spine is that one cannot view their own back in everyday living; thus, visual information about the neck is rarely provided for the somatosensory representation of the body. With chronic pain, providing real-time visual feedback of one’s own back reduces experimental pain ( Diers et al., 2013 ) and
Konstantin Beinert, Katharina Deutsch, Sebastian Löscher, and Martin Diers
Gavin P. Lawrence, Michael A. Khan, Stuart Mourton, and Pierre-Michel Bernier
The objective of the current study was to determine whether the reliance on visual feedback that develops with practice is to due utilizing vision to adjust trajectories during movement execution (i.e., online) and/or to enhance the programming of subsequent trials (i.e., offline). Participants performed a directional aiming task with either vision during the movement, dynamic feedback of the trajectory of the movement or the movement endpoint. The full vision condition was more accurate during practice than the other feedback conditions but suffered a greater decrement in performance when feedback was removed. In addition, the reliance on trajectory feedback was greater compared with the endpoint feedback. It appears that the reliance on visual feedback that develops with practice was due to both online and offline processing.
Jeremy W. Noble, Janice J. Eng, and Lara A. Boyd
This study examined the effect of visual feedback and force level on the neural mechanisms responsible for the performance of a motor task. We used a voxelwise fMRI approach to determine the effect of visual feedback (with and without) during a grip force task at 35% and 70% of maximum voluntary contraction. Two areas (contralateral rostral premotor cortex and putamen) displayed an interaction between force and feedback conditions. When the main effect of feedback condition was analyzed, higher activation when visual feedback was available was found in 22 of the 24 active brain areas, while the two other regions (contralateral lingual gyrus and ipsilateral precuneus) showed greater levels of activity when no visual feedback was available. The results suggest that there is a potentially confounding influence of visual feedback on brain activation during a motor task, and for some regions, this is dependent on the level of force applied.
Michael A. Khan, Gavin P. Lawrence, Ian M. Franks, and Digby Elliott
The purpose of the present study was to establish the contribution of visual feedback in the correction of errors during movement execution (i.e., online) and the utilization of visual feedback from a completed movement in the programming of upcoming trials (i.e., offline). Participants performed 2 dimensional sweeping movements on a digitizing tablet through 1 of 3 targets, which were represented on a video monitor. The movements were performed with and without visual feedback under 4 criterion movement times (150, 250, 350, 450 msec). We analyzed the variability in directional error at 25%, 50%, 75%, and 100% of the distance between the home position and the target. There were significant differences in variability between visual conditions at each movement time. However, in the 150-msec condition, the form of the variability profiles did not differ between visual conditions, suggesting that the contribution of visual feedback was due to offline processes. In the 250-, 350-, and 450-msec conditions, there was evidence for both online and offline control, as the form of the variability profiles differed between the vision and no vision conditions.
Fatemeh Zahed and Max Berniker
reaches are robust to physical perturbations ( Berniker, Franklin, et al., 2014 ; Berniker, Mirzaei, & Kording, 2014 ; Kistemaker et al., 2010 ; Shadmehr & Mussa-Ivaldi, 1994 ) but not alterations of visual feedback ( Arce et al., 2009 ; Danziger & Mussa-Ivaldi, 2012 ; Farshchiansadegh et al., 2016
Mark Cummings, Aditi Doshi, and Sangeetha Madhavan
et al., 2009 ). Visuomotor coordination is the ability to perform motor tasks with extrinsic visual feedback and contributes to our ability to effectively interact with our surroundings ( Atkinson & Nardini, 2008 ). The transfer of visual information to motor performance, especially during the
Jeff E. Goodwin
Participants were randomly assigned to one of four groups. The fade group received 100% concurrent visual feedback on acquisition trials 1–4, 75% on trials 5–8 (concurrent feedback on trials 5, 6, and 7), 50% on trials 9–12 (concurrent feedback on trials 10 and 12), 25% on trials 13–16 (concurrent feedback on
Patrice R. Rougier and Samir Boudrahem
Past studies have emphasized the beneficial effect of additional visual feedback (VFB) on the capacity of healthy adults to decrease the amplitudes of the center-of-pressure minus center-of-gravity (CP-CGv) movements. To better assess these capacities, 56 subjects were asked to stand still on a force platform and to use the visual information provided. Dependency coefficients, based on their capacity to lower their CP-CGv movements and therefore relax their lower limb muscles, as well as parameters aimed at characterizing their postural strategies were measured across VFB conditions including (1) CP displacements in real time (VFBCP0), (2) CP displacements with a 600-ms delay (VFBCP600), and (3) CP-CGv displacements with a 600-ms delay (VFBCP-CG600). A non-VFB condition (eyes open) was also included. Several linear correlations were used to specify the relation between subjects’ capacity to relax, compared with the VFBCP0 condition, across the three remaining conditions. The data highlight the complementary nature of the VFB conditions and establish the postural control behaviors necessary to use these VFB protocols efficiently.
Marcie Fyock, Nelson Cortes, Alex Hulse, and Joel Martin
investigating real-time visual feedback as an intervention choice for the treatment of PFP in adult recreational runners. Focused Clinical Question In adult runners diagnosed with PFP, does gait retraining with real-time visual feedback lead to a decrease in pain? Summary of Search, “Best Evidence” Appraised
Ing-Shiou Hwang, Chia-Ling Hu, Wei-Min Huang, Yi-Ying Tsai, and Yi-Ching Chen
The detection of performance errors via visual feedback during a visuomotor task determines a person’s capacity to utilize error information and correct motor responses on the next attempt ( de Grosbois & Tremblay, 2016 ). Task quality and movement strategy covary with the feedback modality by