When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to visual (V), proprioceptive (P), or visual + proprioceptive (VP) targets under different visual delay conditions (e.g. on V and VP trials, the visual target was available for the entire reach, it was removed with the go-signal or it was removed 1, 2 or 5 seconds before the go-signal). Subjects completed 5 blocks of trials, with 90 trials per block. For 12 subjects, the visual delay was kept consistent within a block of trials, while for the other 12 subjects, different visual delays were intermixed within a block of trials. To establish which sensory cue subjects weighted the most, we compared endpoint positions achieved on V and P reaches to VP reaches. Results indicated that all subjects weighted sensory cues in accordance with the MLE model across all delay conditions and that these weights were similar regardless of the visual delay. Moreover, while errors increased with longer visual delays, there was no change in reaching variance. Thus, manipulating the visual environment was not enough to change subjects’ weighting strategy, further i

When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to visual (V), proprioceptive (P), or visual + proprioceptive (VP) targets under different visual delay conditions (e.g. on V and VP trials, the visual target was available for the entire reach, it was removed with the go-signal or it was removed 1, 2 or 5 seconds before the go-signal). Subjects completed 5 blocks of trials, with 90 trials per block. For 12 subjects, the visual delay was kept consistent within a block of trials, while for the other 12 subjects, different visual delays were intermixed within a block of trials. To establish which sensory cue subjects weighted the most, we compared endpoint positions achieved on V and P reaches to VP reaches. Results indicated that all subjects weighted sensory cues in accordance with the MLE model across all delay conditions and that these weights were similar regardless of the visual delay. Moreover, while errors increased with longer visual delays, there was no change in reaching variance. Thus, manipulating the visual environment was not enough to change subjects’ weighting strategy, further i

When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to visual (V), proprioceptive (P), or visual + proprioceptive (VP) targets under different visual delay conditions (e.g. on V and VP trials, the visual target was available for the entire reach, it was removed with the go-signal or it was removed 1, 2 or 5 seconds before the go-signal). Subjects completed 5 blocks of trials, with 90 trials per block. For 12 subjects, the visual delay was kept consistent within a block of trials, while for the other 12 subjects, different visual delays were intermixed within a block of trials. To establish which sensory cue subjects weighted the most, we compared endpoint positions achieved on V and P reaches to VP reaches. Results indicated that all subjects weighted sensory cues in accordance with the MLE model across all delay conditions and that these weights were similar regardless of the visual delay. Moreover, while errors increased with longer visual delays, there was no change in reaching variance. Thus, manipulating the visual environment was not enough to change subjects’ weighting strategy, further i

Context: Individuals with chronic ankle instability (CAI) rely more on visual information during postural control due to impaired proprioceptive function. The increased reliance on visual information may increase the risk of injury when their vision is limited during complex sports activities. Stroboscopic glasses may help elicit sensory reweighting during postural control. Therefore, we assumed that the glasses would induce and train CAI patients to reweight sensory information for the somatosensory system during dynamic balance training. Purpose: (1) to identify the effects of the 4-week dynamic balance training on the reliance of visual information during postural control in patients with CAI and (2) to compare the effects of the 4-week dynamic balance with and without stroboscopic glasses on postural control in patients with CAI. Methods: This study was a randomized controlled trial. Twenty-eight CAI patients were equally assigned to one of 2 groups: a strobe group (6 males and 8 females) or a control group (8 males and 6 females). The 4-week dynamic balance training consisted of multiple single-legged exercises. The strobe group wore stroboscopic glasses during the training, but the control group did not. The main outcome measures included the following: self-reported function measures, static postural control (center of posture (COP)-based measures), and dynamic postural control including the Dynamic Postural Stability Index (DPSI), and the Star Excursion Balance Test (SEBT). There were 3 visual conditions in the static postural control (eyes-open (EO), strobe vision (SV), and eyes-closed (EC)), and 2 conditions in the dynamic postural control (EO and SV). Two-way randomized block ANOVAs were used to assess changes in postural control in each group and condition by using pretest-posttest mean differences. Results: The strobe group showed a higher difference in COP velocity in medial-lateral direction (VelML) and vertical stability index (VSI) under the SV condition compared with the control group (p = .005 and .004, respectively). In addition, the strobe group had significant decreases in VelML, DPSI, and VSI at the posttest compared with the pretest (p = .0001, .01, and .005, respectively). Conclusion: The 4-week dynamic balance training with stroboscopic glasses appeared to be effective in improving postural control and altering visual reliance in patients with CAI.