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/lp/springer_journal/postural-responses-to-target-jumps-and-background-motion-in-a-fast-9Cvv2Awa7m
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by The Author(s)
- Subject
- Biomedicine; Neurosciences; Neurology
- ISSN
- 0014-4819
- eISSN
- 1432-1106
- DOI
- 10.1007/s00221-018-5222-6
- Publisher site
- See Article on Publisher Site
Abstract
When reaching towards an object while standing, one’s hand responds very quickly to visual perturbations such as the target being displaced or the background moving. Such responses require postural adjustments. When the background moves, its motion might be attributed to self-motion in a stable world, and thereby induce compensatory postural adjustments that affect the hand. The changes in posture associated with a given hand movement response may, therefore, be different for the two types of perturbations. To see whether they are, we asked standing participants to move their hand in the sagittal direction away from their body to targets displayed on a horizontal screen in front of them. The target displacements and background motion were in the lateral direction. We found hand movement responses that were in line with earlier reports, with a latency that was slightly shorter for target displacements than for background motion, and that was independent of target displace- ment size or background motion speed. The trunk responded to both perturbations with a modest lateral sway. The two main findings were that the upper trunk responded even before the hand did so and that the head responded to background motion but hardly responded to target displacements. These findings suggest that postural adjustments associated with adjusting the hand movement precede the actual adjustments to the movement of the hand, while at the same time, participants try to keep their head stable on the basis of visual information. Keywords Postural control · Visual perturbation · Two-step paradigm · Target jump · Background motion · Arm reaching Introduction instance, so when shifting one’s hips backward while leaning forward to reach a floating toy in a tub. In general, balance When we reach out for objects in daily life, we often do is challenged by moving the arm, while the efficiency and not only adjust the angles of the joints of our arm. Some- accuracy of the goal-directed arm movement are challenged times, adjustments to the joints in the leg and trunk con- by the postural requirements of maintaining balance (Ber- tribute directly to reaching the object, such as when stretch- rigan et al. 2006). This relationship explains why arm move- ing out and standing on one’s toes to reach something on ments are accompanied by anticipatory postural adjustments a high shelf. If there is no direct contribution to bringing that are tuned to the requirements of the upcoming arm the hand to the object, we refer to adjustments as postural movement (Aruin and Latash 1995; Bouisset and Zattara adjustments. Postural adjustments are frequently required 1987). Rapid postural adjustments are also observed when a for the control of balance (i.e., not falling over). This is, for moving arm is perturbed mechanically, so the link between arm movements and postural adjustments is not limited to planned aspects of the movement (Lowrey et al. 2017). * Yajie Zhang Another issue that we often have to deal with in daily life y3.zhang@vu.nl is adjusting an ongoing reaching movement. For instance, Department of Human Movement Sciences, Vrije if we want to take a glass off a tray held by a waiter, we Universiteit Amsterdam, Amsterdam Movement Sciences, not only have to adjust our posture to keep balance while Amsterdam, The Netherlands reaching for it, but might also have to adjust the whole Department of Kinesiology, FaBer, KU Leuven, Leuven, movement as the tray moves. It is well known that arm Belgium movements can be adjusted when the target of the action is Department of Rehabilitation Sciences, FaBer, KU Leuven, displaced (Georgopoulos et al. 1981; Pelisson et al. 1986; Leuven, Belgium Vol.:(0123456789) 1 3 1574 Experimental Brain Research (2018) 236:1573–1581 Soechting and Lacquaniti 1983). The trajectory can start to to background motion. If the postural response is in antici- be adjusted 100–150 ms after the target is displaced (Bren- pation of the arm movement adjustment, we expect to see ner and Smeets 1997; Gritsenko et al. 2009; Kadota and very similar postural responses for similar arm movement Gomi 2010; Oostwoud Wijdenes et al. 2011; Oostwoud responses. However, if the background motion induces a Wijdenes et al. 2013), and such adjustments occur even if postural response that includes an arm movement, possibly the person in question is not aware of the change in target to compensate for the suggested self-motion, we might at location (Goodale et al. 1986). least initially expect the response to be quite different from Our first question is whether such fast adjustments to the the postural response that is made to maintain one’s balance trajectory of the arm are accompanied by postural adjust- when adjusting the arm movement after a target is displaced. ments, and in particular whether such postural adjustments Although we expect a clearly different response in the latter precede the adjustments to the arm, as they do in a simple case, it might be that the trunk also responds before the hand reaction time task (e.g., Bouisset and Zattara 1981; Sli- in a purely postural response. jper et al. 2002). Given that adjustments have to be made To answer our questions, we first verify that fast adjust- as quickly as possible, having to first adjust one’s posture ments of reaching movements when the target of the reach is may result in the response having to be delayed, and, there- displaced are accompanied by anticipatory postural adjust- fore, in longer latencies of the response (Slijper et al. 2002). ments (Leonard et al. 2011). We call any response before the Indeed, Leonard et al. (2011) found adjustments in elec- onset of the hand adjustment ‘anticipatory’. We then exam- tromyographic (EMG) activity of some postural muscles ine whether the postural response to background motion is before adjustments in activity of the prime movers for a in anticipation of the arm or is an independent response by hand movement. In their study, the early postural adjust- comparing the postural adjustments in response to target ments were accompanied by a relatively long latency of the jumps and background motion in conditions with similar hand movement adjustment (> 175 ms). Alternatively, rather adjustments to the arm movement. Answering the two ques- than delaying the response of the hand, the postural adjust- tions will contribute to a better understanding of the inter- ments might only occur after the onset of the correction, action between manual and postural control when one is as has been reported for choice reaction time tasks (Slijper standing and reaching. et al. 2002) and for responses to mechanical perturbations of the arm (Lowrey et al. 2017). A final issue that we might have to deal with is that there Methods may be movement in the background, such as many people walking by as we try to take the glass off the tray. There Participants are numerous reports of goal-directed arm movements being influenced by motion in the surrounding (Brenner Sixteen right-handed participants (28.3 ± 3.0 years, 7 males) and Smeets 1997; Saijo et al. 2005; Whitney et al. 2003). participated in the experiment. They had normal or cor- A possible reason for quickly responding to motion in the rected-to-normal vision. None of the participants had any background is that such motion is attributed to self-motion disease that can affect motor or sensory function. The study that requires a postural response (Gomi 2008; Mergner was approved by the Research Ethics Committee of the Fac- et al. 2005). That motion in the surrounding would influ- ulty of Behavioural and Movement Sciences, Vrije Univer- ence postural responses is consistent with peripheral visual siteit Amsterdam. Written informed consent was obtained information playing an important role in postural stability from each participant. when standing (Nashner and Berthoz 1978). However, the response of the arm to background motion is not mainly guided by peripheral visual information (Brenner and Experimental setup Smeets 2015). The latency of responses of the arm to back- ground motion is 110–160 ms (Brenner and Smeets 1997; A screen (60 Hz refresh rate, 91.9 × 51.6 cm, 1920 × 1080 pixel resolution) was positioned horizontally on a table Gomi et al. 2006; Whitney et al. 2003), which is similar to that for target jumps (100 to 150 ms; Brenner and Smeets (Fig. 1a). The participant stood barefoot with his or her feet separated by about 10% of the participant’s height, 15 cm 1997; Gritsenko et al. 2009; Kadota and Gomi 2010; Oost- woud Wijdenes et al. 2011; Oostwoud Wijdenes et al. 2013). from the near edge of the screen. The height of the table could be adjusted to align the screen with the participant’s The magnitude of the response depends on the magnitude of the target displacement and on the speed of background hip. A photodiode was attached to the upper right corner of the screen to detect when the target appeared and when it motion (Brenner and Smeets 1997; Saijo et al. 2005). Our second question is whether postural responses to the changed position or the background started moving (with an error of 5 ms at most). target being displaced are similar to the postural responses 1 3 Experimental Brain Research (2018) 236:1573–1581 1575 Fig. 1 Methods. a Schematic side view of a participant in the exper- file of a typical lateral response with latency determination using the imental setup, with the red discs indicating the marker positions. b extrapolation method Sequence of visual events in the three types of trials. c Velocity pro- An Optotrak 3020 motion capture system (Northern Digi- starting point for a random time between 0.6 and 1.2 s, the tal, Waterloo, Ontario, Canada) with two cameras was used. starting point disappeared and the target dot (radius: 1.5 cm) One camera was behind the participant and one to his or appeared. The participant was instructed to tap on the target her right. The sampling rate was 200 Hz. The posture was as accurately and quickly as possible with the tip of the right recorded with customised cluster markers: three markers index finger. attached rigidly to each other in a triangular configuration. While the participant moved towards the target, either Cluster markers were attached to the forehead, 3rd thoracic target displacement or background motion could occur, trig- vertebra (referred to as ‘upper trunk’), 1st sacral vertebra gered by the finger having moved 5 mm from the starting (referred to as ‘lower trunk’) and the wrist (ulnar side). A point on the screen. Due to delays in measuring the move- single marker was attached to the nail of the index finger of ment of the finger and rendering images on the screen, the the right hand. The latter was used to control the experiment actual perturbation was 60 ms after the finger crossed this on the basis of the movement of the finger. threshold. If the target was hit (i.e., if the contact position of the finger, as determined by the calibration, was within Experimental task and procedure the target), a sound indicated success. Otherwise, the target drifted away from where the finger touched the screen. Each session started with a calibration procedure for deter- The experiment consisted of nine conditions: four tar- mining the position of the index finger when in contact with get jump conditions, four background motion conditions, given positions on the screen in Optotrak coordinates. After and a no-perturbation condition. In the target jump condi- the calibration, participants started individual trials by mov- tions, the target jumped either 1 or 4 cm, leftwards or right- ing their right index finger to the starting point. The starting wards, across the stationary background. In the background point of each arm movement was a dot (radius: 1 cm) that motion conditions, the background moved either leftwards was shown on the checkerboard-like background (square or rightwards at 2 or 6 cm/s, ‘below’ the stationary target. length: 7 cm). Once the index finger had been resting on the We chose perturbation sizes that would be likely to make 1 3 1576 Experimental Brain Research (2018) 236:1573–1581 the magnitude of the response of the hand comparable for the time at which a line through the points at which the target jump and background motion conditions. This was response reached 25% and 75% of the peak response inter- based on a pilot study, in which we varied the target jump sected a baseline value (Fig. 1c; Veerman et al. 2008). The amplitude and background velocity. There were 300 trials baseline value was the average velocity from 50 ms before to in total: 30 trials each in four target jump conditions and 50 ms after the perturbation. This is possible because basing four background motion conditions, and 60 trials in the no- the response on the difference between trials with rightward perturbation condition. All trials were presented in a com- and leftward perturbations removes any systematic lateral pletely random order. The participants practiced for about 20 motion (or angular velocity) that is not related to the pertur- trials (random conditions) before the start of the experiment. bation. The extrapolation method requires a clearly identifi- During the experiment, they could rest at any time they liked able peak. As the data of some participants showed multi- by not moving to the starting point. ple peaks, using the individual responses would have forced us to exclude the data of some participants. The responses Data analysis of body parts other than the finger were very modest with respect to the spontaneous trial-to-trial variability, so it was The 3D kinematic data of all markers were filtered using a impossible to reliably identify response peaks for all indi- second order low-pass Butterworth filter with a cut-off fre- vidual participants. Therefore, we determined the latencies quency of 30 Hz. We determined this cut-off frequency by based on the average response of all participants. We boot- determining the minimum variance in the distances between strapped (resampled) the trials within each participant to the three markers on a cluster (Schreven et al. 2015). We obtain a measure of reliability. We averaged the resampled found this minimum for frequencies between 20 and 30 Hz, responses of all participants and determined the latency for depending on the body part. As the variance increases con- the average response. Doing so 1000 times provided a distri- siderably for cut-off frequencies below the optimum fre- bution of latencies based on resampled trials, which we used quency, and only mildly for higher frequencies, we chose to determine a Bayesian 95% credible interval. 30 Hz to filter all lateral motion data (finger, wrist, head, The cluster markers not only allow us to determine the upper trunk and lower trunk). We checked whether the lateral motion, but also rotations. Although we do not have choice for this cut-off frequency influenced our results by predictions for the rotations, the azimuthal rotation might be re-analysing the data with a 50 Hz cut-off frequency. The informative. Despite optimal filtering at 30 Hz, the filtered effects on observed latencies were less than 2 ms. signal turned out to be quite noisy. Fast Fourier transformed Movement time was calculated as the duration between data revealed a peak in the spectrum of rotations that was the onset of the finger movement (finger lifted higher than absent in the translations (possibly due to cluster vibration). 5 mm) and the finger touching the screen again. We excluded To present interpretable data on rotational movement, we trials (5%) for which the duration or the delay in presenting had to filter the orientations at 10 Hz. Since this additional the perturbation was not within ± 3SD of the mean, or for filtering smooths the responses considerably, we did not ana- which the moment of the perturbation could not be deter- lyse the orientation data quantitatively. mined properly (on the basis of the signal picked up by the Descriptive data are shown as means or means ± standard photodiode). Movements to the right and away from the deviations (SD) across participants. The movement times body were considered positive. were calculated for each trial, and then averaged across the As the perturbations were always in the lateral direction, four target (or background) conditions for each participant. we only analysed responses in the lateral direction. The lat- eral velocity of the finger was calculated from the meas- ured position data using the central difference algorithm. Results We defined time zero as the moment at which the perturba- tions actually happened, which was about 60 ms after the The mean movement times were 382 ± 44 ms for unper- finger had been raised 5 mm from the screen. Responses turbed trials, 400 ± 44 ms for trials with target jumps and were determined by comparing movements after rightward 396 ± 43 ms for trials with background motion. Participants and leftward perturbations (differences between the move- hit the target in 95.0 ± 3.9% of the 300 trials. This means that ments in the direction of the perturbation were considered participants were able to successfully follow the target jumps positive). Since this gives the sum of the responses in both and compensate for their initial responses to background directions, we divided the difference between the responses motion (Fig. 2a). The finger always initially moved in the to rightward and leftward perturbations by two. The result is direction of the perturbation, regardless of whether the target equivalent to a response to a rightward perturbation. jumped or background moved (Fig. 2b). If the background We used the extrapolation method to determine the moved (blue and green traces), the finger followed the back - latency of responses to the perturbations: the latency was ground motion even though the target was stationary, and it 1 3 Experimental Brain Research (2018) 236:1573–1581 1577 Fig. 2 a Overview of the average finger paths of all participants in the nine conditions. The origin is the location of the starting dot. b, c Lateral velocity of the finger, upper trunk and head as a function of the time since the perturbation (about 60 ms after movement onset) moved further in the direction of the perturbation for faster (Fig. 3c, d). Remarkably, the head responded very differ - background motion (dashed blue and green traces). If the ent to target jumps than to background motion (Fig. 3e): target jumped (red and magenta traces), the finger followed there was hardly any initial response of the head to target the target jump. The response reached a higher peak velocity jumps, whereas there was a clear response to background and lasted longer for a larger target displacement (dashed red motion. The rotation of the head within 250 ms after the and magenta traces). The responses of both the upper trunk perturbation was small, but the angular velocities were big- and the head are small in comparison to the lateral move- ger in response to background motion than in response to ments that occur even without any perturbation (Fig. 2c). We target jumps (Fig. 3f). The azimuthal rotation of the upper checked for a possible postural response to the perturbation and lower trunk also started earlier for target jumps than for in the anterior–posterior direction. No postural adjustments background motion (Fig. 3f). were found within 200 ms after the perturbation. Perturbation size (target jump; background velocity) Concentrating on the lateral responses, we find that the did not affect the hand response latencies. The latencies finger and wrist showed similar magnitudes of responses of the lateral responses to the target jumps were shorter when the target jumped as when the background moved than those to the background motion for the finger (109 vs. (compare red and blue traces in Fig. 3a, b). The trunk 123 ms), as well as the wrist (112 vs. 124 ms; Fig. 4). The responses were much smaller than those of the wrist and latency difference between target jumps and background finger, but also similar for the two types of perturbation 1 3 1578 Experimental Brain Research (2018) 236:1573–1581 Fig. 3 Average response to target jumps and background motion as a function of the time since the perturbation for the a finger, b wrist, c upper trunk, d lower trunk and e head. f Response in azimuthal angular velocity for the upper trunk, lower trunk and head (clockwise is positive). Shaded areas represent the SEM across participants. Note that the scales for responses of the hand (a, b) are different from those for the body (c, d, e) motion conditions varied between 14 and 28 ms for dif- Conclusions and discussion ferent body parts (Fig. 4), which is (given the filtering at 30 Hz) within the temporal precision of determining We compared the responses of manual and postural adjust- the latency according to the extrapolation method based ments to two types of perturbations (target jump and back- on velocity (Oostwoud Wijdenes et al. 2014). The head ground motion). Both the perturbations and the responses responded to the background motion after about 116 ms. were in the medio-lateral direction. The upper trunk moved Notably, the upper trunk was the first part of the body to in the same direction as the perturbation, before the hand did respond to the perturbations. It responded about 76 ms so. The postural adjustments to the two types of perturba- after the target jumps, about 33 ms before the hand tion were similar for all parts of the body that we measured, responded (Fig. 4). The lower trunk responded about except the head. One limitation of the study is that we only 32 ms later than the hand. use trunk and head displacements as a measure of anticipa- tory postural adjustments, although some muscle activations 1 3 Experimental Brain Research (2018) 236:1573–1581 1579 Fig. 4 Response latencies of different body parts to target jumps and to background motion. The bars represent latencies calculated from the mean curves shown in Fig. 3. The error bars show Bayes- ian 95% credible intervals. As the bootstrapped data were noisy, the extrapolation method sometimes yielded nonsensical (negative) values for the laten- cies. We included these nonsen- sical values in the determination of the credible interval may control posture without leading to observable displace- a separate cause for the responses of the head. An obvious ments. This limitation would have made the interpretation way to interpret this is that participants were trying to keep of a null-finding problematic, but does not hamper the inter - their head stable relative to the surrounding when adjusting pretation of the clear anticipatory postural adjustments that the reach (which makes sense for arm movements in a stable we observed. environment). Following this reasoning, the head motion We interpret the very early upper trunk response as induced by moving the background is likely to be a reaction an anticipatory postural adjustment. The reason is that it to the motion of the background being attributed to self- occurred about 33 ms before the response became apparent motion (see introduction). Hence, there are different postural in the hand, and thus did not contribute directly to moving responses to target jumps and background motion, but there the hand. Both when the target jumped and when the back- are also common components to the postural responses, ground moved, the first response was in the upper trunk (at which answers our second question. the shoulder level; Fig. 4). The response was in the same We found no effects of target jump size on hand response direction as the subsequent movement of the arm, suggesting latencies, which is in line with earlier research (Brenner and that it was made in anticipation of the rotation of the shoul- Smeets 1997; Veyrat-Masson et al. 2010). We also found no der and elbow. Trunk movements in a direction that matches effect of background velocity on hand response latency, in a future arm movement have been found before when there line with earlier research (Saijo et al. 2005). The latencies is the possibility of a perturbation (Martin et al. 2000). The of finger responses to target jumps were 14 ms shorter than fastest responses have been found in the leg (Fautrelle et al. those to background motion in the present study. In the pre- 2010; Leonard et al. 2011) and at the shoulder level when vious studies with both target jumps and background motion, adjusting to a target jump in depth (Fautrelle et al. 2010). the responses to target jumps had a 40-ms shorter latency In that case, it was the EMG activity in the muscle of the (Brenner and Smeets 1997) or a 15 ms longer latency (Kad- shoulder rather than the displacement of the shoulder that ota and Gomi 2010) than those to background motion. These was earlier. That it took tens of ms longer for the wrist to differences may be caused by differences between the set- respond than for the upper trunk to do so, makes it unlikely ups or stimuli, because the attribute that defines the target that this just has to do with a shoulder-to-wrist sequence. can influence the response latency (Veerman et al. 2008), as Thus, the answer to our first question is yes , arm responses might the contrast, pattern and size of the background. Bren- to target perturbations are preceded by anticipatory postural ner and Smeets (1997) used faint lines as their background, adjustments. while Kadota and Gomi (2010) and we used high-contrast We did not observe differences in the responses of the checkerboards. The high contrast might result in quicker hand and trunk to the two types of perturbation. In con- response latencies. trast, the head clearly responded to background motion, but The difference in latency suggests that the responses to hardly responded to target jumps. The difference in head the two types of perturbations rely on different pathways. response between the two types of perturbations that resulted The background-induced responses are likely to involve in similar responses of hand and trunk suggests that there is cortical pathways. Global motion, such as the background 1 3 1580 Experimental Brain Research (2018) 236:1573–1581 motion in our experiment, activates many visual areas References (Palmisano et al. 2015), including some that appear to be Aruin AS, Latash ML (1995) Directional specificity of postural mus- specialised in analysing optic flow (such as VIP, the ventral cles in feedforward postural reactions during fast voluntary arm intraparietal area; Schaafsma and Duysens 1996; Gabel et al. movements. Exp Brain Res 103:323–332 2002a, b). It has been suggested that the fast corrections of Berrigan F, Simoneau M, Martin O, Teasdale N (2006) Coordination hand movements might rely on subcortical mechanisms (Day between posture and movement: interaction between postural and accuracy constraints. Exp Brain Res 170:255–264. https :// and Brown 2001). This could explain the latency difference. doi.org/10.1007/s0022 1-005-0210-z However, the posterior parietal cortex is also considered to Bouisset S, Zattara M (1981) A sequence of postural movements pre- be involved in fast online adjustments to target displace- cedes voluntary movement. Neurosci Lett 22:263–270. https://doi. ments, because a patient with bilateral posterior parietal org/10.1016/0304-3940(81)90117 -8 Bouisset S, Zattara M (1987) Biomechanical study of the program- lesions could not make such corrections (Pisella et al. 2000), ming of anticipatory postural adjustments associated with and transcranial magnetic stimulation (TMS) of the con- voluntary movement. J Biomech 20:735–742. h t t p s : / / d o i . tralateral parietal cortex disrupts fast corrections (Desmur- org/10.1016/0021-9290(87)90052 -2 get et al. 1999). Moreover, fast online adjustments can be Brenner E, Smeets JBJ (1997) Fast responses of the human hand to changes in target position. J Mot Behav 29:297–310 mediated by the parvocellular pathway (Brenner and Smeets Brenner E, Smeets JBJ (2003) Perceptual requirements for fast 2003; Veerman et al. 2008) and can occur even if responding manual responses. Exp Brain Res 153:246–252. https ://doi. requires the processing of attributes such as colour (Brenner org/10.1007/s0022 1-003-1598-y and Smeets 2004; Veerman et al. 2008). Therefore, whether Brenner E, Smeets JBJ (2004) Colour vision can contribute to fast corrections of arm movements. Exp Brain Res 158:302–307. the use of different pathways is responsible for the latency https ://doi.org/10.1007/s0022 1-004-1903-4 difference is not clear. Brenner E, Smeets JBJ (2015) How moving backgrounds influ- In conclusion, when visual perturbations occur during a ence interception. Plos One. https ://doi.or g/10.1371/jour n hand movement while standing, there are postural adjust- al.pone.01199 03 Day BL, Brown P (2001) Evidence for subcortical involvement in ments that precede the manual adjustments. These postural the visual control of human reaching. Brain 124:1832–1840 adjustments are very similar, but not identical, when the Desmurget M, Epstein CM, Turner RS, Prablanc C, Alexander target of the action is displaced and when the background GE, Grafton ST (1999) Role of the posterior parietal cortex in moves. The main difference is to be found in the movement updating reaching movements to a visual target. Nat Neurosci 2:563–567 of the head. Fautrelle L, Prablanc C, Berret B, Ballay Y, Bonnetblanc F (2010) Pointing to double-step visual stimuli from a standing position: Acknowledgements This research was funded by the European Com- very short latency (express) corrections are observed in upper and mission through MOVE-AGE, an Erasmus Mundus Joint Doctorate lower limbs and may not require cortical involvement. Neurosci programme (2011–2015). 169:697–705. https://doi.or g/10.1016/j.neuroscien ce.2010.05.014 Gabel SF, Misslisch H, Gielen CCAM., Duysens J (2002a) Responses Compliance with ethical standards of neurons in area VIP to self-induced and external visual motion. Exp Brain Res 147:520–528. https ://doi.or g/10.1007/s0022 1-002-1268-5 Ethical approval The experiment is part of an ongoing research pro- Gabel SF, Misslisch H, Schaafsma SJ, Duysens J (2002b) Temporal gram that has been approved by the ethics committee of the Faculty of properties of optic flow responses in the ventral intraparietal area. Behavioural and Movement Sciences of Vrije Universiteit Amsterdam. Vis Neurosci 19:381–388 Georgopoulos AP, Kalaska JF, Massey JT (1981) Spatial trajectories Informed consent All subjects gave their written informed consent. and reaction times of aimed movements: effects of practice, uncer - tainty, and change in target location. J Neurophysiol 46:725–743 Conflict of interest The authors declare that they have no conflict of Gomi H (2008) Implicit online corrections of reaching movements. interest. Curr Opin Neurobiol 18:558–564. https ://doi.or g/10.1016/j. conb.2008.11.002 Open Access This article is distributed under the terms of the Crea- Gomi H, Abekawa N, Nishida S (2006) Spatiotemporal tuning of rapid tive Commons Attribution 4.0 International License (http://creat iveco interactions between visual-motion analysis and reaching move- mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- ment. J Neurosci 26:5301–5308. https ://doi.org/10.1523/JNEUR tion, and reproduction in any medium, provided you give appropriate OSCI.0340-06.2006 credit to the original author(s) and the source, provide a link to the Goodale MA, Pelisson D, Prablanc C (1986) Large adjustments in Creative Commons license, and indicate if changes were made. visually guided reaching do not depend on vision of the hand or perception of target displacement. Nature 320:748–750. https :// doi.org/10.1038/32074 8a0 Gritsenko V, Yakovenko S, Kalaska JF (2009) Integration of predictive feedforward and sensory feedback signals for online control of visually guided movement. J Neurophysiol 102:914–930. https :// doi.org/10.1152/jn.91324 .2008 1 3 Experimental Brain Research (2018) 236:1573–1581 1581 Kadota K, Gomi H (2010) Implicit visuomotor processing for quick Pelisson D, Prablanc C, Goodale MA, Jeannerod M (1986) Visual online reactions is robust against aging. J Neurosci 30:205–209. control of reaching movements without vision of the limb. II. https ://doi.org/10.1523/JNEUR OSCI.2599-09.2010 Evidence of fast unconscious processes correcting the trajectory Leonard JA, Gritsenko V, Ouckama R, Stapley PJ (2011) Postural of the hand to the final position of a double-step stimulus. Exp adjustments for online corrections of arm movements in standing Brain Res 62:303–311 humans. J Neurophysiol 105:2375–2388. https: //doi.org/10.1152/ Pisella L, Gréa H, Tilikete C, Vighetto A, Desmurget M, Rode G, jn.00944 .2010 Boisson D, Rossetti Y (2000) An ‘automatic pilot’ for the hand Lowrey CR, Nashed JY, Scott SH (2017) Rapid and flexible whole in human posterior parietal cortex: toward reinterpreting optic body postural responses are evoked from perturbations to the ataxia. Nat Neurosci 3:729–736. https ://doi.org/10.1038/76694 upper limb during goal-directed reaching. J Neurophysiol Saijo N, Murakami I, Nishida S, Gomi H (2005) Large-field visual 117:1070–1083. https ://doi.org/10.1152/jn.01004 .2015 motion directly induces an involuntary rapid manual following Martin O, Teasdale N, Simoneau M, Corbeil P, Bourdin C (2000) response. J Neurosci 25:4941–4951. https ://doi.or g/10.1523/ Pointing to a target from an upright position in human: tuning JNEUR OSCI.4143-04.2005 of postural responses when there is target uncertainty. Neurosci Schaafsma SJ, Duysens J (1996) Neurons in the ventral intraparietal Lett 281:53–56. https ://doi.org/10.1016/s0304 -3940(00)00801 -6 area of awake macaque monkey closely resemble neurons in the Mergner T, Schweigart G, Maurer C, Blumle A (2005) Human postural dorsal part of the medial superior temporal area in their responses responses to motion of real and virtual visual environments under to optic flow patterns. J Neurophysiol 76:4056–4068 different support base conditions. Exp Brain Res 167:535–556. Schreven S, Beek PJ, Smeets JBJ (2015) Optimising filtering param- https ://doi.org/10.1007/s0022 1-005-0065-3 eters for a 3D motion analysis system. J Electromyogr Kinesiol Nashner L, Berthoz A (1978) Visual contribution to rapid motor 25:808–814. https ://doi.org/10.1016/j.jelek in.2015.06.004 responses during postural control. Brain Res 150:403–407. https Slijper H, Latash ML, Mordkoff JT (2002) Anticipatory postural adjust- ://doi.org/10.1016/0006-8993(78)90291 -3 ments under simple and choice reaction time conditions. Brain Res Oostwoud Wijdenes L, Brenner E, Smeets JBJ (2011) Fast and fine- 924(2):184–197. https://doi.or g/10.1016/S0006-8993(01)03233 -4 tuned corrections when the target of a hand movement is dis- Soechting JF, Lacquaniti F (1983) Modification of trajectory of a point- placed. Exp Brain Res 214:453–462. https ://doi.or g/10.1007/ ing movement in response to a change in target location. J Neu- s0022 1-011-2843-4 rophysiol 49:548–564 Oostwoud Wijdenes L, Brenner E, Smeets JBJ (2013) Comparing Veerman MM, Brenner E, Smeets JBJ (2008) The latency for cor- online adjustments to distance and direction in fast pointing move- recting a movement depends on the visual attribute that defines ments. J Mot Behav 45:395–404. https ://doi.org/10.1080/00222 the target. Exp Brain Res 187:219–228. https ://doi.org/10.1007/ 895.2013.81515 0s0022 1-008-1296-x Oostwoud Wijdenes L, Brenner E, Smeets JBJ (2014) Analysis of Veyrat-Masson M, Briere J, Proteau L (2010) Automaticity of online methods to determine the latency of online movement adjust- control processes in manual aiming. J Vis 10(14):27: 1–14. https ments. Behav Res Methods 46:131–139. https ://doi.org/10.3758/ ://doi.org/10.1167/10.14.27 s1342 8-013-0349-7 Whitney D, Westwood DA, Goodale MA (2003) The influence of Palmisano S, Allison RS, Schira MM, Barry RJ (2015) Future chal- visual motion on fast reaching movements to a stationary object. lenges for vection research: definitions, functional significance, Nature 423:869–873 measures, and neural bases. Frontiers in psychology 6:193. https ://doi.org/10.3389/fpsyg .2015.00193 1 3
Journal
Experimental Brain Research – Springer Journals
Published: Mar 23, 2018