scholarly journals Cerebellar degeneration reduces memory resilience after extended training

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.

2021 ◽  
Author(s):  
ATP Jäger ◽  
JM Huntenburg ◽  
SA Tremblay ◽  
U Schneider ◽  
S Grahl ◽  
...  

AbstractIn motor learning, sequence-specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific increases in functional connectivity during fast learning in the sensorimotor territory of the internal segment of right globus pallidus (GPi), and sequence-specific decreases in right supplementary motor area (SMA) in overall learning. We found that connectivity changes in key regions of the motor network including the superior parietal cortex (SPC) and primary motor cortex (M1) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA and GPi that has previously been identified in online task-based learning studies in humans and primates, and extends it to resting state network changes after sequence-specific MSL. Finally, our results shed light on a timing-specific plasticity mechanism between GPi and SMA following MSL.


2017 ◽  
Vol 16 ◽  
pp. 66-78 ◽  
Author(s):  
Elinor Tzvi ◽  
Christoph Zimmermann ◽  
Richard Bey ◽  
Thomas F. Münte ◽  
Matthias Nitschke ◽  
...  

2006 ◽  
Vol 44 (5) ◽  
pp. 795-798 ◽  
Author(s):  
Catherine J. Stoodley ◽  
Edward P.D. Harrison ◽  
John F. Stein

2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Claire Piochon ◽  
Alexander D. Kloth ◽  
Giorgio Grasselli ◽  
Heather K. Titley ◽  
Hisako Nakayama ◽  
...  

Author(s):  
Shlomi Haar ◽  
A. Aldo Faisal

AbstractMany recent studies found signatures of motor learning in neural Beta oscillations (13– 30Hz), and specifically in the post-movement Beta rebound (PMBR). All these studies were in controlled laboratory-tasks in which the task designed to induce the studied learning mechanism. Interestingly, these studies reported opposing dynamics of the PMBR magnitude over learning for the error-based and reward-based tasks (increase versus decrease, respectively). Here we explored the PMBR dynamics during real-world motor-skill-learning in a billiards task using mobile-brain-imaging. Our EEG recordings highlight the opposing dynamics of PMBR magnitudes (increase versus decrease) between different subjects performing the same task. The groups of subjects, defined by their neural dynamics, also showed behavioural differences expected for different learning mechanisms. Our results suggest that when faced with the complexity of the real-world different subjects might use different learning mechanisms for the same complex task. We speculate that all subjects combine multi-modal mechanisms of learning, but different subjects have different predominant learning mechanisms.


2019 ◽  
Vol 121 (4) ◽  
pp. 1575-1583 ◽  
Author(s):  
Susan K. Coltman ◽  
Joshua G. A. Cashaback ◽  
Paul L. Gribble

Recent work suggests that the rate of learning in sensorimotor adaptation is likely not fixed, but rather can change based on previous experience. One example is savings, a commonly observed phenomenon whereby the relearning of a motor skill is faster than the initial learning. Sensorimotor adaptation is thought to be driven by sensory prediction errors, which are the result of a mismatch between predicted and actual sensory consequences. It has been proposed that during motor adaptation the generation of sensory prediction errors engages two processes (fast and slow) that differ in learning and retention rates. We tested the idea that a history of errors would influence both the fast and slow processes during savings. Participants were asked to perform the same force field adaptation task twice in succession. We found that adaptation to the force field a second time led to increases in estimated learning rates for both fast and slow processes. While it has been proposed that savings is explained by an increase in learning rate for the fast process, here we observed that the slow process also contributes to savings. Our work suggests that fast and slow adaptation processes are both responsive to a history of error and both contribute to savings. NEW & NOTEWORTHY We studied the underlying mechanisms of savings during motor adaptation. Using a two-state model to represent fast and slow processes that contribute to motor adaptation, we found that a history of error modulates performance in both processes. While previous research has attributed savings to only changes in the fast process, we demonstrated that an increase in both processes is needed to account for the measured behavioral data.


2019 ◽  
Vol 133 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Bruno Ouimet ◽  
Élise Pépin ◽  
Yan Bergeron ◽  
Laure Chagniel ◽  
Jean Martin Beaulieu ◽  
...  

Author(s):  
John W. Krakauer

Rehabilitation is a form of directed training and is therefore predicated on the idea that patients respond to such training by learning. Current concepts in motor learning are reviewed. Recovery is not synonymous with re-learning and that it is important to be specific about what learning mechanism is being targeted by any given therapy. There is a unique milieu of heightened plasticity post-stroke that is responsible for reduction in impairment both through spontaneous biological recovery and increased responsiveness to training. In the chronic phase of stroke, plasticity returns to normal levels and learning for the most part only leads to task-specific compensation. Thus, new forms of intervention may have quite distinct effects depending on whether they are initiated in the sensitive period after stroke or in the chronic phase. It is to be hoped that new pharmacological and non-invasive brain stimulation approaches will allow the post-stroke sensitive period to be augmented, extended, and re-opened.


2013 ◽  
Vol 33 (39) ◽  
pp. 15408-15413 ◽  
Author(s):  
Nicolas Gutierrez-Castellanos ◽  
Beerend H.J. Winkelman ◽  
Leonardo Tolosa-Rodriguez ◽  
Benjamin Devenney ◽  
Roger H. Reeves ◽  
...  

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