Effects of task modality, length and complexity on time for activities in lucid dreams

Introduction: Nocturnal dreams can be considered as a kind of simulation of the real world on a higher cognitive level (Erlacher & Schredl, 2008). Within lucid dreams, the dreamer is aware of the dream state and thus able to control the ongoing dream content. Previous studies could demonstrate that it is possible to practice motor tasks during lucid dreams and doing so improved performance while awake (Erlacher & Schredl, 2010). Even though lucid dream practice might be a promising kind of cognitive rehearsal in sports, little is known about the characteristics of actions in lucid dreams. The purpose of the present study was to explore the relationship between time in dreams and wakefulness because in an earlier study (Erlacher & Schredl, 2004) we found that performing squads took lucid dreamers 44.5 % more time than in the waking state while for counting the same participants showed no differences between dreaming and wakefulness. To find out if the task modality, the task length or the task complexity require longer times in lucid dreams than in wakefulness three experiments were conducted. Methods: In the first experiment five proficient lucid dreamers spent two to three non-consecutive nights in the sleep laboratory with polysomnographic recording to control for REM sleep and determine eye signals. Participants counted from 1-10, 1-20 and 1-30 in wakefulness and in their lucid dreams. While dreaming they marked onset of lucidity as well as beginning and end of the counting task with a Left-Right-Left-Right eye movement and reported their dreams after being awakened. The same procedure was used for the second experiment with seven lucid dreamers except that they had to walk 10, 20 or 30 steps. In the third experiment nine participants performed an exercise involving gymnastics elements such as various jumps and a roll. To control for length of the task the gymnastic exercise in the waking state lasted about the same time as walking 10 steps. Results: As a general result we found – as in the study before – that performing a task in the lucid dream requires more time than in wakefulness. This tendency was found for all three tasks. However, there was no difference for the task modality (counting vs. motor task). Also the relative time for the different lengths of the tasks showed no difference. And finally, the more complex motor task (gymnastic routine) did not require more time in lucid dreams than the simple motor task. Discussion/Conclusion: The results showed that there is a robust effect of time in lucid dreams compared to wakefulness. The three experiments could not explain that those differences are caused by task modality, task length or task complexity. Therefore further possible candidates needs to be investigated e.g. experience in lucid dreaming or psychological variables. References: Erlacher, D. & Schredl, M. (2010). Practicing a motor task in a lucid dream enhances subsequent performance: A pilot study. The Sport Psychologist, 24(2), 157-167. Erlacher, D. & Schredl, M. (2008). Do REM (lucid) dreamed and executed actions share the same neural substrate? International Journal of Dream Research, 1(1), 7-13. Erlacher, D. & Schredl, M. (2004). Time required for motor activity in lucid dreams. Perceptual and Motor Skills, 99, 1239-1242.

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.

Effects of sleep fragmentation on the arousability to resistive loading in NREM and REM sleep in normal men

STUDY OBJECTIVE: In healthy subjects, arousability to inspiratory resistive loading is greater during rapid eye movement (REM) sleep compared with non-REM (NREM) sleep but is poorest in REM sleep in patients with sleep apnea. We therefore examined the hypothesis that sleep fragmentation impairs arousability, especially from REM sleep. DESIGN: Two blocks of 3 polysomnographies (separated by at least 1 week) were performed randomly. An inspiratory-loaded night followed either 2 undisturbed control nights (LN(C)) or 2 acoustically fragmented nights (LN(F)) SETTING: Sleep laboratory. PARTICIPANTS: Sixteen healthy men aged 20 to 29 years. INTERVENTIONS: In both loaded nights, an inspiratory resistive load was added via a valved facemask every 2 minutes during sleep and turned off either when arousal occurred or after 2 minutes. MEASUREMENTS AND RESULTS: During LN(F), arousability remained significantly greater in REM sleep (71% aroused within 2 minutes) compared with stage 2 (29%) or stage 3/4 (16%) sleep. After sleep fragmentation, arousability was decreased in stage 2 sleep (LN(F): 29%; LN(C): 38%; p < .05) and low in early REM sleep, increasing across the night (p < .01). In stage 3/4 sleep, neither an attenuation nor a change across the night was seen after sleep fragmentation. CONCLUSIONS: Mild sleep fragmentation is already sufficient to attenuate arousability in stage 2 sleep and to decrease arousability in early, compared with late, REM sleep. This means that sleep fragmentation affects the arousal response to increasing resistance and that the effects are different in stage 2 and REM sleep. The biologic reason for this increase in the arousal response in REM sleep across the night is not clear.

Quantifying the periodicty of Inter Movement Intervals of Leg Movements

ims: Periodic leg movements in sleep (PLMS) are a frequent finding in polysomnography. Most patients with restless legs syndrome (RLS) display PLMS. However, since PLMS are also often recorded in healthy elderly subjects, the clinical significance of PLMS is still discussed controversially. Leg movements are seen concurrently with arousals in obstructive sleep apnoea (OSA) may also appear periodically. Quantitative assessment of the periodicity of LM/PLM as measured by inter movement intervals (IMI) is difficult. This is mainly due to influencing factors like sleep architecture and sleep stage, medication, inter and intra patient variability, the arbitrary amplitude and sequence criteria which tend to broaden the IMI distributions or make them even multi-modal. Methods: Here a statistical method is presented that enables eliminating such effects from the raw data before analysing the statistics of IMI. Rather than studying the absolute size of IMI (measured in seconds) we focus on the shape of their distribution (suitably normalized IMI). To this end we employ methods developed in Random Matrix Theory (RMT). Patients: The periodicity of leg movements (LM) of four patient groups (10 to 15 each) showing LM without PLMS (group 1), OSA without PLMS (group 2), PLMS and OSA (group 3) as well as PLMS without OSA (group 4) are compared. Results: The IMI of patients without PLMS (groups 1 and 2) and with PLMS (groups 3 and 4) are statistically different. In patients without PLMS the distribution of normalized IMI resembles closely the one of random events. In contrary IMI of PLMS patients show features of periodic systems (e.g. a pendulum) when studied in normalized manner. Conclusions: For quantifying PLMS periodicity proper normalization of the IMI is crucial. Without this procedure important features are hidden when grouping LM/PLM over whole nights or across patients. The clinical significance of PLMS might be eluded when properly separating random LM from LM that show features of periodic systems.

Testing the involvement of the prefrontal cortex in lucid dreaming: A tDCS study

Recent studies suggest that lucid dreaming (awareness of dreaming while dreaming) might be associated with increased brain activity over frontal regions during rapid eye movement (REM) sleep. By applying transcranial direct current stimulation (tDCS), we aimed to manipulate the activation of the dorsolateral prefrontal cortex (DLPFC) during REM sleep to induce lucid dreaming. Nineteen participants spent three consecutive nights in a sleep laboratory. On the second and third nights they randomly received either 1 mA tDCS for 10 min or sham stimulation during each REM period starting with the second one. According to the participants' self-ratings, tDCS over the DLPFC during REM sleep increased lucidity in dreams. The effects, however, were not strong and found only in frequent lucid dreamers. While this indicates some preliminary support for the involvement of the DLPFC in lucid dreaming, further research, controlling for indirect effects of stimulation and including other brain regions, is needed.

SMARTnet: First Experience of Setting Up a Telescope System to Survey the Geostationary Ring

Space debris in geostationary orbits may be detected with optical telescopes when the objects are illuminated by the Sun. The advantage compared to Radar can be found in the illumination: radar illuminates the objects and thus the detection sensitivity depletest proportional to the fourth power of the d istance. The German Space Operation Center, GSOC, together with the Astronomical Institute of the University of Bern, AIUB, are setting up a telescope system called SMARTnet to demonstrate the capability of performing geostationary surveillance. Such a telescope system will consist of two telescopes on one mount: a smaller telescope with an aperture of 20cm will serve for fast survey while the larger one, a telescope with an aperture of 50cm, will be used for follow-up observations. The telescopes will be operated by GSOC from Oberpfaffenhofen by the internal monitoring and control system called SMARTnetMAC. The observation plan will be generated by MARTnetPlanning seven days in advance by applying an optimized planning scheduler, taking into account fault time like cloudy nights, priority of objects etc. From each picture taken, stars will be identified and everything not being a star is treated as a possible object. If the same object can be identified on multiple pictures within a short time span, the trace is called a tracklet. In the next step, several tracklets will be correlated to identify individual objects, ephemeris data for these objects are generated and catalogued . This will allow for services like collision avoidance to ensure safe operations for GSOC’s satellites. The complete data processing chain is handled by BACARDI, the backbone catalogue of relational debris information and is presented as a poster.

The spectrum of the non-rapid eye movement sleep electroencephalogram following total sleep deprivation is trait-like

The sleep electroencephalogram (EEG) spectrum is unique to an individual and stable across multiple baseline recordings. The aim of this study was to examine whether the sleep EEG spectrum exhibits the same stable characteristics after acute total sleep deprivation. Polysomnography (PSG) was recorded in 20 healthy adults across consecutive sleep periods. Three nights of baseline sleep [12 h time in bed (TIB)] following 12 h of wakefulness were interleaved with three nights of recovery sleep (12 h TIB) following 36 h of sustained wakefulness. Spectral analysis of the non-rapid eye movement (NREM) sleep EEG (C3LM derivation) was used to calculate power in 0.25 Hz frequency bins between 0.75 and 16.0 Hz. Intraclass correlation coefficients (ICCs) were calculated to assess stable individual differences for baseline and recovery night spectra separately and combined. ICCs were high across all frequencies for baseline and recovery and for baseline and recovery combined. These results show that the spectrum of the NREM sleep EEG is substantially different among individuals, highly stable within individuals and robust to an experimental challenge (i.e. sleep deprivation) known to have considerable impact on the NREM sleep EEG. These findings indicate that the NREM sleep EEG represents a trait.