Delineating the cortico-striatal-cerebellar network in implicit motor sequence learning

Tzvi, Elinor; Münte, Thomas F.; Krämer, Ulrike M.

doi:10.1016/j.neuroimage.2014.03.004

Cited by 53 publications

(71 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This finding is in line with numerous neuroimaging studies showing that the motor component of learning recruits motorrelated structures with associated striatal and cerebellar regions (Bischoff-Grethe et al, 2004;Grafton et al, 1998Grafton et al, , 2002Hikosaka et al, 2002;Hikosaka et al, 1999;Romei et al, 2009). In the same vein, a recent study showed that a specific pattern of effective connectivity between the motor cortex and the cerebellum support the development of the motor component during initial motor sequence learning (Tzvi et al, 2014). Finally, our findings concord with the evidence that the motor cortex is one of the potential sites involved in the development of the motor representation (Grafton et al, 1998;Karni et al, 1995), which codes for an effector-dependent and movement-based skill realized under egocentric coordinates (Bapi et al, 2000(Bapi et al, , 2006Grafton et al, 1998Grafton et al, , 2002Verwey and Clegg, 2005).…”

Section: Cerebral Correlates Of Allocentric and Egocentric Representasupporting

confidence: 87%

“…The concept of reciprocal interactions between memory systems has been supported by a series of recent behavioral studies showing interference between declarative and procedural learning, suggesting that these memory systems share common neural networks (Brown and Robertson, 2007a,b;Cohen and Robertson, 2011;Keisler and Shadmehr, 2010; see Robertson, 2012 for a review). Furthermore, in the framework of procedural memory, neuroimaging investigations of functional activation and connectivity associated to motor sequence learning have revealed that both the corticostriato-cerebellar (e.g., Coynel et al, 2010;Debas et al, 2010Debas et al, , 2014Tzvi et al, 2014;see Doyon et al, 2009;Doyon and Benali, 2005;Doyon et al, 2003; for reviews) and hippocampo-cortical networks (Albouy et al, 2008(Albouy et al, , 2012(Albouy et al, , 2013c; see Albouy et al, 2013b for a review) are not only involved in the acquisition, but also in the consolidation of motor sequence memories. However, the respective roles of the striatum and the hippocampus in motor sequence learning and their respective link with subsequent sleep-related changes in performance, an indicator of memory consolidation, remain unclear.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Maintaining vs. enhancing motor sequence memories: Respective roles of striatal and hippocampal systems

et al. 2015

View full text Add to dashboard Cite

Section: Cerebral Correlates Of Allocentric and Egocentric Representasupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Maintaining vs. enhancing motor sequence memories: Respective roles of striatal and hippocampal systems

et al. 2015

View full text Add to dashboard Cite

“…Finally, our results are consistent with recent work implicating cerebellum in sequence learning (e.g. serial reaction task) (Dirnberger et al, 2013;Tzvi et al, 2014) and predictive processing (Kotz et al, 2014;Leggio and Molinari, 2014).…”

Section: Discussionsupporting

confidence: 92%

Learning temporal statistics for sensory predictions in mild cognitive impairment

et al. 2015

View full text Add to dashboard Cite

Training is known to improve performance in a variety of perceptual and cognitive skills. However, there is accumulating evidence that mere exposure (i.e. without supervised training) to regularities (i.e. patterns that co-occur in the environment) facilitates our ability to learn contingencies that allow us to interpret the current scene and make predictions about future events. Recent neuroimaging studies have implicated fronto-striatal and medial temporal lobe brain regions in the learning of spatial and temporal statistics. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are characterized by hippocampal dysfunction are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards orientated gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. However, our fMRI results demonstrate that MCI-AD patients recruit an alternate circuit to hippocampus to succeed in learning of predictive structures. In particular, we observed stronger learning-dependent activations for structured sequences in frontal, subcortical and cerebellar regions for patients compared to age-matched controls. Thus, our findings suggest a cortico-striatal-cerebellar network that may mediate the ability for predictive learning despite hippocampal dysfunction in MCI-AD.

show abstract

“…Therefore, understanding the functional role of multiple brain regions in motor learning requires investigation of distributed brain networks and connectivity patterns. Task-driven functional connectivity (Coynel et al, 2010) and effective connectivity (Ma et al, 2011;Tzvi et al, 2014) have indicated changes in the connections between M1 and the cerebellum during motor learning (Raymond et al, 1996;Inoue et al, 2000;Della-Maggiore et al, 2009). Alternatively, cortico-cerebellar connectivity has been indirectly assessed by evaluating changes in somatosensory evoked potentials (SEP) or motor evoked potentials (MEP) (Haavik and Murphy, 2013;Andrew et al, 2015;Baarbé et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Upregulation of cortico-cerebellar functional connectivity after motor learning

et al. 2016

View full text Add to dashboard Cite

Interactions between the cerebellum and primary motor cortex are crucial for the acquisition of new motor skills. Recent neuroimaging studies indicate that learning motor skills is associated with subsequent modulation of resting-state functional connectivity in the cerebellar and cerebral cortices. The neuronal processes underlying the motor-learning induced plasticity are not well understood. Here, we investigate changes in functional connectivity in source-reconstructed electroencephalography (EEG) following the performance of a single session of a dynamic force task in twenty young adults. Source activity was reconstructed in 112 regions of interest (ROIs) and the functional connectivity between all ROIs was estimated using imaginary part of the coherence. Significant changes in resting-state connectivity were assessed using partial least squares (PLS). We found that subjects adapted their motor performance during the training session and showed improved accuracy but with slower movement times. A number of connections were significantly upregulated after motor training, principally involving connections within the cerebellum and between the cerebellum and motor cortex. Increased connectivity was confined to specific frequency ranges in the mu and beta bands. Post-hoc analysis of the phase spectra of these cerebellar and corticocerebellar connections revealed an increased phase-lag between motor cortical and cerebellar activity following motor practice. These findings show a reorganization of intrinsic corticocerebellar connectivity related to motor adaption and demonstrate the potential of EEG connectivity analysis in source-space to reveal the neuronal processes that underpin neural plasticity.

show abstract

Delineating the cortico-striatal-cerebellar network in implicit motor sequence learning

Cited by 53 publications

References 65 publications

Maintaining vs. enhancing motor sequence memories: Respective roles of striatal and hippocampal systems

Maintaining vs. enhancing motor sequence memories: Respective roles of striatal and hippocampal systems

Learning temporal statistics for sensory predictions in mild cognitive impairment

Upregulation of cortico-cerebellar functional connectivity after motor learning

Contact Info

Product

Resources

About