Impact of brain arousal and time-on-task on autonomic nervous system activity in the wake-sleep transition.

BACKGROUND: Autonomic nervous system (ANS) activity has been shown to vary with the state of brain arousal. In a previous study, this association of ANS activity with distinct states of brain arousal was demonstrated using 15-min EEG data, but without directly controlling for possible time-on-task effects. In the current study we examine ANS-activity in fine-graded EEG-vigilance stages (indicating states of brain arousal) during two conditions of a 2-h oddball task while controlling for time-on-task. In addition, we analyze the effect of time-on-task on ANS-activity while holding the level of brain arousal constant. METHODS: Heart rate and skin conductance level of healthy participants were recorded during a 2-h EEG with eyes closed under simultaneous presentation of stimuli in an ignored (N = 39) and attended (N = 39) oddball condition. EEG-vigilance stages were classified using the Vigilance Algorithm Leipzig (VIGALL 2.1). The time-on-task effect was tested by dividing the EEG into four 30-min consecutive time blocks. ANS-activity was compared between EEG-vigilance stages across the entire 2 h and within each time block. RESULTS: We found a coherent decline of ANS-activity with declining brain arousal states, over the 2-h recording and in most cases within each 30-min block in both conditions. Furthermore, we found a significant time-on-task effect on heart rate, even when arousal was kept constant. It was most pronounced between the first and all subsequent blocks and could have been a consequence of postural change at the beginning of the experiment. CONCLUSION: Our findings contribute to the validation of VIGALL 2.1 using ANS parameters in 2-h EEG recording under oddball conditions.

Engagement of mental effort in response to mental fatigue: A psychophysiological analysis.

Acute mental fatigue, characterized by a transient decline in cognitive efficiency during or following prolonged cognitive tasks, can be managed through adaptive effort deployment. In response to mental fatigue, individuals can employ two main behavioral patterns: engaging a compensatory effort to limit performance decrements, or disengaging effort, leading to performance deterioration. This study investigated the behavioral pattern used by participants in mental fatigue conditions. Fifty participants underwent a sequential-task protocol with counterbalanced sessions who took place in two separate sessions: a 30-min incongruent Stroop task (fatiguing session) or a 30-min documentary viewing task (control session), followed by a time-to-exhaustion (TTE) handgrip task at 13 % of maximal voluntary contraction. Psychophysiological measures included the preejection period, heart rate variability, blood pressure, and respiration. Behavioral results showed deteriorated TTE handgrip performance after the Stroop task compared to after the documentary viewing task. During the Stroop task participants were more conservative and prioritized accuracy over speed. Self-reported fatigue was greater after the Stroop task. Psychophysiological data revealed a gradual decrease in sympathetic activity over time in both tasks, with the Stroop task showing a more pronounced decrease. Taken together, these findings suggest a disengagement of effort for a large proportion of participants (49 %) that could be partly attributed to a habituation to the demands of the Stroop task. This study illustrates the interplay of behavioral patterns of effort investment in the context of mental fatigue and underscores the role of disengagement as a dominant response to this phenomenon among healthy participants.

Perfusion Imaging of Fatigue and Time-on-Task Effects in Patients With Parkinson's Disease.

Fatigue is a highly prevalent and debilitating non-motor symptom in Parkinson's disease (PD), yet its' neural mechanisms remain poorly understood. Here we combined arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) with a sustained mental workload paradigm to examine the neural correlates of fatigue and time-on-task effects in PD patients. Twenty-one PD patients were scanned at rest and during continuous performance of a 20-min psychomotor vigilance test (PVT). Time-on-task effects were measured by the reaction time changes during the PVT and by self-reported fatigue ratings before and after the PVT. PD subjects demonstrated significant time-on-task effects, including progressively slower reaction time on the PVT and increased post-PVT fatigue ratings compared to pre-PVT. Higher levels of general fatigue were associated with larger increases in mental fatigue ratings after the PVT. ASL imaging data showed increased CBF in the right middle frontal gyrus (MFG), bilateral occipital cortex, and right cerebellum during the PVT compared to rest, and decreased CBF in the right MFG at post-task rest compared to pre-task rest. The magnitude of regional CBF changes in the right MFG and right inferior parietal lobe correlated with subjective fatigue rating increases after the PVT task. These results demonstrate the utility of continuous PVT paradigm for future studies of fatigue and cognitive fatigability in patients, and support the key role of the fronto-parietal attention network in mediating fatigue in PD.

Validating Test Score Interpretations Using Time Information.

A validity approach is proposed that uses processing times to collect validity evidence for the construct interpretation of test scores. The rationale of the approach is based on current research of processing times and on classical validity approaches, providing validity evidence based on relationships with other variables. Within the new approach, convergent validity evidence is obtained if a component skill, that is expected to underlie the task solution process in the target construct, positively moderates the relationship between effective speed and effective ability in the corresponding target construct. Discriminant validity evidence is provided if a component skill, that is not expected to underlie the task solution process in the target construct, does indeed not moderate the speed-ability relation in this target construct. Using data from a study that follows up the German PIAAC sample, this approach was applied to reading competence, assessed with PIAAC literacy items, and to quantitative reasoning, assessed with Number Series. As expected from theory, the effect of speed on ability in the target construct was only moderated by the respective underlying component skill, that is, word meaning activation skill as an underlying component skill of reading competence, and perceptual speed as an underlying component skill of reasoning. Accordingly, no positive interactions were found for the component skill that should not underlie the task solution process, that is, word meaning activation for reasoning and perceptual speed for reading. Furthermore, the study shows the suitability of the proposed validation approach. The use of time information in association with task results brings construct validation closer to the actual response process than widely used correlations of test scores.

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

Refining the continuous tracking paradigm to investigate implicit motor learning.

In two experiments we investigated factors that undermine conclusions about implicit motor learning in the continuous tracking paradigm. In Experiment 1, we constructed a practice phase in which all three segments of the waveform pattern were random, in order to examine whether tracking performance decreased as a consequence of time spent on task. Tracking error was lower in the first segment than in the middle segment and lower in the middle segment than in the final segment, indicating that tracking performance decreased as a function of increasing time-on-task. In Experiment 2, the waveform pattern presented in the middle segment was identical in each trial of practice. In a retention test, tracking performance on the repeated segment was superior to tracking performance on the random segments of the waveform. Furthermore, substitution of the repeated pattern with a random pattern (in a transfer test) resulted in a significantly increased tracking error. These findings imply that characteristics of the repeated pattern were learned. Crucially, tests of pattern recognition implied that participants were not explicitly aware of the presence of a recurring segment of waveform. Recommendations for refining the continuous tracking paradigm for implicit learning research are proposed.