Cognitive and Motor Learning in Internally-Guided Motor Skills.

In this study, we investigated motor and cognitive procedural learning in typically developing children aged 8–12 years with a serial reaction time (SRT) task and a probabilistic classification learning (PCL) task. The aims were to replicate and extend the results of previous SRT studies, to investigate PCL in school-aged children, to explore the contribution of declarative knowledge to SRT and PCL performance, to explore the strategies used by children in the PCL task via a mathematical model, and to see whether performances obtained in motor and cognitive tasks correlated. The results showed similar learning effects in the three age groups in the SRT and in the first half of the PCL tasks. Participants did not develop explicit knowledge in the SRT task whereas declarative knowledge of the cue–outcome associations correlated with the performances in the second half of the PCL task, suggesting a participation of explicit knowledge after some time of exposure in PCL. An increasing proportion of the optimal strategy use with increasing age was observed in the PCL task. Finally, no correlation appeared between cognitive and motor performance. In conclusion, we extended the hypothesis of age invariance from motor to cognitive procedural learning, which had not been done previously. The ability to adopt more efficient learning strategies with age may rely on the maturation of the fronto-striatal loops. The lack of correlation between performance in the SRT task and the first part of the PCL task suggests dissociable developmental trajectories within the procedural memory system.

Motor skill learning involves the acquisition of sequential motor movements with practice. Studies have shown that we learn to execute these sequences efficiently by chaining several elementary actions in sub-sequences called motor chunks. Several experimental paradigms, such as serial reaction task, discrete sequence production, and m × n task, have investigated motor chunking in externally specified sequencing where the environment or task paradigm provides the sequence of stimuli, i.e., the responses are stimulus driven. In this study, we examine motor chunking in a class of more realistic motor tasks that involve internally guided sequencing where the sequence of motor actions is self-generated or internally specified. We employ a grid-navigation task as an exemplar of internally guided sequencing to investigate practice-driven performance improvements due to motor chunking. The participants performed the grid-sailing task (GST) (Fermin et al., 2010), which required navigating (by executing sequential keypresses) a 10 × 10 grid from start to goal position while using a particular type of key mapping between the three cursor movement directions and the three keyboard buttons. We provide empirical evidence for motor chunking in grid-navigation tasks by showing the emergence of subject-specific, unique temporal patterns in response times. Our findings show spontaneous chunking without pre-specified or externally guided structures while replicating the earlier results with a less constrained, internally guided sequencing paradigm.

We introduced haptic cues to the serial reaction time (SRT) task alongside the standard visual cues to explore the relative contributions of haptic and visual cues to motor memory and perceptual memory. Motor learning is a complex process that likely depends on the availability of haptic sensory feedback. Motor learning is also often an implicit process, wherein the learner is not even aware that learning is taking place. The SRT task was devised to study implicit learning. Reaction times (RTs) are reduced with practice even in the absence of explicit learning about a sequence embedded in a train of cues. We adopted an SRT protocol developed by Willingham in 1999 to determine whether haptic cues contribute differently than visual cues to the balance of motor and perceptual learning. Experimental results involving 32 participants showed that sequence learning occurs implicitly with haptic stimuli to much the same extent as visual stimuli. Also, it was revealed that the dependence on motor memory (as opposed to perceptual memory) was greater in the group responding to haptic cues than the group responding to visual cues. Comparing the dependence on motor versus perceptual memory, the haptic group reached marginal significance (p=.09), whereas the visual group difference was not significant (p=.23).

Upper extremity motor performance declines with increasing age. However, older adults need to maintain, learn new and relearn known motor tasks. Research with young adults indicated that regular and acute physical activity might facilitate motor performance and motor learning processes. Therefore, this review aimed to examine the association between chronic physical activity and acute bouts of exercise on motor performance and motor learning in upper extremity motor tasks in older adults. Literature was searched via Cochrane library, PubMED, PsycINFO and Scopus and 27 studies met all inclusion criteria. All studies dealt with the influence of chronic physical activity on motor performance or motor learning, no appropriate study examining the influence of an acute bout of exercise in older adults was found. Results concerning the association of chronic physical activity and motor performance are mixed and seem to be influenced by the study design, kind of exercise, motor task, and exercise intensity. Regarding motor learning, a high physical activity or cardiovascular fitness level seems to boost the initial phase of motor learning; results differ with respect to motor retention. Overall, (motor-coordinative) intervention studies seem to be more promising than cross-sectional studies.

Stroke is one of the leading causes of chronic disability worldwide. Sensorimotor recovery relies on principles of motor learning for the improvement of movement and sensorimotor function after stroke. Motor learning engages several cognitive processes to effectively learn and retain new motor skills. However, cognitive impairments are common and often coexist with motor impairments after stroke. The specific relationships between poststroke cognitive impairments and motor learning have not been determined. To summarize the existing evidence related to cognitive impairments and motor learning after stroke. Specific goals were to determine: (1) how motor learning is studied in individuals with poststroke cognitive impairments; (2) how cognitive impairments are assessed; (3) which cognitive domains impact motor learning. Over 400 studies were screened for specific inclusion criteria and 19 studies that related poststroke cognitive impairments to motor learning were included. Studies used a wide variety of experimental designs, sample sizes, and measures for cognitive evaluation. Cognitive impairments impacting motor improvement and learning capacity after stroke were reported in all but 4 studies. The most common domains impacting motor learning were attention, executive function, and memory. Detailed cognitive assessments, retention testing, and a combination of clinical and kinematic outcomes are recommended for future studies. The presence of specific cognitive impairments measured with sensitive instruments should be considered when designing effective training interventions for patients with stroke to maximize sensorimotor recovery.

Learning manual skills is a fundamental part of health care education, and motor, sensory and cognitive learning processes are essential aspects of professional development. Simulator training has been shown to enhance factors that facilitate motor and cognitive learning. The present study aimed to investigate the students' experiences and thoughts about their learning through simulation skills training. The study was designed for an educational setting at a clinical skills centre. Ten third-year undergraduate nursing students performed urethral catheterisation, using the virtual reality simulator UrecathVision™, which has haptic properties. The students practised in pairs. Each session was videotaped and the video was used to stimulate recall in subsequent interviews. The interviews were analysed using qualitative content analysis. The analysis from interviews resulted in three themes: what the students learn, how the students learn, and the simulator's contribution to the students' learning. Students learned manual skills, how to perform the procedure, and professional behaviour. They learned by preparing, watching, practising and reflecting. The simulator contributed by providing opportunities for students to prepare for the skills training, to see anatomical structures, to feel resistance, and to become aware of their own performance ability. The findings show that the students related the task to previous experiences, used sensory information, tested themselves and practised techniques in a hands-on fashion, and reflected in and on action. The simulator was seen as a facilitator to learning the manual skills. The study design, with students working in pairs combined with video recording, was found to enhance opportunities for reflection.

The human cerebellum contributes to motor, emotional and cognitive associative learning. A review

Although the Serial Reaction-Time Task has been an effective tool in studying procedural learning, there is still a debate as to whether learning in the task is effector-based, stimulus-based, or response-based. In this article, the authors contribute to this debate by contrasting response- and stimulus-based learning by manipulating them selectively and simultaneously. Results show that (a) participants learned response sequences in the absence of stimulus-specific perceptual sequence information but (b) not stimulus sequences without corresponding response information. In a third condition, response sequence and stimulus frequency information were in conflict, and each effect decreased learning in the other domain. Overall, our findings show that learning in these tasks is primarily motor-based, but it is also constrained by relatively salient perceptual information. Together with earlier findings in the literature, the findings also suggest a task and stimulus-arrangement-specific interaction between motor and perceptual learning, where relevance and salience of the specific information plays a crucial role.

Motor and non-motor sequence learning in patients with basal ganglia lesions: the case of serial reaction time (SRT)

An exhaustive review is reported of over 25 years of research with the Discrete Sequence Production (DSP) task as reported in well over 100 articles. In line with the increasing call for theory development, this culminates into proposing the second version of the Cognitive framework of Sequential Motor Behavior (C-SMB 2.0), which brings together known models from cognitive psychology, cognitive neuroscience, and motor learning. This processing framework accounts for the many different behavioral results obtained with the DSP task and unveils important properties of the cognitive system. C-SMB 2.0 assumes that a versatile central processor (CP) develops multimodal, central-symbolic representations of short motor segments by repeatedly storing the elements of these segments in short-term memory (STM). Independently, the repeated processing by modality-specific perceptual and motor processors (PPs and MPs) and by the CP when executing sequences gradually associates successively used representations at each processing level. The high dependency of these representations on active context information allows for the rapid serial activation of the sequence elements as well as for the executive control of tasks as a whole. Speculations are eventually offered as to how the various cognitive processes could plausibly find their neural underpinnings within the intricate networks of the brain.

Motor learning is a fundamental skill to our daily lives. Dysfunction in motor performance in schizophrenia (Sz) has been associated with poor social and functional outcomes. Transcranial direct current stimulation (tDCS), a non-invasive electrical brain stimulation approach, can influence underlying brain function with potential for improving motor learning in Sz. We used a well-established Serial Reaction Time Task (SRTT) to study motor learning, in combination with simultaneous tDCS and EEG recording, to investigate mechanisms of motor and procedural learning deficits in Sz, and to develop refined non-invasive brain stimulation approaches to improve neurocognitive dysfunction. We recruited 27 individuals with Sz and 21 healthy controls (HC). Individuals performed the SRTT task as they received sham and active tDCS with simultaneous EEG recording. Reaction time (RT), neuropsychological, and measures of global functioning were assessed. SRTT performance was significantly impaired in Sz and showed significant correlations with motor-related and working memory measures as well as global function. Source-space time-frequency decomposition of EEG showed beta-band coherence across supplementary-motor, primary-motor and visual cortex forming a network involved in SRTT performance. Motor-cathodal and visual-cathodal stimulations resulted in significant modulation in coherence particularly across the motor-visual nodes of the network accompanied by significant improvement in motor learning in both controls and patients. Here, we confirm earlier reports of SRTT impairment in Sz and demonstrate significant reversal of the deficits with tDCS. The findings support continued development of tDCS for enhancement of plasticity-based interventions in Sz, as well as source-space EEG analytic approaches for evaluating underlying neural mechanisms.

Background/aims Older adults with different physical activity levels have often demonstrated individual differences in motor performance and learning. Serial reaction time task training and anodal transcranial direct current stimulation of the primary motor cortex were used in this study to evaluate how these interventions affected motor learning in older adults with low activity levels. Methods In this randomised controlled trial, 28 healthy, right-handed, older adults with low activity levels, with a mean age of 69.92 years, were randomly allocated to an anodal transcranial direct current stimulation group (n=14) or sham transcranial direct current stimulation group (n=14), based on a simple non-probability sampling method. The experimental group was exposed to 20 minutes of anodal transcranial direct current stimulation of the motor cortex, using a tDCS device, alongside eight sequenced or randomised blocks of serial reaction time task activities, for 5 consecutive days. In the control group, the tDCS device was automatically switched off after 1 minute. To assess implicit motor learning, the response time and error rate of two sequenced blocks of serial reaction time task activities were collected before, immediately following, 1 day and 1 week after the completion of the intervention. Results Immediately following the end of the intervention, at day 5, the mean response time and error rate were 925.09 and 2.55 in the experimental group, and 1016.52 and 4.10 in the control group. At 1 day after the completion of the intervention, the mean response time and error rates were 927.40 and 3.03 in the experimental group and 1021.91 and 4.34 in the control group. At 1 week after the completion of the intervention, the mean response time and error rates were 942.26 and 3.63 in the experimental group and 1050.08 and 5.11 in the control group. These findings indicate that response time and error rate were significantly decreased in both stimulation groups at different time points (P<0.001). At the same time, there were no significant differences in the response time and error rate between the two groups at different time points: immediately (P=0.07, P=0.31), 1 day (P=0.06, P=0.41) and 1 week (P=0.04, P=0.35) after the completion of the intervention respectively. Conclusions Serial reaction time task training, with or without applying anodal transcranial direct current stimulation, can improve motor learning in low-activity older adults. Therefore, it appears that anodal transcranial direct current stimulation did not affect or improve motor learning in older adults with low motor activity. Motor learning training can be used alone as a practical and helpful intervention to improve performance and implicit motor skill learning with long-lasting effects in older adults with low levels of activity.

Can transcranial direct current stimulation (tDCS) of the cerebellum improve implicit social and cognitive sequence learning?

It has been suggested that patients with schizophrenia have corticostriatal circuit dysfunction (Carlsson & Carlsson, 1990). Skill learning is thought to rely on corticostriatal circuitry and different types of skill learning may be related to separable corticostriatal loops (Grafton, Hazeltine, & Ivry, 1995; Poldrack, Prabhakaran, Seger, & Gabrieli, 1999). The authors examined motor (Serial Reaction Time task, SRT) and cognitive (Probabilistic Classification task, PCT) skill learning in patients with schizophrenia and normal controls. Development of automaticity was examined, using a dual task paradigm, across three training sessions. Patients with schizophrenia were impaired at learning on the PCT compared to controls. Performance gains of controls occurred within the first session, whereas patients only improved gradually and never reached the performance level of controls. In contrast, patients were not impaired at learning on the SRT relative to controls, suggesting that patients with schizophrenia may have dysfunction in a specific corticostriatal subcircuit.

The aim was to determine the extent and time course of motor and perceptual learning in a procedural learning task, and the relation of these two processes. Because environmental constraints modulate the relative impact of different learning mechanisms, we chose a simple learning task similar to real-life exercise. Thirty-four healthy individuals performed a visuomotor serial reaction time task. Learning blocks with high stimulus-response compatibility were practiced repeatedly; in between these, participants performed test blocks with the same or a different (mirror-inverted, or new) stimulus sequence and/or with the same or a different (mirror-inverted) stimulus-response allocation. This design allowed us to measure the progress of motor learning and perceptual learning independently. Results showed that in the learning blocks, a steady reduction of the reaction times indicated that - as expected - participants improved their skills continuously. Analysis of the test blocks indicated that both motor learning and perceptual learning were significant. The two mechanisms were correlated (r=0.62, P<0.001). However, their time course was different: the impact of motor learning increased strongly from earlier to later intervals, whereas the progress of perceptual learning was more stable but slower. In conclusion, in a simple visuomotor learning task, participants can learn the motor sequence and the stimulus sequence in parallel. The positive correlation of motor and perceptual learning suggests that the two mechanisms act in synergy and are not alternative opposing strategies. The impact of these two learning mechanisms changes over time: motor learning sets in later and becomes relevant only in the course of training.