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

Collaboration of Cerebello-Rubral and Cerebello-Striatal Loops in a Motor Preparation Task

International audienceIn this study, we used fMRI to identify brain regions associated with concentration (sustained attention) during a motor preparation task. In comparison with a non-concentration task, increased activities were observed (P < 0.05, FWEcorrected P values) in cerebellar lobules VI and VII, motor cortex, pre-supplementary motor area (pre-SMA), thalamus, red nucleus (RN), and caudate nucleus (CN). Moreover, analysis of effective connectivity inter-areal (psychophysiological interactions) showed that during preparation, concentration-related brain activity increase was dependent on Cerebellothalamo-pre-SMA-RN and Pre-SMA-CN-thalamo-M1 loops. We postulate that, while pre-SMA common to both loops is specifically involved in the movement preparation and readiness for voluntary movement through the striatum, the cerebellar lobule VI in conjunction with RN, likely through a cerebellar-rubro-olivary-cerebellar loop, might be implicated in concentration-related optimization of upcoming motor performances

Towards a systems-level view of cerebellar function::the interplay between cerebellum, basal ganglia and cortex

Contains fulltext : 170319.pdf (Publisher’s version ) (Open Access)Despite increasing evidence suggesting the cerebellum works in concert with the cortex and basal ganglia, the nature of the reciprocal interactions between these three brain regions remains unclear. This consensus paper gathers diverse recent views on a variety of important roles played by the cerebellum within the cerebello-basal ganglia-thalamo-cortical system across a range of motor and cognitive functions. The paper includes theoretical and empirical contributions, which cover the following topics: recent evidence supporting the dynamical interplay between cerebellum, basal ganglia, and cortical areas in humans and other animals; theoretical neuroscience perspectives and empirical evidence on the reciprocal influences between cerebellum, basal ganglia, and cortex in learning and control processes; and data suggesting possible roles of the cerebellum in basal ganglia movement disorders. Although starting from different backgrounds and dealing with different topics, all the contributors agree that viewing the cerebellum, basal ganglia, and cortex as an integrated system enables us to understand the function of these areas in radically different ways. In addition, there is unanimous consensus between the authors that future experimental and computational work is needed to understand the function of cerebellar-basal ganglia circuitry in both motor and non-motor functions. The paper reports the most advanced perspectives on the role of the cerebellum within the cerebello-basal ganglia-thalamo-cortical system and illustrates other elements of consensus as well as disagreements and open questions in the field

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

The role of alpha oscillations in premotor-cerebellar connectivity in motor sequence learning: Insights from transcranial alternating current stimulation

Alpha oscillations (8-13 Hz) have been suggested to play an important role in dynamic neural processes underlying learning and memory. The goal of this work was to scrutinize the role of alpha oscillations in communication within a cortico-cerebellar network implicated in motor sequence learning. To this end, we conducted two EEG experiments using a serial reaction time task. In the first experiment, we explored changes in alpha power and cross-channel alpha coherence as subjects learned a motor sequence. We found a gradual decrease in spectral alpha power over left premotor cortex (PMC) and sensorimotor cortex (SM1) during learning blocks. In addition, alpha coherence between left PMC/SM1 and left cerebellar crus I was specifically decreased during sequence learning, possibly reflecting a functional decoupling in the broader motor learning network. In the second experiment in a different cohort, we applied 10Hz transcranial alternating current stimulation (tACS), a method shown to entrain local oscillatory activity, to left M1 (lM1) and right cerebellum (rCB) during sequence learning. We observed a tendency for diminished learning following rCB tACS compared to sham, but not following lM1 tACS. Learning-related alpha power following rCB tACS was increased in left PMC, possibly reflecting increase in local inhibitory neural activity. Importantly, learning-specific alpha coherence between left PMC and right cerebellar lobule VIIb was enhanced following rCB tACS. These findings provide strong evidence for a causal role of alpha oscillations in controlling information transfer in a premotor-cerebellar loop during motor sequence learning. Our findings are consistent with a model in which sequence learning may be impaired by enhancing premotor cortical alpha oscillation via external modulation of cerebellar oscillations.:1 List of Abbreviations 2 Introduction 2.1 Motor Learning Stages 2.2 Motor Learning Tasks 2.3 Motor Learning Network 2.4 Theoretical Models of Motor Learning 2.5 Functional Connectivity of Motor Brain Regions 2.6 Effective Connectivity of Motor Brain Regions 2.7 Oscillations in Neuronal Communication 2.8 Alpha Oscillations 2.8.1 Role of Alpha Oscillations in Motor Sequence Learning 2.9 Transcranial Electric Stimulation 2.9.1 Transcranial Alternating Current Stimulation (tACS) 2.10 Summary of Study Rationale 3 Publication 4 Summary 5 List of References 6 Supplementary Materials 7 Contribution of Authors / Darstellung des eigenen Beitrags 8 Declaration of Authorship 9 Curriculum Vitae 10 Publication and Presentation 11 Acknowledgement / Danksagun

Brain activation during execution and motor imagery of novel and skilled sequential hand movements.

This experiment used functional magnetic resonance imaging (fMRI) to compare functional neuroanatomy associated with executed and imagined hand movements in novel and skilled learning phases. We hypothesized that 1 week of intensive physical practice would strengthen the motor representation of a hand motor sequence and increase the similarity of functional neuroanatomy associated with executed and imagined hand movements. During fMRI scanning, a right-hand self-paced button press sequence was executed and imagined before (NOVEL) and after (SKILLED) 1 week of intensive physical practice (n = 54; right-hand dominant). The mean execution rate was significantly faster in the SKILLED (3.8 Hz) than the NOVEL condition (2.5 Hz) (P &lt; 0.001), but there was no difference in execution errors. Activation foci associated with execution and imagery was congruent in both the NOVEL and SKILLED conditions, though activation features were more similar in the SKILLED versus NOVEL phase. In the NOVEL phase, activations were more extensive during execution than imagery in primary and secondary cortical motor volumes and the cerebellum, while during imagery activations were greater in the striatum. In the SKILLED phase, activation features within these same volumes became increasingly similar for execution and imagery, though imagery more heavily activated premotor areas, inferior parietal lobe, and medial temporal lobe, while execution more heavily activated the precentral/postcentral gyri, striatum, and cerebellum. This experiment demonstrated congruent activation of the cortical and subcortical motor system during both novel and skilled learning phases, supporting the effectiveness of motor imagery-based mental practice techniques for both the acquisition of new skills and the rehearsal of skilled movements

Cerebellar–Motor Cortex Connectivity: One or Two Different Networks?

Anterior-posterior (AP) and posterior-anterior (PA) pulses of transcranial magnetic stimulation over the primary motor cortex (M1) appear to activate distinct interneuron networks that contribute differently to two varieties of physiological plasticity and motor behaviors (Hamada et al., 2014). The AP network is thought to be more sensitive to online manipulation of cerebellar (CB) activity using transcranial direct current stimulation. Here we probed CB-M1 interactions using cerebellar-brain inhibition (CBI) on young healthy female and male individuals. Transcranial magnetic stimulation (TMS) over the cerebellum produced maximal CBI of PA-evoked EMG responses at an inter-stimulus interval of 5ms (PA-CBI), whereas the maximum effect on AP responses was at 7ms (AP-CBI), suggesting that CB-M1 pathways with different conduction times interact with AP and PA networks. In addition, paired associative stimulation using ulnar nerve stimulation and PA TMS pulses over M1, a protocol used in human studies to induce cortical plasticity, reduced PA-CBI but not AP-CBI, indicating that cortical networks process cerebellar inputs in distinct ways. Finally, PA-CBI and AP-CBI were differentially modulated after performing two different types of motor learning tasks that are known to process cerebellar input in different ways. The data presented here are compatible with the idea that applying different TMS currents to the cerebral cortex may reveal cerebellar inputs to both the premotor cortex and M1. Overall, these results suggest there are two independent CB-M1networks that contribute uniquely to different motor behaviors

Dance training shapes action perception and its neural implementation within the young and older adult brain

How we perceive others in action is shaped by our prior experience. Many factors influence brain responses when observing others in action, including training in a particular physical skill, such as sport or dance, and also general development and aging processes. Here, we investigate how learning a complex motor skill shapes neural and behavioural responses among a dance-naïve sample of 20 young and 19 older adults. Across four days, participants physically rehearsed one set of dance sequences, observed a second set, and a third set remained untrained. Functional MRI was obtained prior to and immediately following training. Participants’ behavioural performance on motor and visual tasks improved across the training period, with younger adults showing steeper performance gains than older adults. At the brain level, both age groups demonstrated decreased sensorimotor cortical engagement after physical training, with younger adults showing more pronounced decreases in inferior parietal activity compared to older adults. Neural decoding results demonstrate that among both age groups, visual and motor regions contain experience-specific representations of new motor learning. By combining behavioural measures of performance with univariate and multivariate measures of brain activity, we can start to build a more complete picture of age-related changes in experience-dependent plasticity

Temporal dynamics of cerebellar and motor cortex physiological processes during motor skill learning

Learning motor tasks involves distinct physiological processes in the cerebellum (CB) and primary motor cortex (M1). Previous studies have shown that motor learning results in at least two important neurophysiological changes: modulation of cerebellar output mediated in-part by long-term depression of parallel fiber-Purkinje cell synapse and induction of long-term plasticity (LTP) in M1, leading to transient occlusion of additional LTP-like plasticity. However, little is known about the temporal dynamics of these two physiological mechanisms during motor skill learning. Here we use non-invasive brain stimulation to explore CB and M1 mechanisms during early and late motor skill learning in humans. We predicted that early skill acquisition would be proportional to cerebellar excitability (CBI) changes, whereas later stages of learning will result in M1 LTP-like plasticity modifications. We found that early, and not late into skill training, CBI changed. Whereas, occlusion of LTP-like plasticity over M1 occurred only during late, but not early training. These findings indicate a distinct temporal dissociation in the physiological role of the CB and M1 when learning a novel skill. Understanding the role and temporal dynamics of different brain regions during motor learning is critical to device optimal interventions to augment learning

Explaining the neural activity distribution associated with discrete movement sequences:Evidence for parallel functional systems

To explore the effects of practice we scanned participants with fMRI while they were performing four-key unfamiliar and familiar sequences, and compared the associated activities relative to simple control sequences. On the basis of a recent cognitive model of sequential motor behavior (C-SMB), we propose that the observed neural activity would be associated with three functional networks that can operate in parallel and that allow (a) responding to stimuli in a reaction mode, (b) sequence execution using spatial sequence representations in a central-symbolic mode, and (c) sequence execution using motor chunk representations in a chunking mode. On the basis of this model and findings in the literature, we predicted which neural areas would be active during execution of the unfamiliar and familiar keying sequences. The observed neural activities were largely in line with our predictions, and allowed functions to be attributed to the active brain areas that fit the three above functional systems. The results corroborate C-SMB’s assumption that at advanced skill levels the systems executing motor chunks and translating key-specific stimuli are racing to trigger individual responses. They further support recent behavioral indications that spatial sequence representations continue to be used