Acta Psychologica 120 (2005) 1–18 www.elsevier.com/locate/actpsy

Accessory stimulation in the time course of visuomotor information processing: Stimulus intensity effects on reaction time and response force Jutta Stahl *, Thomas H. Rammsayer Georg Elias Mu¨ller Institute for Psychology, University of Go¨ttingen, Gosslerstr. 14, D-37073 Go¨ttingen, Germany Received 24 August 2004; received in revised form 25 January 2005; accepted 10 February 2005 Available online 23 March 2005

Abstract A series of three visual choice-reaction time experiments were performed to systematically investigate the effects of accessory auditory stimulation on response time (RT) and response force (RF). In Experiment 1, the effect of accessory auditory stimulation on early visual information processing was investigated. Experiments 2 and 3 were designed to examine the effects of accessory intensity on RT and RF across the entire time course of sensorimotor processing. Accessory stimulation accelerated response speed only when presented within 100 ms after onset of the visual response signal. An enhancing effect of accessory stimulation on RF, however, was found as late as 220 ms after onset of the response signal. These findings support the notion that response speed and response dynamics represent functionally independent sensorimotor phenomena.
2005 Elsevier B.V. All rights reserved. PsycINFO classification: 2323; 2326; 2330 Keywords: Response speed; Response dynamics; Accessory stimulation; Sensorimotor processing; Stimulus intensity *

Corresponding author. Tel.: +49 551 393606; fax: +49 551 393662. E-mail address: [email protected] (J. Stahl).

0001-6918/$ - see front matter
2005 Elsevier B.V. All rights reserved. doi:10.1016/j.actpsy.2005.02.003

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1. Introduction The major aim of the present study was to elucidate mechanisms involved in sensorimotor processing by investigating the effect of accessory stimulation on response time (RT) as an indicator of processing speed and response force (RF) as an indicator of response dynamics. A contentious issue within the field of sensorimotor processing refers to the question of how premotor and motor processing are influenced by stimulus characteristic such as intensity (e.g., Jas´kowski, Rybarczyk, & Jaroszyk, 1994; Jas´kowski, Rybarczyk, Jaroszyk, & Leman´ski, 1995; Miller, Franz, & Ulrich, 1999; Ulrich, Rinkenauer, & Miller, 1998). Premotor processing comprises both early perceptual and cognitive processes, which are involved in stimulus-associated processing such as stimulus encoding, stimulus identification, and stimulus evaluation. Motor processing, on the other hand, includes central and peripheral response-associated processes such as response selection, motor programming, and muscular activation. It is well established that an increase in intensity of an imperative stimulus (that is, a response signal) results in faster responses (Cattell, 1886; Keuss & van der Molen, 1982; Kohfeld, 1971; Mattes & Ulrich, 1997; Ulrich et al., 1998; van der Molen & Keuss, 1981). Although this accelerating effect of stimulus intensity on RT clearly indicates faster sensorimotor processing, traditional RT experiments failed to reveal whether effects of stimulus intensity on RT effectively influenced processing speed at the level of premotor or motor processing. Therefore, Miller, Ulrich, and Rinkenauer (1999) applied an electrophysiological measure, the so-called lateralized readiness potential (LRP), to investigate the effect of stimulus intensity on premotor and motor processing times. In this study, faster premotor processing with increasing intensity of the imperative stimulus was shown, whereas motor processing time was not affected. While this finding suggested that effects of stimulus intensity are mediated by premotor rather than motor processes, recent studies on the effect of stimulus intensity on RF led to a different conclusion as will be outlined in the following. Over the last decade, RF was established as an additional response parameter to further elucidate sensorimotor processing (e.g., Franz & Miller, 2002; Jas´kowski, van der Lubbe, Wauschkuhn, Wascher, & Verleger, 2000; Jas´kowski & Wlodarczyk, 1997; Mattes, Ulrich, & Miller, 1997; Mordkoff, Miller, & Roch, 1996). Numerous studies reported a positive relationship between intensity of the imperative stimulus and RF, that is, increasing stimulus intensity was associated with stronger motor responses (Angel, 1973; Jas´kowski et al., 1995; Miller, Ulrich, et al., 1999; Ulrich et al., 1998). Since the primary motor cortex has been shown to be strongly involved in determining the actual level of RF (Dettmers et al., 1995), observed effects on RF seem to be mediated by the motor rather than the premotor system. Therefore, the observed rise in RF as a function of stimulus intensity suggested that changes in stimulus intensity also effectively influence motor processes. From this perspective, the failure to demonstrate an effect of stimulus intensity on motor processing time (Miller, Ulrich, et al., 1999) in combination with the observed effects of stimulus intensity on RF (Angel, 1973; Jas´kowski et al., 1995; Miller et al., 1999; Ulrich et al., 1998) points to the conclusion that temporal and dynamic response measures

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as obtained by LRP and RF data, respectively, reflect qualitatively different aspects of a motor response. The failure of Giray and Ulrich (1993) to detect a correlational relationship between RT and RF provided converging evidence for assumption that temporal and dynamic aspects of a motor response are, at least partly, independent of each other. An alternative approach to investigate the influence of stimulus intensity on sensorimotor processing represents the accessory-stimulus paradigm (cf., Nickerson, 1973). Accessory stimulus refers to a neutral, task-irrelevant stimulus, which is presented in addition to an imperative stimulus within an experimental trial. Thus, the accessory stimulus merely accompanies the imperative stimulus but does not provide any taskspecific information. In general, participants respond faster to an imperative stimulus in the presence of an accessory stimulus (for a review see Nickerson, 1973). In a series of LRP experiments, Hackley and Valle-Incla´n (1998, 1999) examined whether the accelerating effect of accessory auditory stimulation is mediated by premotor and/ or motor processes. According to their results, premotor but not motor processing time accounted for faster RT in the presence of an accessory stimulus. In addition, increasing intensity of accessory stimulation leads to shorter RTs (Bernstein, Chu, & Briggs, 1973; Miller et al., 1999). This finding seems to be consistent with the notion of similar action mechanisms underlying the effect of both accessory and imperative-stimulus intensity on RT. To date, studies on accessory intensity are scant. Therefore, no definitive statement can be made with regard to effects of accessory intensity on premotor and motor processing time. Nevertheless, there is some preliminary, indirect evidence from Hackley and Valle-Incla´nÕs (1998) study that accessory stimulus intensity does not affect motor processing time. In their study, accessory stimulation at an intensity of 80 dB SPL(A) effectively reduced premotor processing time, while no acceleration of motor processing time could be confirmed. Thus, it can be assumed that accessory intensity influences speed of premotor, but not motor processing. Intensity of accessory stimulation also exerts an effect on response dynamics. In two of their experiments, Miller et al. (1999, Experiments 3 & 4) reported reliably stronger responses with increasing accessory intensity. Thus, accessory stimulus intensity seems also to effectively modulate the dynamic aspects of motor responses. Besides stimulus intensity, Miller et al. (1999) also varied stimulus onset asynchrony (SOA; i.e., the temporal delay between onset of the imperative stimulus and onset of the accessory stimulus) for a systematic exploration of accessory intensity effects on RT and RF. After extending SOA from 50 to 400 ms, the accessory-intensity effect on RT failed to reach the level of statistical significance (Miller et al., 1999, Experiment 4). A hypothetical explanation is that, when the accessory stimulus was presented rather late in the time course of information processing, intensity could no longer affect RT as effectively as in the initial phase of information processing. This may indicate that early processing stages are more responsive to intensity-related effects on RT. Unlike RT, with an SOA of 400 ms, RF was still susceptible to accessory intensity as indicated by increased RF with higher levels of accessory intensity (Miller et al., 1999). This finding suggested that RT and RF might represent qualitatively different aspects of information processing.

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1.1. Theoretical background and objectives of the present study The present study was designed to investigate the effect of accessory stimulation on the time course of sensorimotor processing and to contrast predictions derived from three different theoretical views, namely the stimulus–response mapping hypothesis, arousal-based models, and a gating-model that may account for stimulus intensity effects on RT and RF. Romaigue`re, Hasbroucq, Possama, and Seal (1993) referred to the stimulus–response mapping hypothesis to explain intensity effects on RF. This hypothesis proposes the formation of an internal representation of both stimulus intensity (‘‘low’’ or ‘‘high’’) and RF (‘‘weak’’ or ‘‘strong’’). Due to common coding of stimulus and response characteristics, high-intense stimuli should be followed by strong responses, whereas low-intense stimuli should elicit a weak response. Romaigue`re et al. (1993) showed that responses in compatible intensity–force conditions (i.e., low–weak or high–strong) were faster than in incompatible intensity–force conditions (i.e., high–weak or low–strong) and, thus, supporting the assumption of common coding of stimulus intensity and RF (see also Mattes et al., 1997). Based on these considerations, for the present study on the effects of accessory intensity and SOA, stimulus–response mapping hypothesis predicts higher RF with increasing stimulus intensity. Arousal-based models of sensorimotor processing represent an alternative theoretical approach to account for stimulus intensity effects on RT and RF. Based on SandersÕ (1983) cognitive-energetical linear stage model of human information processing and stress, Miller et al. (1999) assumed the existence of at least two parallel processing systems. First, a main processing system is responsible for stimulus analysis and execution of the task-specific response. For this purpose, the main processing system comprises different functional components depending on task modality (e.g., visual or auditory) and response characteristics (e.g., movement direction or RF). Secondly, an arousal system was hypothesized that is sensitive to energy-related stimulus properties such as intensity. For example, a participantÕs effective level of arousal can be enhanced by increasing stimulus intensity (Pribram & McGuinness, 1975). Furthermore, enhanced arousal speeds up the main processing system and activates additional motor force units, which leads to faster and stronger responses, respectively (Jas´kowski et al., 1995; Jas´kowski et al., 2000; Miller et al., 1999; Ulrich & Mattes, 1996; Wlodarczyk, Jas´kowski, & Nowik, 2002). Hence, the arousal system seems to exert an amplifying influence on various functions of the main processing system, which should result in faster and stronger responses with higher stimulus intensity. However, the later the accessory stimulus is presented, the less arousal should be evoked. As a consequence, a monotonically decreasing effect of accessory intensity on RT and RF with increasing SOA is to be expected. The so-called gating model (Ulrich et al., 1998) may also account for effects of accessory stimulation on RT and RF. This model assumes that the onset of an imperative stimulus triggers the accumulation of neural activation within the sensory system. If the amount of neural activation reached a relevant criterion, neural transmission from the sensory system to the motor system will be initiated. In a metaphorical way, the beginning of the transmission process has been compared with the

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opening of a gate separating the sensory from the motor system. The gating model predicts that with higher stimulus intensity, more neural activation was elicited and, thus, the criterion will be reached faster which, in turn, results in shortened RT. Ulrich et al. (1998) presumed that response speed is determined by the time required to open the hypothesized gate. While the gate is open, stimulus intensity could still affect RF but not RT. In an auditory simple-reaction task, Ulrich et al. (1998) showed that RT decreased with increasing stimulus duration. However, saturation of the effect on RT was observed, whereas RF still increased with longer stimulus durations. This finding indicates that RF should be longer sensitive to changes in stimulus characteristics than RT. Assuming that the gating model holds also for accessory intensity, for the present study, we would predict stronger and faster responses with increasing stimulus intensity. This effect, however, should decrease with increasing SOA. Furthermore, the effect of stimulus intensity on RT should diminish in an early phase of sensory motor processing, whereas RF should remain sensitive to an increase of stimulus intensity for a longer period of time. For this purpose, in Experiment 1, the effect of accessory stimulation on early visual information processing was investigated with SOAs ranging from 50 to 100 ms. The outcome of this experiment suggested that the effect of accessory stimulation on RT decreased with increasing SOA, whereas the effect on RF remains constant. Therefore, Experiment 2 was designed to examine the effect of accessory stimulation on RT and RF across the entire time course of sensorimotor processing. Experiment 2 revealed that accessory stimulation loses its impact on RT 100–150 ms after onset of the visual response signal, while the effect on RF was still beyond this period. Eventually, Experiment 3 focused on the influence of accessory stimulation within a time window ranging from 100 to 260 ms with smaller step sizes to more meticulously investigate effects of accessory stimulation during this critical period of time.

2. Experiment 1 The major aim of the first experiment was to elucidate the effect of accessory auditory stimulation on early visual information processing. For this purpose, the accessory stimulus was presented at three different levels of intensity and with SOAs varying from 50 to 100 ms. Since processing of auditory stimuli is much faster than processing of visual stimuli (Brebner & Welford, 1980; Woodworth & Schlosberg, 1954), the shortest SOA duration was 50 ms to prevent the accessory stimulus from acting as a potential ready signal. 2.1. General method 2.1.1. Participants Participants of all three experiments were enrolled in introductory psychology courses at the University of Go¨ttingen. They received course credit for their participation and were naive about the experimental hypothesis. All participants had

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normal hearing and normal or corrected-to-normal vision. For each experiment, a fresh sample was recruited. Participants of Experiment 1 were 12 male and 28 female undergraduate students ranging in age from 19 to 48 years (mean and standard deviation of age: 22.5 ± 5.3 years). 2.1.2. Apparatus RF and RT were assessed by means of force-sensitive keys similar to the ones applied in previous studies (e.g., Giray & Ulrich, 1993; Miller et al., 1999). One response key was used for each hand. Depending on the experimental condition, the participant responded with a brief flexion of the right or the left index finger. The force of this flexion was measured by the force-sensitive key composed of a leaf spring (110 mm · 19 mm · 2 mm) held by an adjustable clamp at one end of the force key, while the participant pressed on the other, free end with his or her index finger. A force of 1000 cN bent the free end of the leaf spring approximately 2 mm. Each response key was mounted on a board that provided full forearm support. Furthermore, a chin rest was used to maintain a constant posture and distance of 65 cm to the computer screen. Strain gauges were attached near the fixed end of the leaf spring. Thus, when the participant pressed the key, the strain gauges produced an analog electrical signal corresponding to the force applied to the leaf spring. This signal was digitized and recorded with a sampling rate of 500 Hz starting at the onset of the imperative stimulus and continuing for 2000 ms. 2.1.3. Stimuli As visual imperative stimuli, the letters ÔvÕ and ÔwÕ were presented for 1000 ms in the center of a computer screen subtending a visual angle of about .60. Auditory accessory stimuli were 1000-Hz sine wave tones presented binaurally through headphones (Sony MDR-V300). Each tone was presented at one of three intensity levels, 59, 69, or 79 dB SPL(A), with a background noise of approximately 38 dB SPL(A). In Experiment 1, one visual stimulus and one auditory accessory stimulus were presented on each trial, with an SOA of 50, 75, or 100 ms, measured from the onset of the imperative stimulus to the onset of the accessory stimulus. Both stimuli were terminated simultaneously 1000 ms after onset of the imperative stimulus. 2.1.4. Procedure The participantsÕ task was to respond with one hand to the letter ÔvÕ and with the other hand to the letter ÔwÕ. The assignment of letter to hand was held constant within each participant but balanced across participants. An experimental session lasted approximately 60–70 min and consisted of one practice block followed by 14 experimental blocks. The purpose of the practice trials was to ensure that the participants understood the instructions and to familiarize them with the stimuli. Each block consisted of 60 trials. The factorial combination of the three levels of intensity of the accessory stimulus and the three SOA conditions, and an additional control condition with no accessory stimulus resulted in 10 types of trials. Within a block, three

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trials of each type were presented for right- and left-hand responses, respectively. The order of trial presentation was randomized within each block. Participants were instructed to respond as quickly as possible without making too many errors. During the first block, visual feedback was provided after each trial to practice the stimulus–response assignment. No such feedback, however, was presented for the experimental blocks. At the beginning of each trial, a white fixation cross was presented for 500 ms as a ready signal. To minimize anticipatory responses, the duration between the ready signal and the onset of the imperative stimulus corresponded to the sum of a constant period of 500 ms and an exponentially distributed random variable with a mean of 2000 ms. Between blocks, there was a short break and visual feedback on overall mean RT and overall mean percentage of errors was provided on the monitor screen. Participants initiated the next block when he or she felt ready to continue the experiment. As measures of performance, mean RT and mean peak RF were determined for each type of trial across all experimental blocks. While RT was defined as the first moment at which RF exceeded a criterion of 50 cN after onset of the imperative stimulus, peak RF represented the maximum force value recorded during a given trial. All performance data were based on correct responses. Wrong-hand responses, misses, RTs greater than 1000 ms, trials with RTs less than the related SOA duration (i.e., responses occurred before the onset of the accessory stimulus) have to be discarded from further analysis, therefore, excluded from data analysis. 2.1.5. Statistical analyses Analyses of variance (ANOVA) with intensity of the accessory stimulus (three levels: 59, 69, and 79 dB) and SOA (three levels: 50, 75, and 100 ms) as two repeatedmeasurement factors were computed for both dependent variables. A second set of one-way ANOVAs included trials without accessory stimulation, treating these as a fourth level of the accessory intensity factor (i.e., no accessory stimulation, 59 dB, 69 dB, and 79 dB accessory stimulation). For this purpose, data were collapsed across the three SOA levels. Contrasts of statistically significant within-subjects effects were tested by TukeyÕs HSD test (Kirk, 1995). The significance levels of the ANOVAs were adjusted according to the procedure proposed by Geisser and Greenhouse (1958). 2.2. Results and discussion Response errors occurred in less than 3% of all trials. Fig. 1 shows mean RT and mean peak RF as a function of accessory stimulus intensity and SOA. This figure also depicts mean RT and peak RF for the control condition in which no accessory stimulus was presented. A two-way ANOVA was performed to test the effects of accessory stimulus intensity and SOA on RT. There was a highly significant main effect of stimulus intensity [F(2, 78) = 8.99, p < .001, g2 = .19]; RT decreased with increasing accessory stimulus intensity. Post-hoc tests revealed that responses were reliably faster in the high-than in the medium- and low-intensity conditions (p < .001), while the latter two intensity

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Fig. 1. Results of Experiment 1. Mean reaction time and mean peak response force as a function of stimulus intensity and SOA. The error bars reflect the standard error of means for repeated measures design as suggested by Loftus and Masson (1994).

conditions did not differ significantly from each other. Furthermore, a reliable main effect of SOA on RT [F(2, 78) = 14.80, p < .001, g2 = .28] was obtained. Post-hoc comparisons showed that responses were faster with the 50-ms SOA than with 75or 100-ms SOAs (both p < .001). There was no significant interaction between intensity of the accessory stimulus and SOA (F < 1). The one-way ANOVA which included the control condition with no accessory stimulus also yielded a significant effect of accessory stimulus intensity [F(3, 117) = 5.96, p < .001, g2 = .13]. Responses were reliably (p < .001) slower when no accessory stimulation was presented than with the medium- or high-intensity condition.

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The ANOVA on peak RF yielded a significant main effect of accessory stimulus intensity [F(2, 78) = 53.05, p < .001, g2 = .58]. Post-hoc comparisons revealed that peak RF was reliably higher with the 79-dB accessory stimulus than with accessory stimuli presented at either 59 or 69 dB (both p < .001); the 59- and 69-dB conditions did not differ significantly. No other significant effects on peak RF could be established (all Fs < 1). The one-way ANOVA, which included the control condition, also yielded highly significant effects of accessory stimulus intensity [F(3, 117) = 47.69, p < .001, g2 = .55]. Post-hoc tests indicated that peak RF was weakest when no accessory stimulation was present (p < .001 for all comparisons that included the control condition). To rule out the possibility that a fast response necessarily leads to higher RF, bin analyses were performed. For this purpose, Pearson-correlation coefficients were computed between individual RT and peak RF separately for each of the 10 experimental conditions. Resulting correlation coefficients ranged from .02 to .18. Thus, there was no evidence for a functional relationship between RT and RF. With accessory stimulation, responses were faster compared to a control condition with no accessory stimulation. Similarly, presentation of an accessory stimulus resulted in a substantial increase in peak RF. There was no monotonic decrease of RT with increasing stimulus intensity and decreasing SOA of the accessory stimulus. Although RT was reliably less with high as compared to medium or low accessory intensity, there was no statistically significant difference between the latter two levels of intensity. Furthermore, the control condition did not differ from the low intensity condition. An almost identical pattern of results was observed for SOA; significantly faster responses were shown for the 50-ms SOA compared to the 75- and 100-ms SOAs, while the RT difference between the two latter SOA durations failed to reach the 5% level of statistical significance. Similar to the RT results, a reliable increase in peak RF could be shown for the highest level of accessory intensity compared to the medium- and low-intensity conditions. Again, the difference between the low- and the medium-intensity conditions did not reach statistical significance. Unlike RT, however, peak RF was not sensitive to experimental variation of SOA ranging from 50 to 100 ms. The outcome of Experiment 1 suggested that the effect of accessory intensity on RT disappears at an early stage of information processing, while the intensity effect on peak RF seemed to be constant across the entire time range investigated. Experiment 2 was designed to examine whether this differential pattern of RT and peak RF results also holds for later stages of the sensorimotor information processing chain.

3. Experiment 2 The main aim of Experiment 2 was to replicate the findings of Experiment 1 and to investigate the effects of accessory intensity on RT and peak RF over the entire time course of sensorimotor processing. For this purpose, SOAs ranging from 50 to 350 ms were applied.

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3.1. Method 3.1.1. Participants A fresh sample of 40 female undergraduate students ranging in age from 21 to 37 years (mean and standard deviation of age: 22.8 ± 4.3 years) was recruited. 3.1.2. Stimuli Four levels of SOA (50, 150, 250, and 350 ms) and two levels of accessory stimulus intensity (59 and 79 dB) were used. Since in Experiment 1 a reliable difference between the 59- and 69-dB conditions could be shown neither for RT nor for peak RF, only two levels of intensity were used. 3.1.3. Procedure The procedure was similar to that of Experiment 1 with the exception that there were one practice block and 12 experimental blocks each consisting of 54 trials. 3.2. Results and discussion Response errors occurred in approximately 1.1% of all trials, which were discarded from data analysis. Trials with RTs less than the related SOA duration occurred only in the 250-ms condition (0.002%) and in the 350-ms SOA condition (9.4%). Due to the high percentage of such invalid trials in the 350-ms condition, we decided to discard this latter SOA condition from further data analysis in order to warrant unbiased results. Fig. 2 depicts mean RT and peak RF as a function of accessory stimulus intensity and SOA. Two-way ANOVA on RT yielded a significant main effect of accessory stimulus intensity [F(1, 39) = 9.29, p < .01, g2 = .19]; responses were faster in the high than in the low intensity condition. Also a highly significant main effect of SOA [F(2, 78) = 28.03, p < .001, g2 = .42] was obtained. Post-hoc tests showed that responses were significantly faster when the accessory stimulus was presented 50 ms rather than 150 or 250 ms after onset of the imperative stimulus (p < .001). There was also a highly significant interaction of accessory intensity and SOA [F(2, 78) = 8.05, p = .001, g2 = .17]. Post-hoc tests revealed reliably faster responses with the 79-dB than with the 59-dB accessory stimulus when presented 50 ms after the onset of the imperative stimulus (p < .001). A similar effect was not observed for longer SOA durations. Furthermore, for both the low and high level of accessory intensity, responses were reliably faster when accessory stimuli were presented with an SOA of 50 ms than with longer SOA durations (p < .001 for all comparisons). A significant main effect of accessory intensity on peak RF [F(1, 39) = 30.75, p < .001, g2 = .44] indicated that peak RF was higher in the 79-dB than in the 59dB condition. Peak RF was also influenced by SOA [F(2, 78) = 4.38, p < .05, g2 = .10]; peak RF was reliably higher when the accessory stimulus was presented 50 ms after the onset of the imperative stimulus than when presented 250 ms after the onset of the imperative stimulus (p < .05). A significant interaction between stimulus intensity and SOA was also obtained [F(2, 78) = 7.65, p = .001, g2 = .17].

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Fig. 2. Results of Experiment 2. Mean reaction time and mean peak response force as a function of stimulus intensity and SOA. The error bars reflect the standard error of means for repeated measures design as suggested by Loftus and Masson (1994).

Post-hoc comparisons revealed higher peak RF for high- compared to low-intensity accessory stimuli when presented with an SOA of 50 ms (p < .001), 150 ms (p < .01), or 250 ms (p > .05). Furthermore, peak RF was reliably higher when the 79-dB accessory stimulus was presented 50 ms rather than 150 ms or 250 ms after the onset of the imperative stimulus (p < .01). No such effect of SOA could be shown for accessory stimuli presented at an intensity of only 59 dB. As in Experiment 1, bin analysis did not yield any statistically significant results; respective correlation coefficients ranged from .06 to .16. Accessory auditory stimulation resulted in faster responses when presented 50 ms rather than 150 ms or 250 ms after onset of the imperative visual stimulus. Furthermore, only with the 50-ms SOA an accelerating effect of increasing accessory intensity on RT could be revealed. Irrespective of SOA duration, peak RF was stronger

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with high than with low accessory intensity. Unlike RT, peak RF seems to be longer sensitive to the level of accessory. It is important to note, however, that this intensity effect on RF decreased with increasing SOA indicating that sensitivity to accessory stimulation is not constant across the entire time course of sensorimotor processing. In combination with the preceding experiment, Experiment 2 provided converging evidence for the general notion that RT and peak RF possess a different time course of sensitivity to accessory stimulation.

4. Experiment 3 Experiment 3 was designed to more precisely investigate the crucial time range between 100 and 260 ms where RT and RF showed differential sensitivity to accessory stimulation. 4.1. Method 4.1.1. Participants A fresh sample of 30 female and 14 male undergraduate students ranging in age from 19 to 35 years (mean and standard deviation of age: 22.0 ± 2.4 years) were recruited. 4.1.2. Stimuli In Experiment 3, five levels of SOA (100, 140, 180, 220, and 260 ms) were used. 4.1.3. Procedure The procedure was similar to that of Experiments 1 and 2 with the exception that there were 11 experimental blocks consisting of 60 trials each. 4.2. Results and discussion Response errors occurred in approximately 0.2% of all trials and were excluded from data analysis. Trials with RTs less than the related SOA duration occurred only in the 260-ms condition (0.03%). Mean RT and peak RF as a function of stimulus intensity and SOA are presented in Fig. 3. Two-way ANOVA yielded a significant effect of stimulus intensity on RT [F(1, 43) = 10.0, p < .01, g2 = .19]; responses were faster with high- than with lowintensity accessory stimuli. Also a significant main effect of SOA was obtained [F(4, 172) = 4.4, p < .01, g2 = .10]. Post-hoc comparisons showed that responses were reliably faster in the 100- than in the 260-ms SOA condition (p < .001). There was also a significant interaction of accessory intensity and SOA [F(4, 172) = 2.33, p < .05, g2 = .06]. Post-hoc comparisons revealed reliably shorter RTs for high- compared to low-intensity accessory stimulation when presented 100 ms after onset of the visual imperative stimulus (p < .001). While no significant differences in RT among SOA durations could be shown with low-intensity accessory stimulation,

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Fig. 3. Results of Experiment 3. Mean reaction time and mean peak response force as a function of stimulus intensity and SOA. The error bars reflect the standard error of means for repeated measures design as suggested by Loftus and Masson (1994). Please note that a different RF scale was used compared to Figs. 1 and 2 due to a lower overall level of peak RF in Experiment 3 than in Experiments 1 and 2.

responses to high-intensity accessory stimuli were faster when presented 100 ms compared to 140 ms (p < .05) or 260 ms (p < .001) after the onset of the imperative stimulus. For peak RF, there was a highly significant effect of accessory intensity [F(1, 43) = 53.55, p < .001, g2 = .55] indicating higher peak RF with high than with low accessory intensity, whereas SOA failed to reach the 5% level of statistical significance [F(4, 172) = 2.58, p > .07, g2 = .06]. The interaction of accessory intensity and SOA also became significant [F(4, 172) = 8.74, p < .001, g2 = .17]. Except for the 260-ms SOA duration, mean RF was reliably stronger for high than for low accessory intensity (p < .001 for all comparisons). As in Experiment 2, with lowintensity accessory stimulation no differences were found between SOA durations.

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With the high level of accessory stimulation, responses were reliably stronger for 100-ms than for 180-, 220- (both p < .01), and 260-ms SOAs (p < .001). Furthermore, peak RF for 140-ms SOAs was higher than for 260-ms SOAs (p < .01). As in the preceding two experiments, bin analyses did not suggest a functional relationship between RT and peak RF. Computed correlation coefficients varied between .08 and .19. In Experiment 3, an effect of accessory intensity could be established for 100-ms but not for 140-ms SOA durations. These findings point to the conclusion that the accelerating effect of accessory intensity on speed of visuomotor processing may be restricted to the early phase of the sensory information processing. With regard to RF, the present data revealed that the effect of accessory intensity on peak RF decreased with increasing SOA. The effect of accessory intensity leveled off when the accessory stimulus was presented 260 ms after onset of the imperative stimulus. Thus, this finding defined the point in time at which the motor system is no longer responsive to accessory stimulus intensity.

5. General discussion In the present study, three experiments were performed to further elucidate the effect of accessory auditory stimulation on visuomotor processing. For this purpose, the intensity of task irrelevant accessory stimulation as well as the temporal delay (SOA) between the onset of an imperative stimulus and the onset of accessory stimulation were systematically varied. Consistent findings across all three experiments were reliable effects of accessory intensity on RT and peak RF. An increase of accessory intensity from 59 dB to 79 dB resulted in faster RT and higher peak RF. The present results are in line with findings of numerous studies reporting intensity effects of imperative and accessory stimuli on both response parameters (Angel, 1973; Dufft & Ulrich, 1999; Jas´kowski et al., 1995; Miller et al., 1999; Ulrich et al., 1998). Across all three experiments, however, an intensity effect on response speed was only observed when the accessory stimulus was presented within the first 100 ms after onset of the imperative stimulus, whereas response dynamics was sensitive to accessory stimulation beyond this temporal delay. RF seems to be sensitive to a change in accessory intensity within a time window ranging from onset of the imperative stimulus up to approximately 250 ms after onset of the imperative stimulus. Across all experimental conditions of the present experiments, there was no indication of a reliable correlational relationship between RT and RF. This outcome replicated Giray and UlrichÕs (1993) findings and, thus, supported their view that specification of both response parameters is largely independent of each other. Converging evidence for this notion has been provided by the differential sensitivity to accessory stimulation as a function of SOA observed for RT and peak RF. While an effect of accessory stimulation on RT was no longer present 100 ms after onset of the imperative stimulus, the enhancing effect of accessory stimulation on RF vanished not until approximately 250 ms after onset of the imperative stimulus. From

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this perspective, our findings were consistent with the notion that RT and RF possess different explanatory power (Giray & Ulrich, 1993), but challenged LuceÕs (1986, p. 51) view that both measures reflect two sides of the same coin. In the light of previous findings (Miller, Ulrich, et al., 1999; Hackley & Valle-Incla´n, 1998, 1999), it seems reasonable to assume that response speed was primarily determined by premotor processes such as stimulus analysis and response selection. The present finding that a reliable effect of accessory stimulation on RT was limited to the first 100 ms after onset of the imperative stimulus, clearly supports the view that specification of response speed takes place during the early phase of information processing. In the following, the findings of the present study will be discussed within the framework of the three theoretical accounts presented in the Introduction. The stimulus–response mapping hypothesis suggests that common coding of stimulus intensity and RF results in stronger responses with higher stimulus intensity. Proceeding from the assumption that common coding also holds for accessory stimuli, we predicted a higher peak RF with increasing levels of accessory stimulation. This prediction was born out by the results of our Experiments 1–3. Within the framework of the stimulus–response mapping hypothesis, Mattes, Leuthold, and Ulrich (2002) proposed that the effect of intensity on RF should be categorical rather than continuous. Our RF data, however, revealed a monotonic decrease of RF with increasing SOA. This finding argues against the notion of a categorical effect as a function of time from onset of the imperative stimulus. Furthermore, the disappearance of the accessory intensity effect on RF after approximately 250 ms suggests a critical point in time at which response specification was completed. Thus, after completion of response specification, accessory stimulation was no longer able to exert an additional effect on RF. Stimulus–response mapping could account for both our findings by assuming that the probability of a sufficient contribution of accessory stimulation to RF specification proportionally declines with increasing SOA. In addition, if accessory stimulation was presented late enough, it might exert no longer an effect on RF because all response parameters were already specified. As a second theoretical view that may account for effects of accessory stimulation on RT and RF, arousal-based models suggest the existence of a main processing system and a modulating arousal system. Several author assumed that, with increasing stimulus intensity, the arousal system effectively modulates the main system by speeding it up and activating more motor force units (Jas´kowski et al., 2000; Miller, Ulrich, et al., 1999; Ulrich & Mattes, 1996; Wlodarczyk et al., 2002). The present finding of faster and stronger responses with increasing accessory stimulation is in line with the predictions derived from the arousal model. The arousal model can also account for the monotonically decreasing effect of accessory stimulation on RF with increasing SOA: the later accessory stimulation is presented, the less arousal can be evoked and, thus, less impact on RF will be exerted. As shown in the present study, accessory stimulation effectively influenced RT and RF only if presented not later than approximately 100 ms and 220 ms, respectively, after onset of the imperative stimuli. Within the framework of the arousal model, these two time intervals may reflect the crucial time windows for the arousal system to effectively modulate RT and RF, respectively. Hackley and Valle-Incla´n (1998,

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1999) argued that the lack of an effect of accessory stimulation on motor processing speed invalidates the idea that arousal could affect motor processing and by this rejected SandersÕ (1983) cognitive-energetical linear stage model of human information processing and stress. In the light of the present data, however, the absence of an effect on motor speed suggests qualitatively different effects of accessory stimulation on sensory and motor processes rather than refuting the general idea of a modulating arousal system as suggested by Miller et al. (1999). Nevertheless, it should be noted that traditional arousal models cannot account for the existence of different time windows for accessory stimulation to become effective in RT and RF, respectively, without further assumptions. Finally, the gating model (Ulrich et al., 1998) supposes that an accumulation process starts with stimulus onset. After reaching a defined level of neural activity, a continuous transmission from the sensory to the motor system will be initiated. According to the gating model, response speed should be influenced by changes in stimulus intensity as long as this critical level of neural activity is not reached. This is because higher stimulus intensity evokes more neural activity and, thus, accelerates the accumulation process. In their study, Ulrich et al. (1998) reported a saturation of this intensity effect for imperative stimuli longer than 60 ms. Similarly, our data indicate that the effect of accessory intensity levels off approximately 100 ms after onset of the imperative stimulus. Differences in the period of time until the intensity effect on RT ceased in both these studies may be due to the fact that Ulrich et al. (1998) used a simple reaction time task while a choice reaction time task was applied in the present study. Furthermore, it is important to note that in Ulrich et al.Õs (1998) study as well as in the present Experiments 2 and 3, a reliable intensity effect on RF was still observed 200 ms after onset of the imperative stimulus. Although it seems that the gating model may account for the major findings of our study, it should be noted that the gating model has been originally developed to explain intensity effects of the imperative stimulus. Therefore, strictly speaking, no direct predictions can be derived from this model with regard to the effects of task-irrelevant, accessory stimulation. Arousal models, on the other hand, fail to explain the disappearance of accessory intensity effect on RT and RF without further assumptions. A possible solution to this problem may represent a hybrid model combining aspects of both the arousal and the gating model. For example, one could assume that after onset of the imperative visual stimulus neural accumulation was initiated within the main processing system. This accumulation process is modulated by the arousal system in a way that a higher effective level of arousal accelerates neural accumulation, which results in an earlier opening of the gate. After the transmission process between the sensory and the motor system was started, RT could no longer be influenced, whereas additional neural activation elicited by the accessory stimulation could still exert an effect on RF. A tentative explanation of the failure to detect an effect of accessory stimulation on RF beyond approximately 250 ms is that the gate was closed, i.e. the transmission process was completed, at approximately this time. In sum, effects of task-irrelevant auditory accessory stimulation on response speed and peak RF were most pronounced when the accessory stimulus was presented

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during the early phase of information processing. Acceleration of RT and enhancement of peak RF only occurred when the onset of accessory stimulation followed the onset of the imperative stimuli not later than 100 and 220 ms, respectively. Moreover, the present results indicated that the specification of response speed and the specification of response dynamics appear to be temporally and functionally independent of each other.

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