Abstract
Difficulties experienced in steering a vehicle can be expected to place a demand on one’s mental resources (O’Donnell, Eggemeier 1986). While the extent of this mental workload (MWL) can be estimated by self-reports (e.g., NASA-TLX; Hart, Staveland 1988), it can also be
physiologically evaluated in terms of how a primary task taxes a common and limited pool of mental resources, to the extent that it reduces the electroencephalographic (EEG) responses to a secondary task (e.g. an auditory oddball task). For example, the participant could be primarily required to control a cursor to track a target while
attending to a series of auditory stimuli, which would infrequently present target tones that should be responded to with a button-press (e.g., Wickens, Kramer, Vanasse and Donchin 1983). Infrequently presented targets, termed oddballs, are known to elicit a large positive potential after approximately 300 ms of their presentation (i.e.,P3). Indeed, increasing tracking difficulty either by decreasing the predictability of the tracked target or by changing the complexity of the controller dynamics has been shown to attenuate P3 responses in the secondary auditory monitoring task (Wickens et al. 1983; Wickens, Kramer and Donchin 1984). In contrast, increasing tracking difficulty—by introducing more frequent direction changes of the tracked target (i.e. including higher frequencies in the function that describes the motion trajectory of the target)—has been shown to bear little influence on the secondary
task’s P3 response (Wickens, Israel and Donchin 1977; Isreal, Chesney, Wickens and Donchin 1980). Overall, the added requirement of a steering task consistently results in a lower P3 amplitude, relative to performing auditory monitoring alone (Wickens et al. 1983; Wickens et al. 1977; Isreal et al. 1980).
Using a dual-task paradigm for indexing workload is not ideal. First, it requires participants to perform a secondary task. This prevents it from being applied in real-world scenarios; users cannot be expected to perform an unnecessary task that could compromise their critical work performance. Second, it can only be expected to work if
the performance of the secondary task relies on the same mental resources as those of the primary task (Wickens, Yeh 1983), requiring a deliberate choice of the secondary task. Thus, it is fortunate that more recent studies have demonstrated that P3 amplitudes can be sensitive to MWL, even if the auditory oddball is ignored (Ullsperger,
Freude and Erdmann 2001; Allison, Polich 2008). This effect is said to induce a momentary and involuntary shift in general attention, especially if recognizable sounds (e.g. a dog bark, opposed to a pure sound) are used (Miller, Rietschel, McDonald and Hatfield 2011).
The current work, containing two experiments, investigates the conditions that would allow ‘novelty-P3’, the P3 elicited by the ignored, recognizable oddball, to be an effective index for the MWL of compensatory tracking. Compensatory tracking is a basic steering task that can be generalized to most implementations of vehicular control. In both experiments participants were required to use a joystick to counteract disturbances of a horizontal plane. To evaluate the generalizability of this paradigm, we depicted this horizontal plane as either a line in a simplified visualization or as the horizon in a realworld
environment. In the latter, participants experienced a large
field-of-view perspective of the outside world from the cockpit of an aircraft that rotated erratically about its heading axis. The task was the same regardless of the visualization. In both experiments, we employed a full factorial design for the visualization (instrument,
world) and 3 oddball paradigms (in experiment 1) or 4 levels of task difficulty (in experiment 2) respectively. Two sessions were conducted on separate days for the different visualizations, which were counter-balanced for order. Three trials were presented per oddball paradigm (experiment 1) or level of task difficulty (experiment 2) in
blocks, which were randomized for order. Overall, we found that steering performance was worse when the visualization was provided by a realistic world environment in experiments 1 (F (1, 11) = 42.8, p\0.01) and 2 (F (1, 13) = 35.0, p\0.01). Nonetheless, this manipulation of visualization had no consequence on our participants’
MWL as evaluated by a post-experimental questionnaire (i.e., NASATLX) and EEG responses. This suggests that MWL was unaffected by our choice of visualization.
The first experiment, with 12 participants, was designed to identify the optimal presentation paradigm of the auditory oddball. For the EEG analysis, two participants had to be excluded, due to noisy electrophysiological recordings (more than 50 % of rejected epochs). Whilst performing the tracking task, participants were presented with a sequence of auditory stimuli that they were instructed to ignore.
This sequence would, in the 1-stimulus paradigm, only contain the infrequent odd-ball stimulus (i.e., the familiar sound of a dog’s bark (Fabiani, Kazmerski, Cycowicz and Friedmann 1996)). In the 2-stimulus paradigm this infrequently presented oddball (0.1) is accompanied by a more frequently presented pure tone (0.9) and in the 3-stimulus paradigm the infrequently presented oddball (0.1) is accompanied by a more frequently presented pure tone (0.8) and an infrequently presented pure tone (0.1). These three paradigms are widely used in P3 research (Katayama, Polich 1996). It should be noted, however, that the target to target interval is 20 s regardless of the paradigm. To obtain the ERPs the epochs from 100 ms before to 900 ms after the onset of the recognizable oddball stimulus, were averaged. Mean amplitude measurements were obtained in a 60 ms window, centered at the group- mean peak latency for the largest positive maximum component between 250 and 400 ms for the oddball P3, for each of the three mid-line electrode channels of interest (i.e., Fz, Cz, Pz). In agreement with previous work, the novelty-P3 response is smaller when participants had to perform the
tracking task compared to when they were only presented with the task-irrelevant auditory stimuli, without the tracking task (F (1, 9) = 10.9, p\0.01). However, the amplitude of the novelty-P3 differed significantly across the presentation paradigms (F (2, 18) = 5.3, p\0.05), whereby the largest response to our task-irrelevant
stimuli was elicited by the 1- stimulus oddball paradigm. This suggests that the 1-stimulus oddball paradigm is most likely to elicit novelty-P3 s that are sensitive to changes in MWL. Finally, the attenuation of novelty-P3 amplitudes by the tracking task varied across the three mid-line electrodes (F (2, 18) = 28.0, p\0.001).
Pairwise comparison, Bonferroni corrected for multiple comparisons, revealed P3 amplitude to be largest at Cz, followed by Fz and smallest at Pz (all p\0.05). This stands in contrast with previous work that found control difficulty to attenuate P3 responses in parietal electrodes
(cf., Isreal et al. 1980; Wickens et al. 1983). Thus, the current paradigm that uses a recognizable, ignored sound is likely to reflect an underlying process that is different from previous studies, which could be more sensitive to the MWL demands of a tracking task.
Given the result of experiment 1, the second experiment with 14 participants, investigated whether the 1-stimulus oddball paradigm would be sufficiently sensitive in indexing tracking difficulty as defined by the bandwidth of frequencies that contributed to the disturbance of the horizontal plane (cf., Isreal et al. 1980). Three
different bandwidth profiles (easy, medium, hard) defined the linear increase in the amount of disturbance that had to be compensated for.
This manipulation was effective in increasing subjective MWL, according to the results of a post- experimental NASA-TLX questionnaire (F (2, 26) = 14.9, p\0.001) and demonstrated the expected linear trend (F (1, 13) = 23.2, p\0.001). This increase in control effort was also reflected in the amount of joystick activity, which grew linearly across the difficulty conditions (F (1, 13) = 42.2,
p\0.001). For the EEG analysis two participants had to be excluded due to noisy electrophysiological recordings (more than 50 % of rejected epochs). A planned contrast revealed that the novelty- P3 was significantly lower in the most difficult condition compared to the baseline viewing condition, where no tracking was done (F (1, 11) = 5.2, p\0.05; see Fig. 1a). Nonetheless, novelty-P3 did not
differ significantly between the difficulty conditions (F (2, 22) = 0.13, p = 0.88), nor did it show the expected linear trend (F (1, 11) = 0.02, p = 0.91). Like (Isreal et al. 1980), we find that EEGresponses do not discriminate for MWL that is associated with controlling increased disturbances. It remains to be investigated, whether
the novelty-P3 is sensitive for the complexity of controller dynamics, like it has been shown for the P3.
The power spectral density of the EEG data around 10 Hz (i.e., alpha) has been suggested by (Smith, Gevins 2005) to index MWL. A post hoc analysis of our current data, at electrode Pz, revealed that alpha power was significantly lower for the medium and hard conditions, relative to the view-only condition (F (1, 11) = 6.081, p\0.05; (F (1, 11) = 6.282, p\0.05). Nonetheless, the expected linear trend across tracking difficulty was not significant (Fig. 1b).
To conclude, the current results suggest that a 1-stimulus oddball task ought to be preferred when measuring general MWL with the novelty-P3. Although changes in novelty-P3 can identify the control effort required in our compensatory tracking task, it is not sufficiently sensitive to provide a graded response across different levels of disturbances.
In this regard, it may not be as effective as self-reports and joystick activity in denoting control effort. Nonetheless, further research can improve upon the sensitivity of EEG metrics to MWL by investigating other aspects that better correlate to the specific demands of a steering task.
