Which of the following is documented, would support the recalibration theory

When reaching to visual objects in one's environment, a series of sensory to motor transformations occurs in order to ensure that one successfully reaches to a desired object. Specifically, visual information related to the hand and target position and proprioceptive information regarding hand position are transformed into appropriate motor commands (Desmurget et al., 1998, Flanders et al., 1992, Jeannerod, 1988). In cases when movements are performed incorrectly (e.g., due to changes within the environment and/or one's body), one tends to rely more on the visual estimate of the limb, rather than the actual or “felt” position to correct their movement. For example, when reaching in a virtual reality environment with distorted visual feedback of the hand, individuals use the distorted visual feedback to rapidly alter their reaches on subsequent trials in order for the visual representation of their hand to achieve the target. This process is referred to as visuomotor adaptation (Cressman and Henriques, 2009, Krakauer et al., 1999, Krakauer et al., 2005, Simani et al., 2007). After adapting their movements in response to the altered visual feedback, individuals continue to reach with the newly acquired movement pattern, even when visual feedback is removed. These reach errors, known as aftereffects, are evidence that persistent motor changes have occurred and an internal model adapted (Baraduc and Wolpert, 2002, Buch et al., 2003, Cressman et al., 2010, Cressman and Henriques, 2009, Cressman and Henriques, 2010, Krakauer et al., 1999, Krakauer et al., 2000, Martin et al., 1996, Zbib et al., 2016).

In addition to changes in reaches, sensory changes have also been shown to occur following reach training with misaligned visual feedback of the hand. Specifically, participants recalibrate their sense of felt hand position (i.e., proprioceptive recalibration), such that after reaching in a virtual reality environment with distorted visual feedback of the hand, they alter their perception of where they feel their hand is to more closely align with the visual feedback provided (Cressman and Henriques, 2009, Zbib et al., 2016). This proprioceptive recalibration has been assessed in tasks during which the participant's hand is guided out passively to different locations in the workspace by a robot manipulandum and the participant indicates the position of their hand relative to a visual or proprioceptive reference marker (Cressman and Henriques, 2009), as well as by performing tasks requiring participants to actively reach to a proprioceptive target (Ruttle et al., 2016, Simani et al., 2007, van Beers et al., 2002).

Recently, Zbib et al. (2016) looked to determine how quickly proprioception was recalibrated when training to reach with a cursor that was rotated 30° clockwise (CW) relative to hand motion. They found that shifts in proprioceptive estimates took longer to arise in comparison to visuomotor adaptation as assessed through aftereffect trials. Specifically, Zbib et al. (2016) found that proprioception had shifted by 8.8° (~30% of the 30° cursor distortion) relative to baseline after participants completed 70 rotated reach training trials, while reaches were adapted by 16.9° (~56% of the 30° distortion) after only 5 reach training trials. Moreover, the shifts in proprioception observed after 70 trials did not increase significantly again with an additional 80 trials of training, such that proprioceptive recalibration plateaued at 8.8° (or 30% of the 30° distortion). On the other hand, the early reach errors observed plateaued after only 40 trials of training at 22.3° (or 74.3% of the 30° distortion). A more recent study by Ruttle and colleagues (2016), also showed greater visuomotor adaptation after only 6 reach training trials with visual feedback rotated relative to hand motion (10.5° or 26.2% of the 40° visuomotor rotation distortion) compared to proprioceptive recalibration following those same 6 training trials (5.2° or 13% of the 40° visuomotor rotation distortion). Like Zbib et al. (2016), proprioceptive recalibration did not continue to significantly increase over additional reach training trials, such that at the end of reach training, the extent of proprioceptive recalibration was much less than visuomotor adaptation. Interestingly, additional reach training sessions within a single testing day do not appear to lead to greater proprioceptive recalibration (Salomonczyk et al., 2011). Together, these results suggest that proprioceptive recalibration arises more slowly compared to visuomotor adaptation and that proprioception may only be able to be recalibrated up to a maximal point, well below the magnitude of visuomotor adaptation.

While the time course and magnitude of changes with respect to reach aftereffects and proprioceptive recalibration following training with distorted visual feedback of the hand have been shown to differ in an initial testing session, both show evidence of retention. Retention can be established by observing (1) aftereffects at the start of a second testing session, which we will refer to as recall (Mawase et al., 2017) and/or (2) savings within a second testing session, such that there is faster relearning upon exposure to a previously experienced environment compared to initial training performance (Huberdeau et al., 2015, Krakauer, 2009, Zarahn et al., 2008). Retention of visuomotor adaptation has been firmly established by observing the recall of aftereffects and savings at various times following training with the initial visuomotor rotation perturbation (e.g., 24 h (Nourouzpour et al., 2014), 1–2 week(s) and 12 months (Yamamoto et al., 2006) post initial training). For example, Nourouzpour et al. (2014) found retention of visuomotor adaptation following reach training with a 40° CW visuomotor rotation, such that immediate aftereffects were not different from those measured 24 h later. Furthermore, results from Yamamoto et al. (2006) showed significant long-lasting changes in motor performance in the form of recall and suggested that even relatively short-term reach training with distorted visual feedback of the hand (e.g., 120 trials for humans & 150 trials for monkeys) leads to long-term changes in reaches (1–2 week(s) & > 1 year). With respect to savings of visuomotor adaptation, Klassen et al. (2005) observed that reaches were adapted more rapidly in a second testing session 24 h after training with a cursor rotated 30° CCW relative to the hand compared to the initial session. Furthermore, studies have shown similar results in follow-up testing sessions 48 h (Caithness et al., 2004) and 1 week (Krakauer et al., 2005) after initial training. While measures of recall and savings of visuomotor adaptation both provide insight into the long-term retention of motor adaptation, they are suggested to arise due to different underlying processes (e.g., an adapted internal model vs. increased error sensitivity (Herzfeld et al., 2014) and/or explicit processes (Huberdeau et al., 2015), respectively). In accordance with this suggestion, Mawase et al. (2017) have recently shown that the neural circuitry underlying retention in the form of recall and savings of (locomotor) adaptation differ.

To date, studies examining retention of proprioceptive recalibration following reach training are limited. Specifically, studies examining retention of proprioceptive recalibration following visuomotor adaptation trials have focused on examining retention in the form of recall 24 h after initial training (Nourouzpour et al., 2014, Ostry et al., 2010), with no examination into potential savings. Within these previous studies, Ostry et al. (2010) showed that changes in sense of limb motion persisted 24 h after reaching in a velocity dependent force-field, while Nourouzpour et al. (2014) found that changes in felt hand position persisted 24 h after adapting to a gradually introduced visuomotor rotation distortion. Results from Hatada et al. (2006) suggest that longer-term retention of sensory changes (e.g., up to 7 days) may be possible, as they found continued changes in reaches to proprioceptive targets 7 days after participants reached to targets while wearing laterally displacing prism lenses, with the greatest recall occurring two days after participants completed initial training. Furthermore, Berniker and Kording, 2008, Berniker and Kording, 2011 source-estimation model also posits retention of sensory changes. Specifically, their model, which suggests that the source of errors experienced during motor adaptation are assigned to a combination of changes in both world-based or body-based properties, predicts that recalibration of our proprioceptive (body-based) estimates should persist over time in the form of savings.

The goal of the current study was to establish retention of proprioceptive recalibration over an extended period of time (4 days) in the form of recall and savings. As well, we looked to determine the benefits of additional training on short-term (24 h) retention of proprioceptive recalibration. All of our participants trained to reach to a visual target when provided with rotated visual feedback of the hand (i.e., a 30° CW cursor rotation). Over the course of the reach training trials on an initial day of testing, we had participants reach to the target without visual feedback to assess the timeline of visuomotor adaptation in the form of aftereffects and estimate where they felt their hand was located in space to determine the timeline of proprioceptive recalibration. Following this initial day of testing, participants were divided into two groups: one with similar, additional, reach training across 4 consecutive days of testing (Training group) and another which did not perform the additional reach training trials (Non-Training group) on days 2 through 4. On the 5th testing day, all participants performed the reach training trials. We measured retention in the form of recall on 4 consecutive days of testing following the initial training day. As well, savings was assessed on each training day in the Training group and in the Non-Training group on Day 5. Similar to previous results (e.g., Nourouzpour et al., 2014), we hypothesized that all participants would recalibrate their sense of felt hand position on the first day of testing and recall these sensory changes 24 h following initial training. Furthermore, given that proprioceptive recalibration has previously shown to be limited in magnitude compared to reach adaptation (Salomonczyk et al., 2011), we hypothesized that the Training group would exhibit a greater magnitude of proprioceptive recalibration as training progressed, thus potentially leading to greater recall of proprioceptive recalibration across the testing days as well. For the Non-Training group, we expected recall of proprioceptive recalibration to decrease across testing days with increased time from reaching with the misaligned visual feedback and hence experiencing the visual-proprioceptive mismatch related to hand position. However, we hypothesized that savings of proprioceptive recalibration would be evident on Day 5, given findings from motor adaptation literature suggesting that different processes, including neural networks, underlie savings and recall (Mawase et al., 2017).

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• Mechanisms of proprioceptive realignment in human motor learning

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  Adaptation is a form of motor learning that alters movement in response to a predictable perturbation to the body or environment. This process can also realign or bias proprioception of the adapted movement. Here, we discuss recent work on two mechanisms that are suggested to underlie proprioceptive realignment following motor learning: a sensory mechanism that hinges on mismatches between estimates of limb state across sensory modalities, and a motor mechanism driven by the recalibration of sensory predictions of movement. We review work focused on normal behavior, neuroimaging studies and assessments of neurologic patients suggesting that motor systems, such as the cerebellum, and sensory association systems, such as somatosensory and posterior parietal cortices, may play a role in proprioceptive realignment.

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• The Influence of Age on the Intermanual Transfer and Retention of Implicit Visuomotor Adaptation

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• Visual and proprioceptive recalibrations after exposure to a visuomotor rotation

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• Motor learning without moving: Proprioceptive and predictive hand localization after passive visuoproprioceptive discrepancy training

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