1: Li Y, Xiao W, Wu P, Deng Z, Zeng C, Li H, Yang T, Lei G. The expression of Nov;23(6) doi: /s Epub Jan 3. Epub Aug PubMed PMID: 2: Yang XY, Yang DS, Wei-Zhang, Wang JM, Li CY, Hui-Ye, Lei KF, Chen XF, Shen NH, Jin LQ, Wang JG. Epub Apr Second Epub Jan Epub Jun J Org Chem Sep 2;83(17) Epub Aug 2. Epub Mar
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In addition, the proprioceptive sensation per se may be not as precise as the visual perception. In the experiment of Van Beers et al. The precision of the visual localization was between 0. Taken together, the proprioceptive sensation of limb movements seems to be highly susceptible and less reliable than the visual sensation.
Empirical evidence shows that humans are able to integrate multisensory signals in an optimized fashion to maximize the reliability of the perception Ernst and Banks, ; Drewing and Ernst, Considering a motor action as an object of perception, integration of sensory feedback from visual and proprioceptive senses should follow the same principle.
Therefore, in connection with the aforementioned lack of reliability of proprioception, it makes perfect sense that vision dominates action control, since the variance of the visual estimation is lower than that of the proprioceptive estimation. The major question addressed in the current study is if there are any factors that moderate the bimodal integration, and consequently, affect the predominance of the visual feedback.
We focused on two potential factors. A process-related factor could be the presence of motor commands.
These can be understood as neural signals generated as exclusive sources of voluntary actions. Since motor commands build a link between distal and proximal action effects the movement mode should play an important role in information processing. The study by Zwickel et al. Judgments were significantly biased in the direction of the produced movement when movements were performed actively, whereas no such effect was observed for passive movements.
Accordingly, we assume that the motor commands could enhance sensory integration and consequently strengthen the impact of distal feedback on proximal movement perception.
A subject-related factor could be age.
Mounting evidence suggests that declines in proprioceptive function represent a fundamental aspect of the aging process Adamo et al. A variety of age-related neurophysiological changes may account for the declines in proprioception. Changes in the peripheral nervous system as potential cause are for example decreased spindle diameter, decreased sensitivity of muscle spindles, decreased number of intrafusal fibers, and a decline in the number of joint mechanoreceptors for a comprehensive review see Goble et al.
Declines in proprioceptive functions are also thought to be a result of changes in the central nervous systems, since increased proprioceptive processing demands were found to significantly impact the assessment of proprioceptive acuity in the elderly Stelmach et al. Based on these findings, we assume that the elderly would be more dependent on the visual feedback, which would then unfold its dominance more intensively. Finally, the following hypotheses were proposed: a Distorted visual feedback makes movement perception more difficult.
To examine these hypotheses, the current study compared the performance in limb movement perception of older and younger adults in various feedback distorted visual feedback vs.
Materials and Methods Participants In total eight younger participants five male , aged between 22 and 29 years mean: 25 years; SD: 2. All of them were right-handed and had normal or corrected-to-normal vision. Participants were all neurologically intact and had no known history of neuromotor disorders. Prior to the experiments, participants signed an informed consent statement.
The robot presents redundant kinematics with seven degrees of freedom, allowing more complexity in the execution of the movements. Sensors evaluating the torque in each joint in real-time provide several useful features, for instance the compensation of the gravity and accelerated reaction when the robot is submitted to external forces.
All triangles were isosceles with a constant horizontal base of 26 cm. The six standardized movement trajectories of the hand solid lines. For visual feedback an equal-sided right-angled triangle with dashed lines was constantly displayed. The participants sat on a chair in front of the robot arm Figure 3. The chair and the robot arm stood immovable through the experiment.
The right shoulder of the participant and the resting robot arm on its start location were on the same sagittal plane. The distance between the shoulder of the participant and the robot arm was approximately 70 cm. Participants put their dominant hand on the robot arm and either performed the movement actively or the relaxed limb was moved passively. Every movement was constrained within one of the six pre-defined trajectories.
Short audio signals pure tone with Hz for ms were provided to mark the beginning and the end of each movement.
The audio signals were clearly audible to the participants, despite the ear protection they were wearing throughout the experiment. The distorted visual feedback consisted of a cursor a blue dot with a diameter of 3 mm moving along the sides of a static equilateral right-angled triangle with a base of 26 cm Figure 2 , dashed lines , which was presented centrally on the display.
Schematic view of the set-up. With help of the robot, limb movements could be carried out passively or actively. A distorted visual feedback about the limb movement could be presented on a LCD monitor, left alongside the robot in front of the participant. Communication between the robot arm and the feedback monitor was facilitated by a MatLab Ra program on a Windows computer.
The movement of the robot arm was proportionally transferred into cursor movement, depending on the ratio between the total length of the actual limb trajectory and the feedback triangle, so that the cursor appeared to be completely synchronized with the robot arm. The passive movements have pre-defined acceleration profiles and a constant duration of approximately 6 s.
In catch trials the blue cursor indicating the movement brightened shortly yellow , which should be detected and reported by the participants as a secondary task. The experimenter registered the responses manually. Procedure The experiment was carried out in two consecutive sessions.
In Session I, a trial started with an audio signal, after which the robot arm began to move. Starting from the vertex down left, the robot led the relaxed right hand of the participant to complete one of the six standardized trajectories. After another audio signal indicated the end of the movement, participants instantaneously estimated the shape of their unseen hand trajectory. Session I contained two blocks differing in feedback conditions: one block contained only trials with distorted visual feedback, while the other block contained only trials without visual feedback.
The sequence of the blocks was counterbalanced across all participants. Every pre-defined trajectory was presented 15 times resulting in 90 trials per block.
Prior to experimental trials 15 practice trials were provided to familiarize the participants with the task and its requirements. The whole session took about 60—70 min. At the end of the session participants were given a short questionnaire, in which they were asked about the strategy for making their estimations.
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