Motor learning in man: A review of functional and clinical studies

Abstract

This chapter reviews results of clinical and functional imaging studies which investigated the time-course of cortical and subcortical activation during the acquisition of motor a skill.

During the early phases of learning by trial and error, activation in prefrontal areas, especially in the dorsolateral prefrontal cortex, is has been reported. The role of these areas is presumably related to explicit working memory and the establishment of a novel association between visual cues and motor commands. Furthermore, motor associated areas of the right hemisphere and distributed cerebellar areas reveal strong activation during the early motor learning. Activation in superior–posterior parietal cortex presumably arises from visuospatial processes, while sensory feedback is coded in the anterior–inferior parietal cortex and the neocerebellar structures.

With practice, motor associated areas of the left-hemisphere reveal increased activity. This shift to the left hemisphere has been observed regardless of the hand used during training, indicating a left-hemispheric dominance in the storage of visuomotor skills. Concerning frontal areas, learned actions of sequential character are represented in the caudal part of the supplementary motor area (SMA proper), whereas the lateral premotor cortex appears to be responsible for the coding of the association between visuo-spatial information and motor commands.

Functional imaging studies which investigated the activation patterns of motor learning under implicit conditions identified for the first, a motor circuit which includes lateral premotor cortex and SMA proper of the left hemisphere and primary motor cortex, for the second, a cognitive loop which consists of basal ganglia structures of the right hemisphere. Finally, activity patterns of intermanual transfer are discussed. After right-handed training, activity in motor associated areas maintains during performance of the mirror version, but is increased during the performance of the original-oriented version with the left hand. In contrary, increased activity during the mirror reversed action, but not during the original-oriented performance of the untrained right hand is observed after left-handed training.

These results indicate the transfer of acquired right-handed information which reflects the mirror symmetry of the body, whereas spatial information is mainly transferred after left-handed training. Taken together, a combined approach of clinical lesion studies and functional imaging is a promising tool for identifying the cerebral regions involved in the process of motor learning and provides insight into the mechanisms underlying the generalisation of actions.

Introduction

Motor learning can be conceived as the establishment of an internal model which represents the exact matching between perceived sensory and motor information (Wolpert et al., 1995). During the early phase of motor learning, movements are unskilled, highly-feedback dependent and require strong demands on attention (Atkeson, 1989). With practice, accuracy and velocity of actions increase, whereas feedback processing becomes less important (Preilowski, 1977).

Concerning the functional neuroanatomy, skill acquisition is paralleled by changes on regional level and on the level of neural circuitry. In the last few years, the development of functional imaging techniques as well as data from EEG studies provided insight into the neuronal mechanisms underlying the changes of behaviour during motor skill acquisition. Importantly, functional imaging data provide a better understanding of clinical observations.

Several reasons can be made responsible for discrepant results, e.g. variations of the tasks investigated, methodological differences and the phase of motor learning.

Results of a single study represent only parts of a puzzle of the neuronal changes underlying motor learning. In this article, a combined view of functional imaging data will be presented.

In general, two forms of motor learning can be distinguished, namely explicit and implicit learning. Explicit learning involves conscious recollection of previous experiences. Implicit learning is defined as an unintentional, non-conscious form of learning characterised by behavioural improvement.

Motor skill progresses from explicit control in the early stages of learning to a more implicit or automatic control when well learned. Finding suggests that motor learning consists of three distinct phases (Halsband, 2006):

• Initial stage: Slow performance under close sensory guidance, irregular shape of movements, variable time of performance.

• Intermediate stage: Gradual learning of the sensory-motor map, increase in speed.

• Advanced stage: Rapid, automised, skillful performance, isochronous movements, whole field sensory control.

During the initial phase of learning by trial and error, subjects have to find out the correct movement. The critical requirement of this phase is the novel establishment of perceived sensory cues with the correct motor commands. For this purpose, subjects have to attend to sensory cues. They have to decide which movement to initialise next and – if feedback is given – they have to encode the perceived response in memory. Thus, the establishment of a novel arbitrary sensorimotor association – as it is required during learning by trial and error – is closely related to attention (Petersen et al., 1994), decision and selection of movements, sensory feedback processing and working memory.

Once subjects find out the correct movements the map of sensorimotor translation is provided. Sensory stimuli have to be retained in working memory to be translated to the motor output (Deiber et al., 1997), performance of actions are still slow and unskilled and feedback and attentional processing play a critical role (Atkeson, 1989, Shadmehr and Mussa-Ivaldi, 1994). With practice, sensorimotor maps become stronger and are stored in long-term memory. Visual cues are transformed accurately and fast to the precise motor response. Hence, action can be performed with less intensive sensory feedback processing and at higher speed. After long-term practice, movements become automatic and can be performed at high speed and accuracy, even if subjects do not attend to the action.

Most recently Säfström and Edin (in press) examined how an entirely new sensorimotor transformation is established. The authors looked at a transformation that is different in kind from the normal visual motor map. The visual information was replaced with visual information with auditory information, where the frequency of a tone was log linearly related to the size of the object. In other words, it was investigated how a so-called “audiomotor map” is established using a reach-to-grasp task. Results indicate that learning of an auditory motor map also consisted of three distinct phases:

• subjects used the maximum grip aperture to grasp any reasonable sized objects; there were no overt signs of learning (∼10–15 trials);

• there was a period of fast learning where the slope of the relationship between maximum grip aperture and object size became steeper;

• subjects reached a plateau level of performance, the slope was constant. The results are in agreement with the findings by Sailer et al. (2005) who reported similar learning stages for a task in which subjects had to coordinate bi manual motor actions.

Looking at the neural mechanisms underlying motor learning, two main questions arise: first, one may ask about the contribution of each brain region in the process of motor learning. Secondly, it is interesting to interpret cerebral activation patterns which are associated with early and advanced stages of learning in terms of neural circuits.

In the following, the role of cortical and subcortical regions is discussed first with respect to the critical demands during early and late motor stages. Thereafter, the phases of motor learning are attributed to distinct neural circuits during explicit and implicit learning. Finally, related forms of motor learning, bimanual tasks and intermanual approaches are described.