scholarly journals Cerebellar degeneration affects cortico-cortical connectivity in motor learning networks

2017 ◽  
Vol 16 ◽  
pp. 66-78 ◽  
Author(s):  
Elinor Tzvi ◽  
Christoph Zimmermann ◽  
Richard Bey ◽  
Thomas F. Münte ◽  
Matthias Nitschke ◽  
...  
2017 ◽  
Vol 128 (10) ◽  
pp. e317
Author(s):  
E. Tzvi-Minker ◽  
R. Bey ◽  
C. Zimmermann ◽  
M. Nitschke ◽  
T. Münte ◽  
...  

2017 ◽  
Author(s):  
Elinor Tzvi ◽  
Christoph Zimmermann ◽  
Richard Bey ◽  
Thomas F. Muente ◽  
Matthias Nitschke ◽  
...  

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 modelling 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.


2020 ◽  
Author(s):  
Thomas Hulst ◽  
Ariels Mamlins ◽  
Maarten Frens ◽  
Dae-In Chang ◽  
Sophia L. Göricke ◽  
...  

AbstractPatients with cerebellar ataxia suffer from various motor learning deficits hampering their ability to adapt movements to perturbations. Motor adaptation is hypothesized to be the result of two subsystems: a fast learning mechanism and a slow learning mechanism. We tested whether training paradigms that emphasize slow learning could alleviate motor learning deficits of cerebellar patients. Twenty patients with cerebellar degeneration and twenty age-matched controls were trained on a visuomotor task under four different paradigms: a standard paradigm, gradual learning, overlearning and long intertrial interval learning. Expectedly, cerebellar participants performed worse compared to control participants. However, both groups demonstrated elevated levels of spontaneous recovery in the overlearning paradigm, which we saw as evidence for enhanced motor memory retention after extended training. Behavioral differences were only found between the overlearning paradigm and standard learning paradigm in both groups.Modelling suggested that, in control participants, additional spontaneous recovery was the result of higher retention rates of the slow system as well as reduced learning rates of the slow system. In cerebellar participants however, additional spontaneous recovery appeared only to be the result of higher retention rates of the slow system and not reduced learning rates of the slow system. Thus, memory resilience was reduced in cerebellar participants and elevated levels of slow learning were less resilient against washing out. Our results suggest that cerebellar patients might still benefit from extended training through use-dependent learning, which could be leveraged to develop more effective therapeutic strategies.


2018 ◽  
Vol 115 (28) ◽  
pp. 7428-7433 ◽  
Author(s):  
Takeru Honda ◽  
Soichi Nagao ◽  
Yuji Hashimoto ◽  
Kinya Ishikawa ◽  
Takanori Yokota ◽  
...  

In performing skillful movement, humans use predictions from internal models formed by repetition learning. However, the computational organization of internal models in the brain remains unknown. Here, we demonstrate that a computational architecture employing a tandem configuration of forward and inverse internal models enables efficient motor learning in the cerebellum. The model predicted learning adaptations observed in hand-reaching experiments in humans wearing a prism lens and explained the kinetic components of these behavioral adaptations. The tandem system also predicted a form of subliminal motor learning that was experimentally validated after training intentional misses of hand targets. Patients with cerebellar degeneration disease showed behavioral impairments consistent with tandemly arranged internal models. These findings validate computational tandemization of internal models in motor control and its potential uses in more complex forms of learning and cognition.


2018 ◽  
Vol 39 (10) ◽  
pp. 3836-3853 ◽  
Author(s):  
Pablo I. Burgos ◽  
Juan J. Mariman ◽  
Scott Makeig ◽  
Gonzalo Rivera-Lillo ◽  
Pedro E. Maldonado

2019 ◽  
Vol 121 (3) ◽  
pp. 729-731 ◽  
Author(s):  
S. A. L. Jayasinghe

Action observation involves the observation of an action followed by an attempt to replicate it. Recent studies show that increased sensorimotor cortical connectivity improves motor performance via observation and that priming the sensory system before observation enhances the effects of observation-based learning. Understanding the role of the sensory system is, therefore, critical for rehabilitation of movement disorders that have a sensory deficit.


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