Changes in brain activity during motor learning measured with PET: Effects of hand of performance and practice

Department of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Journal of Neurophysiology (Impact Factor: 2.89). 11/1998; 80(4):2177-99.
Source: PubMed


The aim of this study is to assess brain activity measured during continuous performance of design tracing tasks. Three issues were addressed: identification of brain areas involved in performing maze and square tracing tasks, investigation of differences and similarities in these areas related to dominant and nondominant hand performance, and most importantly, examination of the effects of practice in these areas. A total of 32 normal, right-handed subjects were instructed to move a pen with the dominant right hand (16 subjects) or nondominant left hand (16 subjects) continuously through cut-out maze and square patterns with their eyes closed during a 40-s positron emission tomography (PET) scan to measure regional blood flow. There were six conditions: 1) holding the pen on a writing tablet without moving it (rest condition); 2) tracing a maze without practice; 3) tracing the same maze after 10 min of practice; 4) tracing a novel maze; and tracing an easily learned square design at 5) high or 6) low speed. To identify brain areas generally related to continuous tracing, data analyses were performed on the combined data acquired during the five tracing scans minus rest conditions. Areas activated included: primary and secondary motor areas, somatosensory, parietal, and inferior frontal cortex, thalamus, and several cerebellar regions. Then comparisons were made between right- and left-hand performance. There were no significant differences in performance. As for brain activations, only primary motor cortex and anterior cerebellum showed activations that switched with hand of performance. All other areas, with the exception of the midbrain, showed activations that were common for both right- and left-hand performance. These areas were further analyzed for significant conditional effects. We found patterns of activation related to velocity in the contralateral primary motor cortex, related to unskilled performance in right premotor and parietal areas and left cerebellum, related to skilled performance in supplementary motor area (SMA), and related to the level of capacity at which subjects were performing in left premotor cortex, ipsilateral anterior cerebellum, right posterior cerebellum and right dentate nucleus. These findings demonstrate two important principles: 1) practice produces a shift in activity from one set of areas to a different area and 2) practice-related activations appeared in the same hemisphere regardless of the hand used, suggesting that some of the areas related to maze learning must code information at an abstract level that is distinct from the motor performance of the task itself.

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    • "Rehabilitation ability depends on motor learning (Hanlon, 1996), and motor learning by repetitive rehabilitation task after stroke effectively improves motor functions of the upper extremity and brain neural network (Hatakenaka et al., 2007). Several studies reported activation of the prefrontal areas, supplementary motor area (SMA), premotor and motor cortices, and cerebellum when novel motor tasks were performed (Roland and Seitz, 1989; Decety et al., 1990; Friston et al., 1992; Jueptner et al., 1997; van Mier et al., 1998) or when a movement was selected based on internal or external cues (Deiber et al., 1991). However, the role of the most rostral part of the prefrontal cortex (PFC), i.e., the anterior part of the dorsomedial prefrontal cortex (aDMPFC), in motor learning remains unclear. "
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    ABSTRACT: To investigate the relationship between the frontal and sensorimotor cortices and motor learning, hemodynamic responses were recorded from the frontal and sensorimotor cortices using functional near infrared spectroscopy (NIRS) while healthy subjects performed motor learning tasks used in rehabilitation medicine. Whole-head NIRS recordings indicated that response latencies in the anterior dorsomedial prefrontal cortex (aDMPFC) were shorter than in other frontal and parietal areas. Furthermore, the increment rate of the hemodynamic responses in the aDMPFC across the eight repeated trials significantly correlated with those in the other areas, as well as with the improvement rate of task performance across the 8 repeated trials. In the second experiment, to dissociate scalp- and brain-derived hemodynamic responses, hemodynamic responses were recorded from the head over the aDMPFC using a multi-distance probe arrangement. Six probes (a single source probe and 5 detectors) were linearly placed 6 mm apart from each of the neighboring probes. Using independent component analyses of hemodynamic signals from the 5 source-detector pairs, we dissociated scalp- and brain-derived components of the hemodynamic responses. Hemodynamic responses corrected for scalp-derived responses over the aDMPFC significantly increased across the 8 trials and correlated with task performance. In the third experiment, subjects were required to perform the same task with and without transcranial direct current stimulation (tDCS) of the aDMPFC before the task. The tDCS significantly improved task performance. These results indicate that the aDMPFC is crucial for improved performance in repetitive motor learning.
    Frontiers in Human Neuroscience 05/2014; 8:292. DOI:10.3389/fnhum.2014.00292 · 3.63 Impact Factor
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    • "In later stages, prefrontal activation shifts more to the left hemisphere [6,7]. This left-hemispheric dominance appears to be independent of the side used for training [9]. Furthermore, the learning process can be categorized into two forms: explicit learning, in which subjects consciously try to learn a task relying on previous experiences, and implicit learning, which takes place unintentionally and unconsciously. "
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    ABSTRACT: Research on the neurophysiological correlates of visuomotor integration and learning (VMIL) has largely focused on identifying learning-induced activity changes in cortical areas during motor execution. While such studies have generated valuable insights into the neural basis of VMIL, little is known about the processes that represent the current state of VMIL independently of motor execution. Here, we present empirical evidence that a subject's performance in a 3D reaching task can be predicted on a trial-to-trial basis from pre-trial electroencephalographic (EEG) data. This evidence provides novel insights into the brain states that support successful VMIL. Six healthy subjects, attached to a seven degrees-of-freedom (DoF) robot with their right arm, practiced 3D reaching movements in a virtual space, while an EEG recorded their brain's electromagnetic field. A random forest ensemble classifier was used to predict the next trial's performance, as measured by the time needed to reach the goal, from pre-trial data using a leave-one-subject-out cross-validation procedure. The learned models successfully generalized to novel subjects. An analysis of the brain regions, on which the models based their predictions, revealed areas matching prevalent motor learning models. In these brain areas, the ¿/µ frequency band (8¿14 Hz) was found to be most relevant for performance prediction. VMIL induces changes in cortical processes that extend beyond motor execution, indicating a more complex role of these processes than previously assumed. Our results further suggest that the capability of subjects to modulate their ¿/µ bandpower in brain regions associated with motor learning may be related to performance in VMIL. Accordingly, training subjects in ¿/µ-modulation, e.g., by means of a brain-computer interface (BCI), may have a beneficial impact on VMIL.
    Journal of NeuroEngineering and Rehabilitation 03/2014; 11(1):24. DOI:10.1186/1743-0003-11-24 · 2.74 Impact Factor
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    • "Various other tasks have been used to study the acquisition and control of sequential movement skills, such as the pursuit rotor task (e.g., Grafton et al., 1992), the tracing of cut-out mazes (e.g., Van Mier et al., 1998), the m × n task (Hikosaka et al., 1995), a sequential elbow flexion and extension task (Park et al., 2004) and the serial reaction time (SRT) task (e.g., Nissen and Bullemer, 1987). Two of these tasks are especially interesting to elaborate upon here because their experimental designs overlap substantially with the DSP task; that is, they also aim at studying sequential representation on the basis of repeatedly performing key-press sequences. "
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    ABSTRACT: Work with the discrete sequence production (DSP) task has provided a substantial literature on discrete sequencing skill over the last decades. The purpose of the current article is to provide a comprehensive overview of this literature and of the theoretical progress that it has prompted. We start with a description of the DSP task and the phenomena that are typically observed with it. Then we propose a cognitive model, the dual processor model (DPM), which explains performance of (skilled) discrete key-press sequences. Key features of this model are the distinction between a cognitive processor and a motor system (i.e., motor buffer and motor processor), the interplay between these two processing systems, and the possibility to execute familiar sequences in two different execution modes. We further discuss how this model relates to several related sequence skill research paradigms and models, and we outline outstanding questions for future research throughout the paper. We conclude by sketching a tentative neural implementation of the DPM.
    Frontiers in Human Neuroscience 03/2013; 7(7):1. DOI:10.3389/fnhum.2013.00082 · 3.63 Impact Factor
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