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Fractioned reaction time as a function of response force
Acta Psychologica North-Holland
21
66 (1987) 21-35
FRACTIONED REACTION TIME AS A FUNCTION OF RESPONSE FORCE * S.A.V.M.
HAAGH
BSO, Eindhouen,
The Netherlands
W.A.C. SPIJKERS Aachen
Uniuersrty
of Technologv, FRG
B. van den BOOGAART Tllburg Univemty,
Accepted
and A. van BOXTEL
The Netherlands
April 1987
The relationship between fractionated reaction time components and response force was studied in a simple reaction time task. Subjects squeezed a force transducer between the right thumb and index finger. Three conditions with 5, 25, and 50% of the maximum voluntary isometric force were investigated in a counterbalanced order. The results showed that premotor reaction time was negatively related to peak force amplitude, while motor reaction time remained constant across force conditions. An interpretation of the effect on premotor reaction time in terms of a shift in the speed-accuracy trade-off function was refuted. Although the data were consistent with a two-stage programming model, it was concluded that differences in motor nerve fiber conduction velocity as a function of response force could explain the results obtained.
In the study of rapid aimed movements, reaction time (RT) seems to be affected by various parameters of the ensuing movement (e.g., Henry and Rogers 1960; Klapp 1977). It is assumed that force and timing characteristics of the forthcoming movement may influence RT * We are indebted to our colleagues in the Physiological Psychology Section for helpful comments with respect to the manuscript. In addition, we would like to thank the personnel of the Technical Service of the Department of Psychology for their invaluable assistance. This research was supported by the Dutch Organization for basic Research (Z.W.O.), grant number 15-35-009. Requests for reprints should be sent to W.A.C. Spijkers, Institut fur Psychologie der Rheinisch Westfalischen Technischen Hochschule, Jagerstrasse zw. 17 u 19, D-5100 Aachen, FRG.
OOOl-6918/87/$3.50
0 1987, Elsevier Science Publishers
B.V. (North-Holland)
22
S.A. V.M. Hugh
et cd. / Response force and simple RT
(Kerr 1978; Schmidt et al. 1978; Kelso 1981). With respect to the timing aspect of a movement, it has been found that the initiation of a slow movement is delayed as compared to that of a fast movement (Klapp and Erwin 1976; Falkenberg and Newell 1980; Spijkers and Walter 1985). However, the results of the few RT studies in which response force has been manipulated systematically, are less clear-cut. In the next three paragraphs a short summary of the literature dealing with this subject, followed by some methodological considerations, will be presented. Based on a motor programming view of movement preparation, predictions are formulated in the final paragraph of the introduction. Klemmer (1957), employing an isometric contraction in a simple RT paradigm, reported no effect of force magnitude on RT. Rebert et al. (1967) investigated an anisometric response - depression of a bar - in a blocked simple RT task at two force levels: 2 lb and 14 lb. They reported a non-significant increase in RT of 10 msec with increasing force. As part of a larger study of response complexity, Glencross (1973) conducted a blocked simple and a two-choice RT task in which force was manipulated. The actual responses were anisometric flexions of the elbow against a 2-lb or a 15lb load. The results showed that RT was not affected by force magnitude, neither in the simple nor in the choice RT task. In another blocked simple RT task, Rebert et al. (1976) required their subjects to pull a weight of 0, 15, 30, or 45 lb at the onset of the imperative stimulus. The only result was that RTs in the 15-lb condition were significantly shorter (10 msec) than in the other conditions. Taken together, the above-mentioned studies are inconclusive and point, at most, to a slight effect of force magnitude on RT. As indicated by Weiss (1965) and Botwinick and Thompson (1966). total RT can be fractionated into premotor RT (PRT; latency of EMG onset) and motor RT (MRT; interval between EMG onset and actual movement initiation), thus allowing for a more detailed analysis and for assessment of central and peripheral factors influencing total RT. Variations in central processing are assumed to mainly affect PRT, while peripheral factors are supposed to affect MRT only. Such a strategy was followed by Baba and Marteniuk (9183) who manipulated magnitude of torque in a Donders’ C-RT task (goonogo). The response was a rapid flexion of the elbow whose inertia was increased by 50% in the force condition by adding mass to the arm support apparatus. Movement time was held constant in the low and high mass conditions.
S.A. V.M. Haagh et al. / Response force and simple RT
23
Increase in torque did not affect PRT or MRT. It was concluded that programming different magnitudes of torque does not influence the time necessary for movement preparation. In a second study of fractionated RT by Nagasaki et al. (1983), an increase of PRT as well as MRT was found when force output of a rapid elbow flexion during a simple RT task was increased. The force magnitude was not explicitly specified by the experimenters, but rather left to voluntary choice of the subjects. Thus, even with a fractionated RT analysis, effects of force magnitude manipulation are rather equivocal. Looking at the literature on force manipulation presented above, several points which seriously impede straightforward conclusions can be noted. In none of these studies, force magnitude was varied relative to the maximum voluntary force (MVF) exerted by the individual subjects. It is obvious that subjects differ greatly with respect to force output. Therefore, normalization of this parameter seems warranted. An additional difficulty in comparing the results arises from the fact that various muscles or muscle groups may have contributed to the exerted force. Differences in the experimental set-up of the aforementioned studies may lead to a diversity in the contribution of different muscle groups to the required performance (Hof 1984; Tanaguchi et al. 1984). Therefore, manipulation of force magnitude can become confounded with manipulation of contraction patterns of different muscle groups. Moreover, in none of the studies we examined were RT and movement time (together constituting the total response time) conjointly studied as a function of response force while such an analysis might provide a better description of force effects (Schmidt 1982). In the present experiment, the effect of force magnitude on RT was studied with the previous comments in mind. Various normalized force levels were employed in an almost isometric contraction. Total response time was fractionated into PRT, MRT, and time to peak force. Although the contraction employed was isometric, the label ‘movement’ is used to designate muscle contraction in this paper. The motor programming notion is nowadays conceived of as one of the major theoretical constructs for explaining effects of movement variables on RT (e.g., Klapp 1977; Schmidt 1982). In short, it is based on the assumption that movements are governed by generalized programs, of which the selection and specification take more time as complexity of the movement increases (e.g., Henry and Rogers 1960; Rosenbaum 1985). Furthermore, it is assumed that under proper condi-
24
S. A. ?IM. Haagh et al. / Rqmse
force md srmple R7
tions preprogramming takes place, that is, selection and specification of the motor program occurs before the imperative signal is received. When preprogramming occurs, RT is expected not to be affected by the time required for selection and specification of the motor program parameters. In a simple RT paradigm the required response is fully known in advance of the imperative signal and thus constitutes an optimal condition for preprogramming to occur. Because in the present experiment force magnitude is manipulated between blocks of trials in a simple RT paradigm, enabling complete preprogramming, one expects no effect of force level on PRT. Recently, the motor program concept has been expanded into a two-stage model of programming (Sternberg et al. 1978; Meyer et al. 1984: Spijkers and Sanders 1984). The two-stage model includes a motor programming stage followed by a program loading stage. Spijkers and Sanders (1984) stated that the motor programming stage is concerned with the specification of motor control parameters, such as force, timing, and direction. which are open to preprogramming. The program loading stage translates the specifications into a format appropriate to the muscular system. The latter stage cannot be preprogrammed and is, therefore. always performed during the PRT. The inability to preprogram may seem inefficient but it actually provides greater versatility since the same program can be adopted for different muscular systems during loading (e.g., Klapp 1977). Spijkers and Sanders (1984) suppose that loading time depends on the accuracy demands of the ensuing movement and the ability to discriminate between the specific muscle commands. In forceful contractions, undifferentiated activation of the motoneuron pool can be assumed, whereas in slight contractions a more discrete and finer activation is required (Milner-Brown et al. 1973; Newell and Carlton 1985). This would imply a shorter duration of the program loading stage in the former condition and, consequently, a negative relation between PRT and force level should be found. Method
Subjects and apparatus Twelve right-handed subjects, seven females and five males, experiment (mean age: 22.8 years. SD = 2.5). Hand dominance 20-item questionnaire. Participants received a financial reward.
participated in the was assessed by a
S.A. V. M. Haagh et al. / Response
forceand simple RT
25
Subjects were comfortably seated behind a sloping desk (11 degrees of inclination) in a dimly illuminated, soundproof, electrically shielded chamber. A panel (70 degrees of inclination) with five LEDs of 2 mm size was mounted centrally on the desk at a viewing distance of 45 cm. The LEDs were positioned in a cross-like form at a maximum visual angle of 1.27 degrees. Subjects were told that only the three vertically arranged LEDs were to be used in the experiment. At the right side of this panel, a linear force-transducer (Brosa EBM 6153) was positioned in such a way that, with the ventral aspect of the right forearm resting on the desk, the location of the transducer was exactly between the slightly flexed thumb and index finger, simulating a pincersgrasp. During the experiment, the right forearm and hand were fixed to the desk by means of adhesive tape. The central green LED was illuminated the moment an auditory warning signal (WS) of 300 msec duration (400 Hz, 70 dBA) went on. Switching off this LED demarcated the end of the fixed 4-set foreperiod (FP) and thus provided the reaction signal (RS). The lower and upper red LEDs, as well as the middle green LED, provided immediate force feedback during execution of the response. The lower red LED signalled the start of the movement; additional illumination of the middle green LED indicated that the force output equalled the criterion value. In case of an overshoot, the upper red LED was illuminated as well (for definitions of ‘criterion value’ and ‘overshoot’ see Procedure and data analysis). The EMG of the first dorsal interosseus muscle was bipolarly recorded by means of Ag-AgCl surface electrodes (Beckmann) with a diameter of 2.1 mm, placed approximately 10 mm apart (center to center) parallel to the direction of the muscle fibers. EMG of the right wrist and finger extensor and flexor muscles was recorded by means of Ag-AgCl surface electrodes (Siemens) with a diameter of 10 mm placed 3 cm apart (center to center) on the centers of the dorsal and ventral aspects of the forearm. EMG signals were fed into differential amplifiers (- 3 dB bandwidth: 3.8-520 Hz, high-pass roll-off 31 dB/octave and low-pass roll-off 13.5 dB/octave) and subsequently full-wave rectified and low-pass filtered (- 3 dB cut-off frequency at 50 Hz, low-pass roll-off 29 dB/octave). The low-pass filtered rectified EMG and the force-transducer output were digitized on-line with a sample frequency of 100 Hz. Control of the experiment and data acquisition were obtained by means of a DEC PDP 11/23 computer. Procedure
and data analysis
Prior to the experimental session, subjects were thoroughly trained to minimize dispersion in movement and RT in a separate session. In order to determine MVF, subjects were asked to squeeze the transducer as hard as possible during a brisk dynamic contraction, to maintain the maximum force for 1 set, and then to relax completely. This procedure was repeated several times with rest periods of at least 2 minutes between the contractions. Care was taken that only thumb and index finger were isometrically involved in the movement. The largest MVF obtained was used to define three force levels: 5, 25, and 50% MVF. Besides the visual force feedback, subjects were verbally guided by the experimenter until they had achieved the correct response: a brisk contraction, immediately followed by complete muscular relaxation. Accuracy constraints were chosen in such a way that the actual exerted peak forces had
to fall within the ranges 5%10%. 25-37.5s’. and 50-75% MVF. This implied a relative tolerance range for the 5%’ MVF condition which was twice the size of those for the other two conditions, that is, 100% versus 50% of the criterion force. but a pilot study showed that a 50% tolerance range for the 5% MVF condition was not feasible (see also Newell and Carlton 1985). These force criteria formed the three experimental conditions. Each trial consisted of a fixed 4-see FP followed by a variable intertrial interval (mean duration: 12.5 set; rectangular distribution with a range of lo-15 set). The training session. as well as the experimental session, consisted of blocks of 40 trials, alternated with pauses of 223 min during which the experimenter readjusted the force detection hardware logic and the subjects could become used to the newly chosen force level. During the experimental session, two series of three blocks of trials were given, each series containing the three force conditions. A pause of approximately 15 min was interspersed between the two series. The order of the conditions was systematically varied between the subjects. Feedback on performance was presented in each trial with a delay of 1 set after the response. When the upper limit of the required force range was exceeded. the upper red LED was illuminated for 1 sec. (This error will. hereafter, he called an overshoot.) If the force output did not attain the lower criterion force limit ~ i.e., if there was an undershoot - RT was considered longer than 400 msec. An auditory signal (2 kHz, 70 dBA. duration: 1 set) giving information on response speed was presented if time to lower criterion force limit was longer than 400 msec or less than 100 msec. It is important to note that subjects did not receive feedback on RT as composed of PRT and MRT, but rather on RT plus a part of the movement time. Admittedly, this is a rather arbitrary definition of RT; its main purpose was to keep the subject alert when the interval between RS onset and exceeding the lower limit of the chosen force range became too long. as well as to prevent premature responding. The training session was terminated as soon as the standard deviation of the individual response latency distributions was approximately 15% of the mean latency in each block and no further progression with respect to movement accuracy or timing errors could he discerned. Besides, the force traces. as displayed on an oscilloscope, had to he constant. All subjects achieved these criteria within 120 trials per force condition. Prior to statistical analysis. all trials with timing and movement errors were removed. Force recording and EMG records of the first dorsal interosseus muscle were used to fractionate the interval between RS onset and peak force as schematically illustrated in fig. 1. For each trial. PRT, MRT, latency from movement onset to lower force limit transition (time to criterion force: TCF), and latency from lower force limit transition to peak force (time to peak force: TPF) were calculated. Great care was taken in the estimation of EMG onset and movement onset because it was known from a previous study that the transition from background EMG to response initiation is gradual rather than distinct (Haagh et al. 1983). The assumption of a distinct onset may, therefore. lead to an arbitrary definition of EMG onset. For instance. in the study performed by Nagasaki et al. (1983). EMG onset was defined as the point in time at which the amplitude of the full-wave rectified EMG exceeded a value of 50 pV. This can lead to an overestimation of the premotor RT because the actual time course of the surface EMG is not taken into account. Therefore, onset of EMG and movement were determined as follows. First, 2Rconfidence intervals of mean EMG values were
S.A. V.M. Hangh et al. / Response force and srmple RT
TARGET
21
FORCE RANGE I
FORCE
EMG ‘T
PRT
MAT
TCF
.TPF
Fig. 1. Schematic illustration of the fractionation of the response by means of EMG and force recordings. RS: reaction signal; PRT: premotor reaction time: MRT: motor reaction time; TCF: time to the lower limit of the criterion force range; TPF: time to peak force.
calculated based on 15 consecutive EMG samples prior to RS onset, i.e., the window encompassed 150 msec. This window was shifted forward, one sample at a time and new 2Sconfidence intervals were calculated. This procedure was repeated until an EMG sample was detected which (a) was larger than the upper confidence limit and (b) was the first sample of a continuous increase in EMG activity over at least seven samples. Then, the aforementioned procedure was applied to the force recording to detect the movement onset. The first force trace sample that was larger than the individual lower criterion force limit demarcated the point in time for TCF calculation. Peak force was simply determined by detecting the largest sample in the force trace for 1 set after RS onset. The entire procedure was repeated for each trial. Single-factor analyses of variance (ANOVAs) with experimental conditions as levels were carried out on individually averaged chronometric data, peak force values, and peak EMG values of the first dorsal interosseus muscle, as well as the coefficients of variation of these measures. Only significant F-ratios will be mentioned in the text. In addition, coefficients of correlation were calculated between the various components of the fractionated response time. All calculations were made with the BMDP statistical package on a DEC VAX 11/780 computer.
Results Chronometric data Overall means required response
per condition are shown in table 1. PRT was inversely related to force (F(2,22) = 5.06. p < 0.02). MRT was constant across condi-
28
S. A. v. M. Haagh er al. / Response /orce und .srmple R T
Table 1 Means of the various components of the fractionated total response time in milliseconds Means of the within-subject coefficients of variation are shown within parentheses. Premotor RT (PRT)
Motor RT (MRT)
Time to criterion force (TCF)
5R MVF
206.1 (0.19)
16.6 (0.74)
50.9 (0.40)
61.2 (0.25)
25% MVF
202.1 (0.19)
16.2 (0.68)
98.5 (0.26)
61.8 (0.41)
50% MVF
196.8 (0.17)
15.4 (0.62)
107.2 (0.20)
70.2 (0.34)
(n = 12).
Time to peak force (TPF)
tions, indicating that the interval between EMG onset and movement initiation was independent of force level. Once movement had begun, however, TCF increased as a function of the required force level (F(2.22) = 203.9, p < 0.001). The factor force also had a significant effect on TPF (F(2,22) = 3.48. p < 0.05).However, this effect was not proportional to produced force (see table 1). probably due to the fact that this dependent variable is strongly affected by the extent to which subjects exceeded the lower criterion force limit. Therefore, it is of little significance to this paper. The coefficients of variation of PRT. MRT, and TPF showed no significant variation across conditions, but variability of TCF decreased significantly with increasing peak force (F(2,22) = 20.47. p < 0.001) (see table 1). Calculation of within-subject correlation coefficients between the various fractionated response latencies as part of a multiple linear regression analysis revealed a slight negative linear relation between PRT and the other latency measures in all conditions. In two of the three conditions, TCF and TPF showed a small positive
Table 2 WIthin-subject total response
coefficients of correlation time (n = 12).
between
PRT 5% MVF
25% MVF
50% MVF
MRT TCF TPF
-0.23 -0.24 -0.14
MRT TCF TPF MRT TCF TPF
the various
components
MRT
of the fractionated
TCF
0.07 0.05
0.10
-0.29 - 0.21 -0.14
- 0.02 -0.01
0.37
-0.18 -0.18 - 0.22
0.09 - 0.04
0.30
S.A. V.M. Haagh et al. / Response force and simple RT
29
correlation. Within-subject correlation coefficients between total RT (PRT + MRT) and movement time (TCF + TPF) were also small: -0.24, - 0.23, and -0.25 in the 5410,10% and 50% MVF conditions, respectively. Numbers of movement errors, i.e., undershoots and overshoots, were computed for each condition. The respective percentages were 2.4% and 12.4% for the 5% MVF condition, 4.3% and 12.6% for the 25% MVF condition, and 2.6% and 1.4% for the 50% MVF condition. These results show that undershoots were most frequent in the middle force condition and that overshoots were almost absent in the high force condition. Force
and EMG
data
Average traces of force records of individual subjects, triggered at force onset, are shown in fig. 2A. As observed by others (e.g., Kamen 1983), rate of force development 578
FORCE LEVEL
299
f%MVF) 6 ,
[rjjz&I;;; f ..__.
..‘~...~.~._;;‘.
I
100
Z%MVF
MSEC
1-A , 1 10 MSEC
125 IA’
e
IRL+ 100
MSEC
Fig. 2. Average traces of force records of individual subjects (n = 12) for each condition (A) and average traces of the surface EMG of the first dorsal interosseus muscle for each condition (C). Beginning of force records is also shown on an extended time scale (B). From above to below, traces represent the 50%, 25% and 5% MVF conditions, respectively. Dashed lines indicate the target force levels. All traces are superimposed with force onset (arrow) as reference point on the time scale.
was faster with increase of exerted force. The duration of force development also increased with increasing peak force, as can be derived from table 1, by adding TCF and TPF. Actual peak forces in the three conditions were 6.7%. 29.9%, and 57.8% MVF (F(2.22) = 731.6, p < 0.001). The coefficient of variation of peak force decreased significantly with increase of peak force (F(2,22) = 43.38, p < 0.001). The latter result is in agreement with recent findings of Newell and Carlton (1985) with respect to the relationship between peak force and peak force variability. Only the surface EMG of the first dorsal interosseus muscle is depicted in fig. 2C because the time courses of the EMGs of wrist and finger extensor and flexor muscles were quite similar. though amplitudes were generally lower. A significant increase in EMG burst duration - i.e., the interval between EMG onset and peak EMG amplitude ~ with increase of peak force was found: respectively 59. 86, and 102 msec (F(2,22) = 71.21, p i 0.001). In addition. the coefficient of variation of peak EMG amplitude decreased significantly when force increased and was respectively 0.31. 0.12. and 0.08 (F(2,22) = 57.75, p < 0.001). Higher peak EMG amplitude was concomitant with higher peak force value (F(2,22) = 50.85. p < 0.001). although, as opposed to force, the increase of EMG amplitude from 25% to 50% MVF was smaller than the increase from 5% to 25% MVF.
Discussion
A definite result of the present study is the negative relation between PRT and exerted peak force. Furthermore, MRT remained constant across conditions. A corresponding result with respect to constancy of MRT was obtained by Brown and Cooke (1981) in a target aiming task. They found a constant epoch between onset of agonist EMG and movement onset, independent of the speed of the contraction, given a certain movement amplitude. Although a positive relationship between PRT and MRT was reported by Nagasaki et al. (1983) their results are hard to compare, as we have argued in the Method section. As a possible explanation for the decrease of PRT with increase of force, a shift in the trade-off function between speed and accuracy of the movement should be considered. The absolute range of tolerated force exertions increased with increase of force level which means that accuracy demands decreased. The relative tolerance range, however, did not increase. As our results show. proportion of undershoots did not differ widely between the conditions while proportion of overshoots was similar in the 5% and 25% MVF conditions but dramatically decreased in the 50% MVF condition. These results might be regarded as evidence against a trade-off shift towards speed. However, it might be objected that overshooting the 75% MVF level might have been
S.A. V.M. Haagh et al. / Response force and simple RT
31
extremely hard to achieve given the allowed total response time of 400 msec. Newell and Carlton (1985) observed that the time allowed for peak force to be generated determined the maximum peak force actually obtained. Our results corroborate their observation that movement time (TCF + TPF) increased with force level. Nevertheless, a second, more important argument against an interpretation in terms of a trade-off function shift can be derived from the constancy of the coefficient of variation of PRT across conditions, something which is not to be expected from a speed-accuracy point of view. In addition, the coefficient of variation of peak force decreased significantly when peak force increased, indicating that higher forces were exerted more consistently. The latter result is in line with the early data of Jenkins on force variability, recently reviewed by Newell et al. (1984). Unfortunately, an insufficient number of force levels investigated prevents us from adequately describing this relation. Furthermore, movement time was not explicitly controlled. Newell and Carlton (1985) view such a control as a prerequisite to a valid estimation of movement variability. Summarizing, we conclude that the speed-accuracy trade-off argument is not tenable to the PRT effect in the present experiment. The negative relation between PRT and exerted peak force is in agreement with the two-stage motor programming model. Such an interpretation is supported by the work of Kimm and Sutton (1973) who taught their subjects to respond with a single spike from one motor unit in a simple RT paradigm. It is well known that the rate of force development initially predominantly depends upon the number of motor units recruited and subsequently predominantly upon the firing frequency of the motor units (Freund 1983). Kimm and Sutton (1973) compared the single spike latency with the latency of a key release response - requiring a burst of EMG activity instead of a single spike _ and reported that, in the latter condition, RTs were significantly shorter (approximately 20 msec) than in the former. Similar results were obtained by Kosarov (1979) who trained subjects to respond with a single spike, a small train of spikes, or a burst of EMG in a blocked simple RT task. RT decreased significantly as a function of the number of motor units involved. Kimm and Sutton (1973) interpreted their results in terms of differences in task requirements. Activation of a single motor unit involves a very discrete muscular contraction while such a differentiated activation is not necessary for an overt movement. Therefore, a key release response might require less program loading
32
S.A. V.M. Haagh et al. / Respome force and simple R T
time than activation of a single motor unit as Spijkers and Sanders (1984) predicted. Support for this hypothesis is provided by the fact that dispersion of single motor unit RTs was larger than dispersion of key release RTs, a result also found by Kosarov (1979). Although the two-stage programming model can accommodate the results of the present study, a simpler explanation can be given from a neurophysiological point of view. In general, the recruitment order within a motoneuron pool is fixed when contraction strength increases, starting with the smaller motoneurons, corresponding with slow-contracting muscle units of little force and adding larger motoneurons, corresponding with fast-contracting, forceful muscle units (for an overview, see Henneman and Mendell 1981). Milner-Brown et al. (1973) reported for the human first dorsal interosseus muscle that the number of additional muscle units recruited during a given force increment declines exponentially with increasing contraction force. Therefore, it is probable that in the present 5% MVF condition, small motoneurons were predominantly involved, and that in the 50% MVF condition almost the whole motoneuron pool was recruited. Indirect support for this assumption is provided by our finding that variability of TCF, as well as of peak force, decreased with increasing peak forces. According to an argument advanced by Newell et al. (1980: 55) variability of movement time is negatively related to the number of muscle units involved. The order of motoneuron recruitment is independent of the speed of contraction, but increase of contraction speed is concomitant with a decrease in recruitment threshold (e.g., Desmedt and Godaux 1977). This decrease is proportionally similar for a large range of motoneurons in the human first dorsal interosseus muscle (Desmedt and Godaux 1978). During very fast contractions, like were performed in the present study, the recruitment threshold becomes very low for all motoneurons, to the point that the entire motoneuron pool is almost simultaneously activated (Biidingen and Freund 1976). This is illustrated in fig. 2B which shows a more detailed comparison of the rate of force development at different criterion force levels. The much faster rise in the 25% and 50% MVF conditions reflects the immediate contribution of fast-contracting muscle units with high twitch tensions. The simultaneous activation of almost all involved motoneurons during fast contractions may be expected to result in variations in PRT when response force is varied. Small motoneurons have relatively slow-conducting axons, while larger motoneurons have relatively fast-
S.A. V.M. Haagh et al. / Response force and simple RT
33
conducting axons (Henneman and Mendell 1981). The diameter of alpha motoneuron axons in the human arm is known to vary between lo-18 pm, indicating a range in conduction velocity from 35-70 m/set. With a peripheral length of motor axons of approximately 90 cm, the conduction time of the fastest-conducting motor axons will be 12 msec less for the 50% MVF condition than for the 5% MVF condition. Therefore, recruitment order during fast contractions seems to be reversed when recorded at the level of the muscle units, that is, when recording EMG potentials (Freund 1983). Based on the aforementioned arguments, we suggest that in the present experiment, with its given force levels, the small but consistent PRT effect can, at least for the greater part, be explained by differences in conduction velocity of motor axons. In conclusion, the present results can be explained by means of the two-stage programming model. However, with the aforementioned interpretation in terms of peripheral mechanisms, and assuming that complete pre-programming has, indeed, taken place, a program loading stage does not need to be invoked to explain the negative relation between response force and PRT. Although most of the evidence points to a crucial role of peripheral mechanisms, that which is presented here is not conclusive.
References Baba, D.M. and R.G. Marteniuk, 1983. Timing and torque involvement in the organisation of rapid forearm flexion. Quarterly Journal of Experimental Psychology 35A, 323-331. Botwinick, J. and L.W. Thompson, 1966. Premotor and motor components of reaction time. Journal of Experimental Psychology 71, 9-15. Brown, S.H.C. and J.D. Cooke, 1981. Amplitudeand instruction-dependent modulation of movement related electromyogram activity in humans. Journal of Physiology (London) 316, 97-107. Btidingen, H.J. and H.-J. Freund, 1976. The relationship between the rate of rise of isometric tension and motor unit recruitment in a human forearm muscle. Pfltigers Archiv 362, 61-67. Desmedt, J.E. and E. Godaux, 1977. Ballistic contractions in man: characteristic recruitment pattern of single motor units of the tibialis anterior muscle. Journal of Physiology (London) 264, 673-693. Desmedt, J.E. and E. Godaux, 1978. Ballistic contractions in fast or slow human muscles: discharge patterns of single motor units. Journal of Physiology (London) 285, 185-196. Falkenberg, L.E. and K.M. Newell, 1980. Relative contribution of movement time, amplitude, and velocity to response initiation. Journal of Experimental Psychology: Human Perception and Performance 6, 760-768.
Freund. H.-J.. 1983. Motor unit and muscle activity in voluntary motor control. Physiological Reviews 63, 387-436. Glencross, D.J.. 1973. Response complexity and the latency of different movement patterns. Journal of Motor Behavior 5. 95-104. Haagh. S.A.V.M., W.T.E. Spoeltman, J.G.M. Scheirs and C.H.M. Brunia. 1983. Surface EMG and Achilles tendon reflexes during a foot movement in a reaction time task. Biological Psychology 17. 81-96. Henneman. E. and L.M. Mendell, 1981. ‘Functional organization of motoneuron pool and its inputs’. In: V.B. Brooks (ed.). Handbook of physiology. Vol. II. part 1. Bethesda. DC: American Physiological Society. pp. 423-508. Henry, F.M. and D.E. Rogers, 1960. Increased response latency for complicated movements and a ‘memory drum’ theory of neuromotor reaction. Research Quarterly 31. 448-458. Hof, A.L., 1984. EMG and muscle force: an introduction. Human Movement Science 3, 119-153. Kamen. G., 1983. The acquisition of maximal isometric plantar flexor strength: a force time curve analysis. Journal of Motor Behavior 15, 63-73. Kelso. J.A.S.. 1981. ‘Contrasting perspectives on order and regulation in move ent’. In: J. Long and A. Baddeley (eds.), Attention and performance 9. Hillsdale, NJ: Erlbaum. pp. 437-457. Kerr. B.. 1978. ‘Task factors that influence selection and preparation for voluntary movements’. In: G.E. Stelmach (ed.). Information processing in motor control. New York: Academic Press. pp. 55569. Kimm, J. and D. Sutton, 1973. Foreperiod effects on human single motor unit reaction times. Physiology and Behavior 10, 539-542. Klapp, ST.. 1977. ‘Reaction time analysis of programmed control’. In: R.S. Hutton (ed.), Exercise and sport science reviews. Santa Barbara. CA: Journal Publishing Affiliates. pp. 231-253. Klapp, S.T. and C.I. Erwin, 1976. Relation between programming time and duration of the response bemg programmed. Journal of Experimental Psychology: Human Perception and Performance 2. 591-598. Klemmer. E.T., 1957. Rate of force application in a simple reaction time test. Journal of Applied Psychology 41. 3299332. Kosarov. D., 1979. The reaction time of single motor units in the human muscle. Agreasologie 20, 279-285. Meyer. D.E.. S. Yantis. A. Osman and K.J.E. Smith. 1984. ‘Discrete versus continuous models of response preparation: a reaction time analysis’. In: S. Kornblum and J. Requin (eds.). Preparatory states and processes. Hillsdale. NJ: Erlbaum. pp. 69994. Milner-Brown. H.S., R.B. Stein and R. Yemm, 1973. The orderly recruitment of human motor units during voluntary isometric contractions. Journal of Physiology (London) 230, 359-370. Nagasaki. H., F. Aoki and R. Nakamura, 1983. Premotor and motor reaction time as a function of force output. Perceptual and Motor Skills 57. 8599867. Newell, K.M. and L.G. Carlton. 1985. On the relationship between force and force variability in isometric tasks. Journal of Motor Behavior 17. 230-241. Newell. K.M.. L.G. Carlton and P.A. Hancock. 1984. Kinetic analysis of response variability. Psychological Bulletin 96, 133-151. Newell. K.M.. L.G. Carlton. M.J. Carlton and J.A. Halbert, 1980. Velocity as a factor in movement timing accuracy. Journal of Motor Behavior 12, 47-56. Rebert. C.. R. Berry and J. Merlo, 1976. ‘DC potential consequences of induced muscle tension effects on contingent negative variation’. In: W. McCallum and J. Knott (eds.), The responsive brain. Bristol: Wright. pp. 1266131. Rebert, C.. D.W. McAdam. J.R. Knott and D.A. Irwin. 1967. Slow potential change in human brain related to level of motivation. Journal of Comparative and Physiological Psychology 63, 20-23.
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35
Rosenbaum, D.A., 1985. ‘Motor programming: a review and scheduling theory’. In: H. Heuer, U. Kleinbeck and K.H. Schmidt (eds.), Motor behavior. Programming, control. and acquisition. Berlin: Springer. pp. l-34. Schmidt. R.A., 1982. Motor control and learning. Champaign, IL: Human Kinetics Publishers. Schmidt, R.A., H.N. Zelaznik and J.S. Frank, 1978. ‘Sources of inaccuracy in rapid movement’. In: G.E. Stelmach (ed.), Information processing in motor control and learning. New York: Academic Press. pp. 183-203. and programming of movement Spijkers, W.A.C. and A.F. Sanders, 1984. Spatial accuracy velocity. Bulletin of the Psychonomic Society 22, 531-534. Spijkers, W.A.C. and A. Walter, 1985. Response processing stages in choice reactions. Acta Psychologica 58, 191-204. Sternberg. S.. S. Monsell, R. Knoll and C.E. Wright, 1978. ‘The latency and duration of rapid movement sequences: comparisons of speech and typewriting’. In: G.E. Stelmach (ed.), Information processing in motor control and learning. New York: Academic Press. pp. 117-152. Tanaguchi. R., R. Nakamura and T. Kasai, 1984. Influence of arm positions on EMG-reaction time of the biceps brachii for elbow flexion and forearm supination. Perceptual and Motor Skills 59. 191-194. Weiss. A.D., 1965. The locus of reaction time changes with set, motivation and age. Journal of Gerontology 20, 60-64.
21
66 (1987) 21-35
FRACTIONED REACTION TIME AS A FUNCTION OF RESPONSE FORCE * S.A.V.M.
HAAGH
BSO, Eindhouen,
The Netherlands
W.A.C. SPIJKERS Aachen
Uniuersrty
of Technologv, FRG
B. van den BOOGAART Tllburg Univemty,
Accepted
and A. van BOXTEL
The Netherlands
April 1987
The relationship between fractionated reaction time components and response force was studied in a simple reaction time task. Subjects squeezed a force transducer between the right thumb and index finger. Three conditions with 5, 25, and 50% of the maximum voluntary isometric force were investigated in a counterbalanced order. The results showed that premotor reaction time was negatively related to peak force amplitude, while motor reaction time remained constant across force conditions. An interpretation of the effect on premotor reaction time in terms of a shift in the speed-accuracy trade-off function was refuted. Although the data were consistent with a two-stage programming model, it was concluded that differences in motor nerve fiber conduction velocity as a function of response force could explain the results obtained.
In the study of rapid aimed movements, reaction time (RT) seems to be affected by various parameters of the ensuing movement (e.g., Henry and Rogers 1960; Klapp 1977). It is assumed that force and timing characteristics of the forthcoming movement may influence RT * We are indebted to our colleagues in the Physiological Psychology Section for helpful comments with respect to the manuscript. In addition, we would like to thank the personnel of the Technical Service of the Department of Psychology for their invaluable assistance. This research was supported by the Dutch Organization for basic Research (Z.W.O.), grant number 15-35-009. Requests for reprints should be sent to W.A.C. Spijkers, Institut fur Psychologie der Rheinisch Westfalischen Technischen Hochschule, Jagerstrasse zw. 17 u 19, D-5100 Aachen, FRG.
OOOl-6918/87/$3.50
0 1987, Elsevier Science Publishers
B.V. (North-Holland)
22
S.A. V.M. Hugh
et cd. / Response force and simple RT
(Kerr 1978; Schmidt et al. 1978; Kelso 1981). With respect to the timing aspect of a movement, it has been found that the initiation of a slow movement is delayed as compared to that of a fast movement (Klapp and Erwin 1976; Falkenberg and Newell 1980; Spijkers and Walter 1985). However, the results of the few RT studies in which response force has been manipulated systematically, are less clear-cut. In the next three paragraphs a short summary of the literature dealing with this subject, followed by some methodological considerations, will be presented. Based on a motor programming view of movement preparation, predictions are formulated in the final paragraph of the introduction. Klemmer (1957), employing an isometric contraction in a simple RT paradigm, reported no effect of force magnitude on RT. Rebert et al. (1967) investigated an anisometric response - depression of a bar - in a blocked simple RT task at two force levels: 2 lb and 14 lb. They reported a non-significant increase in RT of 10 msec with increasing force. As part of a larger study of response complexity, Glencross (1973) conducted a blocked simple and a two-choice RT task in which force was manipulated. The actual responses were anisometric flexions of the elbow against a 2-lb or a 15lb load. The results showed that RT was not affected by force magnitude, neither in the simple nor in the choice RT task. In another blocked simple RT task, Rebert et al. (1976) required their subjects to pull a weight of 0, 15, 30, or 45 lb at the onset of the imperative stimulus. The only result was that RTs in the 15-lb condition were significantly shorter (10 msec) than in the other conditions. Taken together, the above-mentioned studies are inconclusive and point, at most, to a slight effect of force magnitude on RT. As indicated by Weiss (1965) and Botwinick and Thompson (1966). total RT can be fractionated into premotor RT (PRT; latency of EMG onset) and motor RT (MRT; interval between EMG onset and actual movement initiation), thus allowing for a more detailed analysis and for assessment of central and peripheral factors influencing total RT. Variations in central processing are assumed to mainly affect PRT, while peripheral factors are supposed to affect MRT only. Such a strategy was followed by Baba and Marteniuk (9183) who manipulated magnitude of torque in a Donders’ C-RT task (goonogo). The response was a rapid flexion of the elbow whose inertia was increased by 50% in the force condition by adding mass to the arm support apparatus. Movement time was held constant in the low and high mass conditions.
S.A. V.M. Haagh et al. / Response force and simple RT
23
Increase in torque did not affect PRT or MRT. It was concluded that programming different magnitudes of torque does not influence the time necessary for movement preparation. In a second study of fractionated RT by Nagasaki et al. (1983), an increase of PRT as well as MRT was found when force output of a rapid elbow flexion during a simple RT task was increased. The force magnitude was not explicitly specified by the experimenters, but rather left to voluntary choice of the subjects. Thus, even with a fractionated RT analysis, effects of force magnitude manipulation are rather equivocal. Looking at the literature on force manipulation presented above, several points which seriously impede straightforward conclusions can be noted. In none of these studies, force magnitude was varied relative to the maximum voluntary force (MVF) exerted by the individual subjects. It is obvious that subjects differ greatly with respect to force output. Therefore, normalization of this parameter seems warranted. An additional difficulty in comparing the results arises from the fact that various muscles or muscle groups may have contributed to the exerted force. Differences in the experimental set-up of the aforementioned studies may lead to a diversity in the contribution of different muscle groups to the required performance (Hof 1984; Tanaguchi et al. 1984). Therefore, manipulation of force magnitude can become confounded with manipulation of contraction patterns of different muscle groups. Moreover, in none of the studies we examined were RT and movement time (together constituting the total response time) conjointly studied as a function of response force while such an analysis might provide a better description of force effects (Schmidt 1982). In the present experiment, the effect of force magnitude on RT was studied with the previous comments in mind. Various normalized force levels were employed in an almost isometric contraction. Total response time was fractionated into PRT, MRT, and time to peak force. Although the contraction employed was isometric, the label ‘movement’ is used to designate muscle contraction in this paper. The motor programming notion is nowadays conceived of as one of the major theoretical constructs for explaining effects of movement variables on RT (e.g., Klapp 1977; Schmidt 1982). In short, it is based on the assumption that movements are governed by generalized programs, of which the selection and specification take more time as complexity of the movement increases (e.g., Henry and Rogers 1960; Rosenbaum 1985). Furthermore, it is assumed that under proper condi-
24
S. A. ?IM. Haagh et al. / Rqmse
force md srmple R7
tions preprogramming takes place, that is, selection and specification of the motor program occurs before the imperative signal is received. When preprogramming occurs, RT is expected not to be affected by the time required for selection and specification of the motor program parameters. In a simple RT paradigm the required response is fully known in advance of the imperative signal and thus constitutes an optimal condition for preprogramming to occur. Because in the present experiment force magnitude is manipulated between blocks of trials in a simple RT paradigm, enabling complete preprogramming, one expects no effect of force level on PRT. Recently, the motor program concept has been expanded into a two-stage model of programming (Sternberg et al. 1978; Meyer et al. 1984: Spijkers and Sanders 1984). The two-stage model includes a motor programming stage followed by a program loading stage. Spijkers and Sanders (1984) stated that the motor programming stage is concerned with the specification of motor control parameters, such as force, timing, and direction. which are open to preprogramming. The program loading stage translates the specifications into a format appropriate to the muscular system. The latter stage cannot be preprogrammed and is, therefore. always performed during the PRT. The inability to preprogram may seem inefficient but it actually provides greater versatility since the same program can be adopted for different muscular systems during loading (e.g., Klapp 1977). Spijkers and Sanders (1984) suppose that loading time depends on the accuracy demands of the ensuing movement and the ability to discriminate between the specific muscle commands. In forceful contractions, undifferentiated activation of the motoneuron pool can be assumed, whereas in slight contractions a more discrete and finer activation is required (Milner-Brown et al. 1973; Newell and Carlton 1985). This would imply a shorter duration of the program loading stage in the former condition and, consequently, a negative relation between PRT and force level should be found. Method
Subjects and apparatus Twelve right-handed subjects, seven females and five males, experiment (mean age: 22.8 years. SD = 2.5). Hand dominance 20-item questionnaire. Participants received a financial reward.
participated in the was assessed by a
S.A. V. M. Haagh et al. / Response
forceand simple RT
25
Subjects were comfortably seated behind a sloping desk (11 degrees of inclination) in a dimly illuminated, soundproof, electrically shielded chamber. A panel (70 degrees of inclination) with five LEDs of 2 mm size was mounted centrally on the desk at a viewing distance of 45 cm. The LEDs were positioned in a cross-like form at a maximum visual angle of 1.27 degrees. Subjects were told that only the three vertically arranged LEDs were to be used in the experiment. At the right side of this panel, a linear force-transducer (Brosa EBM 6153) was positioned in such a way that, with the ventral aspect of the right forearm resting on the desk, the location of the transducer was exactly between the slightly flexed thumb and index finger, simulating a pincersgrasp. During the experiment, the right forearm and hand were fixed to the desk by means of adhesive tape. The central green LED was illuminated the moment an auditory warning signal (WS) of 300 msec duration (400 Hz, 70 dBA) went on. Switching off this LED demarcated the end of the fixed 4-set foreperiod (FP) and thus provided the reaction signal (RS). The lower and upper red LEDs, as well as the middle green LED, provided immediate force feedback during execution of the response. The lower red LED signalled the start of the movement; additional illumination of the middle green LED indicated that the force output equalled the criterion value. In case of an overshoot, the upper red LED was illuminated as well (for definitions of ‘criterion value’ and ‘overshoot’ see Procedure and data analysis). The EMG of the first dorsal interosseus muscle was bipolarly recorded by means of Ag-AgCl surface electrodes (Beckmann) with a diameter of 2.1 mm, placed approximately 10 mm apart (center to center) parallel to the direction of the muscle fibers. EMG of the right wrist and finger extensor and flexor muscles was recorded by means of Ag-AgCl surface electrodes (Siemens) with a diameter of 10 mm placed 3 cm apart (center to center) on the centers of the dorsal and ventral aspects of the forearm. EMG signals were fed into differential amplifiers (- 3 dB bandwidth: 3.8-520 Hz, high-pass roll-off 31 dB/octave and low-pass roll-off 13.5 dB/octave) and subsequently full-wave rectified and low-pass filtered (- 3 dB cut-off frequency at 50 Hz, low-pass roll-off 29 dB/octave). The low-pass filtered rectified EMG and the force-transducer output were digitized on-line with a sample frequency of 100 Hz. Control of the experiment and data acquisition were obtained by means of a DEC PDP 11/23 computer. Procedure
and data analysis
Prior to the experimental session, subjects were thoroughly trained to minimize dispersion in movement and RT in a separate session. In order to determine MVF, subjects were asked to squeeze the transducer as hard as possible during a brisk dynamic contraction, to maintain the maximum force for 1 set, and then to relax completely. This procedure was repeated several times with rest periods of at least 2 minutes between the contractions. Care was taken that only thumb and index finger were isometrically involved in the movement. The largest MVF obtained was used to define three force levels: 5, 25, and 50% MVF. Besides the visual force feedback, subjects were verbally guided by the experimenter until they had achieved the correct response: a brisk contraction, immediately followed by complete muscular relaxation. Accuracy constraints were chosen in such a way that the actual exerted peak forces had
to fall within the ranges 5%10%. 25-37.5s’. and 50-75% MVF. This implied a relative tolerance range for the 5%’ MVF condition which was twice the size of those for the other two conditions, that is, 100% versus 50% of the criterion force. but a pilot study showed that a 50% tolerance range for the 5% MVF condition was not feasible (see also Newell and Carlton 1985). These force criteria formed the three experimental conditions. Each trial consisted of a fixed 4-see FP followed by a variable intertrial interval (mean duration: 12.5 set; rectangular distribution with a range of lo-15 set). The training session. as well as the experimental session, consisted of blocks of 40 trials, alternated with pauses of 223 min during which the experimenter readjusted the force detection hardware logic and the subjects could become used to the newly chosen force level. During the experimental session, two series of three blocks of trials were given, each series containing the three force conditions. A pause of approximately 15 min was interspersed between the two series. The order of the conditions was systematically varied between the subjects. Feedback on performance was presented in each trial with a delay of 1 set after the response. When the upper limit of the required force range was exceeded. the upper red LED was illuminated for 1 sec. (This error will. hereafter, he called an overshoot.) If the force output did not attain the lower criterion force limit ~ i.e., if there was an undershoot - RT was considered longer than 400 msec. An auditory signal (2 kHz, 70 dBA. duration: 1 set) giving information on response speed was presented if time to lower criterion force limit was longer than 400 msec or less than 100 msec. It is important to note that subjects did not receive feedback on RT as composed of PRT and MRT, but rather on RT plus a part of the movement time. Admittedly, this is a rather arbitrary definition of RT; its main purpose was to keep the subject alert when the interval between RS onset and exceeding the lower limit of the chosen force range became too long. as well as to prevent premature responding. The training session was terminated as soon as the standard deviation of the individual response latency distributions was approximately 15% of the mean latency in each block and no further progression with respect to movement accuracy or timing errors could he discerned. Besides, the force traces. as displayed on an oscilloscope, had to he constant. All subjects achieved these criteria within 120 trials per force condition. Prior to statistical analysis. all trials with timing and movement errors were removed. Force recording and EMG records of the first dorsal interosseus muscle were used to fractionate the interval between RS onset and peak force as schematically illustrated in fig. 1. For each trial. PRT, MRT, latency from movement onset to lower force limit transition (time to criterion force: TCF), and latency from lower force limit transition to peak force (time to peak force: TPF) were calculated. Great care was taken in the estimation of EMG onset and movement onset because it was known from a previous study that the transition from background EMG to response initiation is gradual rather than distinct (Haagh et al. 1983). The assumption of a distinct onset may, therefore. lead to an arbitrary definition of EMG onset. For instance. in the study performed by Nagasaki et al. (1983). EMG onset was defined as the point in time at which the amplitude of the full-wave rectified EMG exceeded a value of 50 pV. This can lead to an overestimation of the premotor RT because the actual time course of the surface EMG is not taken into account. Therefore, onset of EMG and movement were determined as follows. First, 2Rconfidence intervals of mean EMG values were
S.A. V.M. Hangh et al. / Response force and srmple RT
TARGET
21
FORCE RANGE I
FORCE
EMG ‘T
PRT
MAT
TCF
.TPF
Fig. 1. Schematic illustration of the fractionation of the response by means of EMG and force recordings. RS: reaction signal; PRT: premotor reaction time: MRT: motor reaction time; TCF: time to the lower limit of the criterion force range; TPF: time to peak force.
calculated based on 15 consecutive EMG samples prior to RS onset, i.e., the window encompassed 150 msec. This window was shifted forward, one sample at a time and new 2Sconfidence intervals were calculated. This procedure was repeated until an EMG sample was detected which (a) was larger than the upper confidence limit and (b) was the first sample of a continuous increase in EMG activity over at least seven samples. Then, the aforementioned procedure was applied to the force recording to detect the movement onset. The first force trace sample that was larger than the individual lower criterion force limit demarcated the point in time for TCF calculation. Peak force was simply determined by detecting the largest sample in the force trace for 1 set after RS onset. The entire procedure was repeated for each trial. Single-factor analyses of variance (ANOVAs) with experimental conditions as levels were carried out on individually averaged chronometric data, peak force values, and peak EMG values of the first dorsal interosseus muscle, as well as the coefficients of variation of these measures. Only significant F-ratios will be mentioned in the text. In addition, coefficients of correlation were calculated between the various components of the fractionated response time. All calculations were made with the BMDP statistical package on a DEC VAX 11/780 computer.
Results Chronometric data Overall means required response
per condition are shown in table 1. PRT was inversely related to force (F(2,22) = 5.06. p < 0.02). MRT was constant across condi-
28
S. A. v. M. Haagh er al. / Response /orce und .srmple R T
Table 1 Means of the various components of the fractionated total response time in milliseconds Means of the within-subject coefficients of variation are shown within parentheses. Premotor RT (PRT)
Motor RT (MRT)
Time to criterion force (TCF)
5R MVF
206.1 (0.19)
16.6 (0.74)
50.9 (0.40)
61.2 (0.25)
25% MVF
202.1 (0.19)
16.2 (0.68)
98.5 (0.26)
61.8 (0.41)
50% MVF
196.8 (0.17)
15.4 (0.62)
107.2 (0.20)
70.2 (0.34)
(n = 12).
Time to peak force (TPF)
tions, indicating that the interval between EMG onset and movement initiation was independent of force level. Once movement had begun, however, TCF increased as a function of the required force level (F(2.22) = 203.9, p < 0.001). The factor force also had a significant effect on TPF (F(2,22) = 3.48. p < 0.05).However, this effect was not proportional to produced force (see table 1). probably due to the fact that this dependent variable is strongly affected by the extent to which subjects exceeded the lower criterion force limit. Therefore, it is of little significance to this paper. The coefficients of variation of PRT. MRT, and TPF showed no significant variation across conditions, but variability of TCF decreased significantly with increasing peak force (F(2,22) = 20.47. p < 0.001) (see table 1). Calculation of within-subject correlation coefficients between the various fractionated response latencies as part of a multiple linear regression analysis revealed a slight negative linear relation between PRT and the other latency measures in all conditions. In two of the three conditions, TCF and TPF showed a small positive
Table 2 WIthin-subject total response
coefficients of correlation time (n = 12).
between
PRT 5% MVF
25% MVF
50% MVF
MRT TCF TPF
-0.23 -0.24 -0.14
MRT TCF TPF MRT TCF TPF
the various
components
MRT
of the fractionated
TCF
0.07 0.05
0.10
-0.29 - 0.21 -0.14
- 0.02 -0.01
0.37
-0.18 -0.18 - 0.22
0.09 - 0.04
0.30
S.A. V.M. Haagh et al. / Response force and simple RT
29
correlation. Within-subject correlation coefficients between total RT (PRT + MRT) and movement time (TCF + TPF) were also small: -0.24, - 0.23, and -0.25 in the 5410,10% and 50% MVF conditions, respectively. Numbers of movement errors, i.e., undershoots and overshoots, were computed for each condition. The respective percentages were 2.4% and 12.4% for the 5% MVF condition, 4.3% and 12.6% for the 25% MVF condition, and 2.6% and 1.4% for the 50% MVF condition. These results show that undershoots were most frequent in the middle force condition and that overshoots were almost absent in the high force condition. Force
and EMG
data
Average traces of force records of individual subjects, triggered at force onset, are shown in fig. 2A. As observed by others (e.g., Kamen 1983), rate of force development 578
FORCE LEVEL
299
f%MVF) 6 ,
[rjjz&I;;; f ..__.
..‘~...~.~._;;‘.
I
100
Z%MVF
MSEC
1-A , 1 10 MSEC
125 IA’
e
IRL+ 100
MSEC
Fig. 2. Average traces of force records of individual subjects (n = 12) for each condition (A) and average traces of the surface EMG of the first dorsal interosseus muscle for each condition (C). Beginning of force records is also shown on an extended time scale (B). From above to below, traces represent the 50%, 25% and 5% MVF conditions, respectively. Dashed lines indicate the target force levels. All traces are superimposed with force onset (arrow) as reference point on the time scale.
was faster with increase of exerted force. The duration of force development also increased with increasing peak force, as can be derived from table 1, by adding TCF and TPF. Actual peak forces in the three conditions were 6.7%. 29.9%, and 57.8% MVF (F(2.22) = 731.6, p < 0.001). The coefficient of variation of peak force decreased significantly with increase of peak force (F(2,22) = 43.38, p < 0.001). The latter result is in agreement with recent findings of Newell and Carlton (1985) with respect to the relationship between peak force and peak force variability. Only the surface EMG of the first dorsal interosseus muscle is depicted in fig. 2C because the time courses of the EMGs of wrist and finger extensor and flexor muscles were quite similar. though amplitudes were generally lower. A significant increase in EMG burst duration - i.e., the interval between EMG onset and peak EMG amplitude ~ with increase of peak force was found: respectively 59. 86, and 102 msec (F(2,22) = 71.21, p i 0.001). In addition. the coefficient of variation of peak EMG amplitude decreased significantly when force increased and was respectively 0.31. 0.12. and 0.08 (F(2,22) = 57.75, p < 0.001). Higher peak EMG amplitude was concomitant with higher peak force value (F(2,22) = 50.85. p < 0.001). although, as opposed to force, the increase of EMG amplitude from 25% to 50% MVF was smaller than the increase from 5% to 25% MVF.
Discussion
A definite result of the present study is the negative relation between PRT and exerted peak force. Furthermore, MRT remained constant across conditions. A corresponding result with respect to constancy of MRT was obtained by Brown and Cooke (1981) in a target aiming task. They found a constant epoch between onset of agonist EMG and movement onset, independent of the speed of the contraction, given a certain movement amplitude. Although a positive relationship between PRT and MRT was reported by Nagasaki et al. (1983) their results are hard to compare, as we have argued in the Method section. As a possible explanation for the decrease of PRT with increase of force, a shift in the trade-off function between speed and accuracy of the movement should be considered. The absolute range of tolerated force exertions increased with increase of force level which means that accuracy demands decreased. The relative tolerance range, however, did not increase. As our results show. proportion of undershoots did not differ widely between the conditions while proportion of overshoots was similar in the 5% and 25% MVF conditions but dramatically decreased in the 50% MVF condition. These results might be regarded as evidence against a trade-off shift towards speed. However, it might be objected that overshooting the 75% MVF level might have been
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extremely hard to achieve given the allowed total response time of 400 msec. Newell and Carlton (1985) observed that the time allowed for peak force to be generated determined the maximum peak force actually obtained. Our results corroborate their observation that movement time (TCF + TPF) increased with force level. Nevertheless, a second, more important argument against an interpretation in terms of a trade-off function shift can be derived from the constancy of the coefficient of variation of PRT across conditions, something which is not to be expected from a speed-accuracy point of view. In addition, the coefficient of variation of peak force decreased significantly when peak force increased, indicating that higher forces were exerted more consistently. The latter result is in line with the early data of Jenkins on force variability, recently reviewed by Newell et al. (1984). Unfortunately, an insufficient number of force levels investigated prevents us from adequately describing this relation. Furthermore, movement time was not explicitly controlled. Newell and Carlton (1985) view such a control as a prerequisite to a valid estimation of movement variability. Summarizing, we conclude that the speed-accuracy trade-off argument is not tenable to the PRT effect in the present experiment. The negative relation between PRT and exerted peak force is in agreement with the two-stage motor programming model. Such an interpretation is supported by the work of Kimm and Sutton (1973) who taught their subjects to respond with a single spike from one motor unit in a simple RT paradigm. It is well known that the rate of force development initially predominantly depends upon the number of motor units recruited and subsequently predominantly upon the firing frequency of the motor units (Freund 1983). Kimm and Sutton (1973) compared the single spike latency with the latency of a key release response - requiring a burst of EMG activity instead of a single spike _ and reported that, in the latter condition, RTs were significantly shorter (approximately 20 msec) than in the former. Similar results were obtained by Kosarov (1979) who trained subjects to respond with a single spike, a small train of spikes, or a burst of EMG in a blocked simple RT task. RT decreased significantly as a function of the number of motor units involved. Kimm and Sutton (1973) interpreted their results in terms of differences in task requirements. Activation of a single motor unit involves a very discrete muscular contraction while such a differentiated activation is not necessary for an overt movement. Therefore, a key release response might require less program loading
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time than activation of a single motor unit as Spijkers and Sanders (1984) predicted. Support for this hypothesis is provided by the fact that dispersion of single motor unit RTs was larger than dispersion of key release RTs, a result also found by Kosarov (1979). Although the two-stage programming model can accommodate the results of the present study, a simpler explanation can be given from a neurophysiological point of view. In general, the recruitment order within a motoneuron pool is fixed when contraction strength increases, starting with the smaller motoneurons, corresponding with slow-contracting muscle units of little force and adding larger motoneurons, corresponding with fast-contracting, forceful muscle units (for an overview, see Henneman and Mendell 1981). Milner-Brown et al. (1973) reported for the human first dorsal interosseus muscle that the number of additional muscle units recruited during a given force increment declines exponentially with increasing contraction force. Therefore, it is probable that in the present 5% MVF condition, small motoneurons were predominantly involved, and that in the 50% MVF condition almost the whole motoneuron pool was recruited. Indirect support for this assumption is provided by our finding that variability of TCF, as well as of peak force, decreased with increasing peak forces. According to an argument advanced by Newell et al. (1980: 55) variability of movement time is negatively related to the number of muscle units involved. The order of motoneuron recruitment is independent of the speed of contraction, but increase of contraction speed is concomitant with a decrease in recruitment threshold (e.g., Desmedt and Godaux 1977). This decrease is proportionally similar for a large range of motoneurons in the human first dorsal interosseus muscle (Desmedt and Godaux 1978). During very fast contractions, like were performed in the present study, the recruitment threshold becomes very low for all motoneurons, to the point that the entire motoneuron pool is almost simultaneously activated (Biidingen and Freund 1976). This is illustrated in fig. 2B which shows a more detailed comparison of the rate of force development at different criterion force levels. The much faster rise in the 25% and 50% MVF conditions reflects the immediate contribution of fast-contracting muscle units with high twitch tensions. The simultaneous activation of almost all involved motoneurons during fast contractions may be expected to result in variations in PRT when response force is varied. Small motoneurons have relatively slow-conducting axons, while larger motoneurons have relatively fast-
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conducting axons (Henneman and Mendell 1981). The diameter of alpha motoneuron axons in the human arm is known to vary between lo-18 pm, indicating a range in conduction velocity from 35-70 m/set. With a peripheral length of motor axons of approximately 90 cm, the conduction time of the fastest-conducting motor axons will be 12 msec less for the 50% MVF condition than for the 5% MVF condition. Therefore, recruitment order during fast contractions seems to be reversed when recorded at the level of the muscle units, that is, when recording EMG potentials (Freund 1983). Based on the aforementioned arguments, we suggest that in the present experiment, with its given force levels, the small but consistent PRT effect can, at least for the greater part, be explained by differences in conduction velocity of motor axons. In conclusion, the present results can be explained by means of the two-stage programming model. However, with the aforementioned interpretation in terms of peripheral mechanisms, and assuming that complete pre-programming has, indeed, taken place, a program loading stage does not need to be invoked to explain the negative relation between response force and PRT. Although most of the evidence points to a crucial role of peripheral mechanisms, that which is presented here is not conclusive.
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