- Email: [email protected]
Influence of visuoproprioceptive mismatch on postural adjustments
Influence mismatch
of visuoproprioceptive on postural adjustments
V Dietz, M Schubert,
Department Germany
M Discher, M Trippel
of Clinical Neurology
and Neurophysiology,
University
of Freiburg, Freiburg,
Summary The influence of visual input upon body stabilization was studied with subjects standing on a treadmill while a visual flow pattern was displayed. Both the treadmill and image were moved sinusoidally - backward/forward -at a frequency of 0.25 Hz. The effect of the presentation of the visual pattern was studied upon leg muscle electromyographic (EMG) activity and corresponding biomechanical signals for various phase shifts (45-360 degrees) between movements of the legs and the visual flow pattern. Around the posterior turning point of sinusoidal treadmill movement, i.e. at times when there is an anticipatory forward positioning of the body, a modulation of the tibialis anterior EMG was observed. The onset, duration, and amplitude of the latter were dependent upon the phase shift between the movements of the legs and the visual pattern. Maximum responses were recorded at phase shifts of 90/270 degrees and minimum responses at phase shifts of 180/360 degrees. Therefore a coincidence of fast velocities of the visual flow pattern with a phase of maximal body acceleration evoked the strongest tibialis anterior EMG responses. At times around the anterior turning point a modulation only of EMG amplitude occurred in the gastrocnemius muscle. This activity is believed to be linked to the preceding tibialis anterior EMG resulting in ‘resetting’ of the neutral body position. It is suggested that the tibialis anterior is more sensitive than the gastrocnemius muscle to a visual stimulus. The activity of the latter muscle with its antigravity function is more subject to proprioceptive input. Little adaptational changes in EMG pattern occurred between the second and fifth sway cycles after presentation of the optical flow pattern. It is assumed that task-specific factors act against early adaptation. Key
words: vision, muscle receptor, motor control, electromyogram
Gait & Posture, 1994,
Vol. 2, 147-l
55, September
Introduction Well-aimed experimental models are required to investigate the human motor system under physiological conditions such as stance and gait. With afferent inputs being necessary to appropriately modulate programmed patterns involved in the regulation of stance and gait, the relative contributions of known receptor systems are still a matter of controversy. These systems include the visual system’-‘, the vestibular system4J, and muscle proprioceptive system9. Previous studies have shown that horizontal displace-
Received: I8 October 1993 Accepted: 10 March I994 Correspondence und reprint
isches baplegikerzentrum, 340, CH-80008 Ziirich c, 1994 Butterworth-Heinemann 0966-6362/94/030147 -09
to: Dr Volker Dietz. SchweizerUniversitatsklinik Balgrist, Forchstrasse
reyurs~s
Ltd
ment of the support surface elicits powerful compensatory proprioceptive reflex activity” x. In contrast the compensation of slow body sway induced, for example by rotational platform perturbations. was shown to be controlled predominantly by the vestibular systemJ. While there is no question that vision plays a crucial role in the feedforward control of gait, it was presumed that it contributes little toward the modulatory EMG responses to platform displacements”. Conversely there are reports which suggest a significant role for vision during upright stance, especially when a mismatch is presented between visual and other afferent inputs’. Most previous studies concerning the effect of moving visual inputs on driving postural sway were focused on psychophysical aspects without considering the undcrlying motoneuronal mechanisms1”mi4. The aim of the present study was to assess the influence of a continuously moving visual input upon leg muscle activation during a balancing task. Specifically it
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Figure 2. The sinusoidal movements of the treadmill (thick line) and the visual pattern (thin lines) with increasing phase shifts. The presentation of the visual pattern was coincident with a slowing of treadmill frequency from 0.5 to 0.25 Hz (starting at t=O s). Figure 1. The experimental set up (see Methods). Left, subject standing on the treadmill within the hemispherical screen. The visual pattern displayed on the screen was moving along the arrows. Right, subject’s view of the pattern, which was moved to evoke the illusion of motion along the subjects line of sight.
was intended to examine the contributions of visual and muscle proprioceptive afferent input to the programmed EMG pattern. Therefore stance regulation was investigated under conditions of a continuous instability of body equilibrium which was induced by horizontal sinusoidal oscillations of the support surface and the visual flow pattern both moving with the same frequency. The effect of mismatch between proprioceptive and visual input could be studied by the introduction of various phase shifts between oscillatory movements of the visual flow pattern and those of the legs. This allowed us to study the interaction of proprioceptive and visual cues during continuous regulation of upright stance. Also adaptational changes within a series of oscillations at a given phase shift could be examined.
Methods General procedures and experimental conditions
Local ethical committee approval was granted to take recordings from 12 normal, consenting adults between 23 and 38 years (mean, 27.9 years). Subjects stood in an upright position under darkened conditions upon a treadmill moving sinusoidally - backward/forward in relation to the subject - with frequencies of 0.25 (or 0.5 Hz) and an amplitude of f 8 cm. A visual flow pattern was projected onto a hemispheric screen located in front of the subject’s head (radius of the screen: 0.9 m; distance to the subject’s head at eye-level: 0.9 m). The design of the visual flow pattern was chosen to elicit the illusion of viewing a tunnel or a corridor which could be moved, independently from the subject’s supporting surface, along the subject’s line of sight (Figure 1), (i.e. along the same axis as that of the treadmill movement). The visual flow pattern was also moving sinusoidally at 0.25 Hz, thus matching the movement characteristics of the treadmill. According to earlier studies2J5,i6 a visual flow pat-
tern moving at 0.25 Hz can be expected to affect body stabilization. The sinusoidal amplitude of the visual flow pattern was calculated to yield an image velocity (i.e. ‘retinal image’) of twice treadmill speed after superimposing both sinusoidal movements. This was necessary in order to reach reported thresholds for visual motion perception’5.i7. Resulting velocities, Vi, of moving visual flow pattern on the screen amounted to a maximum of 0.2 m s-r. Spatial frequency f,, defined as number of cycles per metre (one ‘cycle’ is the sequence of one light and one dark field within the pattern) along the longitudinal axis of the moving pattern, was equivalent to 1. Temporal frequency, ft, could be calculated to maximally equal 0,25 cycles/s (according to formula ft = Vi x f2). The visual pattern (cf. Figure 1) was apt to produce strong expansion and deformation components of the optic flow fieldi5. These components in combination were reported to be important for the induction of postural responses1°J5. The luminance (I) of the visual pattern was 1 cd/m* (contrast (K) amounted to > 0.8 according to the formula: K = Imax - Imin/Imax + Imin). In order to avoid undesired perception of the two-dimensional quality of the projected scene, the subjects’ vision had to be monocular. Therefore the subjects had to wear spectacles that occluded the borders of the screen and the right eye. The quality of the visible scene was in accordance with earlier findings concerning visual acuity, visual field, and visual scene characteristics 18-2o.Efficacy of this visual flow pattern upon muscle response was tested in preliminary experiments, revealing leg-muscle EMG in stationary subjects clearly being modulated by the moving visual scene (unpublished observations). Frequency changes in sinusoidal treadmill movement were induced in continued darkness or they coincided with the projection of the moving visual stimulus (Figures 1 and 2). A change in treadmill velocity from 0.5 Hz (dark environment) to 0.25 Hz at the onset of visual stimulation forced the subjects to use afferent feedback, visual or proprioceptive, rather than a predictable central set to assure postural stability. The superimposed oscillations of treadmill and visual
Dietz et al.: Visual destabilization
pattern were determined to produce a ‘retinal image’ with various phase shifts (with respect to the treadmill sinus) of 45, 90, 135, 180, 225, 270, 315, and 360 degrees (Figure 2) (We are aware of the fact that the pattern of the visual motion on the retina is not really known. It is influenced by head and body movements in addition to the deliberate motion of the treadmill and the visual flow pattern. Relative head and body movements were, however, small compared to the imposed movements of the treadmill and the visual flow pattern). Conditions with phase shifts of 360 and 180 degrees both produced ‘retinal images’ moving in phase with the treadmill motion; the latter was, however, inverse in direction. Each of the various visual conditions was displayed over a period of five to eight treadmill cycles. Then the treadmill frequency was changed back to 0.5 Hz again and the visual stimulus was turned off. The changes in treadmill frequency were induced at the anterior turning point of the treadmill, i.e. when the body changed from travelling forwards to backwards. Each visual condition (consisting of five oscillatory cycles) was averaged over IO trials for each subject. All conditions were presented randomly during any experimental session. The sinusoidal signals applied to the treadmill and the projector were generated using a two-channel microcomputer-based impulse generator system (Tandon 386/20 MHz).
Electromyographic (EMG) recordings were made using surface electrodes from the medial gastrocnemius and tibialis anterior muscles of the right hand side. Ankleand knee-joint movements were monitored using mechanical goniometers fixed at the lateral aspect of the right foot, leg and thigh6J’. Linear acceleration of the head in space was recorded by two accelerometers (Kistler Piezo-beam; range f 50 g; sensitivity 100 mV/g; time constant 0.5 s) fixed to the forehead and positioned perpendicularly to one another. The treadmill belt was placed over a force-measuring system (Kistler). Thus, from the output of four piezo-elements, fixed at the corners of the treadmill, the anteroposterior swaying of the subjects could be measured in terms of the torque exerted by the centre of force (i.e. the body’s centre of gravity). The additional anteroposterior shift of the torque signal due to the sinusoidal belt movement was taken into account.
EMG and biomechanical recordings were amplified (FM-microvolt amplifier; time constant 0.15 s, bandwidth 0. I ~ 1000 Hz) and, after rectification of the EMG, transferred on-line to a microcomputer system (Tandon 386/20) via an A/D converter sampling at 0.2 kHz”. The averaged data (from IO trials) recorded during the sinusoidal movements under each of the eight visual conditions were studied off-line. The summation of the cycles was triggered by the frequency change itself.
during human stance
149
Because the effects of visual stimulation on the leg muscle activation were of major interest, the responses from an additional condition with a phase shift of 360 degrees and a sinusoidal amplitude of the visual pattern of f 12 cm were individually subtracted from the recordings obtained in all conditions. The individual EMG patterns of all conditions were normalized with respect to the EMG activity obtained after a change in treadmill frequency from 0.5 to 0.25 Hz (adapted cycle) during continuing darkness (labelled ‘relative units’). The following parameters were calculated from the averaged data: 1.
3 i.
By dividing each sinusoidal cycle into 50-ms segments the integrated EMG activity of leg muscles during one movement cycle could be studied. The iatencies and amplitudes of EMG after a change in frequency were measured. The maxima were determined by calculating a weighted ‘centre of activity’ within five segments of 50 ms per interval, similar to a technique of calculating a centre of gravity:
i I=
I;t, I
where Ii = integrated EMG activity i; t, = time delay of segment i.
3.
4.
within
segment
Calculation of discrete EMG maxima instead of time series analysis allowed a more sensitive evaluation of maximal EMG responses and timing. The correlation coefficients between EMG activity and biomechanical signals were calculated using the Pearson’s product-moment correlation. Possible adaptational changes from the first to the fifth sinusoidal cycles were investigated.
Statistical processing (calculation of means. standard deviation (SD). f tests, correlation coefficients. and analysis of variance (repeated measurement design)) was performed upon the individually averaged data using a SPSS/PCIM package.
Results
Ten of twelve subjects felt less stable during the conditions with extreme phase shifts between the movement of the treadmill and that of the visual fow field (e.g. 90. 135. 270. 315 degrees). Overall the subjects, however. reported little influence of the perceived image upon their postural stability and even claimed to disregard the visual How pattern. Irrespective of these observations the EMG and biomechanical recordings gave clear evidence for a considerable influence of visual stimulation upon the subject’s stance regulation.
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Figure 3. Mean values (SD shaded where shown) of the rectified and averaged (n = 10) leg-muscle EMG responses with corresponding head, knee, and ankle-joint movements, treadmill velocity, and torque signals from one subject. The subjects were required to stand on the treadmill under conditions of normal illumination with their eyes open. Treadmill frequency was 0.25 Hz. The inserted stick diagrams were reconstructed from the joint movements.
Figure 3 displays the recorded leg muscle EMG activity and biomechanical parameters during a treadmill sinus of 0.25 Hz in the absence of a visual flow pattern but with the room illuminated. The main activity phase of gastrocnemius is seen around the anterior turning point and that of the tibialis anterior around the posterior turning point of sinusoidal treadmill movement. The EMG activity in the respective muscles serves to compensate for the inertial forces acting upon the body. As indicated by the biomechanical signals (head acceleration, ankle and knee joint goniometer) and the reconstructed stick diagrams, a slight forward positioning of the body associated with a tibialis anterior activation occurred around the posterior turning point and a straightening of the body associated with a gastrocnemius activation around the anterior point22. Figure 4 shows the effect of two phase shifts (90 and 180 degrees) between treadmill and visual sinusoidal movement upon EMG activity in the lower leg muscles (fifth cycle). The different steps of processing of EMG signals are displayed. In Figure 4A, the mean EMG activity of 10 trials with SD of one individual subject is shown. In order to see the pure effects elicited by the visual stimulation, the EMG patterns of the control condition (see Methods) were individually subtracted from those obtained during each experimental condition. All EMG data were normalized with respect to responses
ant
post turning points
ant
Figure 4. Tibialis anterior (left), and gastrocnemius (right) EMG responses to phase shifts of 90 and 180 degrees between movement of the treadmill and of the visual pattern. The EMG activity displayed was recorded during the fifth sinusoidal cycle after changing the treadmill frequency with the concomitant presentation of the visual pattern. (A) mean and SD of the rectified and averaged (n = 10) EMG responses of an individual subject. Mean values from all subjects of the (B) unsubtracted and (C) subtracted EMG traces. In the latter case recordings from the control condition were subtracted from the various EMG patterns in order to demonstrate the true effects of visual stimulation on the EMG activity. (D) Mean values from all subjects of the subtracted, normalized, and integrated EMG responses (50 ms integrals). Exemplary determination of latency (At) and amplitude (AA) in EMG as derived from the weighting of largest integral (50 ms) with its entouring 50-ms integrals (for formula see Data analyses) within an area of 250 ms.
recorded during the darkened condition after a treadmill frequency change to 0.25 Hz (labelled as ‘relative units’). Then mean values of EMG activity obtained from all subjects were calculated. For comparison the mean EMG traces obtained from all subjects before (Figure 4B) and after (Figure 4C) subtraction are shown. The effect of dividing the integrated EMG activity of each sinusoidal cycle into 50-ms segments (mean of all subjects) is shown in Figure 4D. From the subtracted EMG recordings it is seen that there was a distinct modulation of EMG activity in the lower leg muscles by the two different phase shifts. The onset, duration. and amplitude of tibialis anterior EMG activity was markedly modified. These changes occurred around the posterior turning point (around t = 2 s). In contrast, only the amplitude of the gastrocnemius activity was modulated at times between t = 0 and 0.3 s (corresponding to the activity around the anterior turning point).
Dietz et al.: Visual destabilization
Figure 5. Mean values from all subjects of the subtracted and integrated (A) tibialis anterior and, (B) gastrocnemius EMG activity profiles (50-ms integrals) obtained under the various experimental conditions during the fifth cycle of visual stimulation.
As a result of the described data processing Figure 5A shows the modulated traces of tibialis anterior EMG activity induced by the various phase shifts. Results were obtained after the subject’s adaptation, i.e. during the fifth cycle after a change of the treadmill frequency (0.5 to 0.25 Hz). The tibialis anterior EMG was differentially modulated by the various conditions throughout the whole cycle, usually with an activity peak just after the posterior turning point (t = 2 s). Maximal EMG activity of longest duration occurred during phase shifts of 90 and 135 degrees and of somewhat smaller amplitudes during phase shifts of 270 and 3 15 degrees. Figure 5B shows EMG profiles from the gastrocnemius muscle. The main EMG activity phase was more or less restricted to the period after the anterior turning point (from about t = 0 to 1 s). The largest EMG amplitudes appeared during phase shifts of 90, 135, and 270 degrees. Figure 6 displays the modulation of leg-muscle EMG activity by the various phase shifts of the visual flow pattern during distinct phases of the treadmill cycle. The modulation of the tibialis anterior muscle (Figure 6A) around the posterior turning point (t = 2 s) and gastrocnemius muscle (Figure 6B) around the anterior turning point (t = 0 s) is shown (mean f SD from all subjects). The schematic illustrations indicate the various velocities and directions of the retinal image that occur in the different conditions with respect to the two distinct foot positions during the treadmill sinus. The greatest EMG amplitude in both muscles occurred in conditions with highest momentary retinal image velocity, i.e. with visual image and treadmill sinusoidal phase differences of 90 and 270 degrees. The smallest amplitudes in both muscles were obtained when the velocity of the retinal image was zero. In addition the EMG amplitude was larger when the legs and the retinal image moved in opposite directions (90 degrees) compared to the condition when the movement direction of the image was the same as the direction of the legs (eg. 270. 3 15 degrees).
during human stance
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Figure 6. Influence of the phase shifts between movements of the treadmill and of the visual pattern (45-360 degrees). Modulation of the subtracted tibialis anterior EMG activity at the posterior turning point (A) and the gastrocnemius EMG activity at the anterior turning point (B). Mean values (with SD) are taken from all subjects’ rectified and averaged (n = 10) integrated EMG responses. (A) tibialis anterior EMG modulation recorded at times between 2.0 and 2.25 s. (B) gastrocnemius EMG modulation recorded between 0 and 0.25 s. The schematic drawings indicate the degree of phase shift and the actual direction and velocity (the latter informations are indicated by length and direction of the arrow (+) of the retinal image (e) relative to the feet (A) in the respective conditions.
For further quantitative information concerning the time course of EMG modulation during the first five cycles after onset of the visual display, the modulation of both latency (Figure 7) and amplitude (Figure 8) of the respective EMG maxima was calculated separately for each sway cycle (for the determination of EMG maxima see Methods). Figure 7 shows the latency-modulation of the tibialis anterior (Figure 7A) and gastrocnemius (Figure 7B) peak EMG activity. As shown earlier the maximum of tibialis anterior EMG usually appeared after the posterior turning point (at ? < t < 4 s) and the gastrocnemius maximum after the anterior turning point (at 0 < t < 2 s). The latency of maximum was significantly modulated for the tibialis anterior throughout all five cycles but only during the tifth cycle in the gastrocnemius muscle. For both muscles there was only little change in this modulation during the course from the first to the fifth cycle. Corresponding to the latency modulation there was a pronounced modulation of the peak tibiatis anterior EMG amplitude by the various conditions throughout
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Figure 7. Latency modulation of maximum tibialis anterior (A) and gastrocnemius (B) muscle EMG activity is induced by the various phase shifts. The records shown are mean values (with SD) obtained from all subjects during the first, second, third, and fifth cycles after presentation of the visual pattern. Note the change of scales of the ordinate between A and B; significant differences are x: P-C 0.05, xx: P< 0.01, xxx: P
the five cycles (Figure 8). Except for the first cycle the amplitude of the EMG maximum of both muscles was largest during phase shifts of 90 and 270/315 degrees. These represent the conditions with the highest momentary velocity of the visual flow pattern occurring against (90 degrees) and with (270/3 15 degrees) the direction of feet movement at the posterior and anterior turning points (see Figure 6). For the tibialis anterior (Figure 8A) the second peak (270/3 15 degrees) was somewhat smaller than the first one (90 degrees). However, the amplitudes of the maxima barely changed from the second to the fifth cycle. Compared to the tibialis anterior, little amplitude modulation occurred in the gastrocnemius exhibiting the largest amplitudes during phase shifts of 90 and 270 degrees (Figure 8B). Biomechanical efects
Figure 9 displays the recorded signals of head acceleration (Figure 9A) and treadmill torque (Figure 9B) during the various phase shifts. The EMG modulation is reflected in these biomechanical signals. The two signals indicate that a forward movement of the body occurred after the posterior turning point (t = 2 s). Around the anterior turning point (t = 0 s) straightening movements occurred which resulted in the return to a neutral body position (‘resetting movements’). EMG and treadmill torque signals were correlated (Pearson’s productmoment correlation) by using the weighted maxima (see
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Methods) of both signals (Table 1). A high correlation coefficient between tibialis anterior EMG and treadmill torque was found for phase shifts of 90 and 270 degrees, which represent those with the strongest EMG responses. Compared to these values the correlation coefficients between gastrocnemius EMG and treadmill torque were rather small. The time relationship between the appearance of the EMG responses (cf. Figure 5) and
Dietz et al.: Visual destabilization Table 1. Correlation coefficients between the EMG activity (of the tibialis anterior biomechanical signal of treadmill torque during the first, second, third and fifth cycles
during human stance
and gastrocnemius
Correlation coefficient of ant. tibia1 EMG vs treadmill torque
muscles)
153
and the
Correlation coefficient of gastrocnemius EMG vs treadmill torque
Conditions
90”
180”
270”
360”
90”
180”
270”
360”
Latency modulation 1 Cycle 2 3 5
0.83”’ 0.82”” 0.47 0.95””
0.06 0.38 0.33 0.03
0.74” 0.82’” 0.14 0.03
0.34 -0.13 0.45 -0.13
0.35 -0.26 0.65 0.59
0.33 0.14 0.02 0.06
0.24 -0.10 0.44 -0.23
0.13 -0.33 0.17 -0.11
Amplitude 1 Cycle 2 3 5
0.86’” 0.70” 0.90”’ 0.75”
0.18 0.60 0.68” 0.83’”
0.46 0.69” 0.66 0.73”
0.15 -0.05 0.28 0.26
0.48 0.51 0.40 0.65
0.27 0.09 -0.05 0.55
0.41 -0.01 0.26 0.13
0.39 0.07 0.54 0.06
modulation
The maximum values of each parameter were used in the calculation
biomechanical signals as well as the movement direction indicate that the movements most probably were the consequence of visually evoked EMG responses.
Discussion In this study we investigated the influence of visual stimulation upon neuronal control of body sway. A mismatch was produced between proprioceptive and visual input by introducing various phase shifts between the sinusoidal movement of the legs and that of the visual flow pattern. The main results concern: (1) the differential modulation of the antagonistic leg muscles; (2) poor adaptational changes of the EMG pattern. The following discussion will assess these features with respect to the neuronal control of upright stance.
D$k-mtiul
modulution
qfkg muscle uctivit)’
Postural stabilization during the sinusoidal treadmill movements with congruent visual stimulation was achieved mainly by modulation of leg extensor muscles (see Figure 3). However, presentation of the incongruous visual information mainly resulted in modulation of EMG activity in leg flexor muscles. At times around the posterior turning point tibialis anterior EMG was modulated in its onset, duration, and amplitude. This is the time during which the tibialis anterior muscle is most active during sinusoidal treadmill movements. In comparison gastrocnemius EMG activity was only modulated in amplitude within a short time period restricted to the anterior turning point, the time during which predominant extensor EMG activity occurs. The difference between the behaviour of the antagonistic leg muscles. where the leg flexors have a higher responsiveness to visual stimuli but the leg extensors to somatosensory input, agrees with observations from experiments in the cat’j. In addition, corticospinal projections to lower limb motoneurons were recently shown to be stronger to the tibialis anterior than to the soleus and gastrocnemius muscles”. This was suggested to be
of correlation coefficients.
Significant
correlations are +Pi 0.05; **Pi
0.01,
due to a different use of the limb muscles. Lestienne and co-workersI stated earlier that some asymmetry in postural readjustment may be due to the anatomical properties of the foot. while another part of this effect was ascribed to the directional asymmetry in visual motion perceptio+. It is, however, rather unlikely for the present experiments that the biomechanics of the foot are mainly responsible for the differential modulation of EMG activity in the antagonistic leg muscles. Due to its greater basic activity the gastrocnemius EMG would then be expected to become modulated by visual input rather than the tibialis anterior EMG. Visually induced tibialis anterior activation and modulation occurred around the posterior turning point, and according to the ankle torque and head acceleration signals was associated with corresponding body movements. In this time period during ‘pure’ sinusoidal treadmill movement the body becomes inclined forwards due to the tibialis anterior activation (see Figure 3). Depending upon sinusoidal frequency the angle of forward inclination is adjusted to align the resultant of gravitational and inertial forces to the axis of the body2’Jh. Therefore the posterior turning point in the treadmill sinusoid represents a time period during which the tibialis anterior muscle is sensitive towards modulation by a visuoproprioceptive mismatch. It is also a time period of highest accelerative forces acting at the subject. According to earlier publicationW7 the vestibular system as well as force and cutaneous pressure receptors will predominantly respond to accelerative forces whereas the visual system is apt to sense the magnitude of velocity. During the experimental conditions with phase shifts of 90,!970 and 180/360 degrees a coincidence was induced of maximal/minimal momentary velocity of the visual flow pattern and, at the anterior,!posterior turning point, maximal acceleration of the body. This obviously resulted in maximum and minimum EMG responses in the tibialis anterior muscle. During quiet stance, direction-specific EMG reactions are usually elicited by visual stimulil~“. In the experimental condition described here, this effect may be overrid-
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den by the basic programmed pattern of leg muscle activation developing during the sinusoidal treadmill movement that does not allow for a direction-specific reaction seen in static conditions. However, an effect of stimulus direction became apparent when comparing the strength of the visually evoked EMG activity: the tibialis anterior EMG amplitude was larger and of longer duration when the motion direction of the visual stimulus was opposite to that of the feet than when the direction was the same (see Figure 6). The EMG responses in the gastrocnemius muscle were associated with a straightening of the body and ‘resetting’ of a neutral position (see Figure 9) around the anterior turning point: the signals of linear head acceleration and treadmill torque tend to resume lowest values during this phase of the oscillations. The gastrocnemius EMG activity therefore seems not to depend directly on visual influences but is rather dependent upon and has to compensate for the strength of the preceding visually induced tibialis anterior muscle response. This behaviour is also reflected in the relatively small modulation of latency and amplitude of its EMG maxima (see Figures 7 and 8).
the absence of adaptation could be attributable to the presentation of corresponding visual and proprioceptive input conditions, e.g. the presentation of visual stimuli which possess the movement characteristics of the treadmill. This may represent a requirement too complex to allow for adaptation. Moreover, it was reported earlier that during continuous linear motion of a visual scene little adaptation occursz7. This was interpreted as being due to the need for a velocity sensor during locomotionzx. It cannot be deduced from the present experiments which one factor, or alternatively which combination of these factors, may have prevented adaptation.
Adaptive behaviour
References
The visually induced EMG responses in the tibialis anterior and the gastrocnemius muscles showed no significant changes in their amplitude and timing between the second sinusoidal cycle and the following corresponding cycles. Only during the first cycle was the EMG pattern qualitatively different, due to the change in treadmill frequency. Therefore a change from visual feedback control to a predictive feedforward processing of automatic postural response was lacking, at least during the first few trials. These poor adaptational changes are surprising in view of earlier experiments concerning visual mismatch during stance3. In the latter study the visual environment was moved depending upon head movements induced by displacements of the support surface. During the first few trials it was seen that the EMG responses were both small and delayed, which was explained by visual input masking the effect of displacing the feet. After few trials an appropriate, EMG response appeared to compensate for the support surface displacement, i.e. the subjects automatically neglected the visual mismatch when it was presented. It was proposed that during the first few trials adaptation occurred to the relevance afferent input. The poor adaptational changes in the present study could be due to a number of different factors: first, while only one condition of visual mismatch was presented in the experiments of Nashner and Berthoz3, various unpredictable conditions of mismatch were induced in the present study. Consequently it may be that a period of five cycles is not sufficient for adaptation to occur. Second, the basic EMG pattern underlying the sinusoidal treadmill movements may have become programmed to such an extent that the leg muscle EMG pattern can only be slightly modified by visual afferent input. Third,
Acknowledgements We thank Professor L. Spillmann for giving valuable comments on the manuscript and Dr I. Gibson for correcting the English text. Technical assistance was provided by U. Rlimmelt and U. M6llinger. This work was supported by the Deutsche Forschungsgemeinschaft (SFB 325).
Berthoz A, Lacour M, Soechting JF, Vidal PP. The role of vision in the control of posture during linear motion. In:
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Granit R, Pompeiano 0, eds. Progress in Bruin Research. Reflex Control of Posture and Movement Elsevier, Amsterdam, 1979; 197-209 Diener HG, Dichgans J, Bruzek W, Selinka H. Stabilization of human posture during induced oscillations of the body. Exp Brain Res 1982; 45: 12&32 Nashner LM, Berthoz A. Visual contribution to rapid motor responses during postural control. Brain Res 1978; 150: 403-7 Allum JHJ, Keshner EA. Vestibular and proprioceptive control of sway stabilisation. In: Bles W, Brandt T eds. Disorders of Posture and Gait. Elsevier, Amsterdam, 1986; 1940 Allum JHJ, Pfaltz CR. Visual and vestibular contributions to pitch sway stabilisation in the ankle muscles of normals and patients with bilateral peripheral vestibular deficits. Exp Bruin Res 19 1985; 58: 82-94 Dietz V, Quintern J, Sillem M. Stumbling reactions in man: significance of proprioceptive and pre-programmed mechanisms. J Physioll987; 386: 149-63 Berger W, Dietz V, Quintern J. Corrective reactions to stumbling in man: neuronal coordination of bilateral leg muscle activity during gait. J Physiof 1984; 357: 109-25 Dietz, V. Human neuronal control of automatic functional movements: interaction between central programs and afferent input. Physiol Rev 1992; 72: 23-69 Keshner EA, Woollacott MH, Debu B. Neck, trunk and limb muscle responses during postural perturbations in humans. Exp Brain Res 1988; 7 I : 455-66 Gielen CCAM, van Asten WNJC. Postural responses to simulated moving environments are not invariant for the direction of gaze. Exp Brain Res 1990; 79: 167-74 Lee DM, Aronson E. Visual proprioceptive control of standing in human infants. Percept Psychophys 1974; 15: 529-32 Gibson JJ. Visually controlled locomotion and visual orientation in animals. Br J Psycho/ 1958; 49: 182-94 Stoffregen TA. The role of optical velocity in the control of stance. Percept Psychophys 1986; 39: 355-60
Dietz et al.: Visual destabilization 14 Dichgans J. Brandt T. Visual-vestibular interaction: effects on self-motion perception and postural control. In: Held R, Leibowitz H, Teuber H. eds. Handbook of Sensory Ph,vsiolog_v, vol. 8, Springer, Heidelberg. 1978; 7555804 15 van Asten WNJC. Gielen CCAM, Denier van der Gon JJ. Postural adjustments induced by simulated motion of differently structured environments. E.YP Bruin Res 1988; 73: 371-83 B, Bather M. Role 16 Diener HC, Dichgans J, Guschlbauer of visual and static vestibular influence on dynamic posture control. Hum Neurohiol 1986; 5: 105-l 3 17 Lestienne F. Soechting JF, Berthoz A. Postural readjustments induced by linear motion of visual scenes. E_Y~ Brain Rcr 1977; 28: 363-84 18 Paulus W, Straube A, Brandt Th. Visual stabilization of posture: physiological stimulus characteristics and clinical aspects. Bruin 1984; 107: I 143-63 19 Brandt Th. Paulus W, Straube A. Visual acuity, visual held and visual scene characteristics affect postural balance. In: Igarashi M. Black FO, eds. Vestibulur and Visuul Cotltrol OII Posture and Locomotion Equilibrium. Karger. Base]. 1985: 93-8 20 Brandt Th, Dichgans J. Koenig E. Differential effects of central versus peripheral vision on egocentric and
21
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23
24 25
26
27
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exocentric motion perception. E.up Brain Res 1973: 16: 476-9 1 Dietz V. Horstmann GA, Berger W. Interlimb coordination of leg muscle activation during perturbation of stance in humans. J Neurophysiol 1989; 62: 680-93 Dietz V, Trippel M, Jbrahim IK, Berger W. Human stance on a sinusoidally translating platform: balance control by feedforward and feedback mechanisms. E.vp Brain RPS 1993; 93: 352-62 Beloozerova. JN, Sirota MG. Role of motor cortex in control of locomotion. In: Gurfinkel V’S, Joffe ME, Massion J. Roll JP, eds. Facts and Concepfs. Plenum Press, New York; 1988: 163-76 Brouwer B, Ashby P. Corticospinal projections to lower limb motoneurons in man. E.up Brain Res 1992; 89: 649-54 Berthoz A, Pavard B, Young LR. Perception of linear horizontal self-motion induced by peripheral vision. E.yp Bruin Res 1975; 23: 471-89 Dietz V, Schubert M, Trippel M. Visually induced destabilization of human stance: neuronal control of leg muscles. Neuroreport 1992; 3: 449-52 Waespe W, Henn V. Neuronal activity in the vestibular nuclei of the alert monkey during vestibular and optokinetic stimulation. Esp Brain Res 1977; 27: 523-38 Bronstein AM. Suppression of visually evoked postural responses. E.up Bruit? Res 1986; 63: 655-8
of visuoproprioceptive on postural adjustments
V Dietz, M Schubert,
Department Germany
M Discher, M Trippel
of Clinical Neurology
and Neurophysiology,
University
of Freiburg, Freiburg,
Summary The influence of visual input upon body stabilization was studied with subjects standing on a treadmill while a visual flow pattern was displayed. Both the treadmill and image were moved sinusoidally - backward/forward -at a frequency of 0.25 Hz. The effect of the presentation of the visual pattern was studied upon leg muscle electromyographic (EMG) activity and corresponding biomechanical signals for various phase shifts (45-360 degrees) between movements of the legs and the visual flow pattern. Around the posterior turning point of sinusoidal treadmill movement, i.e. at times when there is an anticipatory forward positioning of the body, a modulation of the tibialis anterior EMG was observed. The onset, duration, and amplitude of the latter were dependent upon the phase shift between the movements of the legs and the visual pattern. Maximum responses were recorded at phase shifts of 90/270 degrees and minimum responses at phase shifts of 180/360 degrees. Therefore a coincidence of fast velocities of the visual flow pattern with a phase of maximal body acceleration evoked the strongest tibialis anterior EMG responses. At times around the anterior turning point a modulation only of EMG amplitude occurred in the gastrocnemius muscle. This activity is believed to be linked to the preceding tibialis anterior EMG resulting in ‘resetting’ of the neutral body position. It is suggested that the tibialis anterior is more sensitive than the gastrocnemius muscle to a visual stimulus. The activity of the latter muscle with its antigravity function is more subject to proprioceptive input. Little adaptational changes in EMG pattern occurred between the second and fifth sway cycles after presentation of the optical flow pattern. It is assumed that task-specific factors act against early adaptation. Key
words: vision, muscle receptor, motor control, electromyogram
Gait & Posture, 1994,
Vol. 2, 147-l
55, September
Introduction Well-aimed experimental models are required to investigate the human motor system under physiological conditions such as stance and gait. With afferent inputs being necessary to appropriately modulate programmed patterns involved in the regulation of stance and gait, the relative contributions of known receptor systems are still a matter of controversy. These systems include the visual system’-‘, the vestibular system4J, and muscle proprioceptive system9. Previous studies have shown that horizontal displace-
Received: I8 October 1993 Accepted: 10 March I994 Correspondence und reprint
isches baplegikerzentrum, 340, CH-80008 Ziirich c, 1994 Butterworth-Heinemann 0966-6362/94/030147 -09
to: Dr Volker Dietz. SchweizerUniversitatsklinik Balgrist, Forchstrasse
reyurs~s
Ltd
ment of the support surface elicits powerful compensatory proprioceptive reflex activity” x. In contrast the compensation of slow body sway induced, for example by rotational platform perturbations. was shown to be controlled predominantly by the vestibular systemJ. While there is no question that vision plays a crucial role in the feedforward control of gait, it was presumed that it contributes little toward the modulatory EMG responses to platform displacements”. Conversely there are reports which suggest a significant role for vision during upright stance, especially when a mismatch is presented between visual and other afferent inputs’. Most previous studies concerning the effect of moving visual inputs on driving postural sway were focused on psychophysical aspects without considering the undcrlying motoneuronal mechanisms1”mi4. The aim of the present study was to assess the influence of a continuously moving visual input upon leg muscle activation during a balancing task. Specifically it
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Figure 2. The sinusoidal movements of the treadmill (thick line) and the visual pattern (thin lines) with increasing phase shifts. The presentation of the visual pattern was coincident with a slowing of treadmill frequency from 0.5 to 0.25 Hz (starting at t=O s). Figure 1. The experimental set up (see Methods). Left, subject standing on the treadmill within the hemispherical screen. The visual pattern displayed on the screen was moving along the arrows. Right, subject’s view of the pattern, which was moved to evoke the illusion of motion along the subjects line of sight.
was intended to examine the contributions of visual and muscle proprioceptive afferent input to the programmed EMG pattern. Therefore stance regulation was investigated under conditions of a continuous instability of body equilibrium which was induced by horizontal sinusoidal oscillations of the support surface and the visual flow pattern both moving with the same frequency. The effect of mismatch between proprioceptive and visual input could be studied by the introduction of various phase shifts between oscillatory movements of the visual flow pattern and those of the legs. This allowed us to study the interaction of proprioceptive and visual cues during continuous regulation of upright stance. Also adaptational changes within a series of oscillations at a given phase shift could be examined.
Methods General procedures and experimental conditions
Local ethical committee approval was granted to take recordings from 12 normal, consenting adults between 23 and 38 years (mean, 27.9 years). Subjects stood in an upright position under darkened conditions upon a treadmill moving sinusoidally - backward/forward in relation to the subject - with frequencies of 0.25 (or 0.5 Hz) and an amplitude of f 8 cm. A visual flow pattern was projected onto a hemispheric screen located in front of the subject’s head (radius of the screen: 0.9 m; distance to the subject’s head at eye-level: 0.9 m). The design of the visual flow pattern was chosen to elicit the illusion of viewing a tunnel or a corridor which could be moved, independently from the subject’s supporting surface, along the subject’s line of sight (Figure 1), (i.e. along the same axis as that of the treadmill movement). The visual flow pattern was also moving sinusoidally at 0.25 Hz, thus matching the movement characteristics of the treadmill. According to earlier studies2J5,i6 a visual flow pat-
tern moving at 0.25 Hz can be expected to affect body stabilization. The sinusoidal amplitude of the visual flow pattern was calculated to yield an image velocity (i.e. ‘retinal image’) of twice treadmill speed after superimposing both sinusoidal movements. This was necessary in order to reach reported thresholds for visual motion perception’5.i7. Resulting velocities, Vi, of moving visual flow pattern on the screen amounted to a maximum of 0.2 m s-r. Spatial frequency f,, defined as number of cycles per metre (one ‘cycle’ is the sequence of one light and one dark field within the pattern) along the longitudinal axis of the moving pattern, was equivalent to 1. Temporal frequency, ft, could be calculated to maximally equal 0,25 cycles/s (according to formula ft = Vi x f2). The visual pattern (cf. Figure 1) was apt to produce strong expansion and deformation components of the optic flow fieldi5. These components in combination were reported to be important for the induction of postural responses1°J5. The luminance (I) of the visual pattern was 1 cd/m* (contrast (K) amounted to > 0.8 according to the formula: K = Imax - Imin/Imax + Imin). In order to avoid undesired perception of the two-dimensional quality of the projected scene, the subjects’ vision had to be monocular. Therefore the subjects had to wear spectacles that occluded the borders of the screen and the right eye. The quality of the visible scene was in accordance with earlier findings concerning visual acuity, visual field, and visual scene characteristics 18-2o.Efficacy of this visual flow pattern upon muscle response was tested in preliminary experiments, revealing leg-muscle EMG in stationary subjects clearly being modulated by the moving visual scene (unpublished observations). Frequency changes in sinusoidal treadmill movement were induced in continued darkness or they coincided with the projection of the moving visual stimulus (Figures 1 and 2). A change in treadmill velocity from 0.5 Hz (dark environment) to 0.25 Hz at the onset of visual stimulation forced the subjects to use afferent feedback, visual or proprioceptive, rather than a predictable central set to assure postural stability. The superimposed oscillations of treadmill and visual
Dietz et al.: Visual destabilization
pattern were determined to produce a ‘retinal image’ with various phase shifts (with respect to the treadmill sinus) of 45, 90, 135, 180, 225, 270, 315, and 360 degrees (Figure 2) (We are aware of the fact that the pattern of the visual motion on the retina is not really known. It is influenced by head and body movements in addition to the deliberate motion of the treadmill and the visual flow pattern. Relative head and body movements were, however, small compared to the imposed movements of the treadmill and the visual flow pattern). Conditions with phase shifts of 360 and 180 degrees both produced ‘retinal images’ moving in phase with the treadmill motion; the latter was, however, inverse in direction. Each of the various visual conditions was displayed over a period of five to eight treadmill cycles. Then the treadmill frequency was changed back to 0.5 Hz again and the visual stimulus was turned off. The changes in treadmill frequency were induced at the anterior turning point of the treadmill, i.e. when the body changed from travelling forwards to backwards. Each visual condition (consisting of five oscillatory cycles) was averaged over IO trials for each subject. All conditions were presented randomly during any experimental session. The sinusoidal signals applied to the treadmill and the projector were generated using a two-channel microcomputer-based impulse generator system (Tandon 386/20 MHz).
Electromyographic (EMG) recordings were made using surface electrodes from the medial gastrocnemius and tibialis anterior muscles of the right hand side. Ankleand knee-joint movements were monitored using mechanical goniometers fixed at the lateral aspect of the right foot, leg and thigh6J’. Linear acceleration of the head in space was recorded by two accelerometers (Kistler Piezo-beam; range f 50 g; sensitivity 100 mV/g; time constant 0.5 s) fixed to the forehead and positioned perpendicularly to one another. The treadmill belt was placed over a force-measuring system (Kistler). Thus, from the output of four piezo-elements, fixed at the corners of the treadmill, the anteroposterior swaying of the subjects could be measured in terms of the torque exerted by the centre of force (i.e. the body’s centre of gravity). The additional anteroposterior shift of the torque signal due to the sinusoidal belt movement was taken into account.
EMG and biomechanical recordings were amplified (FM-microvolt amplifier; time constant 0.15 s, bandwidth 0. I ~ 1000 Hz) and, after rectification of the EMG, transferred on-line to a microcomputer system (Tandon 386/20) via an A/D converter sampling at 0.2 kHz”. The averaged data (from IO trials) recorded during the sinusoidal movements under each of the eight visual conditions were studied off-line. The summation of the cycles was triggered by the frequency change itself.
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Because the effects of visual stimulation on the leg muscle activation were of major interest, the responses from an additional condition with a phase shift of 360 degrees and a sinusoidal amplitude of the visual pattern of f 12 cm were individually subtracted from the recordings obtained in all conditions. The individual EMG patterns of all conditions were normalized with respect to the EMG activity obtained after a change in treadmill frequency from 0.5 to 0.25 Hz (adapted cycle) during continuing darkness (labelled ‘relative units’). The following parameters were calculated from the averaged data: 1.
3 i.
By dividing each sinusoidal cycle into 50-ms segments the integrated EMG activity of leg muscles during one movement cycle could be studied. The iatencies and amplitudes of EMG after a change in frequency were measured. The maxima were determined by calculating a weighted ‘centre of activity’ within five segments of 50 ms per interval, similar to a technique of calculating a centre of gravity:
i I=
I;t, I
where Ii = integrated EMG activity i; t, = time delay of segment i.
3.
4.
within
segment
Calculation of discrete EMG maxima instead of time series analysis allowed a more sensitive evaluation of maximal EMG responses and timing. The correlation coefficients between EMG activity and biomechanical signals were calculated using the Pearson’s product-moment correlation. Possible adaptational changes from the first to the fifth sinusoidal cycles were investigated.
Statistical processing (calculation of means. standard deviation (SD). f tests, correlation coefficients. and analysis of variance (repeated measurement design)) was performed upon the individually averaged data using a SPSS/PCIM package.
Results
Ten of twelve subjects felt less stable during the conditions with extreme phase shifts between the movement of the treadmill and that of the visual fow field (e.g. 90. 135. 270. 315 degrees). Overall the subjects, however. reported little influence of the perceived image upon their postural stability and even claimed to disregard the visual How pattern. Irrespective of these observations the EMG and biomechanical recordings gave clear evidence for a considerable influence of visual stimulation upon the subject’s stance regulation.
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Figure 3. Mean values (SD shaded where shown) of the rectified and averaged (n = 10) leg-muscle EMG responses with corresponding head, knee, and ankle-joint movements, treadmill velocity, and torque signals from one subject. The subjects were required to stand on the treadmill under conditions of normal illumination with their eyes open. Treadmill frequency was 0.25 Hz. The inserted stick diagrams were reconstructed from the joint movements.
Figure 3 displays the recorded leg muscle EMG activity and biomechanical parameters during a treadmill sinus of 0.25 Hz in the absence of a visual flow pattern but with the room illuminated. The main activity phase of gastrocnemius is seen around the anterior turning point and that of the tibialis anterior around the posterior turning point of sinusoidal treadmill movement. The EMG activity in the respective muscles serves to compensate for the inertial forces acting upon the body. As indicated by the biomechanical signals (head acceleration, ankle and knee joint goniometer) and the reconstructed stick diagrams, a slight forward positioning of the body associated with a tibialis anterior activation occurred around the posterior turning point and a straightening of the body associated with a gastrocnemius activation around the anterior point22. Figure 4 shows the effect of two phase shifts (90 and 180 degrees) between treadmill and visual sinusoidal movement upon EMG activity in the lower leg muscles (fifth cycle). The different steps of processing of EMG signals are displayed. In Figure 4A, the mean EMG activity of 10 trials with SD of one individual subject is shown. In order to see the pure effects elicited by the visual stimulation, the EMG patterns of the control condition (see Methods) were individually subtracted from those obtained during each experimental condition. All EMG data were normalized with respect to responses
ant
post turning points
ant
Figure 4. Tibialis anterior (left), and gastrocnemius (right) EMG responses to phase shifts of 90 and 180 degrees between movement of the treadmill and of the visual pattern. The EMG activity displayed was recorded during the fifth sinusoidal cycle after changing the treadmill frequency with the concomitant presentation of the visual pattern. (A) mean and SD of the rectified and averaged (n = 10) EMG responses of an individual subject. Mean values from all subjects of the (B) unsubtracted and (C) subtracted EMG traces. In the latter case recordings from the control condition were subtracted from the various EMG patterns in order to demonstrate the true effects of visual stimulation on the EMG activity. (D) Mean values from all subjects of the subtracted, normalized, and integrated EMG responses (50 ms integrals). Exemplary determination of latency (At) and amplitude (AA) in EMG as derived from the weighting of largest integral (50 ms) with its entouring 50-ms integrals (for formula see Data analyses) within an area of 250 ms.
recorded during the darkened condition after a treadmill frequency change to 0.25 Hz (labelled as ‘relative units’). Then mean values of EMG activity obtained from all subjects were calculated. For comparison the mean EMG traces obtained from all subjects before (Figure 4B) and after (Figure 4C) subtraction are shown. The effect of dividing the integrated EMG activity of each sinusoidal cycle into 50-ms segments (mean of all subjects) is shown in Figure 4D. From the subtracted EMG recordings it is seen that there was a distinct modulation of EMG activity in the lower leg muscles by the two different phase shifts. The onset, duration. and amplitude of tibialis anterior EMG activity was markedly modified. These changes occurred around the posterior turning point (around t = 2 s). In contrast, only the amplitude of the gastrocnemius activity was modulated at times between t = 0 and 0.3 s (corresponding to the activity around the anterior turning point).
Dietz et al.: Visual destabilization
Figure 5. Mean values from all subjects of the subtracted and integrated (A) tibialis anterior and, (B) gastrocnemius EMG activity profiles (50-ms integrals) obtained under the various experimental conditions during the fifth cycle of visual stimulation.
As a result of the described data processing Figure 5A shows the modulated traces of tibialis anterior EMG activity induced by the various phase shifts. Results were obtained after the subject’s adaptation, i.e. during the fifth cycle after a change of the treadmill frequency (0.5 to 0.25 Hz). The tibialis anterior EMG was differentially modulated by the various conditions throughout the whole cycle, usually with an activity peak just after the posterior turning point (t = 2 s). Maximal EMG activity of longest duration occurred during phase shifts of 90 and 135 degrees and of somewhat smaller amplitudes during phase shifts of 270 and 3 15 degrees. Figure 5B shows EMG profiles from the gastrocnemius muscle. The main EMG activity phase was more or less restricted to the period after the anterior turning point (from about t = 0 to 1 s). The largest EMG amplitudes appeared during phase shifts of 90, 135, and 270 degrees. Figure 6 displays the modulation of leg-muscle EMG activity by the various phase shifts of the visual flow pattern during distinct phases of the treadmill cycle. The modulation of the tibialis anterior muscle (Figure 6A) around the posterior turning point (t = 2 s) and gastrocnemius muscle (Figure 6B) around the anterior turning point (t = 0 s) is shown (mean f SD from all subjects). The schematic illustrations indicate the various velocities and directions of the retinal image that occur in the different conditions with respect to the two distinct foot positions during the treadmill sinus. The greatest EMG amplitude in both muscles occurred in conditions with highest momentary retinal image velocity, i.e. with visual image and treadmill sinusoidal phase differences of 90 and 270 degrees. The smallest amplitudes in both muscles were obtained when the velocity of the retinal image was zero. In addition the EMG amplitude was larger when the legs and the retinal image moved in opposite directions (90 degrees) compared to the condition when the movement direction of the image was the same as the direction of the legs (eg. 270. 3 15 degrees).
during human stance
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Figure 6. Influence of the phase shifts between movements of the treadmill and of the visual pattern (45-360 degrees). Modulation of the subtracted tibialis anterior EMG activity at the posterior turning point (A) and the gastrocnemius EMG activity at the anterior turning point (B). Mean values (with SD) are taken from all subjects’ rectified and averaged (n = 10) integrated EMG responses. (A) tibialis anterior EMG modulation recorded at times between 2.0 and 2.25 s. (B) gastrocnemius EMG modulation recorded between 0 and 0.25 s. The schematic drawings indicate the degree of phase shift and the actual direction and velocity (the latter informations are indicated by length and direction of the arrow (+) of the retinal image (e) relative to the feet (A) in the respective conditions.
For further quantitative information concerning the time course of EMG modulation during the first five cycles after onset of the visual display, the modulation of both latency (Figure 7) and amplitude (Figure 8) of the respective EMG maxima was calculated separately for each sway cycle (for the determination of EMG maxima see Methods). Figure 7 shows the latency-modulation of the tibialis anterior (Figure 7A) and gastrocnemius (Figure 7B) peak EMG activity. As shown earlier the maximum of tibialis anterior EMG usually appeared after the posterior turning point (at ? < t < 4 s) and the gastrocnemius maximum after the anterior turning point (at 0 < t < 2 s). The latency of maximum was significantly modulated for the tibialis anterior throughout all five cycles but only during the tifth cycle in the gastrocnemius muscle. For both muscles there was only little change in this modulation during the course from the first to the fifth cycle. Corresponding to the latency modulation there was a pronounced modulation of the peak tibiatis anterior EMG amplitude by the various conditions throughout
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the five cycles (Figure 8). Except for the first cycle the amplitude of the EMG maximum of both muscles was largest during phase shifts of 90 and 270/315 degrees. These represent the conditions with the highest momentary velocity of the visual flow pattern occurring against (90 degrees) and with (270/3 15 degrees) the direction of feet movement at the posterior and anterior turning points (see Figure 6). For the tibialis anterior (Figure 8A) the second peak (270/3 15 degrees) was somewhat smaller than the first one (90 degrees). However, the amplitudes of the maxima barely changed from the second to the fifth cycle. Compared to the tibialis anterior, little amplitude modulation occurred in the gastrocnemius exhibiting the largest amplitudes during phase shifts of 90 and 270 degrees (Figure 8B). Biomechanical efects
Figure 9 displays the recorded signals of head acceleration (Figure 9A) and treadmill torque (Figure 9B) during the various phase shifts. The EMG modulation is reflected in these biomechanical signals. The two signals indicate that a forward movement of the body occurred after the posterior turning point (t = 2 s). Around the anterior turning point (t = 0 s) straightening movements occurred which resulted in the return to a neutral body position (‘resetting movements’). EMG and treadmill torque signals were correlated (Pearson’s productmoment correlation) by using the weighted maxima (see
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Methods) of both signals (Table 1). A high correlation coefficient between tibialis anterior EMG and treadmill torque was found for phase shifts of 90 and 270 degrees, which represent those with the strongest EMG responses. Compared to these values the correlation coefficients between gastrocnemius EMG and treadmill torque were rather small. The time relationship between the appearance of the EMG responses (cf. Figure 5) and
Dietz et al.: Visual destabilization Table 1. Correlation coefficients between the EMG activity (of the tibialis anterior biomechanical signal of treadmill torque during the first, second, third and fifth cycles
during human stance
and gastrocnemius
Correlation coefficient of ant. tibia1 EMG vs treadmill torque
muscles)
153
and the
Correlation coefficient of gastrocnemius EMG vs treadmill torque
Conditions
90”
180”
270”
360”
90”
180”
270”
360”
Latency modulation 1 Cycle 2 3 5
0.83”’ 0.82”” 0.47 0.95””
0.06 0.38 0.33 0.03
0.74” 0.82’” 0.14 0.03
0.34 -0.13 0.45 -0.13
0.35 -0.26 0.65 0.59
0.33 0.14 0.02 0.06
0.24 -0.10 0.44 -0.23
0.13 -0.33 0.17 -0.11
Amplitude 1 Cycle 2 3 5
0.86’” 0.70” 0.90”’ 0.75”
0.18 0.60 0.68” 0.83’”
0.46 0.69” 0.66 0.73”
0.15 -0.05 0.28 0.26
0.48 0.51 0.40 0.65
0.27 0.09 -0.05 0.55
0.41 -0.01 0.26 0.13
0.39 0.07 0.54 0.06
modulation
The maximum values of each parameter were used in the calculation
biomechanical signals as well as the movement direction indicate that the movements most probably were the consequence of visually evoked EMG responses.
Discussion In this study we investigated the influence of visual stimulation upon neuronal control of body sway. A mismatch was produced between proprioceptive and visual input by introducing various phase shifts between the sinusoidal movement of the legs and that of the visual flow pattern. The main results concern: (1) the differential modulation of the antagonistic leg muscles; (2) poor adaptational changes of the EMG pattern. The following discussion will assess these features with respect to the neuronal control of upright stance.
D$k-mtiul
modulution
qfkg muscle uctivit)’
Postural stabilization during the sinusoidal treadmill movements with congruent visual stimulation was achieved mainly by modulation of leg extensor muscles (see Figure 3). However, presentation of the incongruous visual information mainly resulted in modulation of EMG activity in leg flexor muscles. At times around the posterior turning point tibialis anterior EMG was modulated in its onset, duration, and amplitude. This is the time during which the tibialis anterior muscle is most active during sinusoidal treadmill movements. In comparison gastrocnemius EMG activity was only modulated in amplitude within a short time period restricted to the anterior turning point, the time during which predominant extensor EMG activity occurs. The difference between the behaviour of the antagonistic leg muscles. where the leg flexors have a higher responsiveness to visual stimuli but the leg extensors to somatosensory input, agrees with observations from experiments in the cat’j. In addition, corticospinal projections to lower limb motoneurons were recently shown to be stronger to the tibialis anterior than to the soleus and gastrocnemius muscles”. This was suggested to be
of correlation coefficients.
Significant
correlations are +Pi 0.05; **Pi
0.01,
due to a different use of the limb muscles. Lestienne and co-workersI stated earlier that some asymmetry in postural readjustment may be due to the anatomical properties of the foot. while another part of this effect was ascribed to the directional asymmetry in visual motion perceptio+. It is, however, rather unlikely for the present experiments that the biomechanics of the foot are mainly responsible for the differential modulation of EMG activity in the antagonistic leg muscles. Due to its greater basic activity the gastrocnemius EMG would then be expected to become modulated by visual input rather than the tibialis anterior EMG. Visually induced tibialis anterior activation and modulation occurred around the posterior turning point, and according to the ankle torque and head acceleration signals was associated with corresponding body movements. In this time period during ‘pure’ sinusoidal treadmill movement the body becomes inclined forwards due to the tibialis anterior activation (see Figure 3). Depending upon sinusoidal frequency the angle of forward inclination is adjusted to align the resultant of gravitational and inertial forces to the axis of the body2’Jh. Therefore the posterior turning point in the treadmill sinusoid represents a time period during which the tibialis anterior muscle is sensitive towards modulation by a visuoproprioceptive mismatch. It is also a time period of highest accelerative forces acting at the subject. According to earlier publicationW7 the vestibular system as well as force and cutaneous pressure receptors will predominantly respond to accelerative forces whereas the visual system is apt to sense the magnitude of velocity. During the experimental conditions with phase shifts of 90,!970 and 180/360 degrees a coincidence was induced of maximal/minimal momentary velocity of the visual flow pattern and, at the anterior,!posterior turning point, maximal acceleration of the body. This obviously resulted in maximum and minimum EMG responses in the tibialis anterior muscle. During quiet stance, direction-specific EMG reactions are usually elicited by visual stimulil~“. In the experimental condition described here, this effect may be overrid-
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den by the basic programmed pattern of leg muscle activation developing during the sinusoidal treadmill movement that does not allow for a direction-specific reaction seen in static conditions. However, an effect of stimulus direction became apparent when comparing the strength of the visually evoked EMG activity: the tibialis anterior EMG amplitude was larger and of longer duration when the motion direction of the visual stimulus was opposite to that of the feet than when the direction was the same (see Figure 6). The EMG responses in the gastrocnemius muscle were associated with a straightening of the body and ‘resetting’ of a neutral position (see Figure 9) around the anterior turning point: the signals of linear head acceleration and treadmill torque tend to resume lowest values during this phase of the oscillations. The gastrocnemius EMG activity therefore seems not to depend directly on visual influences but is rather dependent upon and has to compensate for the strength of the preceding visually induced tibialis anterior muscle response. This behaviour is also reflected in the relatively small modulation of latency and amplitude of its EMG maxima (see Figures 7 and 8).
the absence of adaptation could be attributable to the presentation of corresponding visual and proprioceptive input conditions, e.g. the presentation of visual stimuli which possess the movement characteristics of the treadmill. This may represent a requirement too complex to allow for adaptation. Moreover, it was reported earlier that during continuous linear motion of a visual scene little adaptation occursz7. This was interpreted as being due to the need for a velocity sensor during locomotionzx. It cannot be deduced from the present experiments which one factor, or alternatively which combination of these factors, may have prevented adaptation.
Adaptive behaviour
References
The visually induced EMG responses in the tibialis anterior and the gastrocnemius muscles showed no significant changes in their amplitude and timing between the second sinusoidal cycle and the following corresponding cycles. Only during the first cycle was the EMG pattern qualitatively different, due to the change in treadmill frequency. Therefore a change from visual feedback control to a predictive feedforward processing of automatic postural response was lacking, at least during the first few trials. These poor adaptational changes are surprising in view of earlier experiments concerning visual mismatch during stance3. In the latter study the visual environment was moved depending upon head movements induced by displacements of the support surface. During the first few trials it was seen that the EMG responses were both small and delayed, which was explained by visual input masking the effect of displacing the feet. After few trials an appropriate, EMG response appeared to compensate for the support surface displacement, i.e. the subjects automatically neglected the visual mismatch when it was presented. It was proposed that during the first few trials adaptation occurred to the relevance afferent input. The poor adaptational changes in the present study could be due to a number of different factors: first, while only one condition of visual mismatch was presented in the experiments of Nashner and Berthoz3, various unpredictable conditions of mismatch were induced in the present study. Consequently it may be that a period of five cycles is not sufficient for adaptation to occur. Second, the basic EMG pattern underlying the sinusoidal treadmill movements may have become programmed to such an extent that the leg muscle EMG pattern can only be slightly modified by visual afferent input. Third,
Acknowledgements We thank Professor L. Spillmann for giving valuable comments on the manuscript and Dr I. Gibson for correcting the English text. Technical assistance was provided by U. Rlimmelt and U. M6llinger. This work was supported by the Deutsche Forschungsgemeinschaft (SFB 325).
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