Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across ...paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical–subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network.
► Activation likelihood estimation was used to analyze 70 motor learning experiments. ► Analysis revealed a cortico-subcortical network for motor learning. ► Consistent activations were found across subgroups with differing task demands. ► Left dorsal premotor cortex was identified as a key structure in motor learning.
Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their ...dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was significant improvement in procedural skill in both groups, with the group learning under explicit conditions showing stronger initial acquisition, and greater improvement at the 6 h retest. Immediately following acquisition, this group showed enhanced functional connectivity in networks including frontal and cerebellar areas and in the visual cortex. Thirty minutes later, enhanced connectivity was observed between cerebellar nuclei, thalamus, and basal ganglia, whereas at 6 h there was enhanced connectivity in a sensory-motor cortical network. In contrast, immediately after acquisition under implicit conditions, there was increased connectivity in a network including precentral and sensory-motor areas, whereas after 30 min a similar cerebello-thalamo-basal ganglionic network was seen as in explicit learning. Finally, 6 h after implicit learning, we found increased connectivity in medial temporal cortex, but reduction in precentral and sensory-motor areas. Our findings are consistent with predictions that two variants of the SRTT task engage dissociable functional networks, although there are also networks in common. We also show a converging and diverging pattern of flux between prefrontal, sensory-motor, and parietal areas, and subcortical circuits across a 6 h consolidation period.
Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, ...neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops.
•Different forms of learning interact within the cortex-cerebellum-basal ganglia system.•Unsupervised, supervised and reinforcement learning are often studied in isolation.•Unsupervised, supervised ...and reinforcement learning mechanisms influence each other.•Neuromodulation supports interactions between different learning mechanisms.•Cortical-subcortical hierarchies support interactions between different learning mechanisms.
Despite wide evidence suggesting anatomical and functional interactions between cortex, cerebellum and basal ganglia, the learning processes operating within them --often viewed as respectively unsupervised, supervised and reinforcement learning-- are studied in isolation, neglecting their strong interdependence. We discuss how those brain areas form a highly integrated system combining different learning mechanisms into an effective super-learning process supporting the acquisition of flexible motor behaviour. The term “super-learning” does not indicate a new learning paradigm. Rather, it refers to the fact that different learning mechanisms act in synergy as they: (a) affect neural structures often relying on the widespread action of neuromodulators; (b) act within various stages of cortical/subcortical pathways that are organised in pipeline to support multiple sensation-to-action mappings operating at different levels of abstraction; (c) interact through the reciprocal influence of the output compartments of different brain structures, most notably in the cerebello-cortical and basal ganglia-cortical loops. Here we articulate this new hypothesis and discuss empirical evidence supporting it by specifically referring to motor adaptation and sequence learning.
The cerebellum has been proposed to be a crucial component in the state estimation process that combines information from motor efferent and sensory afferent signals to produce a representation of ...the current state of the motor system. Such a state estimate of the moving human arm would be expected to be used when the arm is rapidly and skillfully reaching to a target. We now report the effects of transcranial magnetic stimulation (TMS) over the ipsilateral cerebellum as healthy humans were made to interrupt a slow voluntary movement to rapidly reach towards a visually defined target. Errors in the initial direction and in the final finger position of this reach-to-target movement were significantly higher for cerebellar stimulation than they were in control conditions. The average directional errors in the cerebellar TMS condition were consistent with the reaching movements being planned and initiated from an estimated hand position that was 138 ms out of date. We suggest that these results demonstrate that the cerebellum is responsible for estimating the hand position over this time interval and that TMS disrupts this state estimate.
Functionally related brain networks are engaged even in the absence of an overt behavior. The role of this resting state activity, evident as low-frequency fluctuations of BOLD (see 1 for review, ...2–4) or electrical 5, 6 signals, is unclear. Two major proposals are that resting state activity supports introspective thought or supports responses to future events 7. An alternative perspective is that the resting brain actively and selectively processes previous experiences 8. Here we show that motor learning can modulate subsequent activity within resting networks. BOLD signal was recorded during rest periods before and after an 11 min visuomotor training session. Motor learning but not motor performance modulated a fronto-parietal resting state network (RSN). Along with the fronto-parietal network, a cerebellar network not previously reported as an RSN was also specifically altered by learning. Both of these networks are engaged during learning of similar visuomotor tasks 9–22. Thus, we provide the first description of the modulation of specific RSNs by prior learning—but not by prior performance—revealing a novel connection between the neuroplastic mechanisms of learning and resting state activity. Our approach may provide a powerful tool for exploration of the systems involved in memory consolidation.
Previous work has highlighted the role of haptic feedback for manual dexterity, in particular for the control of precision grip forces between the index finger and thumb. It is unclear how fine motor ...skills involving more than just two digits might be affected, especially given that loss of sensation from the hand affects many neurological patients, and impacts on everyday actions. To assess the functional consequences of haptic deficits on multi-digit grasp of objects, we studied the ability of three rare individuals with permanent large-fibre sensory loss involving the entire upper limb. All three reported difficulties in everyday manual actions (ABILHAND questionnaire). Their performance in a reach–grasp–lift task was compared to that of healthy controls. Twenty objects of varying shape, mass, opacity and compliance were used. In the reach-to-grasp phase, we found slower movement, larger grip aperture and less dynamic modulation of grip aperture in deafferented participants compared to controls. Hand posture during the lift phase also differed; deafferented participants often adopted hand postures that may have facilitated visual guidance, and/or reduced control complexity. For example, they would extend fingers that were not in contact with the object, or fold these fingers into the palm of the hand. Variability in hand postures was increased in deafferented participants, particularly for smaller objects. Our findings provide new insights into how the complex control required for whole hand actions is compromised by loss of haptic feedback, whose contribution is, thus, highlighted.
Healthy ageing involves degeneration of the neuromuscular system which impacts movement control and proprioception. Yet the relationship between these sensory and motor deficits in upper limb ...reaching has not been examined in detail. Recently, we reported that age-related proprioceptive deficits were unrelated to accuracy in rapid arm movements, but whether this applied in motor tasks more heavily dependent on proprioceptive feedback was not clear. To address this, we have tested groups of younger and older adults on a force-field adaptation task under either full or limited visual feedback conditions and examined how performance was related to dynamic proprioceptive acuity. Adaptive performance was similar between the age groups, regardless of visual feedback condition, although older adults showed increased after-effects. Physically inactive individuals made larger systematic (but not variable) proprioceptive errors, irrespective of age. However, dynamic proprioceptive acuity was unrelated to adaptation and there was no consistent evidence of proprioceptive recalibration with adaptation to the force-field for any group. Finally, in spite of clear age-dependent loss of spatial working memory capacity, we found no relationship between memory capacity and adaptive performance or proprioceptive acuity. Thus, non-clinical levels of deficit in dynamic proprioception, due to age or physical inactivity, do not affect force-field adaptation, even under conditions of limited visual feedback that might require greater proprioceptive control.
Mounting evidence indicates that posterolateral portions of the cerebellum (right Crus I/II) contribute to language processing, but the nature of this role remains unclear. Based on a well-supported ...theory of cerebellar motor function, which ascribes to the cerebellum a role in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II supports prediction of upcoming sentence content. We tested this hypothesis using event-related fMRI in male and female human subjects by manipulating the predictability of written sentences. Our design controlled for motor planning and execution, as well as for linguistic features and working memory load; it also allowed separation of the prediction interval from the presentation of the final sentence item. In addition, three further fMRI tasks captured semantic, phonological, and orthographic processing to shed light on the nature of the information processed. As hypothesized, activity in right posterolateral cerebellum correlated with the predictability of the upcoming target word. This cerebellar region also responded to prediction error during the outcome of the trial. Further, this region was engaged in phonological, but not semantic or orthographic, processing. This is the first imaging study to demonstrate a right cerebellar contribution in language comprehension independently from motor, cognitive, and linguistic confounds. These results complement our work using other methodologies showing cerebellar engagement in linguistic prediction and suggest that internal modeling of phonological representations aids language production and comprehension.
The cerebellum is traditionally seen as a motor structure that allows for smooth movement by predicting upcoming signals. However, the cerebellum is also consistently implicated in nonmotor functions such as language and working memory. Using fMRI, we identify a cerebellar area that is active when words are predicted and when these predictions are violated. This area is active in a separate task that requires phonological processing, but not in tasks that require semantic or visuospatial processing. Our results support the idea of prediction as a unifying cerebellar function in motor and nonmotor domains. We provide new insights by linking the cerebellar role in prediction to its role in verbal working memory, suggesting that these predictions involve phonological processing.
Cerebellar transcranial direct current stimulation (ctDCS) is known to enhance adaptation to a novel visual rotation (visuomotor adaptation), and it is suggested to hold promise as a therapeutic ...intervention. However, it is unknown whether this effect is robust across varying task parameters. This question is crucial if ctDCS is to be used clinically, because it must have a consistent and robust effect across a relatively wide range of behaviors. The aim of this study was to examine the effect of ctDCS on visuomotor adaptation across a wide range of task parameters that were systematically varied. Therefore, 192 young healthy individuals participated in 1 of 7 visuomotor adaptation experiments in either an anodal or sham ctDCS group. Each experiment examined whether ctDCS had a positive effect on adaptation when a unique feature of the task was altered: position of the monitor, offline tDCS, use of a tool, and perturbation schedule. Although we initially replicated the previously reported positive effect of ctDCS on visuomotor adaptation, this was not maintained during a second replication study or across a large range of varying task parameters. At the very least, this may call into question the validity of using ctDCS within a clinical context where a robust and consistent effect across behavior would be required.
Cerebellar transcranial direct current stimulation (ctDCS) is known to enhance motor adaptation and thus holds promise as a therapeutic intervention. However, understanding the reliability of ctDCS across varying task parameters is crucial. To examine this, we investigated whether ctDCS enhanced visuomotor adaptation across a range of varying task parameters. We found ctDCS to have no consistent effect on visuomotor adaptation, questioning the validity of using ctDCS within a clinical context.
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