changes of DMN and DAN related areas suggests that DAN shows high contribution during both early and late MSL stages, possibly due to attention requirement for automatization of spatial and temporal aspects of motor sequence. In contrast, spatial learning occurring during early MSL stage was sufficient for releasing DMN resources.

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.

The Planning Horizon for Movement Sequences

When performing a long chain of actions in rapid sequence, future movements need to be planned concurrently with ongoing action. However, how far ahead we plan, and whether this ability improves with practice, is currently unknown. Here, we designed an experiment in which healthy volunteers produced sequences of 14 finger presses quickly and accurately on a keyboard in response to numerical stimuli. On every trial, participants were only shown a fixed number of stimuli ahead of the current keypress. The size of this viewing window varied between 1 (next digit revealed with the pressing of the current key) and 14 (full view of the sequence). Participants practiced the task for 5 days, and their performance was continuously assessed on random sequences. Our results indicate that participants used the available visual information to plan multiple actions into the future, but that the planning horizon was limited: receiving information about more than three movements ahead did not result in faster sequence production. Over the course of practice, we found larger performance improvements for larger viewing windows and an expansion of the planning horizon. These findings suggest that the ability to plan future responses during ongoing movement constitutes an important aspect of skillful movement. Based on the results, we propose a framework to investigate the neuronal processes underlying simultaneous planning and execution.

Neural Competitive Queuing of Ordinal Structure Underlies Skilled Sequential Action

Fluent retrieval and execution of movement sequences is essential for daily activities, but the neural mechanisms underlying sequence planning remain elusive. Here participants learned finger press sequences with different orders and timings and reproduced them in a magneto-encephalography (MEG) scanner. We classified the MEG patterns for each press in the sequence and examined pattern dynamics during preparation and production. Our results demonstrate the “competitive queuing” (CQ) of upcoming action representations, extending previous computational and non-human primate recording studies to non-invasive measures in humans. In addition, we show that CQ reflects an ordinal template that generalizes across specific motor actions at each position. Finally, we demonstrate that CQ predicts participants’ production accuracy and originates from parahippocampal and cerebellar sources. These results suggest that the brain learns and controls multiple sequences by flexibly combining representations of specific actions and interval timing with high-level, parallel representations of sequence position.

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Non-invasive recordings in humans show “competitive queuing” of upcoming actions

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Queuing gradient mainly reflects a high-level template of sequence position

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Queuing gradient originates in ipsilateral parahippocampal and cerebellar areas

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Strength of queuing gradient predicts production accuracy

Early Behavioural Facilitation by Temporal Expectations in Complex Visual-motor Sequences

In daily life, temporal expectations may derive from incidental learning of recurring patterns of intervals. We investigated the incidental acquisition and utilisation of combined temporal-ordinal (spatial/effector) structure in complex visual-motor sequences using a modified version of a serial reaction time (SRT) task. In this task, not only the series of targets/responses, but also the series of intervals between subsequent targets was repeated across multiple presentations of the same sequence. Each participant completed three sessions. In the first session, only the repeating sequence was presented. During the second and third session, occasional probe blocks were presented, where a new (unlearned) spatial-temporal sequence was introduced. We first confirm that participants not only got faster over time, but that they were slower and less accurate during probe blocks, indicating that they incidentally learned the sequence structure. Having established a robust behavioural benefit induced by the repeating spatial-temporal sequence, we next addressed our central hypothesis that implicit temporal orienting (evoked by the learned temporal structure) would have the largest influence on performance for targets following short (as opposed to longer) intervals between temporally structured sequence elements, paralleling classical observations in tasks using explicit temporal cues. We found that indeed, reaction time differences between new and repeated sequences were largest for the short interval, compared to the medium and long intervals, and that this was the case, even when comparing late blocks (where the repeated sequence had been incidentally learned), to early blocks (where this sequence was still unfamiliar). We conclude that incidentally acquired temporal expectations that follow a sequential structure can have a robust facilitatory influence on visually-guided behavioural responses and that, like more explicit forms of temporal orienting, this effect is most pronounced for sequence elements that are expected at short inter-element intervals.

Deciphering the functional role of spatial and temporal muscle synergies in whole-body movements

Voluntary movement is hypothesized to rely on a limited number of muscle synergies, the recruitment of which translates task goals into effective muscle activity. In this study, we investigated how to analytically characterize the functional role of different types of muscle synergies in task performance. To this end, we recorded a comprehensive dataset of muscle activity during a variety of whole-body pointing movements. We decomposed the electromyographic (EMG) signals using a space-by-time modularity model which encompasses the main types of synergies. We then used a task decoding and information theoretic analysis to probe the role of each synergy by mapping it to specific task features. We found that the temporal and spatial aspects of the movements were encoded by different temporal and spatial muscle synergies, respectively, consistent with the intuition that there should a correspondence between major attributes of movement and major features of synergies. This approach led to the development of a novel computational method for comparing muscle synergies from different participants according to their functional role. This functional similarity analysis yielded a small set of temporal and spatial synergies that describes the main features of whole-body reaching movements.

A unifying motor control framework for task-specific dystonia

Task-specific dystonia is a movement disorder characterized by a painless loss of dexterity specific to a particular motor skill. This disorder is prevalent among writers, musicians, dancers and athletes. No current treatment is predictably effective, and the disorder generally ends the careers of affected individuals. Traditional disease models of dystonia have a number of limitations with regard to task-specific dystonia. We therefore discuss emerging evidence that the disorder has its origins within normal compensatory mechanisms of a healthy motor system in which the representation and reproduction of motor skill are disrupted. We describe how risk factors for task-specific dystonia can be stratified and translated into mechanisms of dysfunctional motor control. The proposed model aims to define new directions for experimental research and stimulate therapeutic advances for this highly disabling disorder.

Temporal alignment of anticipatory motor cortical beta lateralisation in hidden visual-motor sequences

Performance improves when participants respond to events that are structured in repeating sequences, suggesting that learning can lead to proactive anticipatory preparation. Whereas most sequence‐learning studies have emphasised spatial structure, most sequences also contain a prominent temporal structure. We used MEG to investigate spatial and temporal anticipatory neural dynamics in a modified serial reaction time (SRT) task. Performance and brain activity were compared between blocks with learned spatial‐temporal sequences and blocks with new sequences. After confirming a strong behavioural benefit of spatial‐temporal predictability, we show lateralisation of beta oscillations in anticipation of the response associated with the upcoming target location and show that this also aligns to the expected timing of these forthcoming events. This effect was found both when comparing between repeated (learned) and new (unlearned) sequences, as well as when comparing targets that were expected after short vs. long intervals within the repeated (learned) sequence. Our findings suggest that learning of spatial‐temporal structure leads to proactive and dynamic modulation of motor cortical excitability in anticipation of both the location and timing of events that are relevant to guide action.

Early behavioural facilitation by temporal expectations in complex visual-motor sequences

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We show incidental spatial-temporal sequence learning in an adapted SRT task.

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Incidentally acquired temporal expectations have the largest effect for short intervals.

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The facilitation for short intervals mirrors explicit temporal orienting results.

In daily life, temporal expectations may derive from incidental learning of recurring patterns of intervals. We investigated the incidental acquisition and utilisation of combined temporal-ordinal (spatial/effector) structure in complex visual-motor sequences using a modified version of a serial reaction time (SRT) task. In this task, not only the series of targets/responses, but also the series of intervals between subsequent targets was repeated across multiple presentations of the same sequence. Each participant completed three sessions. In the first session, only the repeating sequence was presented. During the second and third session, occasional probe blocks were presented, where a new (unlearned) spatial-temporal sequence was introduced. We first confirm that participants not only got faster over time, but that they were slower and less accurate during probe blocks, indicating that they incidentally learned the sequence structure. Having established a robust behavioural benefit induced by the repeating spatial-temporal sequence, we next addressed our central hypothesis that implicit temporal orienting (evoked by the learned temporal structure) would have the largest influence on performance for targets following short (as opposed to longer) intervals between temporally structured sequence elements, paralleling classical observations in tasks using explicit temporal cues. We found that indeed, reaction time differences between new and repeated sequences were largest for the short interval, compared to the medium and long intervals, and that this was the case, even when comparing late blocks (where the repeated sequence had been incidentally learned), to early blocks (where this sequence was still unfamiliar). We conclude that incidentally acquired temporal expectations that follow a sequential structure can have a robust facilitatory influence on visually-guided behavioural responses and that, like more explicit forms of temporal orienting, this effect is most pronounced for sequence elements that are expected at short inter-element intervals.

Encoding Temporal Features of Skilled Movements-What, Whether and How?

In order to reliably produce intelligible speech or fluently play a melody on a piano, learning the precise timing of muscle activations is essential. Surprisingly, the fundamental question of how memories of complex temporal dynamics of movement are stored across the brain is still unresolved. This review outlines the constraints that determine whether and how the timing of skilled movements is represented in the central nervous system and introduces different computational and neural mechanisms that can be harnessed for temporal encoding. It concludes by proposing a schematic model of how these different mechanisms may complement and interact with each other in fast feedback loops to achieve skilled motor timing.

Visual statistical learning of temporal structures at different hierarchical levels

Visual environments are complex. In order to process the complex information provided by visual environments, the visual system adopts strategies to reduce its complexity. One strategy, called visual statistical learning, or VSL, is to extract the statistical regularities from the environment. Another strategy is to use the hierarchical structure of a scene (e.g., the co-occurrence between local and global information). Through a series of experiments, this study investigated whether the utilization of the statistical regularities and the hierarchical structure could work together to reduce the complexity of a scene. In the familiarization phase, the participants were asked to passively view a stream of hierarchical scenes where the shapes were concurrently presented at the local and global levels. At each of the two levels there were temporal regularities among the three shapes, which always appeared in the same order. In the test phase, the participants judged the familiarity between 2 triplets, whose temporal regularities were either preserved or not. We found that the participants extracted the temporal regularities at each of the local and global levels (Experiment 1). The hierarchical structure influenced the ability to extract the temporal regularities (Experiment 2). Specifically, VSL was either enhanced or impaired depending on whether the hierarchical structure was informative or not. In summary, in order to process a complex scene, the visual system flexibly uses statistical regularities and the hierarchical structure of the scene.

Basal ganglia and cortical networks for sequential ordering and rhythm of complex movements

Voluntary actions require the concurrent engagement and coordinated control of complex temporal (e.g., rhythm) and ordinal motor processes. Using high-resolution functional magnetic resonance imaging (fMRI) and multi-voxel pattern analysis (MVPA), we sought to determine the degree to which these complex motor processes are dissociable in basal ganglia and cortical networks. We employed three different finger-tapping tasks that differed in the demand on the sequential temporal rhythm or sequential ordering of submovements. Our results demonstrate that sequential rhythm and sequential order tasks were partially dissociable based on activation differences. The sequential rhythm task activated a widespread network centered around the supplementary motor area (SMA) and basal-ganglia regions including the dorsomedial putamen and caudate nucleus, while the sequential order task preferentially activated a fronto-parietal network. There was also extensive overlap between sequential rhythm and sequential order tasks, with both tasks commonly activating bilateral premotor, supplementary motor, and superior/inferior parietal cortical regions, as well as regions of the caudate/putamen of the basal ganglia and the ventro-lateral thalamus. Importantly, within the cortical regions that were active for both complex movements, MVPA could accurately classify different patterns of activation for the sequential rhythm and sequential order tasks. In the basal ganglia, however, overlapping activation for the sequential rhythm and sequential order tasks, which was found in classic motor circuits of the putamen and ventro-lateral thalamus, could not be accurately differentiated by MVPA. Overall, our results highlight the convergent architecture of the motor system, where complex motor information that is spatially distributed in the cortex converges into a more compact representation in the basal ganglia.

Motor skill learning between selection and execution

Learning motor skills evolves from the effortful selection of single movement elements to their combined fast and accurate production. We review recent trends in the study of skill learning which suggest a hierarchical organization of the representations that underlie such expert performance, with premotor areas encoding short sequential movement elements (chunks) or particular component features (timing/spatial organization). This hierarchical representation allows the system to utilize elements of well-learned skills in a flexible manner. One neural correlate of skill development is the emergence of specialized neural circuits that can produce the required elements in a stable and invariant fashion. We discuss the challenges in detecting these changes with fMRI.

Human premotor areas parse sequences into their spatial and temporal features

Skilled performance is characterized by precise and flexible control of movement sequences in space and time. Recent theories suggest that integrated spatio-temporal trajectories are generated by intrinsic dynamics of motor and premotor networks. This contrasts with behavioural advantages that emerge when a trained spatial or temporal feature of sequences is transferred to a new spatio-temporal combination arguing for independent neural representations of these sequence features. We used a new fMRI pattern classification approach to identify brain regions with independent vs integrated representations. A distinct regional dissociation within motor areas was revealed: whereas only the contralateral primary motor cortex exhibited unique patterns for each spatio-temporal sequence combination, bilateral premotor areas represented spatial and temporal features independently of each other. These findings advocate a unique function of higher motor areas for flexible recombination and efficient encoding of complex motor behaviours.

DOI:http://dx.doi.org/10.7554/eLife.03043.001

Once a pianist has learned to play a song, he or she can nearly effortlessly reproduce the sequence of finger movements needed to play the song with a particular rhythm. A skilled pianist can also improvise, pairing the same keystrokes with a different rhythm or playing the same rhythm with a slightly different sequence of keys. This ability to flexibly modify and recombine sequences of physical movements in space and time enables humans to exhibit great creativity in music, language, and many other tasks that require motor skills. However, the underlying brain mechanisms that allow this flexibility are only beginning to be explored.

Some scientists have theorized that networks of brain cells in the parts of the brain that control movement store a sequence in time and space as one inseparable unit. However, this theory doesn't explain why pianists and other skilled individuals can separate and recombine the physical movements and timing of a sequence in new ways. An alternate idea is that the brain captures the information necessary to execute a series of physical movements separately from the timing at which the movements are to be carried out. This would allow these features to be put together in new ways.

Kornysheva and Diedrichsen taught a group of volunteers a series of finger movements paired with particular rhythms. Half the volunteers performed the task using their left hand and the other half with their right hand. After training the volunteers performed better when producing sequences they had been trained on, even in trials where either the rhythm or the finger sequence was slightly changed.

The volunteers were also asked to perform the trained movements while their brain activity was monitored in a functional magnetic resonance imaging (fMRI) machine. Kornysheva and Diedrichsen looked for areas that showed similar patterns of increases and decreases in activity whenever a particular sequence was performed. This identified areas that showed unique patterns for each trained sequence combination of finger movements and rhythm, which could be distinguished from areas where the activity patterns for sequences remained similar across rhythms or across finger movements.

Kornysheva and Diedrichsen found that a region of the brain that controls movement encodes sequences on the opposite side of the brain from the moving hand. In this part of the brain, the movement and timing were encoded together as one unit. However, in premotor areas—which are known to help individuals to plan movements—the timing and the finger movements appeared to be encoded separately in overlapping patches on both sides of the brain. This automatic separation appears to be a fundamental function of the premotor cortex, enabling behavioural flexibility and the storage of complex sequences of movements in space and time.

DOI:http://dx.doi.org/10.7554/eLife.03043.002

Primary motor cortex disinhibition during motor skill learning

Motor learning requires practice over a period of time and depends on brain plasticity, yet even for relatively simple movements, there are multiple practice strategies that can be used for skill acquisition. We investigated the role of intracortical inhibition in the primary motor cortex (M1) during motor skill learning. Event-related transcranial magnetic stimulation (TMS) was used to assess corticomotor excitability and inhibition thought to involve synaptic and extrasynaptic γ-aminobutyric acid (GABA). Short intracortical inhibition (SICI) was assessed using 1- and 2.5-ms interstimulus intervals (ISIs). Participants learned a novel, sequential pinch-grip task on a computer in either a repetitive or interleaved practice structure. Both practice structures showed equivalent levels of motor performance at the end of acquisition and at retention 1 wk later. There was a novel task-related modulation of 1-ms SICI. Repetitive practice elicited a greater reduction of 1- and 2.5-ms SICI, i.e., disinhibition, between rest and task acquisition, compared with interleaved practice. These novel findings support the use of a repetitive practice structure for motor learning because the associated effects within M1 have relevance for motor rehabilitation.

Dorsal parietal area 5 encodes immediate reach in sequential arm movements

To generate a coherent action sequence, it is essential to integrate all component movements beforehand, and such sequence-related information has been observed in numerous brain regions. However, this high-level sequential plan encompassing multiple motor elements in parallel ultimately must be decomposed into serial motor commands to be executed by the musculoskeletal system. In the present study, we recorded single-neuron activity from dorsal parietal area 5 (area 5d) while monkeys performed a double-reach task, and found that area 5d conveys the immediate upcoming reach, but not the subsequent movement, as opposed to the entire movement sequence being encoded as in other cortical sensorimotor areas. The elementary movement coded in area 5d suggests that unfolding of the motor sequence begins in the parietal-frontal cortex, instead of being exclusively implemented by downstream subcortical and spinal circuits.

Skill learning strengthens cortical representations of motor sequences

Motor-skill learning can be accompanied by both increases and decreases in brain activity. Increases may indicate neural recruitment, while decreases may imply that a region became unimportant or developed a more efficient representation of the skill. These overlapping mechanisms make interpreting learning-related changes of spatially averaged activity difficult. Here we show that motor-skill acquisition is associated with the emergence of highly distinguishable activity patterns for trained movement sequences, in the absence of average activity increases. During functional magnetic resonance imaging, participants produced either four trained or four untrained finger sequences. Using multivariate pattern analysis, both untrained and trained sequences could be discriminated in primary and secondary motor areas. However, trained sequences were classified more reliably, especially in the supplementary motor area. Our results indicate skill learning leads to the development of specialized neuronal circuits, which allow the execution of fast and accurate sequential movements without average increases in brain activity.

DOI:http://dx.doi.org/10.7554/eLife.00801.001

Functional magnetic resonance imaging (fMRI) is a widely used technique that makes it possible to observe changes in a person’s brain activity as they perform specific tasks while lying in a scanner. These could range from listening to music or looking at images, to recalling words or imagining a scene, and each will produce a distinct pattern of neural activity.

However, fMRI data can be difficult to interpret. Say a particular area of the brain is very active when a subject is trying to perform a new task, but becomes less active as the subject becomes better at the task and performs it more easily. Does this mean that the brain region is used for learning the task, but not for performing once it has been learned? Or alternatively, does it show that the brain area is involved in carrying out the task, but that it becomes more efficient with practice, and so shows less activity in later scans?

Now, Wiestler and Diedrichsen have obtained data that help to distinguish between these alternatives. Subjects were trained to carry out four specific sequences of finger movements and then asked either to reproduce these ‘trained’ sequences or to perform four ‘untrained’ sequences while in the fMRI scanner. All eight sequences produced high levels of activity in the areas of motor cortex that control finger movements.

However, closer analysis showed marked differences between the patterns of activity produced during the ‘trained’ sequences and those seen during ‘untrained’ sequences that involved moving the same fingers.

Wiestler and Diedrichsen proposed that when subjects train to perform specific movement sequences, this should lead to the development of neural circuits that are specialized to carry out those specific movements—and that detailed analysis of the fMRI data would allow them to identify patterns of activity that correspond to these circuits. Sure enough, when they analysed the fMRI scans, Wiestler and Diedrichsen found that the activation patterns associated with ‘trained’ movement sequences were more readily distinguishable from each other than those associated with the ‘untrained’ movement sequences, even in areas where training led to an overall reduction in activity.

As well as showing that movement sequences become associated with specific spatial patterns of activation as they are learned, this study provides a new way to study learning in fMRI that should be useful for many future studies.

DOI:http://dx.doi.org/10.7554/eLife.00801.002