Eye movements discriminate fatigue due to chronotypical factors and time spent on task--a double dissociation

Systematic differences in circadian rhythmicity are thought to be a substantial factor determining inter-individual differences in fatigue and cognitive performance. The synchronicity effect (when time of testing coincides with the respective circadian peak period) seems to play an important role. Eye movements have been shown to be a reliable indicator of fatigue due to sleep deprivation or time spent on cognitive tasks. However, eye movements have not been used so far to investigate the circadian synchronicity effect and the resulting differences in fatigue. The aim of the present study was to assess how different oculomotor parameters in a free visual exploration task are influenced by: a) fatigue due to chronotypical factors (being a 'morning type' or an 'evening type'); b) fatigue due to the time spent on task. Eighteen healthy participants performed a free visual exploration task of naturalistic pictures while their eye movements were recorded. The task was performed twice, once at their optimal and once at their non-optimal time of the day. Moreover, participants rated their subjective fatigue. The non-optimal time of the day triggered a significant and stable increase in the mean visual fixation duration during the free visual exploration task for both chronotypes. The increase in the mean visual fixation duration correlated with the difference in subjectively perceived fatigue at optimal and non-optimal times of the day. Conversely, the mean saccadic speed significantly and progressively decreased throughout the duration of the task, but was not influenced by the optimal or non-optimal time of the day for both chronotypes. The results suggest that different oculomotor parameters are discriminative for fatigue due to different sources. A decrease in saccadic speed seems to reflect fatigue due to time spent on task, whereas an increase in mean fixation duration a lack of synchronicity between chronotype and time of the day.

The Coin Rotation Task: A Valid Test for Manual Dexterity in Multiple Sclerosis

BACKGROUND: Impaired manual dexterity is frequent and disabling in patients with multiple sclerosis (MS). Therefore, convenient, quick and validated tests for manual dexterity in MS patients are needed. OBJECTIVE: The aim of this study was to validate the Coin Rotation task (CRT) to examine manual dexterity in patients with MS. DESIGN: Cross-sectional study. METHODS: 101 outpatients with MS were assessed with the CRT, the Expanded Disability Status Scale (EDSS), the Scale for the assessment and rating of ataxia (SARA), the Modified Ashworth Scale (MAS), and their muscle strength and sensory deficits of the hands were noted. Concurrent validity and diagnostic accuracy of the CRT were determined by comparison with the Nine Hole Peg Test (9HPT). Construct validity was determined by comparison with a valid dexterity questionnaire. Multiple regression analysis was done to explore correlations of the CRT with the EDSS, SARA, MAS, muscle strength and sensory deficits. RESULTS: The CRT correlated significantly with the 9HPT (r=.73, p<.0001) indicating good concurrent validity. The cut-off values for the CRT relative to the 9HPT were 18.75 seconds for the dominant (sensitivity: 81.5%; specificity 80.0%) and 19.25 seconds for the non-dominant hand (sensitivity: 90.3%; specificity: 81.8%) demonstrating good diagnostic accuracy. Furthermore, the CRT correlated significantly with the dexterity questionnaire (r=-.49, p<.0001) indicating moderate construct validity. Multiple regression analyses revealed that the EDSS was the strongest predictor for impaired dexterity. LIMITATIONS: Mostly relapsing-remitting MS patients with an EDSS up to 7 were examined. CONCLUSIONS: This study validates the CRT as a test that can be used easily and quickly to evaluate manual dexterity in patients with MS.

Time for actions in lucid dreams: effects of task modality, length, and complexity

The relationship between time in dreams and real time has intrigued scientists for centuries. The question if actions in dreams take the same time as in wakefulness can be tested by using lucid dreams where the dreamer is able to mark time intervals with prearranged eye movements that can be objectively identified in EOG recordings. Previous research showed an equivalence of time for counting in lucid dreams and in wakefulness (LaBerge, 1985; Erlacher and Schredl, 2004), but Erlacher and Schredl (2004) found that performing squats required about 40% more time in lucid dreams than in the waking state. To find out if the task modality, the task length, or the task complexity results in prolonged times in lucid dreams, an experiment with three different conditions was conducted. In the first condition, five proficient lucid dreamers spent one to three non-consecutive nights in the sleep laboratory. Participants counted to 10, 20, and 30 in wakefulness and in their lucid dreams. Lucidity and task intervals were time stamped with left-right-left-right eye movements. The same procedure was used for these condition where eight lucid dreamers had to walk 10, 20, or 30 steps. In the third condition, eight lucid dreamers performed a gymnastics routine, which in the waking state lasted the same time as walking 10 steps. Again, we found that performing a motor task in a lucid dream requires more time than in wakefulness. Longer durations in the dream state were present for all three tasks, but significant differences were found only for the tasks with motor activity (walking and gymnastics). However, no difference was found for relative times (no disproportional time effects) and a more complex motor task did not result in more prolonged times. Longer durations in lucid dreams might be related to the lack of muscular feedback or slower neural processing during REM sleep. Future studies should explore factors that might be associated with prolonged durations.

Electrophysiological indices of response inhibition in a Go/NoGo task predict self-control in a social context.

Recent research demonstrates that response inhibition-a core executive function-may subserve self-regulation and self-control. However, it is unclear whether response inhibition also predicts self-control in the multifaceted, high-level phenomena of social decision-making. Here we examined whether electrophysiological indices of response inhibition would predict self-control in a social context. Electroencephalography was recorded as participants completed a widely used Go/NoGo task (the cued Continuous Performance Test). Participants then interacted with a partner in an economic exchange game that requires self-control. Results demonstrated that greater NoGo-Anteriorization and larger NoGo-P300 peak amplitudes-two established electrophysiological indices of response inhibition-both predicted more self-control in this social game. These findings support continued integration of executive function and self-regulation and help extend prior research into social decision-making processes.

Measurement of kT splitting scales in W→lv events at sqrt(s)=7 TeV with the ATLAS detector

A measurement of splitting scales, as defined by the kT clustering algorithm, is presented for final states containing a W boson produced in proton-proton collisions at a centre-of-mass energy of 7 TeV. The measurement is based on the full 2010 data sample corresponding to an integrated luminosity of 36 pb(-1) which was collected using the ATLAS detector at the CERN Large Hadron Collider. Cluster splitting scales are measured in events containing W bosons decaying to electrons or muons. The measurement comprises the four hardest splitting scales in a k(T) cluster sequence of the hadronic activity accompanying the W boson, and ratios of these splitting scales. Backgrounds such as multi-jet and top-quark-pair production are subtracted and the results are corrected for detector effects. Predictions from various Monte Carlo event generators at particle level are compared to the data. Overall, reasonable agreement is found with all generators, but larger deviations between the predictions and the data are evident in the soft regions of the splitting scales.