What is time between the presentation of a stimulus and the one set of movement?

Relationship between reaction time and speed of movement among different age group of teen age school going children

Author(s): Habib SK and Ashoke Kumar Biswas

Abstract: Reaction time denotes the elapsed time between the presentation of a stimulus and the subsequent behavioural response. “Reaction time is the period from the stimulus to beginning of the over response”. In other words “time from the stimulus to the beginning of movement”. Reaction time is the elapses from the occurrence of the stimulus of the to act to the beginning of the muscle movement.

Method: The study was from the Patha Bhavana of Visva-Bharati University. A total 40 students were selected from different teen age group as subject. 40 subjects were divided into two group each group i.e. one group was 13-15 years and other group was 16-18 years. Again this group has further divided into two groups, one groups is Boys and another groups is Girls.

Criterion measure: Reaction time measured by Nelson Foot Reaction Time and Speed of movement measured by Nelson Hand Reaction Time, those subjects were measured in seconds with the help of Stick drop test.

Statistics: Mean, Standard Deviation and Correlation Coefficient were used. Level of Significance was set at 0.05.

Result: The mean, Standard deviation and correlation coefficient of Reaction time and Speed of movement of 13-15 years Boys 0.190±0.005, 0.193±0.007 and r value 0.2622. And Girls 0.202±0.005, 0.202±0.008 and r value 0.812 seconds respectively. While mean, Standard deviation and correlation coefficient of Reaction time and Speed of movement of 16-18 years Boys 0.189±0.005, 0.188±0.006 and r value 0.977. And Girls 0.205±0.005, 0.204±0.003 and r value 0.604 seconds respectively.

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How to cite this article:

Habib SK, Ashoke Kumar Biswas. Relationship between reaction time and speed of movement among different age group of teen age school going children. Int J Phys Educ Sports Health 2017;4(5):93-95.

Address for reprint requests and other correspondence: E. Christou, Dept. of Applied Physiology and Kinesiology, Univ. of Florida, Room 100, Florida Gym Stadium RD, Gainesville, FL 32611-8205 (e-mail: ude.lfu@uotsirhcae).

Received 2018 May 15; Revised 2018 Jun 22; Accepted 2018 Jun 26.

Copyright © 2018 the American Physiological Society

Abstract

Reaction time (RT) is the time interval between the appearance of a stimulus and initiation of a motor response. Within RT, two processes occur, selection of motor goals and motor planning. An unresolved question is whether perturbation to the motor planning component of RT slows the response and alters the voluntary activation of muscle. The purpose of this study was to determine how the modulation of muscle activity during an RT response changes with motor plan perturbation. Twenty-four young adults (20.5 ±1.1 yr, 13 women) performed 15 trials of an isometric RT task with ankle dorsiflexion using a sinusoidal anticipatory strategy (10–20% maximum voluntary contraction). We compared the processing part of the RT and modulation of muscle activity from 10 to 60 Hz of the tibialis anterior (primary agonist) when the stimulus appeared at the trough or at the peak of the sinusoidal task. We found that RT (P = 0.003) was longer when the stimulus occurred at the peak compared with the trough. During the time of the reaction, the electromyography (EMG) power from 10 to 35 Hz was less at the peak than the trough (P = 0.019), whereas the EMG power from 35 to 60 Hz was similar between the peak and trough (P = 0.92). These results suggest that perturbation to motor planning lengthens the processing part of RT and alters the voluntary activation of the muscle by decreasing the relative amount of power from 10 to 35 Hz.

NEW & NOTEWORTHY We aimed to determine whether perturbation to motor planning would alter the speed and muscle activity of the response. We compared trials when a stimulus appeared at the peak or trough of an oscillatory reaction time task. When the stimulus occurred at the trough, participants responded faster, with greater force, and less EMG power from 10-35 Hz. We provide evidence that motor planning perturbation slows the response and alters the voluntary activity of the muscle.

Keywords: electromyography, motor neuron pool modulation, reaction time

INTRODUCTION

Reaction time (RT) is the short time interval between the appearance of a stimulus and initiation of a motor response. The present belief is that within this time two important processes take place, namely selection of motor goals (perception of what needs to be achieved) and motor planning (how it needs to be achieved) (Wong et al. 2015). Although challenging any of these two processes can lengthen RT, most studies have challenged the perceptual process. An important but unresolved question is whether challenging the motor planning process slows the response and alters the voluntary drive to the muscle. Here, we determine how the modulation of muscle activity, a proxy of the voluntary muscle activation (Brown 2000; Neto and Christou 2010; Salenius et al. 1997), changes with motor plan perturbation. To accomplish this, we use a RT task in which subjects anticipate a visual stimulus while exerting a sinusoidal force task. We compare RT and modulation of muscle activity when the stimulus appears at the trough or at the peak of the sinusoidal task. We hypothesize that, when the stimulus occurs at the peak of the sinusoid, it will perturb motor planning (anticipatory motor plan is incompatible with the response) and induce a longer RT and an altered modulation of muscle activity.

RT tasks are common experimental paradigms to understand changes in cognitive processing. A common manipulation to lengthen the RT is to challenge the perceptual process of the task (Wong et al. 2015). Previous paradigms include choice RT tasks (Hyman 1953; Schmidt et al. 1988; Smith 1968; Woods et al. 2015), stimuli selection based on saliency (Theeuwes et al. 1998), and performance of two or more tasks concurrently (dual tasking; Bekkering et al. 1994). To date, it remains unclear how challenging the motor planning process would affect the RT and muscle activity.

In this study, we are focusing on challenging the motor planning component of the RT. In anticipation of the visual stimulus, participants performed a sinusoidal force. Although the stimulus can occur at any point of the sinusoidal force, it is compatible with the response requirements when the stimulus appears at the trough. When it appears at the trough, the anticipation motor plan and response require a force increase. In contrast, when the stimulus occurs at the peak, the anticipation motor plan and response are incompatible because the anticipation motor plan is to decrease force, whereas the response requires an increase in force. Thus we expect that, when the stimulus occurs at the peak of the sinusoidal force, the RT will be longer.

Changes to the voluntary muscle activity in response to challenging the motor planning process remain largely unknown. Previous studies have used the modulation of whole muscle activity as a proxy to understand the voluntary activation of muscle (Brown 2000; Neto and Christou 2010; Salenius et al. 1997). There is evidence that greater modulation of the interference electromyography (EMG) from 10 to 60 Hz is associated with increased voluntary drive (Neto and Christou 2010). For example, a voluntary increase in force from 15 to 50% maximum increased the interference EMG power from 10 to 60 Hz but not the power from 60 to 300 Hz (Neto and Christou 2010). Thus greater modulation of 10–60 Hz in the surface EMG is related to a voluntary excitation of the spinal motor neuron pool from higher centers to achieve a stronger contraction. The power from 10 to 35 Hz, termed beta band (Berger 1930), is associated with steadier movements and often referred to as the antikinetic band (Engel and Fries 2010). In contrast, the power from 35 to 60 Hz, termed gamma band (Berger 1930), has been associated with movement initiation (Baker et al. 1999; Conway et al. 1995; Halliday et al. 1998; Kilner et al. 2000; Omlor et al. 2007). Therefore, we expect the voluntary muscle activation for a faster RT to attenuate power in the beta band and increase power in the gamma band.

In this study, we examined whether perturbing the motor plan lengthens the processing time and alters the voluntary muscle activation. To achieve this, we compared trials where the stimulus appeared at the peak or trough of a sinusoidal task. We examined processing time with the length of the premotor component of RT (Botwinick and Thompson 1966; Schmidt et al. 1988) and voluntary drive with the modulation of muscle activity (Brown 2000; Neto and Christou 2010; Salenius et al. 1997) during the RT task. We hypothesized that stimulus appearance at the peak (incompatible intention and response requirements) compared with the trough would result in a longer processing time and an altered modulation of the muscle by decreasing power from 10 to 35 Hz and increasing power from 35 to 60 Hz.

METHODS

Participants

Twenty-four young adults (20.5 ± 1.1, 13 women) volunteered to participate in this study. All participants reported being healthy without any known neurological or orthopedic disorders. On average, participants had a body mass index of 22.5 ± 2.4 and a Montreal Cognitive Assessment score of 28.1 ± 1.4 (Nasreddine et al. 2005). All participants were right handed and right footed as assessed with the Edinburgh Handedness Inventory (Oldfield 1971) and the Waterloo Footedness Questionnaire (Elias and Bryden 1998), respectively. The Institutional Review Board at the University of Florida approved the procedures, and participants signed a written, informed consent before participating in the study.

Experimental Approach

Participants performed one testing session that lasted ~1 h. This session involved performing a sinusoidal anticipatory RT task. Participants performed the following: 1) familiarization of the experimental procedure that included a verbal explanation and practice trials of the RT task, 2) maximum voluntary contraction (MVC) task with ankle dorsiflexion, 3) 15 trials of the RT task, and 4) repetition of the MVC task.

Experimental Arrangement

Experimental setup and apparatus.

Each participant sat comfortably in an upright position and faced a 32-inch monitor (SyncMasterTM 320MP-2; Samsung Electronics America, Ridgefield Park, NJ) that was located 1.25 m away at eye level. The monitor displayed the targeted force, the force produced by ankle dorsiflexion, and the stimulus using a custom-written program in Matlab (MathWorks, Natick, MA). All participants affirmed that they could see the display clearly. Participants flexed the left hip joint to ∼90°, abducted by ∼10°, and flexed the knee to ∼90°. The left foot rested on a customized foot device with an adjustable footplate and secured by straps over the metatarsals to ensure a secure position and an isolated dorsiflexion of the ankle (Fig. 1A). The initial ankle position was ∼90° of ankle dorsiflexion. All participants performed the RT tasks with their nondominant foot (i.e., the left) to introduce greater novelty to the task (Sainburg 2002).

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Fig. 1.

A: schematic drawing of the experimental set up and arrangement of the left foot for 1 participant. The left foot was placed and rested on a customized foot device with an adjustable footplate and secured by a strap over the metatarsals. Participants performed a sinusoidal reaction time task with ankle dorsiflexion. B: representation for 1 participant of the reaction time task at 3 different time points. Participants were presented with unanticipated visual stimulus in the middle of the screen while performing a sinusoidal isometric force-tracking task. This stimulus appeared with illumination of a green background. Participants were asked to respond to the stimulus as quickly as possible by dorsiflexing the ankle with adequate force to show the reaction clearly. The duration of the task was 37 s. Left: anticipatory strategy (type of force control before the stimulus). Middle: moment when the stimulus first occurs. Right: reaction of the participant.

Force measurements.

We quantified the force exerted during the MVC and RT task with a force transducer (model MB-100; Interface, Scottsdale, AZ) placed in parallel with the direction on the customized foot device. This allowed us to analyze the ankle dorsiflexion force vector that was perpendicular to the transducer. The ankle force signals were amplified 100 times (Bridge-8; World Precision Instruments, Sarasota, FL), sampled at 1,000 Hz with a Power 1401 A/D card and a NI-DAQ card (model USB6210; National Instruments, Austin, TX), and stored on a personal computer.

EMG measurements.

To identify the onset of muscle activity during the RT task, we recorded the muscle activity of the primary ankle dorsiflexor (tibialis anterior, TA) with surface EMG (Bagnoli EMG system; Delsys, Boston, MA). We placed the recording electrodes on the skin and in line with the muscle fibers of the TA at the proximal third between the head of the fibula and the medial malleolus to avoid the innervation zone of the muscle (Corti et al. 2015). We placed the reference electrode over the patella. The EMG signals were amplified 1,000 times, sampled at 1,000 Hz with a Power 1401 A/D card and a NI-DAQ card, and stored on a personal computer.

MVC task.

We identified the MVC for ankle dorsiflexion force before and after the RT tasks. Participants increased their ankle dorsiflexion force to their maximum and maintained it for 3 s. Participants exerted three to five MVCs until two MVC values were within 5% of each other. There was 1 min of rest between trials to minimize fatigue. We repeated the MVC task at the end of the experiment to assess whether the experimental task induced fatigue.

RT task.

The RT task consisted of a sinusoidal anticipatory force control (~15 s) before a reaction to an unanticipated visual stimulus. We instructed participants to increase and decrease their ankle dorsiflexion force within a target area (15 ± 5% MVC) at their own preferred frequency and amplitude. We displayed the target area as two red horizontal lines over a white background in the middle of the monitor and the force produced by the participant as a blue line progressing with time from left to right (Fig. 1B) at a rate of 0.02 m/s. We kept the visual gain constant at 1.2° (visual angle) (Vaillancourt et al. 2006).

The visual stimulus consisted of a transient change in background color, from white to green, that lasted for 1 s (Fig. 1B). We instructed the participants to respond to the stimulus as quickly as possible by increasing their ankle dorsiflexion with sufficient force to show the reaction clearly. Each trial lasted 37 s, comprised of the following phases: 1) 4 s of rest, 2) 1.5 s of a ramp to increase force to the target, 3) 3 s of maintaining a constant force of 15% MVC, 4) 20 s of exerting a sinusoidal force task, 5) 3 s of maintaining a constant force of 15% MVC, 6) 1.5 s of a ramp to decrease force to resting levels, and 7) 4 s of rest (Fig. 1B). Participants performed 15 trials for each condition. For 12 out of the 15 trials, we randomly presented the stimulus between 22 and 25 s. For the other three trials, the stimulus was presented at 13.5 s. We did this to prevent participants from predicting an occurrence of the stimulus around the 22-s mark.

Data Analysis

We recorded the force and EMG signals analyzed using a custom-written program in Matlab. In the analysis, we included only the 12 trials that occurred from 22 to 25 s. Before data analysis, the program low-pass filtered the raw force signal at 20 Hz with a fourth-order (bidirectional) Butterworth filter and detrended. Detrending the force signal removed the linear trend from the data and eliminated any drift. We identified force onset as the first time point in which the force exceeded 2 SD of the mean force around the stimulus onset (200 ms before stimulus and 100 ms after stimulus; Fig. 2). Moreover, the EMG signals were detrended, rectified, and low-pass filtered at 6 Hz. We used this processing to identify the onset of EMG associated with the reaction to the stimulus. We identified EMG onset as the first time point in which the low-pass filtered EMG was >2 SD of the mean EMG around the stimulus onset (200 ms before stimulus and 100 ms after stimulus; Fig. 2, dashed box). We identified EMG end as the first time point in which the low-pass filtered EMG was <2 SD of the mean EMG around the stimulus onset.

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Fig. 2.

Example of data collection and analysis of a trial in the trough (left) and peak (right) condition. Force (A) and electromyography (EMG) (B) data were collected from 1 participant for the trough condition and another participant for the peak condition with anticipation, stimulus, and response identified. C: wavelet analysis from frequencies 10–35 Hz corresponding to the same length of time as force and EMG data. D: representation of motor planning hypothesis in which the trough shows compatibility in the intention and reaction, whereas, in the peak, there is incompatibility. RT, reaction time.

Strength.

We quantified strength with the force produced during the MVC task. From the MVC trials that were within 5% of each other, we selected the trial with the highest force as a representation of the participant’s maximal strength.

Trough, peak, and RT.

From the 12 trials, we included only the fastest trial for each participant in which the stimulus occurred at the trough and peak of the sinusoidal task for analysis (Fig. 2). We use the fastest trial because it identifies the maximal potential of the subject to perform an RT task. We quantified the processing part of the RT (termed premotor time) as the time from presentation of the stimulus to EMG onset (Fig. 2). We use the premotor time synonymously with RT in this study for the following reasons: 1) it is the largest component of the RT (~85%), 2) it signifies the processing part of RT, which is the interest in this study, and 3) we quantified RT as the time between the stimulus onset to EMG onset, which is the definition of premotor time.

Response force output.

To determine the amplitude of the response from the peak and trough locations, we quantified the force exerted during the response. We chose this variable as a representation of the executed motor plan. Peak force during the response was considered the amount of force exerted from the start of force following the stimulus to the maximum force exerted. The peak force was normalized to the maximum force exerted before the RT task (pre-MVC).

Modulation of EMG Activity

EMG frequency structure.

We performed a frequency domain analysis on the detrended and 10-Hz high-pass filtered interference EMG using Morlet wavelet transform:

ψ0(t)=π−14e−iω0ηe−η22

(1)

Where η is dimensionless time and ω0 is dimensionless frequency (in this study we used ω0 = 6, as suggested by Grinsted et al. 2004).

The Morlet wavelet (with ω0 = 6) is appropriate when performing wavelet and cross-wavelet analysis because it provides a reasonable balance between time and frequency localization. The wavelet transform applies the wavelet function as a band-pass filter to the time series:

W(s,t)X=∫X(t)ψs,τ*(t)dt

(2)

where X(t) represents the original function that is being transformed, s represents the dilation parameter (scale shifting), τ represents the location parameter (time shifting), and the basic function ψs,τ* is obtained by dilating and translating the mother wavelet Ψ0(t)0.125. We calculated wavelet transforms by using a base Matlab algorithm developed by Torrence and Compo (Torrence and Compo 1998) (available at: http://paos.colorado.edu/research/wavelets). In Matlab 7.0.1 (MathWorks), we developed an algorithm to measure the relative importance of different frequency bands of a single or pair of interference EMG signals or force signals.

Anticipatory and response modulation.

We analyzed the wavelet transform for the response within the full EMG burst of the response (Fig. 2). On the basis of previous findings (Christou and Neto 2010a; Neto et al. 2010), the oscillations we see in the EMG signal of voluntary contractions reflect the voluntary command from the motor cortex (i.e., cortical drive or voluntary drive). We focused on this activity as a representation of the executed response to the stimulus. We divided the wavelet spectra into 10- to 35-Hz (beta) and 35- to 60-Hz (gamma) frequency bands. To compare the power between participants, we quantified the normalized power of each frequency bin relative to the total power from 10 to 100 Hz. We only analyzed sub-100-Hz EMG frequency because power in the EMG signal from 5 to 100 Hz reflects the modulation of the motor neuron pool with voluntary effort, and it is not associated with the shape of the motor unit action potential (Brown 2000; Christou and Neto 2010a, 2010b; Neto and Christou 2010; Neto et al. 2010). We divided the EMG signal into the two different frequency bands (10–35 Hz and 35–60 Hz) because they have been previously associated with specific cortical drives (Myers et al. 2003).

For the EMG spectral analysis, we used the interference EMG signal because we (Christou and Neto 2010a, 2010b) and others (Farina et al. 2004; McClelland et al. 2012) have shown that the interference EMG more accurately estimates the common activity of two EMG signals compared with the rectified EMG.

Statistical Analysis

We used preplanned dependent t-tests to determine whether the following variables were different: 1) pre- and post-MVC force, 2) RT when the stimulus occurred at the peak vs. the trough, 3) response peak force exerted when the stimulus occurred at the peak vs. the trough, 4) response EMG power from 10 to 60 Hz (10–35 and 35–60 Hz) when the stimulus occurred at the peak vs. the trough, and 5) EMG power from 10 to 60 Hz (10–35 and 35–60 Hz) at the peak vs. the trough of the sinusoid during the anticipation period. A mixed two-way ANOVA compared sex and RT at the peak and trough. Any significant interactions were followed up by appropriate post hoc analysis. We used linear regression analyses to determine the contribution of the EMG power from 10 to 35 Hz and 35 to 60 Hz to the peak force exerted during the response. The goodness of fit of each regression was given by the squared correlation (R2; Green and Salkind 2011). The alpha level for all statistical tests was 0.05, which was corrected for multiple comparisons. We performed all statistical analyses with the IBM statistics 24.0 statistical package (IBM, Armonk, NY). Data are reported as means ± SD within the text and as means ± SE in the figures.

RESULTS

Strength and fatigue.

We compared participants’ MVC before and after the RT task to determine whether the experimental protocol reduced their maximal force capacity. MVC forces before and after the RT tasks were similar for participants (before: 192.8 ± 53.1 N vs. 195.4 ± 48.6 N, t = −0.409, P = 0.69), suggesting that our experiment did not reduce maximal force capacity and thus did not play a role in the results below.

RT.

We compared RT between males and females and when the stimulus occurred at the trough (compatible motor plan and response) or peak (incompatible motor plan and response) of the sinusoid. There was no significant interaction between sex and RT at the peak and trough (F1,22 = 0.792, P = 0.383) and no significant main effect for sex (F1,22 = 0.061, P = 0.807). When the stimulus occurred at the trough, RT was significantly shorter than when the stimulus occurred at the peak (trough: 340.9 ± 115.1 ms, peak: 424.7 ± 75.2 ms, t = −3.27, Cohen’s d = 0.67, P = 0.003; Fig. 3A).

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Fig. 3.

A: reaction time (RT) (premotor time) was faster when the stimulus occurred at the trough than at the peak. B: during the response, the force produced was greater when the stimulus occurred at the peak than at the trough. C: electromyography (EMG) power from 10 to 35 Hz, on the other hand, was less when the stimulus occurred at the peak than at the trough. *Significant differences between the stimulus occurring at the trough and the peak (n = 24). MVC, maximum voluntary contraction.

Response.

We quantified response in two different ways. First, we quantified the peak force exerted by the participants in response to the stimulus. We found that, when the stimulus occurred at the peak, the force of the response was ~8% higher than when the stimulus occurred at the trough (trough: 43.9 ± 20.1%, peak: 52.3 ± 23.3%; t = −2.67, Cohen’s d = 0.55, P = 0.014; Fig. 3B). Second, we quantified the modulation of muscle activity from 10 to 60 Hz at the peak and trough. We found that the EMG power from 10 to 35 Hz was significantly less when the stimulus occurred at the peak compared with the trough (trough: 25.0 ± 9.7%, peak: 20.5 ± 9.9%; t = 2.53, Cohen’s d = 0.52, P = 0.019; Fig. 3C), whereas the EMG power from 35 to 60 Hz was similar for the two conditions (trough: 36.7 ± 9.0%, peak: 37.0 ± 10.3%; t = −0.096, P = 0.92). The increase in force response when the stimulus occurred at the peak was associated with a decrease in EMG power from 10 to 35 Hz (R2 = 0.24, Cohen’s f = 0.32, P = 0.015; Fig. 4) but not with power from 35 to 60 Hz (R2 = 0.053, P = 0.278). These findings suggest that the motor plan and the voluntary activation of muscle was different when the stimulus occurred at the peak than at the trough.

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Fig. 4.

On the y-axis is the change in force produced during the response as a percentage of pre-maximum voluntary contraction (MVC) between peak and trough. On the x-axis is the change in electromyography (EMG) power from 10 to 35 Hz as a percentage of the total power from 10 to 100 Hz between peak and trough. An increase in force produced during the response is significantly associated with a decrease in EMG power from 10 to 35 Hz (n = 24).

Anticipation.

To determine whether the muscle activation was similar during the peak and trough in the anticipatory period, we compared the EMG power from 10 to 60 Hz. We found that the EMG power from 10 to 35 Hz (trough: 31.6 ± 16.4%, peak: 28.1 ± 13.2%; t = 0.99, P = 0.331) and 35 to 60 Hz (trough: 31.8 ± 13.1%, peak: 33.1 ± 8.6%; t = −0.51, P = 0.615) was similar for the trough and peak. This finding suggests that the presence of the stimulus modulates EMG at the peak and trough of the sinusoid differently than the anticipatory period.

DISCUSSION

In this experiment, we sought to determine how perturbing the motor planning process alters RT and the voluntary drive to the muscle. To accomplish this, we compared trials where the stimulus occurred at the peak or the trough of the sinusoidal anticipatory period. When the stimulus occurred at the peak, the anticipatory motor plan, which was to decrease force, was perturbed because participants had to increase force during the response. In contrast, when the stimulus occurred at the trough, the anticipatory motor plan and response were compatible (increase force). We found that, when the stimulus occurred at the peak compared with the trough, participants exhibited a slower RT, increased force, and decreased 10- to 35-Hz EMG power of the agonist muscle. These results provide evidence that a perturbation to the motor plan slows RT and alters the voluntary muscle activity.

To manipulate the compatibility of the anticipatory and response motor plan, we altered the location of the stimulus. We compared the trials in which the stimulus occurred at the peak with the trials in which the stimulus occurred at the trough. At the peak, the motor plan was to decrease force by reducing net motor unit activity in accordance with tracing the sinusoidal task. However, the response requirement was to increase force by increasing net motor unit activity, which required a change in the motor plan. Thus, when the stimulus was presented at the peak, it perturbed the motor plan of the anticipatory period. At the trough, the motor plan was to increase force in accordance with the task, and participants would simply continue increasing force to react. Thus, when the stimulus was presented at the trough, the motor plan for the anticipatory and response phases was compatible, and no perturbation to the anticipatory motor plan occurred. This manipulation allowed us to determine whether altering the motor plan lengthened RT and changed the voluntary activation of muscle.

Within RT, two processes occur, selection of motor goals and motor planning (Wong et al. 2015). The selection of motor goals reflects the perceptual part of the task and is concerned with the “what” is needed to be done (Wong et al. 2015). Previous studies have manipulated the selection of motor goals by using choice RT (Hyman 1953; Schmidt et al. 1988; Smith 1968; Woods et al. 2015) and dual tasking paradigms (Bekkering et al. 1994). These studies show that challenging the perceptual part of the task increases RT. However, the effects on RT by manipulating the motor planning process are still unclear. In this study, we keep the perceptual part consistent by having a consistent anticipation, stimuli, and response requirements. We perturb the motor planning process by comparing trials with an incompatible anticipatory-response motor plan (stimulus occurs at the peak) to trials with a compatible anticipatory-response motor plan (stimulus occurs at the trough). We found that RT is slower when there is an incompatible anticipatory-response motor plan relative to a compatible anticipatory-response motor plan. These results suggest that, in addition to challenging the perceptual process, perturbing the motor planning process also increases RT.

In addition to the slower motor response, we found that the motor output was different in terms of amplitude and EMG activity. Participants responded with ~8% greater force when the stimulus occurred at the peak vs. the trough. This may reflect an overcompensation of the anticipatory motor plan, which was to decrease force by 10% (going from peak to the trough of the sinusoid required a decrease in force from 20% to 10% MVC). Therefore, it is possible that the motor output amplitude changed with motor plan perturbation as an overcompensation to the original motor plan.

Contrary to our hypothesis, we found that when the stimulus occurred at the peak (slower response), there was less EMG power from 10 to 35 Hz than when the stimulus occurred at the trough (faster response) but similar EMG power from 35 to 60 Hz. The decrease in EMG power from 10 to 35 Hz was associated with an increase in force production during the response. A greater modulation of the interference EMG from 10 to 35 Hz is associated with an increased voluntary drive (Neto et al. 2010). Specifically, the power from 10 to 35 Hz (i.e., beta band) has been associated with an antikinetic role in voluntary movements (Brown 2000; Engel and Fries 2010) along with a maintenance role of cognitive processes (i.e., motor planning) (Engel and Fries 2010). The decreased modulation of the agonist motor neuron pool from 10 to 35 Hz, therefore, could reflect the change in motor plan for the following two reasons: 1) participants wanted to overcompensate for the force reduction planned originally and increase force by 10% (see explanation above). To achieve this, they reduced the antikinetic modulation of the motor neuron pool (beta band) and thus increased the amplitude of voluntary movement (Brown 2000; Engel and Fries 2010). 2) The decrease in power from 10 to 35 Hz occurred because there was a disruption to the motor plan from an unexpected event (Engel and Fries 2010). The EMG modulation from 10 to 60 Hz, our proxy of the voluntary activation of the agonist muscle, remained consistent throughout anticipation (similar between the peaks and troughs). This is important because no stimulus was presented to the participants, and thus, without an unexpected event, the EMG power from 10 to 60 Hz was not modulated. In contrast, following the unexpected event (i.e., stimulus), the motor plan was likely perturbed from the RT task increasing in difficulty as evidenced from slower RT (Hyman 1953; Schmidt et al. 1988; Smith 1968; Woods et al. 2015). There is also evidence that a more difficult task alters the voluntary drive to the muscle (Reyes et al. 2017). Specifically, Reyes et. al. (2017) reported a decrease in beta band activity during an inherently more difficult task. Thus it is possible that the voluntary activation of the muscle changed with motor plan perturbation either to increase force as an overcompensation to the original motor plan or because the task difficulty increased.

Limitations

This study is limited to measures of the motor plan based on the motor output (EMG and force). Our findings are also limited to healthy young adults and cannot be generalized to other age groups or individuals with movement disorders. Future studies can measure the modulation from the voluntary drive more directly by recording multiple motor units. Studies can potentially incorporate measures at the brain level, such as EEG and MRI, and examine how motor planning perturbation influences other age groups or individuals with neurological disorders.

Conclusions

In summary, our findings provide novel evidence that motor planning perturbation slows the response and alters the voluntary activation of muscle in healthy young adults. Specifically, we showed that, when the motor plan was perturbed, it resulted in a slower RT with lesser EMG power from 10 to 35 Hz and greater force produced. These findings suggest that perturbations to the processes that occur during the short time interval between the appearance of a stimulus and initiation of a motor response, not only slow the response, but also change the voluntary drive to the muscle with consequences to the motor response. An interesting implication of this project is that future studies can determine whether motor planning deficits occur in older individuals or individuals with movement disorders.

GRANTS

This work was supported by the National Institutes of Health Grants R21 NS 093695 and R01 NS 58487 to E. A. Christou and Interdisciplinary Training in Neuromuscular Plasticity and Rehabilitation (T32-{"type":"entrez-nucleotide","attrs":{"text":"HD043730","term_id":"300609204"}}HD043730).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

SD and A.C.M. performed experiments; S.D., A.C.M., B.Y., and E.A.C. analyzed data; S.D., A.C.M., B.Y., and E.A.C. interpreted results of experiments; SD and E.A.C. prepared figures; S.D., A.C.M., and E.A.C. drafted manuscript; S.D., A.C.M., S.H.P., B.Y., and E.A.C. edited and revised manuscript; SD and E.A.C. approved final version of manuscript; A.C.M., B.Y., and E.A.C. conceived and designed research.

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  What is the length of time required to react to a stimulus?

  The average reaction time for humans is 0.25 seconds to a visual stimulus, 0.17 for an audio stimulus, and 0.15 seconds for a touch stimulus.

  What can be described as a time interval between the stimulation and any form of response?

  Reaction time is the time interval between the application of a stimulus and the appearance of appropriate voluntary response by a subject.

  What type of reaction time is a stimulus response?

  Simple reaction time If the reaction is to a single stimulus, the time taken for the response is called simple reaction time. Typical reaction time for simple reactions is very quick. It generally takes 0.13 to 0.18 seconds to react to a single stimulus.

  What is the relationship between reaction time and movement time?

  Reaction time is the interval time between the presentation of a stimulus and the initiation of the muscular response to that stimulus. Movement time involves the execution of a subsequent motor task response, and is included in many reaction time tests.