Time Course and Magnitude of Movement-Related Gating of Tactile Detection in Humans. I. Importance of Stimulus Location

Stephan R. Williams1, 2, Jafar Shenasa1, 2, and C. Elaine Chapman1, 2, 3

1 Centre de Recherche en Sciences Neurologiques, 2 Département de Physiologie, and 3 École de Réadaptation, Faculté de Médecine, Université de Montréal, Montreal, Quebec H3C 3J7, Canada

    ABSTRACT
Abstract
Introduction
Methods
Results
Discussion
References

Williams, Stephan R., Jafar Shenasa, and C. Elaine Chapman. Time course and magnitude of movement-related gating of tactile detection in humans. I. Importance of stimulus location. J. Neurophysiol. 79: 947-963, 1998. The time course and spatial extent of movement-related suppression of the detection of weak electrical stimuli (intensity, 90% detected at rest) was determined in 118 experiments carried out in 47 human subjects. Subjects were trained to perform a rapid abduction of the right index finger (D2) in response to a visual cue. Stimulus timing was calculated relative to the onset of movement and the onset of electromyographic (EMG) activity. Electrical stimulation was delivered to 10 different sites on the body, including sites on the limb performing the movement (D2, D5, hand, forearm and arm) as well as several distant sites (contralateral arm, ipsilateral leg). Detection of stimuli applied to the moving digit diminished significantly and in a time-dependent manner, with the first significant decrease occurring 120 ms before movement onset and 70 ms before the onset of EMG activity. Movement-related and time-dependent effects were obtained at all stimulation sites on the homolateral arm as well as the adjacent trunk. A pronounced spatiotemporal gradient was observed: the magnitude of the movement-related decrease in detectability was greatest and earliest at sites closest to the moving finger and progressively weaker and later at more proximal sites. When stimuli were applied to the distant sites, only a small (~10%), non-time-dependent decrease was observed during movement trials. A simple model of perceptual performance adequately described the results, providing insight into the distribution of movement-related inhibitory controls within the CNS.

    INTRODUCTION
Abstract
Introduction
Methods
Results
Discussion
References

The CNS has a variety of mechanisms at its disposal that modulate the quantity and quality of the sensory information that it processes. One such mechanism, gain control, enhances or diminishes sensory feedback. Several forms of gain control are found in the somatosensory system, including direct controls over receptor sensitivity (fusimotor control of muscle spindle sensitivity) and controls over the transmission of somatosensory signals within the CNS. An example of the latter is the suppression or "gating" of the transmission of cutaneous signals seen in association with voluntary movement. Single-unit and evoked-potential studies have demonstrated that the transmission of cutaneous signals through the dorsal column-medial lemniscal pathway to primary somatosensory cortex is decreased during movement (e.g., Chapman et al. 1988; Ghez and Lenzi 1971; Rushton et al. 1981; see Chapman 1994 for a recent review). Movement-related gating also exerts powerful influences on perception. Thus the detection of near-threshold cutaneous stimuli is decreased during movement (Coquery et al. 1971; Dyhre-Poulsen 1978), and detection threshold is elevated correspondingly (Chapman et al. 1987; Post et al. 1994). Magnitude estimates of clearly supra threshold innocuous stimuli, including vibrotactile stimuli, also are diminished during movement, although relative differences are preserved and so discrimination thresholds are unchanged (Chapman et al. 1987; Milne et al. 1988; Post et al. 1994).

Knowledge of the timing of movement-related decreases in transmission and perception provides insight into the source of the gating influences. Modulation that precedes the onset of movement and electromyographic (EMG) activity generally is interpreted as evidence that central signals, related to the preparation and execution of the movement, play a role in the phenomenon (Chapman et al. 1988; Coulter 1974; Dyhre-Poulsen 1978; Ghez and Lenzi 1971; Jiang et al. 1990b). Peripheral feedback, generated during movement execution, also plays an important role in the modulation that follows movement onset (e.g., Chapman et al. 1988; Huttunen and Hömberg 1991; Jones et al. 1988). Estimates of the time of onset of gating influences from cortical somatosensory evoked-potential (SEP) studies and psychophysical studies vary widely. Some studies observed modulation 60-100 ms before the onset of EMG activity and so well before movement onset, whereas other studies reported modulation only after the onset of EMG and movement (Chapman et al. 1988; Cohen and Starr 1987; Coquery et al. 1971; Dyhre-Poulsen 1978; Jiang et al. 1990b). These different results may arise from a number of factors, including differences in the intensity of the stimulus, differences in the spatial relation between the stimulus and the movement, and differences in the motor tasks, including the movement studied (digit vs. elbow) as well as the associated movement kinematics (Chapman et al. 1988; Ghez and Pisa 1972; Rauch et al. 1985).

Insight into the mechanisms underlying movement-related decreases in transmission and perception also comes from studies of the modulation's spatial extent, which defines the distribution of the gating influences. There is limited evidence that proximity is an important factor in determining the magnitude of the gating influence on cortical SEPs in humans (Rushton et al. 1981; Tapia et al. 1987). In monkeys, on the other hand, the gating effects have been described as widespread and nonspecific (Jiang et al. 1990b). The latter contrasts with the topographically organized gating influences elicited by intracortical microstimulation applied to motor cortex (area 4), a potential source of central gating signals: Jiang et al. (1990a) reported that these influences show a proximal to distal gradient whereby the modulation is directed toward cutaneous inputs from the skin either overlying or distal to the motor output. Several psychophysical studies have examined the spatial extent of the gating influences on perception (Coquery et al. 1971; Post et al. 1994; Schmidt et al. 1990), and all reported that proximity between the site of stimulation and the movement was an important factor with sites closer to the movement showing a greater modulation. In contrast to the results of Jiang et al. (1990a), however, Coquery et al. (1971) reported that magnitude estimates were decreased at sites located both distal and also proximal to the site of movement. The latter results were confounded potentially by differences in the associated movements because subjects were required to make a variety of movements (digits, wrist, elbow, and shoulder). Furthermore, potential differences in the time course of the gating influences at the different sites may have contributed to the results.

Differences in stimulus intensity, stimulus location, and the motor task probably account for much of the variation seen in the literature. Clearly further experiments are warranted to define more precisely the influence of each of these variables. The purpose of this study was to examine in detail the importance of location on the time course and spatial extent of movement-related decreases in the ability to perceive weak, near-threshold cutaneous stimuli. In this study, the time course was established both in relation to the onset of movement and the onset of EMG activity for a discrete and relatively invariant motor task, abduction of the index finger (D2). A single clearly defined stimulus intensity was used to test perceptual performance at several stimulation sites both close and distant to the body part in motion. The results presented here form part of a larger investigation aimed at quantifying the influence of the various factors that may account for previously reported variations in the distribution, timing, and amplitude of movement-related decreases in tactile perception. A preliminary account of these results has been published (Williams and Chapman 1996).

    METHODS
Abstract
Introduction
Methods
Results
Discussion
References

Subjects

A total of 47 naive, paid volunteers (25 males and 22 females, ages 15-30 yr) participated in this study. Four subjects were left handed for writing and 43 were right handed. The experimental protocol was approved by the institutional ethics committee, and all subjects or their legal guardian gave their informed consent before participating in the study. Data from each subject were gathered in one or two sessions lasting 1-3 h each. At the beginning of each session, subjects received verbal instructions about the motor and perceptual tasks that they were to perform. This was followed by a small block of practice trials. In brief, the motor task consisted of an active abduction of the right index finger (D2), whereas the perceptual task consisted of determining whether or not a weak near-threshold electrical stimulus had been delivered to the skin. One stimulation site was investigated in each experiment, and two to three different sites were tested in each experimental session. Altogether, 118 experiments were performed, using 10 different stimulation sites mainly located on the right arm.

Motor task

A simple reaction time (RT) task was employed, whereby subjects made a rapid abduction of the right D2 as soon as possible after the appearance of a visual "GO" cue (illumination of a 3 × 3 array of LEDs placed at eye level, 1 m in front of the subject). As shown in Fig. 1A, subjects were seated in a chair beside a small table on which the right arm rested. The index finger rested on a small pivoting plate (1.8 × 10 cm) the base of which was aligned with the axis of rotation of the D2 metacarpophalangeal joint (Fig. 1B). The subjects were asked to relax with D2 in a neutral position. An oscilloscope was used to display D2 position (Fig. 1A) along with two reference lines corresponding to the starting (neutral) position and to the minimal required amplitude of movement (15°). No maximal movement amplitude was specified, but subjects were instructed to avoid hitting the stop situated 45° from the start position. Subjects also were requested to limit muscle contraction to the relevant agonist muscle (1st dorsal interosseous, 1st DI) during the initial phase of the movement to the extent that this was possible.


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FIG. 1. A: experimental set-up showing the subject's position facing the visual cue and the oscilloscope that displayed movement-related information. B: close-up of hand showing the pivoting plate on which the right index finger rested (here in initial rest position). Shown also are the positions of the stimulating electrodes applied to the index finger and the electromyographic (EMG) recording electrodes over the 1st dorsal interosseous muscle. C: time course of events in movement + stimulation trials. Stimuli were applied at one of 5 (solid lines) or 9 delays, encompassing the time of EMG onset and the reaction time (RT).

Perceptual task

Subjects were asked to report whether or not they detected the occurrence of weak electrical stimuli delivered to a site on the skin (see further) under two experimental conditions: at rest and while performing the motor task. No information regarding the proportion of trials with and without a stimulus was given to the subjects. No feedback was given with regard to the accuracy of the subject's perceptual judgements. The stimulus consisted of a single 2-ms square wave pulse generated by a Grass S88 stimulator and delivered via a SIU7 constant current photoelectric stimulation isolation unit. The stimulus was applied to the skin via surface electrodes (7 mm diam) spaced 30 mm apart, and in all cases only a localized sensation was produced. Before applying the electrodes, skin resistance was minimized and electrode adhesion maximized by vigorous cleansing of the area immediately beneath the electrodes with 70% alcohol. For experiments involving stimulation of a digit, the electrodes were not in contact with the supporting surface but were recessed in a specially designed cavity in the foam padding. At the beginning of each experiment (subject at rest), a modified sequential tracking procedure using six observations per stimulus intensity tested (as described by Wetherhill and Levitt 1965) was used to find the stimulus intensity level at which ~90% of the stimuli were detected. This intensity (range 0.18-1.32 mA) then was used throughout the experiment.

Stimulation sites

Ten stimulation sites were employed (Fig. 2). Six sites were situated on the arm ipsilateral to the moving digit: the glabrous skin of the middle and distal phalanges of digits 2 (iD2) and 5 (iD5), the dorsum of the hand (iHA), the mid-forearm (iFA), the lower arm (iA), and the shoulder (iSH). The remaining sites were one on the ipsilateral pectoral girdle just below the sternocleidomastoid joint (iPG), two sites on the contralateral arm (cSH and cD2), and one on the ipsilateral thigh (iTH). Three subjects were tested at 8 stimulation sites, 6 at 7 sites, 1 at 6 sites, 5 at 3 sites, and 31 at 1 site (iD2). Those subjects tested at three or fewer sites participated in other experiments, not reported in this paper, which will form the basis of other publications. The order of testing for the different stimulation sites in each subject was randomly determined. The exact number of subjects tested at each site is given in Fig. 2.


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FIG. 2. Stimulation sites tested relative to the moving digit (iD2). Distance between each stimulation site and iD2 as a proportion of subject height is shown in parentheses. Number of subjects tested at each site also is indicated. A, arm; c, contralateral; D2, digit 2; D5, digit 5; HA, hand; i, ipsilateral; PG, pectoral girdle; SH, shoulder; TH, thigh.

The distance between the various stimulation sites and the body part in motion (iD2) also is reported in Fig. 2. Distances are shown as a proportion of subject height and were estimated to the nearest 0.025 using standard anthropometric tables (Contini 1972; NASA 1978). Distances were estimated from the metacarpophalangeal joint of iD2; iD2 itself was assigned a distance of 0, being the body part in motion.

Data collection

The data acquisition and task were under the control of a PDP 11/73 minicomputer. Each trial was initiated by the experimenter and lasted for 2 s. Three types of trials were presented. In the majority of trials (70%), subjects were invited to move and a stimulus was presented (movement + stimulation); these trials were used to gather data on the effects of movement on the perception of the test stimulus. In 20% of the trials, subjects were asked not to move during the trial, and the stimulus was applied at rest (rest + stimulation); these trials monitored the stability of perceptual performance at rest. Finally, catch trials (no stimulus) represented 10% of the total trials and were divided between the movement and no-movement trials; these trials evaluated each subject's rate of false positive responses. Subjects were not aware of the proportion of trials in which a stimulus was presented. Subjects were instructed verbally before the onset of each trial whether to move or not; no information was given as to whether or not there would be a stimulus, and the experimenter could not be seen by the subjects. Figure 1C schematizes the events occurring during a movement + stimulation trial. Data collection was initiated at time 0. The light signaling the subject to move was illuminated 500 ms after the beginning of the trial, allowing a period during which any spontaneous movement or EMG activity could be observed. The stimulus was given at one of five or nine delays relative to the onset of the GO cue (see further). At the end of each trial, subjects indicated verbally whether or not they had perceived a stimulus, and their response was entered into the computer by the experimenter and stored with the trial. The intertrial interval varied from 1 to 10 s. Subjects were observed carefully by the experimenter during each trial. Any trial during which the subject produced movements unrelated to the motor task, as well as any trial after which the subjects reported inattention, discomfort, or lack of readiness was rejected and repeated later in the session.

To concentrate sampling around the onset of movement, each subject's mean RT, i.e., the mean difference between the time at which the GO signal was presented and the time of movement onset, was estimated from a series of practice trials performed at the beginning of the session. Using this value, five delays relative to the GO cue were calculated: RT - 120 ms, RT - 80 ms, RT - 40 ms, RT, and RT + 40 ms. Four additional delays (RT - 160 ms, RT + 80 ms, RT + 120 ms, and RT + 160 ms) were used in 10 experiments at the iD2 site. Natural trial-to-trial variations in RT, combined with the use of multiple stimulus presentation delays, resulted in the collection of an adequate sample of perceptual ability during a 200-ms time interval, which included EMG onset and movement onset. Because of variation in RT, trial-by-trial delays between the onset of peripheral movement-related activity and stimulus delivery were not known to either the subject or the experimenter at the time of the experiment. Data were collected in blocks of >= 22 trials, one stimulus delay being tested in each block, with the order of delay testing being varied between experiments. Within a block, >= 15 movement + stimulation trials, 5 rest + stimulation trials, and 2 catch trials were performed. The different types of trials were intermixed randomly, the order of presentation varying from block to block. Thus at each stimulation site, a minimum of 110 trials were recorded.

Angular displacement of D2 was measured using a potentiometer integrated into the plate that supported the finger. The EMG activity of 1st DI was recorded via 4-mm-diam surface electrodes placed 15 mm apart (center to center) on the skin overlying the muscle. In a few subjects, the EMG activity of forearm extensors (n = 3), elbow extensors (triceps brachii, n = 6), and the muscles of the hypothenar eminence (n = 1) also was recorded to evaluate the extent of coactivation present during the motor task. EMG activity was amplified and filtered with a band-pass width of 100-3,000 Hz, then full wave rectified and integrated during 5 ms. Both D2 position and EMG activity were digitized at 200 Hz and stored for later off-line analysis.

Data analysis

For each movement trial, the onset of EMG was determined visually. Several timing values were calculated off-line automatically, including RT (determined by an algorithm that found the first of 5 consecutive position samples that changed in the same direction), the lead time between 1st DI EMG onset and movement onset, and movement duration. Kinematic parameters also were calculated, including movement amplitude, peak velocity (computed by 3-point numerical differentiation and appropriate digital filtering of the displacement trace), and peak acceleration. Approximately 1% of the trials were discarded at this stage, usually because EMG activity was observed in the 500-ms interval before the GO signal. The presence of a causal relationship between EMG and movement was assessed by performing linear regression analyses between EMG onset and movement onset. The rationale for this test is that EMG activity responsible for the movement should not only precede the onset of movement but also show a high degree of correlation with RT with a slope approaching 1 (see e.g., Chapman et al. 1986). The possibility of significant intersite differences in the temporal and kinematic parameters was evaluated by calculating individual subject averages for each parameter and then comparing across the stimulation sites using one-way analyses of variance (ANOVA, level of significance P < 0.05).

Data from different sites were gathered from different, but not completely independent, groups of subjects. To determine whether the data from different sites could be treated as independent, the effects of intersubject differences in performance on the interpretation of the data were quantified. For this, trials from a given subject and site were grouped into 40-ms bins relative to either movement or EMG onset, and the proportion of stimuli perceived was calculated for each bin. Analysis of covariance (ANCOVA) examined the relative importance of site, timing, and subject on perceptual performance. This analysis showed that <5% of the total variation in the data could be explained by intersubject differences in performance, whether or not the significant effects of both timing and site were taken into account. As such, the data from different sites were treated as independent in the ensuing analyses.

All trials from a given stimulation site were pooled for further analyses. The proportion of stimuli that were perceived while performing each trial type was calculated for each stimulation site. ANOVAs were used to examine whether or not the stimulation site influenced perceptual performance for each type of trial. A Fischer one-tailed exact probability test for a 2 × 2 contingency table (level of significance, P < 0.01) was used to compare the average proportion of stimuli perceived at rest to the average proportion of stimuli perceived during trials involving movement. The latter test was used in all subsequent proportion comparisons.

Because performance during movement was to be compared with performance at rest, it was important that perceptual performance during immobile trials be constant throughout the experimental sessions. To verify this, the first and last 20% of immobile trials performed at each stimulation site were grouped, and performance was compared.

To study the time course of any variation in perception during movement, trials occurring within 300 ms of movement or EMG onset were grouped into 20-ms bins relative to either movement or EMG onset at each stimulation site. The proportion of stimuli perceived was calculated for each bin along with the 95% confidence interval. These proportions then were compared with the proportion of stimuli perceived during the corresponding immobile trials. To provide an adequate description of the temporal evolution of perceptual abilities relative to movement and EMG onset, linear and logistic functions (APPENDIX A) were fitted to the pooled data from each stimulation site (Matlab, version 4.2, The Mathworks). The fitting algorithm attempted to minimize total squared error between the descriptive function and the data points. The goodness of fit of the linear and logistic descriptions was evaluated by comparing the total squared error between the model and actual data to the appropriate chi 2 distribution [df = number of points that defined perceptual performance at the site (number of parameters in the fitting equation + 1)]. The best fitting model (linear or logistic) was retained if it provided an adequate description of the data, i.e., if the probability of obtaining the observed amount of total squared error was >0.05. If a linear model was retained, the presence of a slope significantly different from zero was evaluated using a t-test. If a logistic descriptor was retained, four parameters then were determined: the maximum predicted perceptual performance, the minimum predicted perceptual performance, the peak slope (measure of the peak rate of decrease in perceptual performance), and the timing of the peak slope (the time at which perceptual performance decreased most rapidly). The effects of distance on these parameters were evaluated using adjusted correlation coefficients and F tests.

Bias

Our experimental approach was designed to minimize the duration of each experiment, so minimizing drift in performance and fatigue (recognizing that there was a motor component to the task), and to maximize the collection of data by presenting a relatively high proportion of trials with a stimulus. Positive bias was monitored continuously throughout each experiment using catch trials (Green and Swets 1988). The existence of systematic and significant positive or negative biases induced by the method or the experimenter was further evaluated in experiments that compared detection performance obtained with the main experimental method to detection performance obtained using a bias-free two alternative forced-choice (2AFC) procedure (3 subjects: 2 females, 1 male; 2 of 3 right handed). Stimuli were delivered to the iD2 site. Both experimental methods were tested in a single session, ensuring that stimulating conditions were similar. The main experimental method was as described above. For the 2AFC procedure, in each "trial," the GO cue was presented twice, i.e., there were two observation periods per trial, separated by a delay of ~1 s. Observation period duration, stimulus presentation delays, etc., remained the same. The stimulus was assigned randomly to one of the GO cue presentations in each trial: 50% of the trials contained the stimulus in the first interval and 50% in the second interval. At the end of each trial, the subject was asked to report in which of two intervals a stimulus was presented. Immobile trials were again interspersed between the movement trials to provide for a continuous monitoring of performance at rest.

The results obtained using both procedures were analyzed as described above, and are shown in Fig. 3. With both methods, detection performance declined rapidly ~40-60 ms before movement onset or 10-20 ms before EMG onset. During movement, performance was close to chance using the 2AFC method (0.52-0.53) and complete nondetection using the main method (0-0.01). To compare the results, the detection performance data obtained using the main experimental procedure were transformed in the following manner: p'(i) = [p(i) + 1]/2, where p(i) = the proportion of stimuli perceived in a given time interval, and a logistic function was fitted to the resulting data. No significant differences were observed when this logistic function was compared with that describing the 2AFC data (P > 0.05, Kolmogorov-Smirnov statistic), making it unlikely that experimenter- or procedure-induced biases played a significant role in the results obtained with the main experimental procedure.


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FIG. 3. A-D: effects of iD2 abduction on the detection of stimuli applied to the moving digit in 3 subjects using a 2 alternative forced-choice (2AFC) version of the experiment (A and B) and using the main experimental procedure (C and D). Perceptual performance over time is plotted relative to movement onset (A and C) and the onset of 1st DI EMG (B and D). Error bars represent the 95% confidence intervals. The shaded area shows the 95% confidence interval for perceptual performance at rest. For all bins (20 ms), bullet , perceptual performance during movement + stimulation trials was significantly lower than that observed at rest (P < 0.01); open circle , no change.

    RESULTS
Abstract
Introduction
Methods
Results
Discussion
References

Performance of the movement task

A total of 118 experiments were performed in 47 subjects (Fig. 2). Figure 4 shows an example of the movement traces and EMG records from one subject. First dorsal interosseus EMG activity, the principal agonist, consistently preceded movement onset by an average of 27 ms in this example (Fig. 4, A and B) and showed a strong linear correlation with movement onset (Fig. 4C). Cocontraction was evident in abductor digiti minimi (Fig. 4, A, B, and D), but the activity was weaker (note the change in scale), more irregular, and always followed the onset of 1st DI EMG activity (average delay, 10 ms). At the forearm extensor site, EMG activity was weak, frequently absent, and followed movement onset. In 118 experiments, the mean correlation coefficient between 1st DI and movement onset was 0.96 ± 0.02 (mean ± SE) and the mean slope of the linear regression line was 0.95 ± 0.04. First DI EMG activity led movement onset by 50 ± 14 ms (Table 1).


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FIG. 4. A: sample movement and EMG traces for 1st dorsal interosseous (1st DI), abductor digiti minimi, and the forearm extensors aligned on the onset of the GO cue. B: averaged movement and EMG traces for the same muscles, aligned on the onset of movement (same scales as A). C and D: scatter plots of EMG onset as a function of RT for 1st DI (SE of the residual, 1.0 ms; regression constants: m = 0.99, b = -21 ms) (C) and abductor digiti minimi (SE of the residual, 3.5 ms; regression constants: m = 1.10, b = -51 ms; D). Linear regression lines are shown along with the slope (m) and the correlation coefficient (r).

 
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TABLE 1. Temporal and kinematic parameters describing the performance of the motor task, iD2 abduction and the results of ANOVAs comparing values across 10 stimulation sites

Before examining site-related differences in perceptual performance, the possibility that the movements themselves might have varied as a function of the site of stimulation was evaluated using one-way ANOVAs applied to the various temporal and kinematic parameters (Table 1). All but one measure, mean peak amplitude, showed no significant change across the 10 stimulation sites. With regard to movement amplitude, post hoc Scheffé analyses showed that only a few intersite comparisons were significantly different [iD2 and iD5 (smallest movement amplitudes) vs. cD2, cSH, and iSH (largest movement amplitudes)]. The effect of this difference on the results was minimal because the sampling period did not include the time at which movement reached its peak amplitude.

Finally, regression analyses showed that stimulus delay had no effect on RT. The average correlation coefficient between stimulus delay and RT at all sites was close to zero (0.005).

Performance of the perceptual task

Table 2 summarizes the global performance of all subjects in the three trial types. Overall, pooled data showed that subjects perceived 94% of the stimuli presented at rest. A one-way ANOVA failed to discern any significant difference in pooled perceptual performance at rest across the experimental test sites, thus providing a constant baseline against which performance during movement could be evaluated. Of 1,479 catch trials (pooled data), only 12 false positive responses were noted (0.8%), indicating that subjects used a very conservative response strategy throughout the series of experiments. As detailed in the legend for Table 2, no stimulation site was associated with significantly more false positives than any other. Pooled data showed that subjects perceived 58% of the stimuli presented during movement + stimulation trials, and a one-way ANOVA (Table 2) showed that there was significant intersite variability in pooled perceptual performance for these trials. Inspection of Table 2 reveals that sites closer to the body part in motion, iD2, showed greater reductions in the proportion of stimuli perceived during movement than did those that were more distant from the movement site. Comparisons between performance in the rest + stimulation trials and the movement + stimulation trials showed that significantly fewer stimuli were perceived during movement at all 10 stimulation sites (P < 0.001, Fischer exact tests for a 2 × 2 contingency table).

 
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TABLE 2. Proportion of stimuli detected in the three trial types as a function of the site of stimulation

Variation over time of perceptual performance at rest

For each stimulation site, perceptual performance in the first 20% of immobile trials was compared with perceptual performance in the last 20% of immobile trials. No significant differences were observed at any of the sites (P > 0.01, Fischer exact probability tests). For data from all sites pooled together, the proportion of stimuli perceived in the first 20% of immobile trials was 0.95, whereas performance in the last 20% was 0.93.

Time-dependent change in the detection of stimuli applied to the moving digit (iD2)

Figure 5 shows that the effects of iD2 movement on the ability of 41 subjects to detect stimuli applied to the moving digit were not uniform over time. Although modest but significant decreases in the proportion of stimuli perceived were observed <= 200 ms before the onset of movement (Fig. 5A), performance declined precipitously beginning 60-80 ms before movement onset so that practically no stimuli were perceived after the onset of movement. A logistic function was found to best fit the data. A number of parameters were calculated from the logistic function (see METHODS), and these are detailed in Fig. 5A. In particular, the time of the peak decrease in perceptual performance preceded movement onset by 50 ms.


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FIG. 5. A and B: effects of iD2 abduction on the detection of stimuli applied to the moving digit in 41 subjects. Perceptual performance over time is plotted relative to movement onset (A) and the onset of 1st DI EMG (B). Plotted as in Fig. 3.

When the same data were replotted in relation to 1st DI EMG onset (Fig. 5B), a similar pattern was observed, but the peak decrease in perceptual performance now occurred 8 ms before EMG onset, in effect coinciding with the onset of agonist EMG given the temporal resolution of the analysis (20-ms bins). The other parameters of the logistic function were essentially the same. Thus the major change was an ~40- to 50-ms shift in the data points, corresponding to the lead time between EMG onset and movement onset. Given the similarity in the results, perceptual performance is only plotted against the onset of 1st DI EMG for the nine other stimulation sites tested in this study.

Effects of changing the site of stimulation on the movement-related decrease in tactile detection

Figure 6 summarizes the results obtained at the six other stimulation sites located on, or adjacent to, the ipsilateral arm, in increasing order of distance from the moving digit (Fig. 6, A-F). All six sites showed time-dependent modifications in perceptual performance that were best described by logistic functions. Two major observations were made. First, the depth of modulation of tactile detection, reflected in logistic function minima, lessened as the distance between the stimulation site and the site of movement increased. Second, the timing of the peak decrease in perceptual performance shifted as distance increased, from just around EMG onset for the sites immediately adjacent to iD2 (Fig. 6, A-C) to well after EMG onset for the sites located on the proximal arm and adjacent trunk (Fig. 6, D-F).


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FIG. 6. A-F: effects of iD2 abduction on perceptual performance over time for the 6 ipsilateral limb stimulation sites. Data plotted relative to EMG onset as in Fig. 5B. At each stimulation site, there was a significant, time-dependent reduction in the proportion of stimuli perceived during movement trials (bullet : P < 0.01) as compared with at rest. As distance increased, peak reductions occurred later and the minimum proportion of stimuli perceived increased.

To quantify the effect of distance, logistic function parameters from the seven stimulation sites closest to the body part in motion were plotted as a function of distance from the body part in motion (Fig. 7, A-D). Site-dependent trends were described using the best-fit linear or logistic functions and evaluated using adjusted correlation coefficients (see legend, Fig. 7). A strong positive correlation between the timing of the peak decrease in perceptual performance and distance from the site of movement was observed (Fig. 7A). A strong positive correlation between the minimum predicted perceptual performance and distance also was obtained (Fig. 7B). In contrast, the peak slope and maximum predicted perceptual performance values did not show significant trends with increasing distance (Fig. 7, C and D).


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FIG. 7. A-D: logistic equation parameters plotted as a function of distance (proportion of body height) from the site of movement, iD2, for the 7 closest stimulation sites, all of which showed a time-dependent decease in perceptual performance. Both the timing of peak decreases in perceptual performance (A, ±10 ms) and the minimum predicted perceptual performance (B) showed strong positive correlations with distance. Maximum predicted perceptual performance varied very little with distance (D) and peak slope varied irregularly (C). R2A, coefficient of determination adjusted for the number of parameters in the fitted equation.

A different pattern of perceptual modulation was observed at the three more distant sites, cD2, cSH, and iTH (Fig. 8, A-C). Even though overall performace during movement was decreased significantly with regard to performance at rest (Table 2) at each of these sites, no sustained decrease in perceptual performance was observed at any of these sites when the data were placed into 20-ms bins. Moreover, linear equations with slopes not significantly different from zero (P > 0.05) provided the best description of the data, indicating that there was no time-dependent change in performance. An ANCOVA showed that the site variable did not explain a significant portion of the variation present in the data from these sites (F test, P = 0.30). These data therefore were combined into a single "Distant" data set (Fig. 8D, 21 subjects). A slight but significant and sustained decrease in perceptual performance, consistent with the small overall reduction in perceptual performance at these sites (Table 2), now was observed. A linear equation with a slope of 0 and a y intercept of 0.85 (as compared with 0.96 at rest) provided the best description of the Distant data set. These findings suggested that there was a relatively small and non-time-dependent decrease in perceptual performance at these sites.


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FIG. 8. A-C: effects of iD2 abduction on perceptual performance over time for the 3 most distant stimulation sites. At each site, performance was best described by a linear function with a slope not significantly different from zero (P > 0.05). D: data were pooled to generate a single "Distant" data set. Plotted as in Fig. 5B.

The non-time-dependent decrease in perceptual performance observed at the Distant sites also may have been present at the sites closer to the moving digit. ANCOVAs performed on the data from each site showed that the effect of timing on performance only became significant (P < 0.05) when data from bins later than -70 ms were included in the analyses. The effect of site on performance only became significant (P < 0.05) when data from bins later than -50 ms were included in the analyses. The data from the three earliest bins at each site were pooled, and significant differences with perceptual performance at rest were seen (P < 0.05) at all sites but iSH (P = 0.09). Performance observed over the initial three bins (60 ms) for the seven locations closest to iD2 was not significantly different from perceptual performance during the movement + stimulation trials at the Distant sites (P > 0.05, Fischer exact probability test). All of these results suggest that site- and timing-independent modulation was present at all sites, along with superimposed time- and location-dependent modulation at the seven closest sites. To provide a precise estimate of the time of onset of the time- and location-dependent effect at each of the seven locations closest to iD2, performance in each time bin at each of these sites was compared with perceptual performance in the same time bin for the Distant data set (P < 0.05). The results are summarized in Fig. 9. The earliest sustained decrease (>3 consecutive bins) was at iD2 where performance was significantly decreased beginning in the bin centered 70 ms before EMG onset. The latest decrease was seen at iPG, 50 ms after EMG onset. These data were best described by a linear function with a positive slope significantly different from zero (P < 0.05), indicating that the time of onset of perceptual suppression increased significantly as the distance between the stimulation site and the moving digit (iD2) increased.


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FIG. 9. Time of onset of the 1st significant time-dependent decrease in perceptual performance during movement trials (20-ms bins), measured relative to 1st DI EMG onset, as a function of the distance (proportion of body height) from the site of movement, iD2. See text for further description.

On the basis of the results of the preceding analyses, a model of perceptual performance during the motor task that incorporated the importance of stimulus timing and distance between the stimulation site and the body part in motion was created (Fig. 10, APPENDIX B). Data from the Distant sites were assigned a distance that corresponded to the average of the distances for each of the three sites (0.875). The perceptual data during the movement + stimulation trials then were used to define a surface, presented in Fig. 10A. This representation permitted a visualization of modifications in perceptual performance at all locations at any given time. A model surface (Eq. B5, APPENDIX B) then was fitted to the surface created by the perceptual data (Fig. 10B). The total squared error between the surface described by the perceptual data and the surface described by the model was 0.31, and the peak squared error was <0.03 (Fig. 10C). The maximum predicted perceptual performance for the model surface was 0.86. The minimum predicted perceptual performance was 0, although it increased sharply as distance increased; performance was constant at 0.86 at the Distant site. The timing of the peak decrease in performance varied with distance, increasing >85 ms from the iD2 stimulation site to the iPG site.


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FIG. 10. A-C: surfaces showing time and location dependence of perceptual performance. A: pooled performance data during movement trials (z axis) plotted as a function of time (x axis), and distance (as a proportion of body height) between the moving digit and the site of stimulation (y axis). B: best-fit model surface for the data shown in A. Model surface was not significantly different from the actual performance data (P > 0.05). Model parameters are described in the text. C: contour map of the squared error between the surfaces plotted in A and B.

Relationship between movement parameters and perceptual performance

It has been reported that movement-related gating is a function of the kinematics of the movement, with faster movements producing larger gating effects (Angel and Malenka 1982; Chapman et al. 1988, 1996; Rauch et al. 1985). With this in mind, for each of the seven stimulation sites that showed a time-dependent decrease in the proportion of stimuli perceived, movement + stimulation trials were examined to see if modifications in perceptual performance could be related to variations in kinematic parameters (peak amplitude, peak velocity, peak acceleration). Two different analyses were performed. First, the entire data set was divided into two groups: trials in which stimulation was applied before the onset of EMG and trials in which stimulation was applied after the onset of EMG. For each group, the kinematic parameters were compared across trials in which the stimulus was, or was not, perceived (t-tests). No significant differences were found. Second, the analysis was repeated, this time using only trials in which a stimuli was delivered within 30 ms of the time of the peak decrease in perceptual performance. In effect, this served to minimize the confounding effect of the time-dependent variation in detection previously described by concentrating on the time period where changes in detection were occurring. As shown in Fig. 11, significant differences were now obtained (filled symbols), especially at the stimulation sites closest to the moving digit, iD2. At these sites, the kinematic parameters were consistently, and usually significantly, smaller when the stimulus was perceived as compared with when the stimulus was not perceived. Sites further away showed more variability in their kinematic relationships.


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FIG. 11. A-C: comparison of kinematic parameters during movement + stimulation trials at the 7 sites showing a time-dependent decrease in detection, as a function of whether the stimulus was perceived (circles) or not perceived (diamonds). Analysis was restricted to those trials in which the stimulus was delivered within 30 ms of the time of peak decrease in perceptual performance. Significant t-test results (P < 0.05) are shown as filled symbols (nonsignificant, open symbols). Kinematic parameters were often significantly smaller in those trials where the stimulus was perceived than in those trials where the stimulus was not perceived. Peak velocity (B) was more frequently a significant factor (5 of 7 sites) than peak amplitude (A) or peak acceleration (C).

    DISCUSSION
Abstract
Introduction
Methods
Results
Discussion
References

The results of the present study have shown that the movement-related decrease in detection of near-threshold cutaneous stimuli can precede movement onset and the onset of EMG activity. In addition, both the time course and amplitude of the modulation were dependent on the distance between the stimulation site and the body part in motion.

Methodological considerations

Electrical stimulation was used in this study for the following reasons. It had been shown previously that detection thresholds for electrical stimuli the parameters of which were identical to those used in this study are increased during movement (Chapman et al. 1987). In addition, electrical stimulation represented a reliable means of providing stimuli of identical duration and detectability to different body parts. The stimulating electrodes were placed at sites where stimulation affected mainly cutaneous afferents, although the electrodes on the finger sites also may have stimulated articular afferents traveling in the digital nerves. Subjects reported that the electrical stimuli did not feel particularly unnatural, just "extremely weak" at all stimulation sites. By calibrating stimulus intensity relative to a given detection level (~90% detected), baseline detection performance at rest was identical from site to site and subject to subject. This considerably facilitated intersite comparisons and permitted the pooling of data from multiple subjects. Finally, the inclusion of two contralateral sites identical to the ipsilateral sites made it possible to ensure that the observed distance-related effects could be distinguished from possible differences in the psychometric function at each stimulation site.

The movement performed in this study, abduction of the index finger, was chosen because it has only one major agonist (1st DI). Other intrinsic and extrinsic hand muscles showed relatively little co-contraction, and their activity followed 1st DI contraction (Fig. 4, A and B). First DI EMG activity thus represented the earliest peripheral response to the motor command, simplifying both data analysis and interpretation of the results.

Practice and fatigue effects did not appear to play a significant role on perceptual performance in these experiments. Perceptual performance at rest did not change between the beginning and the end of each experiment.

Experimenter- and method-induced biases do not appear to have played an important role in the results obtained in this study. In test subjects, the same results were obtained using a bias-free experimental strategy (Fig. 3). Moreover, the experimental design minimized experimenter-subject interaction and did not favor particular response strategies; also no feedback was given to the subjects on their performance. Subject strategy in the absence of feedback was almost optimal in terms of maximizing signal detection while minimizing false positives. The rate of false positive responses was always extremely low, a good indication that positive bias was not a significant factor in the experimental results. Negative bias at rest was also extremely low. With 94% of stimuli perceived at rest and a false positive rate of 1%, the area under a receiver operating characteristic curve, which includes this point, a simple measure of the detectability of the stimuli (Green and Swets 1988), was >= 0.965 and at most 0.995. Maximum negative bias at rest was therefore between 0.025 and 0.055.

During movement + stimulation trials, estimates of maximum perceptual performance at the closer stimulation sites (Figs. 7D and 10) as well as performance at the distant sites (Fig. 8) were 8-10% lower than performance at rest. This observation may reflect an increase in negative bias during movement trials, although other factors may also have contributed (see further). The time-dependent decreases in performance are unlikely to be the result of an overconservative response strategy that varied over time because subjects showed the same time-dependent decrease when a bias-free 2AFC procedure was used. The results are consistently explained only by a time- and distance-dependent decrease in the detectability of the stimuli, an explanation that is entirely compatible with previous results from this laboratory and others.

Distribution of non-time-dependent decreases in tactile detection

The three distant sites showed no time-dependent decrease in perceptual performance, but rather a constant, ~10%, decrease. Chapman et al. (1987) had seen small elevations in detection threshold for sites contralateral to the movement, but previous experiments using suprathreshold stimuli showed no significant change in either perception (Chapman et al. 1987; Milne et al. 1988) or cortical SEPs (Cohen and Starr 1987; Rushton et al. 1981) when the stimuli were delivered to a limb other than the one producing the movement. Analyses indicated that the non-time-dependentdecrease was present at all stimulation sites and that the time-dependent decreases were superimposed on this. As explained above, an increase in negative bias could have produced this sort of result; the low false positive rate at rest makes it impossible to exclude this hypothesis. On the other hand, similar reductions were observed in test experiments using a bias-free experimental procedure. Previous studies have shown that spatial and cross-modal shifts in attention can modify tactile detection (Butter et al. 1989; Meyer et al. 1963; Post and Chapman 1991). Given that the subjects had to divide their attention between the motor and perceptual tasks, it is suggested that attentional influences might have been responsible for the non-time-dependent decrease in performance.

Spatiotemporal characteristics of decreases in tactile detection

All sites on the moving limb (including the adjacent trunk, iPG) showed time-dependent reductions in the proportion of stimuli perceived. At the four sites closest to the moving digit, these reductions began before EMG onset (Fig. 9). The timing of these reductions is in agreement with the earliest modulation reported in previous psychophysical investigations (Coquery et al. 1971; Dyhre-Poulsen 1978), as well as the earliest modulation reported in evoked-potential and single-unit recording studies (Chapman et al. 1988; Cohen and Starr 1987; Jiang et al. 1991). On the other hand, the timing of the peak decrease in perceptual performance at the four distal sites coincided with the onset of agonist EMG (Fig. 7B). The possible significance of this with regard to the role of peripheral feedback in the reduction of detection during movement is discussed in the text following.

During movement, there was almost complete suppression of detection at the four sites closest to the moving digit (iD2, iHA, iD5, and iFA). At these sites, movement kinematic parameters likely play a role in determining the maximal amplitude of the observed suppression (see further). As the distance between the site of stimulation and the site of movement increased, the magnitude of the reduction declined. In addition as distance increased there was a 60-ms shift in the time of the peak decrease and a 120-ms shift in the first significant decrease. These results are compatible with the findings of previous studies that showed that detection thresholds are increased during movement (e.g., Chapman et al. 1987; Duysens et al. 1995; Post et al. 1994), with the largest change occurring at sites closest to the moving segment.

Sources and mechanisms of the movement-related decrease in tactile detection

The spatiotemporal characteristics of the movement-related decrease in detectability, discussed earlier, help to define the necessary attributes of the gating mechanism(s). Both centrally mediated inhibition, originating from central and/or peripheral sources, and also physical factors in the periphery may have contributed to generating the observed spatiotemporal gradient.

CENTRAL SOURCES. One finding in favor of a central source for the gating signals is the observation that at the sites closest to the moving digit, detection began to decline 120 ms before movement onset and 70 ms before the onset of EMG, i.e., well before any peripheral feedback could have been generated. The earliest time-dependent decrease may be related to the preparation and execution of the movement, as has been suggested by others (Chapman et al. 1988; Coulter 1974; Ghez and Lenzi 1971; Jiang et al. 1990a,b, 1991). Although the timing is consistent with the precentral motor areas playing a role, the spatial distribution observed here is not consistent with the pattern of modulation of cutaneous transmission elicited by intracortical microstimulation of primary motor cortex in nonhuman primates (Jiang et al. 1989, 1990a). In the latter studies, only sites on the same segment or distal to the activated muscle showed evidence of sensory gating, and microstimulation did not modulate transmission from the glabrous skin of the hand (although inputs from the hairy dorsum of the digit and hand were gated). In contrast, the present findings showed that sensory modulation extends to sites located proximal to the moving segment and to the glabrous skin of the digits. Providing the mechanisms are similar in humans and monkeys, this suggests that area 4 is unlikely to be the only source for the widely distributed gating effects reported here. Other areas (e.g., premotor cortical regions) also must be involved if the present findings are to be explained by a centrally originating signal.

PERIPHERAL SOURCES. Other spatial and temporal characteristics of the gating argue in favor of a role for peripheral sources in mediating the movement-related gating. The timing of the peak decrease at the stimulation sites closest to the moving digit coincided with the onset of EMG activity. It is reasonable to assume that peripheral feedback begins at this moment, e.g., muscle spindle discharge elicited by alpha-gamma coactivation, and that this feedback contributed to the sharp decrease in detection performance at this time. In support of this, passive movements can be as effective as active movements in generating movement-related decreases in tactile inputs (e.g., Chapman et al. 1987, 1988; Huttunen and Hömberg 1990), although in a study of cortical SEPs elicited by suprathreshold cutaneous stimuli, Chapman et al. (1988) found that the time course for modulation was delayed considerably for passive as compared with active movements, i.e., the modulation followed movement onset instead of preceding it. A variety of mechanoreceptors are activated by passive movements, and evidence suggests that muscle spindle feedback contributes to the decrease in cortical SEPs during active and passive movement (Brooke et al. 1997). Cutaneous feedback also diminishes the amplitude of cortical SEPs (Jones et al. 1988).

CENTRAL MECHANISMS. Whatever the source of the gating signal(s), any explanation for the results needs to explain the widespread spatial distribution of the time-dependent decrease in detectability and the pronounced temporal gradient across the homolateral limb. Clearly a single inhibitory signal distributed simultaneously across a given somatosensory relay would not produce the complex spatiotemporal gradient observed here. Several, not necessarily exclusive, explanations can be advanced to explain the large changes in time and magnitude at the more proximal sites on the arm. The spatial distribution may be the result of lateral inhibition generated by the gating signals. The timing of the modulation would reflect the time necessary for spread of the lateral inhibition, whereas the amplitude of the observed decrease in detectability would reflect the strength of the inhibitory signal. The distant sites that showed no obvious time-dependent modulation would either be outside the zone of effective inhibition or the inhibition might have occurred at delays >100 ms after movement onset (the longest delay tested here). Given that synaptic delay is only 0.5 ms and that conduction distances within any candidate relay (dorsal column nuclei (DCN), ventrobasal thalamus, primary somatosensory cortex) are short, then this suggestion requires an extremely slow rate of spread through multiple synapses to explain delays of the order of 60 ms. This makes it more likely that multiple loops within the CNS may be involved in generating this spatiotemporal gradient, possibly via descending cortical projections to somatosensory relays, including cortico-thalamic, cortico-DCN, cortico-reticulo-DCN, and corticospinal projections. If such is the case, then it may well be that a combination of signals interact to produce the observed spatiotemporal gradient, with only a subset of these mechanisms being effective at the more distant sites. Such a suggestion is supported by our observation that only the sites closest to the moving digit showed evidence of a relationship between perceptual performance and movement kinematics.

The preceding suggestions are independent of the potential source of the gating signal, peripheral or central. It needs to be stressed, however, that there is evidence that a strong peripheral signal can modify the perception of weaker and earlier peripheral stimuli (backward masking). Evidence for this comes from studies in humans that have shown that detection of cutaneous stimuli is decreased if the stimulus is followed by a second "masking" stimulus (Laskin and Spencer 1979; Scherrick 1964; Schmid 1961; Weisenberger 1994). Although the spatial pattern is similar to that seen here, no temporal shift over distance has been reported in masking studies, leaving the importance of these observations unclear with regard to the present findings.

CONTRIBUTION OF PERIPHERAL FACTORS. Although central mechanisms can explain the results, the potential contribution of physical factors (distance, nerve conduction velocity) to the spatiotemporal gradient also should be considered. The shift in timing of the peak decrease over distance might be explained by the decrease in distance (and therefore travel time) between the more proximal stimulation sites and the CNS. Assuming that conduction velocity was similar at all stimulation sites, that low-intensity electrical stimuli preferentially activated large diameter (A beta) cutaneous fibers with a conduction velocity of >= 50 m/s (Diabetes Control and Complications Trial Research Group 1995) and that the average distance between the proximal and distal sites was ~70 cm, then at most a 10-ms shift in the timing of the modulation would be explained by differences in travel times. This suggests that differences in path length did not contribute significantly to the results.

Second, we considered the possibility that the gating signal originated from faster conducting afferents (group I muscle afferents) than those activated by our near-threshold stimulus. Considering the iD2 stimulation site and assuming that spindle feedback begins at EMG onset and that cutaneous and muscle afferent conduction velocites are ~50 and 60 m/s, respectively, then a test stimulus given at EMG onset would arrive ~3 ms later at the spinal cord as compared with the EMG-related feedback in an average subject. The earliest modulation at the iD2 site, on the other hand, preceded EMG onset by 70 ms, which again could only be explained by differences in conduction velocity if test stimulus conduction was much slower than it presumably was. The latter is not supported by studies in humans that have shown no significant difference in the conduction velocities of the fastest muscle and cutaneous afferents (Macefield et al. 1989). In summary, physical factors likely made a small contribution to the results and it appears more likely that central mechanisms need to be invoked.

Functional significance

We recently suggested that simple reductions in the signal-to-noise ratio, produced by an increase in background noise, could not explain all of the changes in perception that accompany movement (Chapman et al. 1996; Post et al. 1994). Although such a mechanism explains well the decreases in tactile detection with unchanged discrimination thresholds, it also predicts reduced magnitude estimates at low, but not high, intensities of stimulation. Using spatially distributed vibrotactile stimuli, however, we found that magnitude estimates were decreased at high, but not low, intensities (Post et al. 1994). Consideration of other models, linear and nonlinear inhibitory surrounds, led us to suggest that the latter provided the closest approximation to the experimental data (Chapman et al. 1996). The model developed here, based largely on logistic functions, thus provides some support for our suggestion that the underlying inhibitory processes may have a nonlinear distribution. Relative distances between body parts were used in the model. This permits the generation of simple, testable predictions for the amount of gating that will be observed at a given distance on the body surface from the site of motion. However, because the gating effects are exerted within the CNS where the representation reflects peripheral innervation density and not absolute size, it would be interesting to incorporate the relative distance between body parts at each of the somatosensory relays within the CNS into the model. Unfortunately, such data for humans are not currently available. In summary, the model represents an initial step toward developing a complete description of the effects of inhibitory mechanisms associated with movement-related gating on detection performance and provides a framework for future physiological studies aimed at characterizing the exact sources and sites of action of these mechanisms.

These movement-related inhibitory controls diminish the amount of afferent input that must be processed within the CNS during movement. As suggested by Coulter (1974), movement-related gating controls may suppress redundant inputs that can be predicted from the motor command so that the detection of other unexpected or novel stimuli is enhanced. The spatial distribution and large temporal shift in the gating actions (hand vs. shoulder) may reflect the spread of nonspecific lateral inhibition originating from the body part in motion. Alternatively, the spatiotemporal gradient could be the result of "hard wired" gating, which reflects common patterns of use for the upper limb, thus providing an automatic reduction in afferent input during natural goal-directed movements.

    ACKNOWLEDGEMENTS

  We gratefully acknowledge the late R. Bouchoux for the construction of the apparatus, the excellent technical assistance of R. Albert, M. Bourdeau, D. Cyr, G. Filosi, C. Gauthier, and C. Valiquette, and the mathematical assistance of C. Bourget and J. F. Anger. We also thank Drs. T. Drew and W. Jiang for helpful comments on the manuscript.

  This work was supported by the Medical Research Council of Canada. S. R. Williams was supported by bursaries from the Groupe de Recherche sur le Système Nerveux Central (GRSNC) and Fonds pour la Formation de Chercheurs et l'Aide à la Recherche (FCAR), Fonds de la Recherche en Santé du Québec (FRSQ), and Unimédia. J. Shenasa was supported by a bursary from the GRSNC. C. E. Chapman was a chercheur-boursier of the FRSQ.

    APPENDIX A

Logistic equation used to fit perceptual data for each stimulation site, where P represents the proportion of stimuli perceived, t represents time (ms), mpk represents the peak slope, tpk represents the time of the peak slope, max represents the maximum proportion of stimuli perceived, and min represents the minimum proportion of stimuli perceived.
<IT>P</IT>= [(max − min)(1/1 + <IT>e</IT><SUP>−4<IT>mpk</IT>(<IT>t−tpk</IT>)</SUP>)] + min (A1)

    APPENDIX B

The equation for the model surface was constructed using the following reasoning. Because logistic functions provided a good description of the effects of time on perceptual performance (Figs. 5 and 6) and distance on function minima (Fig. 7B), this type of function again was used to model these effects. A linear function was used to model distance-dependent modifications in the timing of peak decreases in performance based on the finding that a linear model provided an adequate description of the effect of distance (Fig. 7A). Because maximum performance was invariant between sites, it was modeled with a constant. The resultant model can be described as follows, where Fdist is a function representing the proportion of stimuli detected, i represents time (ms), j represents the distance between the stimulation site and iD2 (proportion of subject height), and max represents the maximum proportion of stimuli detected.

Distance-dependent component (affects mostly minimum predicted perceptual performance)
Distlogistic<SUB>(<IT>j</IT>)</SUB>= 1/[1 + <IT>e</IT><SUP>(−96<IT>j</IT>+41)</SUP>] (B1)
Distance-dependent shift in the timing of the peak decrease in perceptual performance
Shift<SUB>(<IT>j</IT>) </SUB>= −9.4<IT>j</IT> (B2)
Time-dependent component (modifies perceptual performance over time)
Timelogistic<SUB>(<IT>i</IT>)</SUB>= 1/[1 + <IT>e</IT><SUP>(0.046<IT>i</IT>+(0.36+Shift<SUB>(<IT>j</IT>)</SUB>))</SUP>] (B3)
Maximum predicted perceptual performance
max = 0.86 (B4)
Global equation
<IT>F</IT>dist<SUB>(<IT>i,j</IT>)</SUB>= max [Distlogist + Timelogist(1 − Distlogist)] (B5)
The model surface was fitted first to the actual data using a least mean squares method, producing a mean square error value (MSE1). The peak difference between the model surface and the data points was calculated using this model surface (PEAK1). The final fitting minimized the value of an error variable calculated in the following manner
Error variable = MSE + (MSE1/PEAK1)PEAK (B6)
For the model surface presented in this paper, this produced a 25% decrease in peak error with only a 5% increase in MSE.

    FOOTNOTES

  Address for reprint requests: C. E. Chapman, Centre de Recherche en Sciences Neurologiques, Faculté de Médecine, Université de Montréal, PO Box 6128, Station Centre Ville, Montréal, Québec H3C 3J7, Canada.

  Received 27 March 1997; accepted in final form 15 October 1997.

    REFERENCES
Abstract
Introduction
Methods
Results
Discussion
References

0022-3077/98 $5.00 Copyright ©1998 The American Physiological Society