Reaching with altered visual feedback of the hand’s position in a virtual environment leads to reach adaptation in the trained hand, and also in the untrained hand (Wang & Sainburg, 2002). In the current study, we asked if reach adaptation in the untrained (right) hand is due to transfer of explicit (i.e., EA; conscious strategy) and/or implicit adaptation (i.e., IA; unconscious) from the left (trained) hand, and if the transfer of EA and IA changes depending on how one is made aware of the visuomotor distortion. We further asked if EA and IA are retained in the trained and untrained hand for 24 hours. Participants (n=60) were evenly divided into 3 groups (Strategy, No-Strategy, and Control). All participants reached to visual targets while seeing a cursor on the screen that was rotated 40° clockwise relative to their hand motion. Participants in the Strategy group were instructed on how to counteract the visuomotor distortion. The No-Strategy group was not told of the upcoming visuomotor distortion but was later asked to reach while engaging in any strategy they had learned in order to assess EA. Participants in the Control group were also not told of the upcoming visuomotor distortion and were never instructed to engage in any strategy when reaching. EA and IA were assessed in both the trained and untrained hands immediately following rotated reach training, and 24 hours later by having participants reach without the cursor when instructed to: (1) aim so that your hand lands on the target (to assess IA) and (2) use what was learned during training so that the cursor lands on the target (to assess EA + IA; exception of Control group). Results revealed that the groups differed with respect to the extent of reach adaptation achieved when initially training with the rotated cursor, such that the Strategy group had greater EA and less IA compared to the No-Strategy group in the trained hand. Unexpectedly, the Control group also showed less IA compared to the No-Strategy group, but was similar to the Strategy group. For both the Strategy and No-Strategy groups, EA was transferred between hands and was retained over time. While the extent of IA varied between groups in the trained (left) hand immediately following reach training trials, significant transfer of IA was not found in any of the three groups. Retention of IA was observed in the trained hand but decayed over testing days. Together, these results suggest that while initial EA and IA in the trained hand is dependent on how one is made aware of the visuomotor distortion, transfer and retention of visuomotor adaptation is driven almost exclusively by EA, regardless of instructions provided.

Visuomotor adaptation arises when reaching in an altered visual environment, where one’s seen hand position does not match their felt (i.e., proprioceptive) hand position in space. Here, we investigated if proprioceptive training (PT) benefits visuomotor adaptation, and if these benefits arise due to implicit (unconscious) or explicit (conscious strategy) processes. A total of 72 participants were divided equally into 3 groups: Proprioceptive training with feedback (PTWF), Proprioceptive training no feedback (PTNF), and Control (CTRL). The PTWF and PTNF groups completed proprioceptive training (PT), where a participant’s hand was passively moved to an unknown reference location and they judged the felt position of their unseen hand relative to their body midline on every trial. The PTWF group received verbal feedback with respect to their response accuracy on the middle 60% of trials. The CTRL group did not complete PT and instead sat quietly during this time. Following PT or time delay, all three groups reached when seeing a cursor that was rotated 30° clockwise relative to their hand motion, followed by a series of no-cursor reaches to assess implicit and explicit adaptation. Results indicated that the PTWF group improved their sense of felt hand position following PT. However, this improved proprioceptive acuity did not benefit visuomotor adaptation, as all three groups showed similar visuomotor adaptation across rotated reach training trials. Visuomotor adaptation arose implicitly, with minimal explicit contribution for all three groups. Thus, these results suggest that passive proprioceptive training with feedback does not benefit, nor hinder, implicit visuomotor adaptation.

Previous investigations comparing direct versus indirectly cued movements have consistently shown that indirectly cued movements take longer to prepare (Neely and Heath, 2010) and involve the recruitment of additional brain areas (Connolly et al., 2000). This increase in processing time has been associated with the additional cognitive transformations required of the task (Neely and Heath, 2010). In the present study we investigated whether differences between direct versus indirectly cued movements are also reflected in the time course of motor preparation. Participants performed a targeting task, moving directly to the location of a visual cue (i.e., directly cued movement) or to a location that differed by 60˚, 90˚, or 120˚ with respect to the visual cue provided (i.e., indirectly cued movements). Participants were instructed to initiate their movements concurrently with an anticipated go-signal. To examine the time course of motor preparation, a startling acoustic stimulus (SAS, 124dB) was randomly presented 150 ms, 500 ms, or 1000 ms prior to the go-signal. Results from the startle trials revealed that the time course of motor preparation was similar regardless of the angle of rotation required and hence whether it was a direct or indirectly cued trial. Specifically, motor preparation was delayed until less than 500 ms prior to movement initiation for both direct and indirectly cued movements. These findings indicate that similar motor preparation strategies are engaged for both types of cued movements, suggesting that the time to prepare a motor response may be similar regardless of whether a cognitive transformation is required.

O presente estudo teve como objetivo avaliar o efeito da expectativa na reorganização de aspectos espaciais e temporais em ações interceptativas. O estudo foi conduzido em dois experimentos, nos quais os participantes interceptaram manualmente um alvo móvel virtual em situações com diferentes probabilidades de mudança de trajetória/velocidade de deslocamento do alvo. Em ambos os experimentos foi realizada a comparação entre um grupo que recebeu informação verbal sobre a probabilidade de mudança de trajetória/velocidade (PR), e outro que não recebeu informação (SI) sobre as características probabilísticas da tarefa. Os resultados do experimento com mudança de trajetória indicaram que, além da reorganização na dimensão espacial ocorrer de maneira gradativa, as ações interceptativas parecem ter sido controladas por um mecanismo preditivo que é atualizado ao longo do tempo por informação visual. Em ambos os experimentos foi mostrado que a probabilidade do contexto influenciou as características espaciais e temporais da reorganização do movimento. Contudo, essa influência ocorreu somente no fim de uma série de tentativas. Este resultado, em conjunto com a ausência de diferença em aspectos cinemáticos e de desempenho entre os grupos experimentais, sugere que a expectativa de deslocamento futuro do alvo foi criada em função das tentativas iniciais de uma série e não pela informação verbal / The aim of the present study was to evaluate the effect of expectancy on reorganization of spatial and temporal dimensions in interceptive actions. The study was conducted through two experiments in which participants were to manually intercept a virtual moving target with different probabilities of target trajectory/velocity shift. Comparison between a group that received verbal information concerning probability of target trajectory/velocity shift (PR), and another group that did not receive that information (SI) was made in both experiments. Results of the experiment on target trajectory shift showed that, in addition to gradual movement reorganization in the spatial dimension, interceptive actions were controlled by a predictive mechanism which seemed to be continuously updated by visual information. Of main interest, it was shown that in both experiments probability of target trajectory/velocity change influenced the spatial and temporal characteristics of movement reorganization. However, this influence occurred only at the end of a series of trials. The same effect was observed in the experiment on target velocity shift. This result, adjoined with the absence of difference in kinematic and performance aspects between experimental groups, suggests that expectancy about future target displacement was created by the initial trials of a series and not by verbal information on probability of target trajectory/velocity shift

Previous investigations comparing direct versus indirectly cued movements have consistently shown that indirectly cued movements take longer to prepare (Neely and Heath, 2010) and involve the recruitment of additional brain areas (Connolly et al., 2000). This increase in processing time has been associated with the additional cognitive transformations required of the task (Neely and Heath, 2010). In the present study we investigated whether differences between direct versus indirectly cued movements are also reflected in the time course of motor preparation. Participants performed a targeting task, moving directly to the location of a visual cue (i.e., directly cued movement) or to a location that differed by 60˚, 90˚, or 120˚ with respect to the visual cue provided (i.e., indirectly cued movements). Participants were instructed to initiate their movements concurrently with an anticipated go-signal. To examine the time course of motor preparation, a startling acoustic stimulus (SAS, 124dB) was randomly presented 150 ms, 500 ms, or 1000 ms prior to the go-signal. Results from the startle trials revealed that the time course of motor preparation was similar regardless of the angle of rotation required and hence whether it was a direct or indirectly cued trial. Specifically, motor preparation was delayed until less than 500 ms prior to movement initiation for both direct and indirectly cued movements. These findings indicate that similar motor preparation strategies are engaged for both types of cued movements, suggesting that the time to prepare a motor response may be similar regardless of whether a cognitive transformation is required.

Superior parietal cortex has been implicated in visuomotor guidance and is proposed to be specialised for action in the lower visual field and peripersonal space. Two patients, one with a right superior parietal lesion leading to optic ataxia (ME), and one with a lesion affecting right inferior parietal cortex (LH), were compared to elderly controls (n=8) and young controls (n=8) on a reciprocal pointing task with movements made in the near-far direction (i.e., sagittal plane) or right-left direction (i.e., fronto-parallel plane). In contrast to both control groups, who demonstrated a speed-accuracy trade-off in movement time and peak velocity, neither of the patients did. When the time spent post-peak velocity (represented as a percentage of total movement time) was examined, both patients demonstrated larger times post-peak velocity than controls for all movement directions. Furthermore, while rightward movements of the right hand had higher times post-peak velocity than leftward movements there were no directional patterns for near-far movements which contrasted with controls who had larger times post-peak velocity for near movements. The patient with the more superior lesion (ME) had the greatest difficulty with movements made back toward the body suggestive of a role for superior parietal cortex in the fine tuning of movements made in this region of space (i.e., personal or peripersonal space). In contrast, all directions of movement seemed to be equally affected in the patient with a more inferior lesion. These results are discussed in terms of the different roles played by inferior and superior parietal cortex in the control of visually guided movements.

Superior parietal cortex has been implicated in visuomotor guidance and is proposed to be specialised for action in the lower visual field and peripersonal space. Two patients, one with a right superior parietal lesion leading to optic ataxia (ME), and one with a lesion affecting right inferior parietal cortex (LH), were compared to elderly controls (n=8) and young controls (n=8) on a reciprocal pointing task with movements made in the near-far direction (i.e., sagittal plane) or right-left direction (i.e., fronto-parallel plane). In contrast to both control groups, who demonstrated a speed-accuracy trade-off in movement time and peak velocity, neither of the patients did. When the time spent post-peak velocity (represented as a percentage of total movement time) was examined, both patients demonstrated larger times post-peak velocity than controls for all movement directions. Furthermore, while rightward movements of the right hand had higher times post-peak velocity than leftward movements there were no directional patterns for near-far movements which contrasted with controls who had larger times post-peak velocity for near movements. The patient with the more superior lesion (ME) had the greatest difficulty with movements made back toward the body suggestive of a role for superior parietal cortex in the fine tuning of movements made in this region of space (i.e., personal or peripersonal space). In contrast, all directions of movement seemed to be equally affected in the patient with a more inferior lesion. These results are discussed in terms of the different roles played by inferior and superior parietal cortex in the control of visually guided movements.

Two experiments were designed to examine the influence of the strength of perceptionaction coupling on the control and learning of a visuomotor tracking pattern. Participants produced rhythmic elbow flexion-extension motions to learn a visually defined 90° relative phase tracking pattern with an external sinusoidal signal which was set at 0.8 Hz with 8 cycles in a trial. Day 1 and Day 2 practice sessions consisted of a total of 72 practice trials. There were two visuomotor congruency groups, a congruent group with visual feedback representing the elbow’s rotation and an incongruent group with feedback representing the elbow’s rotation transformed by 180°. Before Day 1 practice (pre-practice) and 24 hours after Day 2 practice (post-practice), participants produced 0°, 45°, 90°, 135°, and 180° relative phase tracking patterns either with or without tracking feedback. The external signal and the limb’s feedback were provided in the same workspace in Experiment 1, while both signals were provided in a separate workspace in Experiment 2. The pre-practice results demonstrated that the 0° relative phase pattern was the most accurate and stable pattern, whereas the 90° and 135° relative phase patterns were less accurate and more variable. The incongruent group produced a more accurate and less variable 180° relative phase pattern compared to the congruent group. Practice led to a decrease in phase error and variability toward the required 90° relative phase pattern in both experiments. The congruent group produced more accurate tracking and less variable elbow amplitude compared to the incongruent group in the separate workspace, whereas no such congruency effects were found in the same workspace during practice. The post-practice results showed overall improvements in phase accuracy and stability in most relative phase patterns with practice. Overall deterioration in tracking performance was found when tracking without feedback in the pre- and post-practice sessions. These findings demonstrated that the perception-action coupling strength was modified by feedback, visuomotor mapping, perceptual pattern, and workspace framework. The differential strength of perception-action impacted the learning of the required visuomotor tracking pattern as well as the production of tracking accuracy and stability differentially among the other tracking patterns.

<p>Cognition has for a long time been viewed as a process that can be described in terms of computational symbol manipulation, i.e. a process that takes place inside people’s heads and is largely unaffected by contextual aspects. In recent years, however, there has been a considerable change in the way researchers look at and study human cognition. These changes also have far-reaching implications for education and educational research. Situated learning is a theoretical framework in which sociocultural aspects of cognition and learning are strongly emphasised, that is, the context in which learning takes place is an important part of learning activity. The concept of activity is central to situated learning theories, but activity has been considered an exclusively sociocultural process in which the body only plays a minor role. In embodied cognition research, on the other hand, there is an increasing awareness that mind and body are inextricably intertwined and cannot be viewed in isolation. Findings in cognitive neuroscience provide additional evidence that cognition is tightly linked to perception and action. The aim of this thesis has been to investigate the role of the body in situated learning activity by integrating these different perspectives on cognition and learning. The analysis suggests that, like individual human conceptualization and thought, situated learning is in fact deeply rooted in bodily activity. In social interactions the body provides individuals with a similar perspective on the world, it functions as a means of signalling to others what cannot (yet) be expressed verbally, and it serves as a resonance mechanism in the understanding of others.</p>

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