Christopher Steele

Parallel contributions of cerebellar, striatal and M1 mechanisms to motor sequence learning.

When learning a new motor sequence, we must execute the correct order of movements while simultaneously optimizing sensorimotor parameters such as trajectory, timing, velocity and force. Neurophysiological studies in animals and humans have identified the major brain regions involved in sequence learning, including the motor cortex (M1), basal ganglia (BG) and cerebellum. Current models link these regions to different stages of learning (early vs. late) or different components of performance (spatial vs. sensorimotor). At the same time, research in motor control has given rise to the concept that internal models at different levels of the motor system may contribute to learning. The goal of this review is to develop a new framework for motor sequence learning that combines stage and component models within the context of internal models. To do this, we review behavioral and neuroimaging studies in humans and neurophysiological studies in animals. Based on this evidence, we present a model proposing that sequence learning is underwritten by parallel, interacting processes, including internal model formation and sequence representation, that are instantiated in specific cerebellar, BG or M1 mechanisms depending on task demands and the stage of learning. The striatal system learns predictive stimulus-response associations and is critical for motor chunking. The role of the cerebellum is to acquire the optimal internal model for sequence performance in a particular context, and to contribute to error correction and control of on-going movement. M1 acts to store the representation of a learned sequence, likely as part of a distributed network including the parietal lobe and premotor cortex.

Early Musical Training and White-Matter Plasticity in the Corpus Callosum: Evidence for a Sensitive Period

Training during a sensitive period in development may have greater effects on brain structure and behavior than training later in life. Musicians are an excellent model for investigating sensitive periods because training starts early and can be quantified. Previous studies suggested that early training might be related to greater amounts of white matter in the corpus callosum, but did not control for length of training or identify behavioral correlates of structural change. The current study compared white-matter organization using diffusion tensor imaging in early- and late-trained musicians matched for years of training and experience. We found that early-trained musicians had greater connectivity in the posterior midbody/isthmus of the corpus callosum and that fractional anisotropy in this region was related to age of onset of training and sensorimotor synchronization performance. We propose that training before the age of 7 years results in changes in white-matter connectivity that may serve as a scaffold upon which ongoing experience can build.

Specific Increases within Global Decreases: A Functional Magnetic Resonance Imaging Investigation of Five Days of Motor Sequence Learning

Our capacity to learn movement sequences is fundamental to our ability to interact with the environment. Although different brain networks have been linked with different stages of learning, there is little evidence for how these networks change across learning. We used functional magnetic resonance imaging to identify the specific contributions of the cerebellum and primary motor cortex (M1) during early learning, consolidation, and retention of a motor sequence task. Performance was separated into two components: accuracy (the more explicit, rapidly learned, stimulus–response association component) and synchronization (the more procedural, slowly learned component). The network of brain regions active during early learning was dominated by the cerebellum, premotor cortex, basal ganglia, presupplementary motor area, and supplementary motor area as predicted by existing models. Across days of learning, as performance improved, global decreases were found in the majority of these regions. Importantly, within the context of these global decreases, we found specific regions of the left M1 and right cerebellar VIIIA/VIIB that were positively correlated with improvements in synchronization performance. Improvements in accuracy were correlated with increases in hippocampus, BA 9/10, and the putamen. Thus, the two behavioral measures, accuracy and synchrony, were found to be related to two different sets of brain regions—suggesting that these networks optimize different components of learning. In addition, M1 activity early on day 1 was shown to be predictive of the degree of consolidation on day 2. Finally, functional connectivity between M1 and cerebellum in late learning points to their interaction as a mechanism underlying the long-term representation and expression of a well learned skill.

Structural correlates of skilled performance on a motor sequence task

The brain regions functionally engaged in motor sequence performance are well-established, but the structural characteristics of these regions and the fiber pathways involved have been less well studied. In addition, relatively few studies have combined multiple magnetic resonance imaging (MRI) and behavioral performance measures in the same sample. Therefore, the current study used diffusion tensor imaging (DTI), probabilistic tractography, and voxel-based morphometry (VBM) to determine the structural correlates of skilled motor performance. Further, we compared these findings with fMRI results in the same sample. We correlated final performance and rate of improvement measures on a temporal motor sequence task (TMST) with skeletonized fractional anisotropy (FA) and whole brain gray matter (GM) volume. Final synchronization performance was negatively correlated with FA in white matter (WM) underlying bilateral sensorimotor cortex—an effect that was mediated by a positive correlation with radial diffusivity. Multi-fiber tractography indicated that this region contained crossing fibers from the corticospinal tract (CST) and superior longitudinal fasciculus (SLF). The identified SLF pathway linked parietal and auditory cortical regions that have been shown to be functionally engaged in this task. Thus, we hypothesize that enhanced synchronization performance on this task may be related to greater fiber integrity of the SLF. Rate of improvement on synchronization was positively correlated with GM volume in cerebellar lobules HVI and V—regions that showed training-related decreases in activity in the same sample. Taken together, our results link individual differences in brain structure and function to motor sequence performance on the same task. Further, our study illustrates the utility of using multiple MR measures and analysis techniques to specify the interpretation of structural findings.

Impairment of emotional facial expression and prosody discrimination due to ischemic cerebellar lesions

A growing literature points to a specific role of the cerebellum in affect processing. However, understanding of affect processing disturbances following discrete cerebellar lesions is limited. We administered the Tübingen Affect Battery to assess recognition of emotional facial expression and emotional prosody in 15 patients with a cerebellar infarction and 10 age-matched controls. On emotional facial expression tasks, patients compared to controls showed impaired selection and matching of facial affect. On prosody tasks, patients showed marked impairments in naming affect and discriminating incongruencies. These deficits were more pronounced for negative affects. Our results confirm a significant role of the cerebellum in processing emotional recognition, a component of social cognition.

Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity.

Over the last two decades, numerous human MRI studies of neuroplasticity have shown compelling evidence for extensive and rapid experience-induced brain plasticity in vivo. To date, most of these studies have consisted of simply detecting a difference in structural or functional images with little concern for their lack of biological specificity. Recent reviews and public debates have stressed the need for advanced imaging techniques to gain a better understanding of the nature of these differences - characterizing their extent in time and space, their underlying biological and network dynamics. The purpose of this article is to give an overview of advanced imaging techniques for an audience of cognitive neuroscientists that can assist them in the design and interpretation of future MRI studies of neuroplasticity. The review encompasses MRI methods that probe the morphology, microstructure, function, and connectivity of the brain with improved specificity. We underline the possible physiological underpinnings of these techniques and their recent applications within the framework of learning- and experience-induced plasticity in healthy adults. Finally, we discuss the advantages of a multi-modal approach to gain a more nuanced and comprehensive description of the process of learning.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Effect of transcranial direct current stimulation (tDCS) during complex whole body motor skill learning

The aim of the study was to investigate tDCS effects on motor skill learning in a complex whole body dynamic balance task (DBT). We hypothesized that tDCS over the supplementary motor area (SMA), a region that is known to be involved in the control of multi-joint whole body movements, will result in polarity specific changes in DBT learning. In a randomized sham-controlled, double-blinded parallel design, we applied 20 min of tDCS over the supplementary motor area (SMA) and prefrontal cortex (PFC) while subjects performed a DBT. Anodal tDCS over SMA with the cathode placed over contralateral PFC impaired motor skill learning of the DBT compared to sham. This effect was still present on the second day of training. Reversing the polarity (cathode over SMA, anode over PFC) did not affect motor skill learning neither on the first nor on the second day of training. To better disentangle whether the impaired motor skill learning was due to a modulation of SMA or PFC, we performed an additional control experiment. Here, we applied anodal tDCS over SMA together with a larger and presumably more ineffective electrode (cathode) over PFC. Interestingly this alternative tDCS electrode setup did not affect the outcome of DBT learning. Our results provide novel evidence that a modulation of the (right) PFC seems to impair complex multi-joint motor skill learning. Hence, future studies should take the positioning of both tDCS electrodes into account when investigating complex motor skill learning.

Augmenting mirror visual feedback-induced performance improvements in older adults

Previous studies have indicated that age‐related behavioral alterations are not irreversible but are subject to amelioration through specific training interventions. Both training paradigms and non‐invasive brain stimulation (NIBS) can be used to modulate age‐related brain alterations and thereby influence behavior. It has been shown that mirror visual feedback (MVF) during motor skill training improves performance of the trained and untrained hands in young adults. The question remains of whether MVF also improves motor performance in older adults and how performance improvements can be optimised via NIBS. Here, we sought to determine whether anodal transcranial direct current stimulation (a‐tDCS) can be used to augment MVF‐induced performance improvements in manual dexterity. We found that older adults receiving a‐tDCS over the right primary motor cortex (M1) during MVF showed superior performance improvements of the (left) untrained hand relative to sham stimulation. An additional control experiment in participants receiving a‐tDCS over the right M1 only (without MVF/motor training of the right hand) revealed no significant behavioral gains in the left (untrained) hand. On the basis of these findings, we propose that combining a‐tDCS with MVF might be relevant for future clinical studies that aim to optimise the outcome of neurorehabilitation.

Instrument specific use-dependent plasticity shapes the anatomical properties of the corpus callosum: a comparison between musicians and non-musicians

Long-term musical expertise has been shown to be associated with a number of functional and structural brain changes, making it an attractive model for investigating use-dependent plasticity in humans. Physiological interhemispheric inhibition (IHI) as examined by transcranial magnetic stimulation has been shown to be correlated with anatomical properties of the corpus callosum as indexed by fractional anisotropy (FA). However, whether or not IHI or the relationship between IHI and FA in the corpus callosum can be modified by different musical training regimes remains largely unknown. We investigated this question in musicians with different requirements for bimanual finger movements (piano and string players) and non-expert controls. IHI values were generally higher in musicians, but differed significantly from non-musicians only in string players. IHI was correlated with FA in the posterior midbody of the corpus callosum across all participants. Interestingly, subsequent analyses revealed that this relationship may indeed be modulated by different musical training regimes. Crucially, while string players had greater IHI than non-musicians and showed a positive structure-function relationship, the amount of IHI in pianists was comparable to that of non-musicians and there was no significant structure-function relationship. Our findings indicate instrument specific use-dependent plasticity in both functional (IHI) and structural (FA) connectivity of motor related brain regions in musicians.