Lucid dreaming: Am I doing it wrong? – What if we told you that the key ingredient for lucid dreaming lies in your grey matter?

Lucid dreaming: Am I doing it wrong? - What if we told you that the key ingredient for lucid dreaming lies in your grey matter?

More or less, every person is dreaming. Others may be able to recall their dreams, whereas some people do not. However, there is a great distinction between the types of dreams one can experience. Regardless of the content of a dream (from a simple routine to a great cinematic adventure full of joy or terror), dreams are also characterized by their intensity, including vividness and lucidity.

Lucid dreaming is characterized as a realistic experience during REM sleep, where dreamers are aware of their mental state and act with volition (Hearne, 1978; La Berge et al., 1981), in comparison with a common dream, where dreamers are not aware that they are dreaming and are not acting voluntarily in their personal adventure. In addition, lucid dreaming can be experienced by a smaller number of dreamers compared to normal REM dreams (Schredl and Erlacher, 2011). However, what makes lucid dreaming different than vivid or common dreams, apart from the awareness and volition? This is the point, where researchers come to undertake the case. According to Filevich et al. (2015), lucid dreaming underlies metacognitive processes.

Metacognition refers to the ability of one being aware of his/her own mental states (Schooler, 2002). Metacognitive ability has been associated with prefrontal cortical regions of the brain. For instance, visual metacognition has been linked with grey matter (GM) in Brodman Area 10 (anterior prefrontal cortex), which is involved in several executive functions, such as memory recall and strategic processes. Dreaming in general has shown not to be accessible to metacognitive monitoring, such as critical thinking, insight of mental states and volition (Hobson and Pace-Schott, 2002). However, when metacognitive processes occur during dreams, they have been shown to be associated with an increased activation in prefrontal cortical areas, which in common REM sleep has shown to decrease (Maquet et al., 1996).

Furthermore, researchers are able to study lucid dreaming even during wakefulness when some of its enable mechanisms are constant and trait-like. There is a significant amount of studies supporting an association between lucid dreaming and personality traits, specifically openness to new experiences and vivid imagination (Patrick and Durndell, 2004; Schredl and Erlacher, 2004).   

Consequently, researcher E. Filevich from the Max Planck Institute for Human Development in Berlin, along with her colleagues hypothesized that lucid dreaming underlies metacognitive processes, which according to literature, would make a neural activation distinction between lucid dreamers and non-lucid dreamers. Researchers thus, hypothesized that lucid dreamers would demonstrate a difference in GM volume in prefrontal cortical areas, as well as a difference in the activation of those areas during metacognitive monitoring compared to non-lucid dreamers.

Filevich et al. (2015) collected a sample of sixty-three healthy participants with different lucid dreaming frequency, including both males and females, dividing them into two groups in accordance with their lucid dreaming frequency: high-lucid dreamers and low-lucid dreamers. At the first phase of the experiment, participants completed a thought-monitoring task (adapted from Smallwood et al., 2008; Christoff et al., 2009), where each of the runs was divided in monitor and non-monitor condition, which was used as control. In the monitor condition, participants completed eleven minutes runs of a thought monitoring task in a MRI scanner, where they were fixating on a white cross appeared on black background. After a small period of twenty to forty seconds, a visual analogue scale appeared on the screen with two extremes including internally oriented thoughts labelled as ‘INT’, and externally oriented thoughts labelled as ‘EXT’, where participants were pressing either one of the two right-handed buttons to move a cursor on the ‘INT’ or ‘EXT’ (See Figure 1).

Figure 1: MRI monitor task trials (monitor, non-monitor tasks). Monitor group slides cursor towards ‘INT’ and ‘EXT’ to indicate how internally or externally their thoughts were. Non-monitor group slides cursor to match the target circle (retrieved from Filevich et al., 2015).

Researchers defined ‘INT’ as thoughts related to internal environment, such as thinking about plans of the day, or remembering past events, and ‘EXT’ as external environment thoughts, such as scanner noise. Participants then, used their left hand on button box to give their response. In the non-monitor condition, participants moved the cursor to match a white circle target, ignoring the ‘INT’ and ‘EXT’ signs. Finally, participants of monitor condition were asked to evaluate their own thoughts and provide judgements for the ‘INT’ and ‘EXT’ thoughts compared to binary responses of the non-monitor condition. At the second phase of the experiment, participants were asked to complete the LuCiD scale (Voss et al., 2013) regarding their most recent lucid dream, which investigated aspects of insight, memory, control, positive and negative emotions and vividness in dreams. However, because LuCiD scale does not test the frequency of lucid dreaming, researchers asked participants to complete this scale each morning, for a week, referring specifically on their previous night dream. Flevich et al., computed the frequency and quality of lucid dreaming, coming up with the term ‘trait-lucidity’ to describe the quality and quantity of lucid dreaming capability. Finally, researchers also included public and private self-consciousness, and visual imagery scales in order to gather a greater picture of lucid dreaming and metacognition ability.

Figure 2: GM volume differences between high-lucidity and low-lucidity groups in prefrontal cortical areas, hippocampus, and ACC (retrieved from Filevich et al., 2015).

Results of the study have shown to verify the hypotheses of researchers. MRI scanning results suggested that high lucidity group demonstrated greater GM volume in prefrontal cortical areas (BA9/10), as well as in hippocampus, right and left anterior cingulate cortex (ACC), and left supplementary motor area than low-lucidity group (See Figure 2). Moreover, monitoring related BOLD activity, suggested that the two groups were differentially involved in thought monitoring task, which was a specific event attributed to BA9/10 areas.

Researchers explained that although they did not find any significant differences between high-lucidity dreamers and low-lucidity dreamers on monitoring tasks, high-lucidity group tended to show a greater difference between the monitor and non-monitor tasks, suggesting that the corresponding patterns of the brain activity in high-lucidity group might be more clear between conditions than in low-lucidity group, demonstrating thus for the first time a neural connection between metacognitive mechanisms and lucid dreaming.

Moreover, Flavich et al., suggest that BA9/10 areas play a significant role in metacognition, especially in self-reflection and conscious switching between internally and externally directed cognition, which also occurs during lucid dreaming. Indeed, fMRI studies have shown an increased activation of BA9/10 areas to be related to dream lucidity. Furthermore, results of the study suggested a greater GM volume in left hippocampus in high-lucidity group, which explains that greater hippocampal GM allows for a greater acknowledgement of one that is dreaming, gaining thus volitional control.

In conclusion, Filevich et al. study, suggests that people with high lucid dreaming frequency, demonstrate greater GM volume in prefrontal cortical areas than those with low lucidity frequency, supporting also a greater GM volume in the left hippocampus, which enable the dreamer to gain insight that is dreaming and gain volitional control. Results of the study show for the first time the underlying neural mechanisms of metacognition that are related to lucid dreaming capability. Nevertheless, there are several suggested ways by research in order to increase GM and thus enhance metacognition, including physical activity such as yoga (Froeliger, Garland and McClernon, 2012) and walking (Erickson et al., 2010), mindfulness meditation (Holzel et al., 2011), eating breakfast (Taki et al., 2011), omega 3 consumption (Raji et al., 2014), learning and training (Draganski et al., 2004), and playing action video games (Gong et al., 2015, Kuhn et al., 2014). Therefore, if you have been trying for ages to experience the ‘freedom’ of your own volition in your dreams, you should definitely consider your brain and lifestyle. It is never too late to gain a bit of grey matter volume, is it?       

 

References

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  • Erickson, K., I., Raji, C., A., Lopez, O., L., Becker, J., T., Rosano, C., Newman, A., B. et al. (2010). Physical activity predicts grey matter volume in late adulthood. Neurology, 75(16), 1415-1422.
  • Filevich, E., Dresler, M., Brick, T., R. & Kuhn, S. (2015). Metacognitive mechanisms underlying lucid dreaming. The Journal of Neuroscience, 35(3), 1082-1088.
  • Froeliger, B., Garland, E., L. & McClernon, D., J. (2012). Yoga meditation practitioners exhibit greater grey matter volume and fewer reported cognitive failures: results of a preliminary voxel-based morphometric analysis. Evidence Based Complement Alternative Medicine.
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  • Taki et al. (2011). Breakfast staple types affect brain grey matter volume and cognitive function in healthy children. PLoS ONE.
  • Voss U, Schermelleh-Engel K, Windt J, Frenzel C, Hobson A (2013) Measuring consciousness in dreams: the lucidity and consciousness in dreamsscale. Conscious Cogn, 22(8), 21.
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  1. Ο/Η Justin Hamilton λέει:

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