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1Department of Biobehavioral Sciences, Teachers College and 4Department of Rehabilitation Medicine, College of Physicians and Surgeons, Columbia University, New York City, New York; 2Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, Florida; and 3Institute of Human Movement Sciences and Sport, ETH Zurich, Switzerland
Submitted 15 May 2008; accepted in final form 21 August 2008
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ABSTRACT |
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INTRODUCTION |
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; Flanagan and Tresilian 1994; Flanagan and Wing 1995; Flanagan et al. 1993; Kinoshita et al. 1996; Serrien and Wiesendanger 2001; Zatsiorsky et al. 2005). We have shown that grip force is also timed and scaled to the sinusoidal inertial force that is generated as a consequence of normal locomotion (Diermayr et al. 2008; Gysin et al. 2003). Grip force was modulated concurrently with the gait cycle with the highest grip force at the instances of maximum inertial force occurring when the object was at its lowest vertical position shortly after heel contact. We suggested that the CNS uses an internal representation of the task demands that predicts the moment-to-moment inertial force acting on the hand-held object then times and scales grip force accordingly. An alternative to this moment-to-moment prediction of inertial changes is that subjects may generate grip forces based on the overall regularity of the inertial forces produced during the gait cycle. This alternative hypothesis is supported by studies showing subjects are remarkably adept at predicting the overall timing of locomotion associated with regularly paced steps using motor imagery (Bakker et al. 2007; Decety et al. 1989; Papaxanthis et al. 2002a). Thus the strength of the grip-inertial force coupling may be determined by the regularity of the walking cycle in a manner similar to the coordination of breathing with walking, running, or other cyclical limb movements (i.e., via entrainment) (Bernasconi et al. 1995; Ebert et al. 2000; Kohl et al. 1981; Rassler and Kohl 2000; Seebauer et al. 2003), and a shift from a regular pattern to an irregular one could disrupt this relationship (e.g., Nishino and Hiraga 1991; Prokop et al. 1995; Reisman et al. 2005). The purpose of the present investigation was to test between moment-to-moment predictability versus longer interval predictability by investigating whether the grip-inertial force coupling in normal gait is preserved when the gait cycle is varied. To this end, the locomotor pattern was altered to produce variations in the inertial forces acting on a transported object. Specifically we asked subjects to alter their gait pattern by either changing their step length or by stepping on and over an obstacle (uneven terrain). We hypothesized that if the timing and magnitude of grip force was primarily based on inertial force estimates arising from regularly paced locomotion, then disturbing the gait cycle would lead to transient deteriorations in the coordination of grip relative to inertial force during the step variations. Specifically we would expect early or delayed grip force peaks when the step frequency decreases or increases, respectively. In contrast, if grasping was based on a moment-to-moment prediction of the object's inertia, then predictable gait variations would be compensated for in a feed-forward manner, thereby preserving a similar grip-load force relationship as observed during regularly paced steps.
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METHODS |
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Eight right-handed subjects (4 females, 4 males; age: 24–38 yr, mean: 29 yr) without evidence of neurological or orthopedic dysfunction participated in the study after giving their informed consent according to the Declaration of Helsinki. To minimize natural variations in step length and width, subjects recruited were of similar size (155–169 cm, mean: 164 cm) and had normal body mass indexes (National Institutes of Health Publication 98-4083, 1998>) (19.32–24.62, mean: 22.22). The experimental procedures were approved by the Teachers College, Columbia University Institutional Review Board.
Experimental setup
The grip instrument (Fig. 1 A; 320 g) consisted of two parallel triaxial force transducers (Nano F/T transducer, ATI Industrial Automation, Apex, NC) covered with two plastic grip surfaces (diameter: 1.9 cm, 4.5 cm apart). The transducers (0.05 N resolution), attached 3 cm above the upper surface of a rectangular box (7.8 x 4.3 x 4.7 cm), measured grip forces normal to the planes of the grip surfaces, and vertical and horizontal forces tangential to the grip surfaces.
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Procedures
All subjects washed their hands prior to data collection. During the experiment, subjects held the grip instrument in their right hand using a two-digit (thumb opposing index finger) precision grip. Static grip force was measured while standing during four 5-s trials. Subjects were then instructed to maintain the instrument in an upright and forward-oriented position with the grip surfaces parallel to the plane of motion during the walking trials. Subjects initiated gait with their left leg and transported the grip instrument while walking under five self-paced conditions: a baseline walking condition and four altered (3 predictable and 1 with an unpredictable support surface) walking conditions (Fig. 1B). During the trials with gait alterations, the modified step was the fifth step from the start (i.e., the 3rd of the analyzed steps) and taken with the left leg. The tapelines were used as visual cues for foot placement on every step in all conditions. Subjects were instructed to contact the lines approximately with the middle of their foot (i.e., accuracy was not emphasized). The five conditions were as follows.
BASELINE WALK CONDITION.
Subjects walked across the walkway and stepped on tapelines spaced uniformly 60 cm apart. This spacing was based on the mean step length observed in a previous study (Gysin et al. 2003). Of note, we purposely selected subjects similar in height to those used in the previous study so that the distances between tape lines during the baseline condition would be similar to their normal step lengths, which are influenced by body height. Because gait velocity and step frequency during the baseline condition in this experiment were comparable to our previous study, we concluded that attention directed at the taped lines did not affect subjects' natural walking pattern.
SHORT STEP CONDITION (PREDICTABLE). Subjects were required to shorten their step length from 60 to 20 cm (33% of the baseline length) at the altered step. During this step, it was expected that subjects would decrease their walking speed and increase their step frequency. The condition served to investigate how a sudden decrease in gait velocity and increase in the frequency of the locomotor rhythm along with an expected decrease of the inertial force would affect the coordination of grip and inertial forces.
LONG STEP CONDITION (PREDICTABLE). Subjects were required to increase their step length from 60 to 104 cm (173% of the baseline length) at the altered step. This condition served to investigate how a sudden increase in gait velocity and decrease in step frequency along with an expected increase of the inertial force would affect the coordination of grip and inertial forces.
STABLE OBSTACLE CONDITION (PREDICTABLE). For the altered step, subjects were required to place their left foot on the middle (marked with a tapeline) of a raised, solid support surface. The right foot had to step over the raised support and land on the successive line, then resume baseline steps. The spacing between the steps remained 60 cm. This condition assessed whether a sudden change in the locomotor pattern through changes in step height rather than step length would affect the coordination of grip and inertial forces. Adjustments of the gait pattern would be needed, first to step on, then over the obstacle. Furthermore, a decrease in step frequency and increase of the inertial force when moving the swing leg over the obstacle back down to the level walkway was expected.
UNSTABLE OBSTACLE CONDITION (UNPREDICTABLE SUPPORT SURFACE). This condition was similar to the stable obstacle condition except that subjects were required to step on and then over a raised, pliant support surface, resulting in unpredictable changes in ground reaction and inertial forces acting on the transported object. This condition served as a way to differentiate between feedback and -forward control of grip force, since subjects would have difficulty anticipating the resulting inertial force when stepping on an unpredictable support surface. After one or two practice trials, four trials were performed under each condition and were subsequently analyzed. Subjects always started with the baseline walk condition followed by the four variable gait conditions (order counterbalanced across subjects). To avoid fatigue, rest periods were provided between conditions.
Data analysis
The force-transducer and heel contact signals were sampled at 400 Hz, digitized with a 12-bit resolution, and stored using SC/ZOOM software (Department of Physiology, Umeå University, Sweden). The force transducer signals were processed through a second-order dual-pass Butterworth digital low-pass filter with a cutoff frequency of 6 Hz. A step was defined as the event from heel contact of one foot to heel contact of the contralateral foot. Four steps were analyzed from each trial of the five walking conditions (see Fig. 1B), starting with the third step, after steady-state gait had been achieved (Jian et al. 1993) and ending one or two steps prior to gait termination. In the four variable gait conditions, the analyzed data consisted of two baseline steps prior to the altered step (subsequently referred to as steps –2 and –1), the altered step, and the first step following the altered step (referred to as step +1). The same nomenclature was used for the corresponding five heel contacts. Average gait velocities (m/s) defined by distance/time and step frequencies (step/s) were calculated during each of the four analyzed steps.
The tangential forces acting on the object were inertial and gravitational in the vertical direction and inertial in the horizontal direction. The net resultant of these forces [vector size of the vertical load forces (LF) and horizontal load forces (HF)] was calculated from the two force transducers [SQRT (LF12 + HF12) + SQRT (LF22 + HF22)] at each sampled point, and were referred to simply as the "inertial force" (IF) (Gysin et al. 2003). Grip force (GF) was calculated by averaging the forces applied through the force transducers on each side of the grip device [(GF1 + GF2)/2]. To determine whether any tertiary forces generated through out-of-plane object motions would influence the grip force measures, an adjusted grip force was calculated {[(GF1 + GF2) –abs(GF1 –GF2)]/2} (Gysin et al. 2008) and compared with the raw data. This comparison indicated that the magnitude of the differences was consistently <3% of their maxima and that these differences were similar to those observed during stance. Due to these findings and the observation that the relative differences between steps and conditions did not change statistically, we suggest that the tertiary forces were of negligible influence on grip force oscillations. Thus we report only the results of the raw grip force.
To quantify the grip-inertial force relationship with respect to step adjustments, i.e., at the instances where changes in the object's maximum inertial force (shortly after each heel contact) and minimum inertial force (
mid-stance) occur, the following measures were taken from each of the four steps within a trial: peak-to-peak time lag (ms), defined as the time of the maximum/minimum grip force relative to the maximum/minimum inertial force, and grip and inertial forces (N) at the time of maximum inertial force. To determine the extent of modulation of the grip force relative to the inertial force, the GF/IF ratio was calculated from the measurements of the two forces at the time of maximum inertial force during each step of the gait cycle. A static force ratio (GF/LF ratio) was also obtained by calculating average grip force 1 s in the middle of the hold period of the stance trials and dividing it by the load of the object. To assess whether the relationship of grip force to load force changed between static and dynamic conditions, the GF/LF ratio during stance and the GF/IF ratios during the baseline walk condition were compared.
Statistical comparisons between conditions were made using a two-way (5 conditions x 4 steps and 5 conditions x 5 heel contacts) repeated-measures ANOVA, followed by Newman-Keuls post hoc comparisons where appropriate. Static GF/LF ratios and GF/IF ratios (average across the measured instances) of the baseline walk condition were compared with a paired-samples t-test. Differences were considered statistically significant at the P < 0.05 level.
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RESULTS |
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Gait velocities [1.04 ± 0.02 (SE) m/s], step frequencies (1.74 ± 0.03 step/s), inertial force frequencies (1.73 ± 0.03 peak/s), grip force frequencies (1.75 ± 0.02 peak/s), and maximum inertial forces (3.47 ± 0.06 N) were similar across all four steps (P > 0.05), indicating that subjects had reached and maintained steady-state gait during the data analysis phase of the trials. Maximum grip force (4% missing values due to indistinct peaks) occurred after heel contact and was concurrent with maximum inertial force (grip force maxima lagged inertial force maxima on average 3 ± 8 ms). At the time of maximum inertial force, average grip force was 8.21 ± 0.62 N. This resulted in a GF/IF ratio (2.38 ± 0.19), similar to the GF/LF ratio (2.11 ± 0.18) observed during static stance (P > 0.05). The value of all measured variables for the two unaltered steps of the four altered gait conditions (heel contacts –3 and –2) were similar to the measures obtained during the baseline walk condition (P > 0.05).
Changes in gait mechanics and inertial force magnitudes
As expected, decreasing step length led to decreased gait velocity and increased step and inertial force frequencies, whereas increasing step length led to the opposite pattern (Fig. 2A) [condition x step interaction F(12,84) = 190.513, P < 0.001]. Furthermore, maximum inertial force decreased for the short step and increased for the long step relative to the forces during the preceding steps [condition x heel contact interaction F(16,112) = 14.888, P < 0.001; Fig. 2A, bottom]. When stepping on the stable and unstable obstacles, gait velocity and step and inertial force frequencies did not change. However, these variables decreased when the swing leg subsequently moved past the raised support surface and back to the ground [Fig. 2B; condition x step interaction F(12,84) = 190.513, P < 0.001, and F(12,84) = 38.647, P < 0.001]. Furthermore, in both obstacle conditions, higher inertial forces occurred on the subsequent step (heel contact +1) compared with the steps prior to obstacle contact [condition x heel contact interaction F(16,112) = 14.888, P < 0.001; Fig. 2B, bottom].
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Compared with the preceding steps, subjects increased their grip force by 36% when taking the long step and by 35 and 33% when stepping on (altered heel contact) and over (heel contact +1) the unstable obstacle, respectively [condition x heel contact interaction F(16,112) = 9.553, P < 0.001]. These grip force increases also resulted in higher GF/IF ratios (Fig. 3) compared with the steps prior to the altered ones [F(16,112) = 5.948, P < 0.001]. The GF/IF ratio increased by 19% for the long step and by 26% and 19% when stepping on and over the unstable obstacle, respectively. When taking a short step and when stepping on and over the stable obstacle, no significant differences were observed in the GF/IF ratios compared with prior steps.
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Figure 4 shows the forces of a representative subject and illustrates the cyclic relationship between the grip and inertial forces throughout the variable gait conditions. Across gait variations, the grip and inertial forces fluctuated in a cyclical manner with maxima occurring at the object's lowest point shortly after each heel contact and minima occurring at the object's highest point during mid-stance. During the obstacle conditions, maximum inertial and grip forces of the altered step occurred after the swing foot contacted the obstacle and as the body started to rise off the walkway to the higher surface. The minimum inertial and grip forces occurred as the swing leg passed the stance leg while crossing the raised support surface, followed by another maxima shortly after landing back on the level walkway (heel contact +1). The two forces fluctuated together, with the pattern of grip force largely mimicking the large changes (but ignoring small changes) in inertial force as previously reported (Diermayr et al. 2008). As seen in Fig. 4D, when stepping on the unpredictable support surface, the peak grip force occurred after (the altered) heel contact and was later than in the other conditions (153 ms after the peak inertial force in this trial).
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On average, maximum grip force lagged the maximum inertial force associated with each heel contact by a greater time for the altered step compared with previous (heel contacts –3 and –2) and following (heel contact +1) ones in the long step and both obstacle conditions [condition x heel contact interaction F(12,84) = 4.844, P < 0.001); (Fig. 5]. These increases in peak-to-peak time remained below the minimum time of 60 ms necessary for a somatosensory feedback response except in the unstable obstacle condition. The timing of the peak-to-peak minima in inertial and grip force (associated with mid-stance) was not affected by the altered step (35 ± 12 ms) compared with the preceding and following steps (33 ± 8 ms across steps) in any condition (P > 0.05 in all cases). Interestingly, the mean peak-to-peak time lag of the maxima inertial and grip force for the step prior to obstacle contact (heel contact –1) was also longer (but within 60 ms) than previous (heel contacts –3 and –2) or following (heel contact +1) ones in both obstacle conditions [condition x heel contact interaction F(12,84) = 4.844, P < 0.001; Fig. 5B]. The short step condition was the only condition, where peak-to-peak timing was similar across all steps (P > 0.05; Fig. 5A).
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DISCUSSION |
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Grip and inertial forces remain synchronized during predictable gait variations
When walking with an object in a predictable environment, subjects could specify grip force based on moment-to-moment predictions or inertial force estimates arising from regularly paced locomotion over a longer interval. We investigated the possibility that if the gait cycles became irregular, longer interval predictions would lead to transient deteriorations in the grip-inertial force coordination. Previous research showed that lower extremity kinematics and kinetics were altered by stepping on and over obstacles, compared with level-ground locomotion (Ivanenko et al. 2005; McFadyen and Carnahan 1997). Comparable changes were observed in the present study when subjects crossed the stable obstacle, resulting in an increase in magnitude and latency of the peak inertial force as they moved their swing leg past the raised support surface back down to the level walkway. Given the temporal deviation from the baseline walking condition, this step could result in an early grip force peak if the grip-inertial force coupling was based on longer interval predictions of inertial forces (i.e., its overall timing). Similarly, early or delayed grip force peaks could occur when there are increases (long step) or decreases (short step) in step durations, respectively. Despite variations in the timing and magnitude of inertial force, grip force remained tightly linked to inertial force across predictable step alterations with time lags below the minimum needed for a feedback response. The observed time lags were similar to those observed during normal locomotion (Gysin et al. 2003). Although longer interval timing predictions may be used during regular cyclical stepping, moment-to-moment predictions of the locomotor-induced inertial force appear to be utilized when gait variations occur in a predictable fashion. These predictions include variations in inertial force magnitude as evidenced by increases or decreases in grip force, relative to the level of the inertial force peaks.
Typically, when unpredictable loads are applied to a hand-held object, feedback is used to track inertial changes and make appropriate grip force adjustments (e.g., Cole and Abbs 1988; Delevoye-Turell et al. 2003; Johansson and Westling 1988; Johansson et al. 1992a,b; Macefield and Johansson 1996; Nowak 2004; Serrien et al. 1999; Turrell et al. 1999). Consistent with this finding, we observed that when stepping on an unpredictable, pliant obstacle, peak grip force lagged peak inertial force by 95 ms, indicating that feedback may be used to generate an appropriate response (Cole and Abbs 1988; Johansson and Westling 1984, 1987). This feedback-based control was specific to the walking condition where changes in ground reaction and inertial forces could not be predicted accurately. The temporal delay in achieving peak grip force relative to peak inertial force when stepping on the unstable surface likely indicates a feedback-based response to terminate the increasing grip force (Gordon et al. 1991; Johansson and Westling 1988). Interestingly, peak grip force delays occurred even though the step onto the raised support surface did not vary in length and frequency from previous steps. Thus predictability of the walking environment, rather than regularity of the locomotor cycles, appears to be the primary factor in determining the grip-inertial force temporal coupling.
The grip force adjustments that occurred when stepping on the unstable obstacle and landing back on the level walkway resulted in higher force ratios at the moment of maximum inertial force. Thus during this step subjects appeared to increase their grasping force in approximation of the upcoming inertial force maxima. This response was similar to preparatory grip force increases seen when pulling a drawer to its mechanical stop (Serrien et al. 1999). The higher force ratios (implying higher grip force safety margins) observed in the long step and steps on and over the unstable obstacle might have been chosen as a strategy to reduce the likelihood of dropping the object when there is an increased risk of losing balance. A similar increase in grip force safety margin was previously observed in unfamiliar physical environments (Nowak et al. 2001) and during bimanual anti-phase object manipulations (Serrien and Wiesendanger 2001).
Temporal precision of anticipatory grip force varies depending on task demands
Although the timing of grip relative to the inertial force remained within the anticipatory window for all predictable step variations, there was a slightly longer lag for the long step and for the steps prior to and onto the stable obstacle. Allocation of attentional resources to a secondary task (transporting the object) may have been reduced during altered gait, and as a consequence this may have affected grip-inertial force precision, similar to performance decrements shown in other dual-task performances (e.g., Chen et al. 1996; Müller et al. 2004; Siu et al. 2008; Sternad et al. 2007; Weerdesteyn et al. 2003). Even though grip force oscillation are usually not consciously perceived (Flanagan et al. 1993), subjects may still be susceptible to temporal decrements related to the overall attention demands of a task.
During obstacle crossing paradigms, subjects transfer their gaze to the target prior to lifting the foot onto or over an obstacle (Di Fabio et al. 2003a,b; Patla and Vickers 1997), suggesting that subjects use visual information to plan for the upcoming movements. The posterior parietal cortex could be ascribed a key role in this process, given its activity during tasks requiring higher-level somatosensory processes (for review, see Andersen and Buneo 2002), movement planning (e.g., Fernandez-Ruiz et al. 2007), and visually guided gait modifications (Lajoie and Drew 2007). Posterior parietal regions also demonstrated importance in varying limb postures (Pellijeff et al. 2006), dual-task performance (Mochizuki et al. 2007), and single isolated actions versus repetitive automated ones (Schaal et al. 2004). Thus additional visuo-motor planning involved in the context of gait variations may have interfered with the planning processes for grip-inertial force coupling and explain the observed variations in temporal precision of anticipatory grip force control.
It remains unclear why the temporal precision of grip force differed between the short and long step given that both tasks involved visuo-motor processes to place the foot on the new target distance. There are two potential reasons for this finding. First, the long step produced a significant increase in the time spent in single limb support and thus may have required greater attentional demands to ensure stability than the short step. Dynamic stability during gait is greatest during the double support phase as the body's center of mass is constrained within a large base of support. Conversely, greater active postural control is needed to maintain stability during the single support phase as the center of mass pivots over the stance foot. Second, the considerably longer distance to the target for the long step may have imposed relatively higher accuracy demands on determining the motor commands for accurate foot placement. In particular, visual control and real-time trajectory modifications based on comparison of the foot and target position (similar to reaching movements of the arm) (e.g., Desmurget et al. 1999; Pisella et al. 2000) may have been more demanding during the long than during the short step.
Mechanisms underlying anticipatory grip force control during predictable gait variations
Motor imagery that estimates the duration of discrete arm motions performed under variable dynamic conditions have been shown to match the actual duration of the movement (Gentili et al. 2004; Papaxanthis et al. 2002b). Similarly, internal representations of the relevant sensorimotor features of the upcoming action may underlie the anticipatory grip-load force coupling (Blakemore et al. 1998; Flanagan and Lolley 2001; Flanagan and Wing 1997; Flanagan et al. 2001, 2003; Salimi et al. 2000; Wing and Lederman 1998; White et al. 2005) and explain grip force accuracy observed throughout the predictable gait variations. Presumably, this representation takes into account interactions between body segments during locomotion through which inertia is transferred to the object-digit interface on a step-to-step basis.
The cerebellum is the principle structure involved in temporal force coupling during cyclical object manipulations (Boecker et al. 2005; Kawato et al. 2003). Given the cerebellar role in feedforward control of reaching movements under altered dynamics (Smith and Shadmehr 2005) and in predictive locomotor adaptations (Morton and Bastian 2006), it may also play a fundamental role in predicting inertial force changes elicited by predictable gait variations. Locomotor neural networks that vary depending on the walking rhythms and patterns (Choi and Bastian 2007) may be involved in these predictive control processes. Furthermore, propriospinal connections that link movements of the arms to the legs (Dietz et al. 2001) may assist in the coordination between grip and inertial forces while transporting an object during locomotion.
There are two ways that grip force may have been specified when the gait pattern was modified. First, subjects could have predicted the change in the object's inertial forces from memory representations acquired during previous experience. This information may have been retrieved when visually identifying task parameters (location of the stepping cues and location/dimensions of the obstacle) that affect the grasping demands (Gordon et al. 1993). Alternatively, prediction may have involved generalizable rules related to the timing and magnitude of forces associated with step variations. The use of general rules that allow interpolation of appropriate levels of grip force, without practicing every task variation, has been suggested in the context of adjusting grip force to novel load torques (Wing and Lederman 1998). Furthermore, during locomotion, proprioceptive inputs provide cues about the mechanical state of the musculoskeletal apparatus (Lam and Pearson 2002), and this information may have been used to predict subsequent motor activity. Specifically, kinesthetic sensory information about the height of the obstacles after the foot was placed on them or position of the legs during the shortened and lengthened step may have contributed to the accuracy of estimating the inertial force associated with the succeeding step.
Conclusion
Similar degrees of coupling between grip and inertial forces during regular gait and predictable gait variations suggests that the CNS used ongoing estimates of the inertial forces acting on the object and adjusted the grasping forces continuously. These findings support the hypothesis that grip force is based on moment-to-moment predictions of the varying rhythms and impact magnitudes of the inertial force generated during the gait cycle.
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GRANTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: A. M. Gordon, Dept of Biobehavioral Sciences, Teachers College, Columbia University, 525 W. 120th St., Box 199, New York, NY 10027 (E-mail: ag275{at}columbia.edu)
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REFERENCES |
|---|
|
Bakker M, de Lange FP, Stevens JA, Toni I, Bloem BR. Motor imagery of gait: a quantitative approach. Exp Brain Res 179: 497–504, 2007.[CrossRef][Web of Science][Medline]
Bernasconi P, Bürki P, Bührer A, Koller EA, Kohl J. Running training and co-ordination between breathing and running rhythms during aerobic and anaerobic conditions in humans. Eur J Appl Physiol Occup Physiol 70: 387–393, 1995.[CrossRef][Web of Science][Medline]
Blakemore SJ, Goodbody SJ, Wolpert DM. Predicting the consequences of our own actions: the role of sensorimotor context estimation. J Neurosci 18: 7511–7518, 1998.
Boecker H, Lee A, Mühlau M, Ceballos-Baumann A, Ritzl A, Spilker ME, Marquart C, Hermsdörfer J. Force level independent representations of predictive grip force-load force coupling: a PET activation study. Neuroimage 25: 243–252, 2005.[CrossRef][Medline]
Chen HC, Schultz AB, Ashton-Miller JA, Giordani B, Alexander NB, Guire KE. Stepping over obstacles: dividing attention impairs performance of old more than young adults. J Gerontol A Biol Sci Med Sci 51: M116–M122, 1996.[Abstract]
Choi JT, Bastian AJ. Adaptation reveals independent control networks for human walking. Nat Neurosci 10: 1055–1062, 2007.[CrossRef][Web of Science][Medline]
Cole KJ, Abbs JH. Grip force adjustments evoked by load force perturbations of a grasped object. J Neurophysiol 60: 1513–1522, 1988.
Decety J, Jeannerod M, Prablanc C. The timing of mentally represented actions. Behav Brain Res 34: 35–42, 1989.[Web of Science][Medline]
Delevoye-Turrell YN, Li FX, Wing AM. Efficiency of grip force adjustments for impulsive loading during imposed and actively produced collisions. Q J Exp Psychol A 56: 1113–1128, 2003.[Web of Science][Medline]
Descoins M, Danion F, Bootsma RJ. Predictive control of grip force when moving object with an elastic load applied on the arm. Exp Brain Res 172: 331–342, 2006.[CrossRef][Web of Science][Medline]
Desmurget M, Epstein CM, Turner RS, Prablanc C, Alexander GE, Grafton ST. Role of the posterior parietal cortex in updating reaching movements to a visual target. Nat Neurosci 2: 563–567, 1999.[CrossRef][Web of Science][Medline]
Diermayr G, Gysin P, Hass CJ, Gordon AM. Grip force control during gait initiation with a hand-held object. Exp Brain Res 190: 337–345, 2008.[CrossRef][Web of Science][Medline]
Di Fabio RP, Greany JF, Zampieri C. Saccade-stepping interactions revise the motor plan for obstacle avoidance. J Mot Behav 35: 383–397, 2003a.[Web of Science][Medline]
Di Fabio RP, Zampieri C, Greany JF. Aging and saccade-stepping interactions in humans. Neurosci Lett 339: 179–182, 2003b.[CrossRef][Web of Science][Medline]
Dietz V, Fouad K, Bastiaanse CM. Neuronal coordination of arm and leg movements during human locomotion. Eur J Neurosci 14: 1906–1914, 2001.[CrossRef][Web of Science][Medline]
Ebert D, Rassler B, Hefter H. Coordination between breathing and forearm movements during sinusoidal tracking. Eur J Appl Physiol 81: 288–296, 2000.[CrossRef][Web of Science][Medline]
Fernandez-Ruiz J, Goltz HC, Desouza JF, Vilis T, Crawford JD. Human parietal "reach region" primarily encodes intrinsic visual direction, not extrinsic movement direction, in a visual motor dissociation task. Cereb Cortex 17: 2283–2292, 2007.
Flanagan JR, King S, Wolpert DM, Johansson RS. Sensorimotor prediction and memory in object manipulation. Can J Exp Psychol 55: 87–95, 2001.[Web of Science][Medline]
Flanagan JR, Lolley S. The inertial anisotropy of the arm is accurately predicted during movement planning. J Neurosci 21: 1361–1369, 2001.
Flanagan JR, Tresilian JR. Grip-load force coupling: a general control strategy for transporting objects. J Exp Psychol Hum Percept Perform 20: 944–957, 1994.[CrossRef][Web of Science][Medline]
Flanagan JR, Tresilian JR, Wing AM. Coupling of grip force and load force during arm movements with grasped objects. Neurosci Lett 152: 53–56, 1993.[CrossRef][Web of Science][Medline]
Flanagan JR, Vetter P, Johansson RS, Wolpert DM. Prediction precedes control in motor learning. Curr Biol 13: 146–150, 2003.[CrossRef][Web of Science][Medline]
Flanagan JR, Wing AM. The stability of precision grip forces during cyclic arm movements with a hand-held load. Exp Brain Res 105: 455–464, 1995.[Web of Science][Medline]
Flanagan JR, Wing AM. The role of internal models in motion planning and control: evidence from grip force adjustments during movements of hand-held loads. J Neurosci 17: 1519–1528, 1997.
Gentili R, Cahouet V, Ballay Y, Papaxanthis C. Inertial properties of the arm are accurately predicted during motor imagery. Behav Brain Res 155: 231–239, 2004.[CrossRef][Web of Science][Medline]
Gordon AM, Forssberg H, Johansson RS, Westling G. Visual size cues in the programming of manipulative forces during precision grip. Exp Brain Res 83: 477–482, 1991.[Web of Science][Medline]
Gordon AM, Westling G, Cole KJ, Johansson RS. Memory representations underlying motor commands used during manipulation of common and novel objects. J Neurophysiol 69: 1789–1796, 1993.
Gysin P, Kaminski TR, Gordon AM. Coordination of fingertip forces in object transport during locomotion. Exp Brain Res 149: 371–379, 2003.[Web of Science][Medline]
Gysin P, Kaminski TR, Gordon AM. Dynamic grasp control during gait. In: Sensorimotor Control of Grasping: Physiology and Pathophysiology, edited by Nowak DA, Hermsdörfer J. Cambridge, UK: Cambridge. In press.
Ivanenko YP, Cappellini G, Dominici N, Poppele RE, Lacquaniti F. Coordination of locomotion with voluntary movements in humans. J Neurosci 25: 7238–7253, 2005.
Jian Y, Winter DA, Ishac MG, Gilchrist L. Trajectory of the body COG and COP during initiation and termination of gait. Gait Posture 1: 9–22, 1993.[CrossRef]
Johansson RS, Häger C, Riso R. Somatosensory control of precision grip during unpredictable pulling loads. II. Changes in load force rate. Exp Brain Res 89: 192–203, 1992a.[Web of Science][Medline]
Johansson RS, Riso R, Häger C, Bäckström L. Somatosensory control of precision grip during unpredictable pulling loads. I. Changes in load force amplitude. Exp Brain Res 89: 181–191, 1992b.[CrossRef][Web of Science][Medline]
Johansson RS, Westling G. Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Exp Brain Res 56: 550–564, 1984.[Web of Science][Medline]
Johansson RS, Westling G. Signals in tactile afferents from the fingers eliciting adaptive motor responses during precision grip. Exp Brain Res 66: 141–154, 1987.[Web of Science][Medline]
Johansson RS, Westling G. Programmed and triggered actions to rapid load changes during precision grip. Exp Brain Res 71: 72–86, 1988.[Web of Science][Medline]
Kawato M, Kuroda T, Imamizu H, Nakano E, Miyauchi S, Yoshioka T. Internal forward models in the cerebellum: fMRI study on grip force and load force coupling. Prog Brain Res 142: 171–188, 2003.[Web of Science][Medline]
Kinoshita H, Kawai S, Ikuta K, Teraoka T. Individual finger forces acting on a grasped object during shaking actions. Ergonomics 39: 243–256, 1996.[Medline]
Kohl J, Koller EA, Jäger M. Relation between pedalling- and breathing rhythm. Eur J Appl Physiol Occup Physiol 47: 223–237, 1981.[CrossRef][Web of Science][Medline]
Lajoie K, Drew T. Lesions of area 5 of the posterior parietal cortex in the cat produce errors in the accuracy of paw placement during visually guided locomotion. J Neurophysiol 97: 2339–2354, 2007.
Lam T, Pearson KG. The role of proprioceptive feedback in the regulation and adaptation of locomotor activity. Adv Exp Med Biol 508: 343–355, 2002.[Web of Science][Medline]
Macefield VG, Johansson RS. Control of grip force during restraint of an object held between finger and thumb: responses of muscle and joint afferents from the digits. Exp Brain Res 108: 172–184, 1996.[Web of Science][Medline]
McFadyen BJ, Carnahan H. Anticipatory locomotor adjustments for accommodating versus avoiding level changes in humans. Exp Brain Res 114: 500–506, 1997.[CrossRef][Web of Science][Medline]
Mochizuki H, Tashiro M, Gyoba J, Suzuki M, Okamura N, Itoh M, Yanai K. Brain activity associated with dual-task management differs depending on the combinations of response modalities. Brain Res 1172: 82–92, 2007.[CrossRef][Web of Science][Medline]
Morton SM, Bastian AJ. Cerebellar contributions to locomotor adaptations during splitbelt treadmill walking. J Neurosci 26: 9107–9116, 2006.
Müller ML, Jennings JR, Redfern MS, Furman JM. Effect of preparation on dual-task performance in postural control. J Mot Behav 36: 137–146, 2004.[CrossRef][Web of Science][Medline]
Nishino T, Hiraga K. Coordination of swallowing and respiration in unconscious subjects. J Appl Physiol 70: 988–993, 1991.
Nowak DA. Different modes of grip force control: voluntary and externally guided arm movements with a hand-held load. Clin Neurophysiol 115: 839–848, 2004.[CrossRef][Web of Science][Medline]
Nowak DA, Hermsdörfer J, Philipp J, Marquardt C, Glasauer S, Mai N. Effects of changing gravity on anticipatory grip force control during point-to-point movements of a hand-held object. Mot Control 5: 231–253, 2001.[Web of Science][Medline]
Papaxanthis C, Pozzo T, Skoura X, Schieppati M. Does order and timing in performance of imagined and actual movements affect the motor imagery process? The duration of walking and writing task. Behav Brain Res 134: 209–215, 2002a.[CrossRef][Web of Science][Medline]
Papaxanthis C, Schieppati M, Gentili R, Pozzo T. Imagined and actual arm movements have similar durations when performed under different conditions of direction and mass. Exp Brain Res 143: 447–452, 2002b.[CrossRef][Web of Science][Medline]
Patla AE, Vickers JN. Where and when do we look as we approach and step over an obstacle in the travel path? Neuroreport 8: 3661–3665, 1997.[Web of Science][Medline]
Pellijeff A, Bonilha L, Morgan PS, McKenzie K, Jackson SR. Parietal updating of limb posture: an event-related fMRI study. Neuropsychologia 44: 2685–2690, 2006.[CrossRef][Web of Science][Medline]
Pisella L, Grea H, Tilikete C, Vighetto A, Desmurget M, Rode G, Boisson D, Rossetti Y. An "automatic pilot" for the hand in human posterior parietal cortex: toward reinterpreting optic ataxia. Nat Neurosci 3: 729–736, 2000.[CrossRef][Web of Science][Medline]
Prokop T, Berger W, Zijlstra W, Dietz V. Adaptational and learning processes during human split-belt locomotion: interaction between central mechanisms and afferent input. Exp Brain Res 106: 449–456, 1995.[Web of Science][Medline]
Rassler B, Kohl J. Coordination-related changes in the rhythms of breathing and walking in humans. Eur J Appl Physiol 82: 280–288, 2000.[CrossRef][Web of Science][Medline]
Reisman DS, Block HJ, Bastian AJ. Interlimb coordination during locomotion: what can be adapted and stored? J Neurophysiol 94: 2403–2415, 2005.
Salimi I, Hollender I, Frazier W, Gordon AM. Specificity of internal representations underlying grasping. J Neurophysiol 84: 2390–2397, 2000.
Schaal S, Sternad D, Osu R, Kawato M. Rhythmic arm movement is not discrete. Nat Neurosci 7: 1136–1143, 2004.[CrossRef][Medline]
Seebauer M, Sidler MA, Kohl J. Gender differences in workload effect on coordination between breathing and cycling. Med Sci Sports Exerc 35: 495–499, 2003.[CrossRef][Web of Science][Medline]
Serrien DJ, Kaluzny P, Wicki U, Wiesendanger M. Grip force adjustments induced by predictable load perturbations during a manipulative task. Exp Brain Res 124: 100–106, 1999.[CrossRef][Web of Science][Medline]
Serrien DJ, Wiesendanger M. Regulation of grasping forces during bimanual in-phase and anti-phase coordination. Neuropsychologia 39: 1379–1384, 2001.[CrossRef][Web of Science][Medline]
Siu KC, Catena RD, Chou LS, van Donkelaar P, Woollacott MH. Effects of a secondary task on obstacle avoidance in healthy young adults. Exp Brain Res 184: 115–120, 2008.[CrossRef][Web of Science][Medline]
Smith MA, Shadmehr R. Intact ability to learn internal models of arm dynamics in Huntington's disease but not cerebellar degeneration. J Neurophysiol 93: 2809–2821, 2005.
Sternad D, Wei K, Diedrichsen J, Ivry RB. Intermanual interactions during initiation and production of rhythmic and discrete movements in individuals lacking a corpus callosum. Exp Brain Res 176: 559–574, 2007.[CrossRef][Web of Science][Medline]
Turrell YN, Li FX, Wing AM. Grip force dynamics in the approach to a collision. Exp Brain Res 128: 86–91, 1999.[CrossRef][Web of Science][Medline]
Weerdesteyn V, Schillings AM, van Galen GP, Duysens J. Distraction affects the performance of obstacle avoidance during walking. J Mot Behav 35: 53–63, 2003.[Web of Science][Medline]
White O, McIntyre J, Augurelle AS, Thonnard JL. Do novel gravitational environments alter the grip-force/load-force coupling at the fingertips? Exp Brain Res 163: 324–334, 2005.[CrossRef][Web of Science][Medline]
Wing AM, Lederman SJ. Anticipating load torques produced by voluntary movements. J Exp Psychol Hum Percept Perform 24: 1571–1581, 1998.[CrossRef][Web of Science][Medline]
Zatsiorsky VM, Gao F, Latash ML. Motor control goes beyond physics: differential effects of gravity and inertia on finger forces during manipulation of hand-held objects. Exp Brain Res 162: 300–308, 2005.[CrossRef][Web of Science][Medline]
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