The cerebellum plays an important role in motor learning as part of a cortico-striato-cerebellar network. Patients with cerebellar degeneration typically show impairments in different aspects of motor learning, including implicit motor sequence learning. How cerebellar dysfunction affects interactions in this cortico-striato-cerebellar network is poorly understood. The present study investigated the effect of cerebellar degeneration on activity in causal interactions between cortical and subcortical regions involved in motor learning. We found that cerebellar patients showed learning-related increase in activity in two regions known to be involved in learning and memory, namely parahippocampal cortex and cerebellar Crus I. The cerebellar activity increase was observed in non-learners of the patient group whereas learners showed an activity decrease. Dynamic causal modeling analysis revealed that modulation of M1 to cerebellum and putamen to cerebellum connections were significantly more negative for sequence compared to random blocks in controls, replicating our previous results, and did not differ in patients. In addition, a separate analysis revealed a similar effect in connections from SMA and PMC to M1 bilaterally. Again, neural network changes were associated with learning performance in patients. Specifically, learners showed a negative modulation from right SMA to right M1 that was similar to controls, whereas this effect was close to zero in non-learners. These results highlight the role of cerebellum in motor learning and demonstrate the functional role cerebellum plays as part of the cortico-striato-cerebellar network.

Theoretical models and experimental evidence suggest that cortico-striatal-cerebellar networks play a crucial role in mediating motor sequence learning. However, how these different regions interact in order to mediate learning is less clear. In the present fMRI study, we used dynamic causal modeling to investigate effective connectivity within the cortico-striatal-cerebellar network while subjects performed a serial reaction time task. Using Bayesian model selection and family wise inference, we show that the cortico-cerebellar loop had higher model evidence than the cortico-striatal loop during motor learning. We observed significant negative modulatory effects on the connections from M1 to cerebellum bilaterally during learning. The results suggest that M1 causes the observed decrease in activity in the cerebellum as learning progresses. The current study stresses the significant role that the cerebellum plays in motor learning as previously suggested by fMRI studies in healthy subjects as well as behavioral studies in patients with cerebellar dysfunction. These results provide important insight into the neural mechanisms underlying motor learning.

Dystonia is conceptualized as a network disorder involving basal ganglia, thalamus, sensorimotor cortex and the cerebellum. The cerebellum has been implicated in dystonia pathophysiology, but studies testing cerebellar function in dystonia patients have provided equivocal results. This study aimed to further elucidate motor network deficits in cervical dystonia with special interest in the role of the cerebellum. To this end we investigated motor learning tasks, that differ in their dependence on cerebellar and basal ganglia functioning. In 18 cervical dystonia patients and 18 age matched healthy controls we measured implicit motor sequence learning using a 12-item serial reaction time task mostly targeting basal ganglia circuitry and motor adaptation and eyeblink conditioning as markers of cerebellar functioning. ANOVA showed that motor sequence learning was overall impaired in cervical dystonia (p = 0.01). Moreover, unlike healthy controls, patients did not show a learning effect in the first part of the experiment. Visuomotor adaptation and eyeblink conditioning were normal. In conclusion, these data lend support to the notion that motor learning deficits in cervical dystonia relate to basal ganglia-thalamo-cortical loops rather than being a result of defective cerebellar circuitry.

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 study 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.

The fast and slow learning stages of motor sequence learning are suggested to be realized through plasticity in a distributed cortico-striato-cerebellar network. To better understand the causal interactions within this network in the different phases of motor sequence learning, we investigated the effective connectivity within this network during encoding (Day 1) and after consolidation (Day 2) of a serial reaction time task. Using Dynamic Causal Modelling of fMRI data, we found general changes in network connections reflected in altered input nodes and endogenous connections when comparing the early and fast learning session to the late and slow learning session. Whereas encoding of a motor memory early on modulated several connections in a distributed network, slow learning resulted in a pruned network. More specifically, we found a negative modulation of connections from left M1 to right cerebellum, right premotor cortex to left cerebellum, as well as backward connections from putamen to cerebellum bilaterally in the encoding session. While connections during pre-sleep were significantly modulated by learning per se (i.e., specifically modulated by performance on sequence conditions), the connections observed after sleep were rather modulated by general performance (i.e., modulated by performance on both sequence and random conditions). A forward connection from left cerebellum to right putamen was found to be consistent across participants for the sequence condition only during slow learning. Together these findings suggest that whereas encoding in the fast learning phase requires plasticity in several connections implementing both motor and perceptual learning components, slow learning is mediated through connectivity from left cerebellum to right putamen.

Non-invasive transcranial stimulation of cerebellum and primary motor cortex (M1) has been shown to enhance motor learning. However, the mechanisms by which stimulation improves learning remain largely unknown. Here, we sought to shed light on the neural correlates of transcranial direct current stimulation (tDCS) during motor learning by simultaneously recording functional magnetic resonance imaging (fMRI). We found that right cerebellar tDCS, but not left M1 tDCS, led to enhanced sequence learning in the serial reaction time task. Performance was also improved following cerebellar tDCS compared to sham in a sequence production task, reflecting superior training effects persisting into the post-training period. These behavioral effects were accompanied by increased learning-specific activity in right M1, left cerebellum lobule VI, left inferior frontal gyrus and right inferior parietal lobule during cerebellar tDCS compared to sham. Despite the lack of group-level changes comparing left M1 tDCS to sham, activity increase in right M1, supplementary motor area, and bilateral middle frontal cortex, under M1 tDCS, was associated with better sequence performance. This suggests that lack of group effects in M1 tDCS relate to inter-individual variability in learning-related activation patterns. We further investigated how tDCS modulates effective connectivity in the cortico-striato-cerebellar learning network. Using dynamic causal modelling, we found altered connectivity patterns during both M1 and cerebellar tDCS when compared to sham. Specifically, during cerebellar tDCS, negative modulation of a connection from putamen to cerebellum was decreased for sequence learning only, effectively leading to decreased inhibition of the cerebellum. These results show specific effects of cerebellar tDCS on functional activity and connectivity in the motor learning network and may facilitate the optimization of motor rehabilitation involving cerebellar non-invasive stimulation.