From the open-access Frontiers in Psychology: Consciousness Research, researchers from the Max Planck Institute of Psychiatry in Munich looked at the reflective (volitional) aspects of consciousness across three different states - waking, dreaming, lucid dreaming (becoming conscious of the dream while in the dream).

From the abstract:

Overall, experienced volition was comparable for lucid dreaming and wakefulness, and rated significantly higher for both states compared to non-lucid dreaming. However, three subscales showed specific differences across states of consciousness: planning ability was most pronounced during wakefulness, intention enactment most pronounced during lucid dreaming, and self-determination most pronounced during both wakefulness and lucid dreaming. Our data confirm the multifaceted nature of consciousness: different higher-order aspects of consciousness are differentially expressed across different conscious states.

In essence, lucid dreaming is clearly a higher order state of consciousness. Nice research that will hopefully be replicated by others so that lucid dreaming becomes a more widely accepted phenomena.


Full Citation: 
Dresler M, Eibl L, Fischer CFJ, Wehrle R, Spoormaker VI, Steiger A, Czisch M and Pawlowski M. (2014, Jan 2). Volitional components of consciousness vary across wakefulness, dreaming, and lucid dreaming. Frontiers in Psychology: Consciousness Research; 4:987. doi: 10.3389/fpsyg.2013.00987

Volitional components of consciousness vary across wakefulness, dreaming, and lucid dreaming

Martin Dresler, Leandra Eibl, Christian F. J. Fischer, Renate Wehrle, Victor I. Spoormaker, Axel Steiger, Michael Czisch, and Marcel Pawlowski

Max Planck Institute of Psychiatry, Munich, Germany

Abstract 

Consciousness is a multifaceted concept; its different aspects vary across species, vigilance states, or health conditions. While basal aspects of consciousness like perceptions and emotions are present in many states and species, higher-order aspects like reflective or volitional capabilities seem to be most pronounced in awake humans. Here we assess the experience of volition across different states of consciousness: 10 frequent lucid dreamers rated different aspects of volition according to the Volitional Components Questionnaire for phases of normal dreaming, lucid dreaming, and wakefulness. Overall, experienced volition was comparable for lucid dreaming and wakefulness, and rated significantly higher for both states compared to non-lucid dreaming. However, three subscales showed specific differences across states of consciousness: planning ability was most pronounced during wakefulness, intention enactment most pronounced during lucid dreaming, and self-determination most pronounced during both wakefulness and lucid dreaming. Our data confirm the multifaceted nature of consciousness: different higher-order aspects of consciousness are differentially expressed across different conscious states.

Introduction

The ability to engage in volitional behavior has traditionally been closely associated with human consciousness: to freely act implies to make conscious decisions (Dijksterhuis and Aarts, 2010). However, consciousness is not an all-or-nothing phenomenon; its multiple facets differ across species, vigilance states, or health conditions. A striking variation in consciousness is experienced every day during the sleep–wake cycle: during wakefulness, human subjects are normally alert, aware of external and internal stimuli, able to reflect on their perceptions, emotions and thoughts, and capable to volitionally act according to their intentions. While most of these properties of waking consciousness fade during the process of falling asleep, many basal features of consciousness reappear during dreaming. Dream mentation may occur in all sleep stages, but is most intense and vivid during rapid eye movement (REM) sleep (Hobson et al., 2000). The dreamer perceives and interacts with a hallucinated dream environment and often experiences strong emotions (Hobson and Pace-Schott, 2002). However, typical dreaming is deficient of many higher-order aspects of consciousness: the dreaming subject experiences highly impoverished self-reflective capabilities and therefore does not recognize that he is dreaming. Instead of volitionally and systematically acting according to his intentions, the dreamer is a rather passive subject in the chaotic flow of the dream narrative. In contrast, the rare state of lucid dreaming is characterized by full-blown consciousness including all higher-order aspects: the dreamer regains metacognitive abilities and memory, becomes fully aware of his current state of consciousness, and experiences volition and fully realized agency (Metzinger, 2003; Windt and Metzinger, 2007). As phrased by Van Eeden (1913), who coined the term lucid dreaming: “the sleeper remembers his day-life and his own condition, reaches a state of perfect awareness, and is able to direct his attention, and to attempt different acts of free volition.”

On a closer look, however, the situation is less clear: on the one hand, during alert wakefulness, the experience of volitional capabilities may be strikingly impaired as seen, e.g., in pathological cases such as delusions of alien control in schizophrenic patients (Lafargue and Franck, 2009) or in alien hand syndrome (Biran and Chatterjee, 2004). On the other hand, during altered states of consciousness such as hypnosis (Oakley and Halligan, 2013) or even non-lucid REM sleep (Takahara et al., 2006), volitional behavior can be observed. Moreover, lucid dreaming is not an all-or-nothing phenomenon, but might occur in different degrees from pre-lucid reflections to full-blown lucid control dreams (Tyson et al., 1984; Barrett, 1992; Kahan and LaBerge, 1994). Descriptions of higher-order aspects of consciousness in lucid dreaming, including volitional capacities, rely mainly on anecdotal evidence, but have rarely been studied systematically. Two recent exceptions are the Metacognitive, Affective, Cognitive Experience questionnaire (MACE; Kahan and Sullivan, 2012) and the Lucidity and Consciousness in Dreams scale (LuCiD; Voss et al., 2013) which have been used to assess metacognition during different states of consciousness including lucid dreaming.

Here, we assessed different aspects of volition during normal dreaming, lucid dreaming, and wakefulness with an adapted version of the Volitional Components Questionnaire (VCQ; Kuhl and Fuhrmann, 1998) in lucid dreamers. We hypothesized that experienced volition would be generally higher in both wakefulness and lucid dreaming compared to non-lucid dreaming. We exploratively tested if the subscales of the VCQ would differentially vary between the three states of consciousness.

Materials and Methods

Ten healthy subjects (mean age 28.1 ± 9.8 years, age range 19–47 years, five female) recruited at the University of Munich or from a volunteer database of the Max Planck Institute of Psychiatry participated in this study. They all were experienced lucid dreamers with a reported mean frequency of 1.9 ± 0.7 lucid dreams per week. Lucid dreaming ability was verified in five of the subjects in a sleep laboratory with full polysomnographic recordings, exploiting the classical eye signaling technique (LaBerge et al., 1981). For the other five subjects, lucid dreaming ability was assessed by self-report.

To measure volition in different states of consciousness, we adapted the German short version of the VCQ (Selbststeuerungs-Inventar, SSI-K3; Kuhl and Alsleben, 2012). The VCQ is an instrument to measure different aspects of volitional competence; it specifically aims at assessing the subjective experience of volitional components supporting central coordination of goal-maintenance and self-maintenance (Kuhl and Fuhrmann, 1998). The short form includes 13 subscales consisting of four items each. The test subjects have to rate the extent to which the item applies to themselves on a four-point Likert scale from 1 (not at all) to 4 (wholly). The validity of both the long and short versions has been repeatedly demonstrated (Forstmeier and Rüddel, 2008). Since several of the 13 subscales are not meaningfully applicable to the dreaming state, as they, e.g., ask to evaluate time frames of several weeks, we chose to restrict the study to six subscales: self-determination, planning ability, intention enactment, powers of concentration, self-access, and integration. As a measure for the general experience of volitional capacity, an overall score consisting of the mean of all six subscales was calculated. Where necessary, questions were adapted to be applicable to the dreaming state, e.g., the integration subfactor item “On many days I feel the opposite of what I felt before” was changed to “I often feel the opposite of what I felt before.” The sequential order of questions was adopted from the original questionnaire.

Subjects were asked to complete the questionnaire at least once for each of the three states of consciousness: in the morning after awakening from a non-lucid dream, in the morning after awakening from a lucid dream, and after a normal day of wakefulness, i.e., before going to bed in the evening. Specifically, subjects were instructed to rate their general experience during the respective state, using the preceding dream or day as an anchor or reminder thereof. For those individuals who completed the questionnaire more than once for one of the three states of consciousness, we used the mean score of the given state for further analysis. For wakefulness, four subjects contributed multiple questionnaires adding up to a total of 15; for non-lucid dreaming, five subjects contributed multiple questionnaires adding up to a total of 20; for lucid dreaming, four subjects contributed multiple questionnaires adding up to a total of 14.

For statistical analysis of the VCQ overall score, we performed a repeated measures ANOVA with the three factor levels non-lucid dreaming, lucid dreaming, and wakefulness. For specific comparisons between the three states of consciousness, we performed post hoc two-sided paired t-tests. For statistical analysis of the six subscales, we first performed a repeated measures MANOVA with the three factor levels non-lucid dreaming, lucid dreaming, and wakefulness. For further analysis of the subscales that revealed significant results in the following ANOVAs, we subsequently performed two-sided paired t-tests to analyze specific differences between the states of consciousness. All significance levels were set at p = 0.05.

Results

The ANOVA for the VCQ overall score revealed a significant effect of the state of consciousness (F2,18 = 4.4, p = 0.027, η2 = 0.33). Subsequent t-tests demonstrated that both wakefulness (t9 = 2.7, p = 0.026, r = 0.66) and lucid dreaming (t9 = 2.3, p = 0.044, r = 0.61) differed from non-lucid dreaming, however not from each other (t = 0.5, p = 0.618, r = 0.17). Hence, volition was strongly experienced during wakefulness and lucid dreaming, but considerably less so during non-lucid dreaming. For comparisons of the overall results, see Table 1.

TABLE 1

TABLE 1. Experienced volition during wakefulness, lucid dreaming and non-lucid dreaming according to theVolitional Components Questionnaire (VCQ) overall and subscale results.

The MANOVA for the subscales of the VCQ revealed a significant effect of the state of consciousness (F12,26 = 8.9, p < 0.001, η2 = 0.80), which turned out to be significant for the subscales self-determination (F2,18 = 15.4, p < 0.001, η2 = 0.63), planning ability (F2,18 = 31.2, p < 0.001, η2 = 0.78), and intention enactment (F2,18 = 7.3, p = 0.007, η2 = 0.45), but not for powers of concentration (F2,18 = 0.1, p = 0.942, η2 = 0.01), self-access (F2,18 = 0.6, p = 0.573, η2 = 0.06), or integration (F2,18 = 0.7, p = 0.503, η2 = 0.07). Subsequent t-tests demonstrated that self-determination was significantly more pronounced during both wakefulness (t9 = 5.6, p < 0.001, r = 0.88) and lucid dreaming (t9 = 5.2, p < 0.001, r = 0.87) compared to non-lucid dreaming, however did not differ between the two former states of consciousness (t9 = 0.9, p = 0.461, r = 0.28). Planning ability was most pronounced during wakefulness compared to both lucid (t9 = 6.5, p < 0.001, r = 0.91) and non-lucid dreaming (t9 = 5.7, p < 0.001, r = 0.88), but did not differ between the latter two states (t9 = 0.8, p = 0.407, r = 0.25). Intention enactment turned out to be most pronounced during lucid dreaming compared to both wakefulness (t9 = 3.9, p = 0.004, r = 0.79) and non-lucid dreaming (t9 = 3.2, p = 0.011, r = 0.73), while the latter two states did not differ from each other (t9 = 0.2, p = 0.862, r = 0.06). For subscale comparisons, see Table 1.

Discussion

Comparing the experience of volition as assessed by the VCQ during three different states of consciousness, we found volition to be generally most pronounced during both wakefulness and lucid dreaming as compared to non-lucid dreaming. A more differential picture appeared when the subscales of the VCQ were analyzed separately.

For both lucid dreaming and wakefulness, self-determination was rated higher than for non-lucid dreaming. This subscale is probably the most prototypical volitional component, asking to what degree the subject experiences being able to act freely according to his will. The fact that the result of this subscale is in line with the overall score confirms the hypothesis that volition is generally more pronounced during both wakefulness and lucid dreaming compared to non-lucid dreaming.

For wakefulness, planning ability was rated higher than for both lucid and non-lucid dreaming. This subscale asks for how well organized the subject pursues his plans and intentions. The fact that this subfactor is most pronounced during wakefulness compared to both dreaming states might be interpreted as a sign for a more spontaneous execution of intentions during dreaming.

For lucid dreaming, intention enactment was rated higher than for both wakefulness and non-lucid dreaming. This factor asks for how promptly and determined intentions are executed. On first sight, this seems to be a surprising finding, demonstrating that a component of volition is more strongly experienced during a state of sleep than during wakefulness. However, on second sight a strong feeling of being able to enact one’s intentions during lucid dreaming seems reasonable, as the dreamer is aware that in contrast to the constraints of waking life, during dreams all potential obstacles are not real and hence can easily be overcome. This interpretation would also be in line with the former finding of a comparably low level of experienced planning ability during lucid dreaming: organized planning might be possible during lucid dreaming in principle, however is rarely actually performed since intention execution is possible without such effort.

Neither powers of concentration, nor self-access, nor integration differed between the three states of consciousness. The first of these subfactors asks for how easily the subject gets distracted from his current line of intentional thought. The failure to find any difference between the three states of consciousness is rather surprising, since concentration and goal-directed thinking are generally thought to be strongly impaired during non-lucid dreaming (Hobson and Pace-Schott, 2002; Metzinger, 2003). The subfactor self-access asks for the quality of access to one’s intentions and feelings in stressful situations. It might be speculated that in such situations, also during wakefulness and lucid-dreaming, self-reflection might be impaired, thereby leveling potential differences of self-access that would occur in non-stressed situations. The subfactor integration asks for the occurrence of seemingly contradictory behaviors and emotions. It is rather surprising that non-lucid dreaming does not differ from the other two states, since incongruities and inconsistencies are generally associated most strongly with the dreaming state (Mamelak and Hobson, 1989). However, such inconsistencies are typically attributed to the dream plot rather than to the dreamer, whose mental complexity is narrow and “single-minded” compared to a much broader repertoire of behaviors and thoughts experienced during wakefulness or lucid dreaming (Rechtschaffen, 1978). Hence, compared to a bizarre and highly incongruent dream plot, the single-mindedness of dream cognition might be experienced as relatively straightforward.

In the following, we will try to embed the topic of volition in a broader discussion of the multiple facets and neural correlates of human consciousness.

Basal Vs. Higher-Order Aspects of Consciousness

The enquiry into consciousness has long been the domain of philosophy, however recent years witnessed a growing interest also among neuroscientists in the problems surrounding consciousness. While there is still little agreement on a specific characterization or definition, it seems clear that consciousness is a multifaceted concept, with its different aspects varying dramatically between species, vigilance states, or health conditions. A common categorization differentiates between basal and higher-order aspects of consciousness: the concept of basal (or primary) consciousness comprises perceptions and emotions, whereas higher-order (or secondary) consciousness is proposed to constitute reflections on these (for a review cf. Morin, 2006). As phrased by Edelman (2003, p. 5521):“Higher-order consciousness allows its possessors to go beyond the limits of the remembered present of primary consciousness. An individual’s past history, future plans, and consciousness of being conscious all become accessible.”

A striking variation in consciousness is experienced every day during the sleep–wake cycle: awake human subjects are normally alert, aware of external and internal stimuli, and able to reflect on their perceptions and emotions and to volitionally act according to their intentions. These experiences and capabilities fade during the process of falling asleep, however the progress through the sleep cycle is associated with a reinstatement of essential features of consciousness: REM sleep evokes the most vivid and intense dreams, in which the sleeper perceives a hallucinated environment and often experiences strong emotions.

However, the dreaming state instantiates only basal aspects of consciousness, being deficient in reflective thought, metacognition and volitional capabilities: the internally generated perceptions and emotions experienced during dreaming typically show many cognitive abnormalities, with a bizarre dream plot full of gaps, delusional thought, and a complete lack of insight into the current condition (Hobson and Pace-Schott, 2002; Metzinger, 2003). Rechtschaffen (1978) called this persistence of a single train of related thoughts and images without disruption from other simultaneous thoughts or reflections the “single-mindedness” of dreams. He pointed out that without reflectiveness, there could hardly be volitional control. Nevertheless, some rudimentary processes of reflection and volition have been reported to occur during dreaming (Kahan et al., 1997; Wolman and Kozmová, 2007), even though less often than for waking episodes (Kahan et al., 1997; Voss et al., 2013). Our results confirm these findings, suggesting a generally weaker experience of volition during non-lucid dreaming compared to wakefulness, however with some components being similarly expressed during wakefulness and dreaming.

Lucid Dreaming as Higher-Order Consciousness

In contrast to the restricted consciousness of normal dreaming, the rare state of lucid dreaming is characterized by full-blown consciousness including all higher-order aspects: the sleeping subject is no longer deluded by the dream narrative, but becomes fully aware of the true nature of his current state of consciousness (LaBerge et al., 1981). This wake-like intellectual clarity comprises a restored access to memory functions including increased availability of self-related information, and fully realized agency, enabling the dreamer to volitionally execute his intentions within the dream narrative (Metzinger, 2003; Windt and Metzinger, 2007). Lucid dreaming can be trained (LaBerge, 1980; Purcell et al., 1986), which makes this phenomenon a promising research topic despite its rarity in untrained subjects (Schredl and Erlacher, 2011).

In comparing lucid and non-lucid REM sleep, the distinction between basal and higher-order consciousness is of great value, since the contrast between lucid and non-lucid dreaming strikingly mirrors the conceptual contrast between basal and higher-order consciousness (Dresler et al., 2009; Hobson, 2009): while all basal features of consciousness like perceptions and emotions are present in normal dreaming, metacognitive reflections and the insight into the current state of consciousness is – by definition – bound to lucidity. Since also in non-lucid dream reports some reflective thoughts have been reported and since also during daydreaming and other phases of wakefulness active reflections are frequently absent, it has been argued that metacognitive activity differs only quantitatively and not qualitatively between dreaming and waking consciousness (Kahan et al., 1997; Kahan and LaBerge, 2011). However, this absence is only a “local,” not global feature of such phases: it is hardly imaginable, at least for non-pathological cases, that the day-dreaming subject misinterprets the daydream for reality once paying attention to his current state. For the dreaming state, in contrast, this is completely normal – unless the dreamer eventually achieves lucidity through these “prelucid” reflections (Tyson et al., 1984).

Lucid dreaming may even be critical to fully understanding the neural correlates of higher-order consciousness, because in contrast to, e.g., coma–wake, anesthesia–wake, or sleep–wake comparisons, there is no major shift in vigilance state as defined by formal neurophysiological criteria: lucid REM sleep still is REM sleep proper according to the classical Rechtschaffen and Kales (1968) or new AASM (Iber et al., 2007) sleep scoring criteria. When compared to wakefulness, pathological or pharmaceutically induced loss of consciousness also reduces the brain’s basal metabolism, as does deep sleep. Dreaming therefore provides the only phenomenon we know of, that can contrast basal consciousness with full-blown higher-order consciousness within the same vigilance level (Spoormaker et al., 2010), allowing for comparison of cerebral activity by means of EEG, PET, or fMRI without differences in the basal activity state.

Neural Correlates of Lucid Dreaming

On the phenomenological level, REM sleep is the sleep stage associated with the most vivid sleep mentation (Fosse et al., 2001). On the neurobiological level, it is associated with strong activation of visual association areas and limbic structures such as the amygdala, while the dorsolateral prefrontal cortex (DLPFC) and parietal areas are deactivated (Maquet et al., 1996; Braun et al., 1998). This activation pattern has been proposed to underlie the visual hallucinations, emotional intensifications, and metacognitive impairments experienced in most dreams (Hobson and Pace-Schott, 2002; Schwartz and Maquet, 2002). In particular diminished activity in the DLPFC during REM sleep has been related to cognitive aspects of dreaming such as impaired directed thought, volitional control, and a complete lack of insight into the current state of consciousness (Hobson and Pace-Schott, 2002; Schwartz and Maquet, 2002).

In contrast to normal dreaming, the regaining of wake-like metacognitive capabilities during lucid dreaming is related to increased EEG gamma-band activity over dorsolateral prefrontal areas (Voss et al., 2009). fMRI data have confirmed increased activation of the DLPFC during lucid dreaming, as well as of bilateral frontopolar and parietal areas (Dresler et al., 2012). These brain regions have been related to self-focused metacognitive evaluation (Stuss et al., 2001; Schmitz et al., 2004), supervisory modes (Burgess et al., 2007), and self-referential processing in general including the experience of agency (Cavanna and Trimble, 2006). Their activation during lucid dreaming is in line with the notion that lucidity consists in an increased availability of self-related information, leading to a much higher degree of coherence and stability of the phenomenal self during lucid dreaming (Metzinger, 2003). Our findings fit well into this literature, demonstrating that volition is similarly experienced during wakefulness and lucid dreaming as compared to non-lucid dreaming.

Neural Correlates of Volition

As is the case for consciousness, volition is a multifaceted concept, hence not traceable to one specific brain region. However, several cortical areas have repeatedly been demonstrated to be related to volitional processes. While most studies show motor areas to be involved in volitional action, this research mainly focuses on willed motor actions (Haggard, 2008), which seem to share similar neural substrates during wakefulness and dreaming (Erlacher and Schredl, 2008; Dresler et al., 2011). In contrast, more general or abstract intentions are thought to rely on the dorsolateral prefrontal cortex (Roskies, 2010). In addition, early stages of intentional action have been related to anterior prefrontal brain regions. Such processing of complex information, only broadly determined by specific task demands, is then thought to travel posteriorly to enter later stages of intentional action (Brass et al., 2013). The subjective experience of volitional agency has been associated with parietal brain regions (Roskies, 2010). Hence, in line with our findings, general aspects of volitional control and the subjective experience thereof rely on brain regions that are highly active during lucid compared to non-lucid dreaming.

Consciousness in Humans and Non-Human Animals

Higher-order aspects of consciousness are traditionally thought to be most pronounced in humans (Edelman, 2001). In particular volitional capabilities have been proposed to be a distinctive human attribute (Dijksterhuis and Aarts, 2010; Frith, 2013). If the contrast between ordinary and lucid dreaming mirrors that between basal and higher-order consciousness, data on the neural correlates of dream lucidity might shed new light on this debate. Indeed it turns out that cerebral regions showing increased activity during lucid dreaming also show extensive volumetric expansion in humans as compared to non-human primates (Van Essen and Dierker, 2007; see Figure 1). Recently the hypothesis was proposed that only animals possessing higher-order aspects of consciousness may develop psychotic states – “in other words an animal needs to have a highly developed mind in order to go out of it” (Hobson and Voss, 2011, p. 993). Neuroimaging data on lucid dreaming support this claim: areas activated during lucid dreaming (Dresler et al., 2012) do not only mirror human vs. non-human primate brain differences (Van Essen and Dierker, 2007), but also show striking overlap with brain areas associated with insight deficits in psychosis (Dresler et al., in revision).

FIGURE 1 

FIGURE 1. Brain areas subserving the transition from basal to higher-order consciousness in REM sleep dreaming mirror those with strongest volumetric expansion in humans compared to non-human primates. Left: during lucid dreaming, the dorsolateral prefrontal and frontopolar cortices, parietal lobules, and inferior/middle temporal gyri among other cortical regions are strongly activated as compared with non-lucid REM sleep (republished with permission of the American Academy of Sleep Medicine, from Dresler et al. (2012); permission conveyed through Copyright Clearance Center, Inc.). Right: neuroanatomical differences between humans and non-human primates (Van Essen and Dierker, 2007; reprint with permission of Cell Press). Color-coded are regional volumetric expansions in the human relative to the macaque brain hot colors depict up to a 32-fold volumetric increase in humans. Right lateral view.

Limitations
A couple of limitations have to be kept in mind for the interpretation of our study’s results. First, we used an adapted version of VCQ that was not specifically validated for its use in different states of consciousness. This applies in particular to the overall score combining the six subscales. While the original version was created to evaluate time frames of several weeks, for our adapted version only items were chosen that are applicable to shorter episodes like dreams. Second, whereas the ratings for lucid and non-lucid dreaming were collected after awakening from the respective dream phase in the early morning, the ratings for wakefulness were collected after a full day of wakefulness in the evening. Thus, the length of the rated episodes differed, and it cannot be excluded that chronobiological influences affected the ratings. Third, the order of data collection was not randomized, but started for all subjects with the wakefulness ratings, followed by the non-lucid dreaming ratings, which were finally followed by the lucid dreaming ratings. Thus, order effects might have influenced the results. However, several subjects completed more than one questionnaire and did so after a complete round of ratings. Since the scores from these repeated ratings did not differ from the first ratings, it is rather unlikely that rating order affected the results. Fourth, gender differences for content and recall have been reported for non-lucid (Schredl et al., 2004) and lucid (Schredl and Erlacher, 2011) dreams, however our small sample size does not allow a reliable analysis of possible gender effects on state-dependent volition. An explorative analysis did not reveal gender effects (p > 0.2) or gender × state interactions (p > 0.4).

Conclusion and Future Directions

Our study confirmed the multifaceted nature of consciousness: volitional components of higher-order consciousness are differentially expressed among different conscious states. On a coarser level, the generally wake-like expression of volition during lucid dreaming is well in line with the neural activity pattern observed during this state. Up until 15 years ago, using lucid dreaming for the study of consciousness was not seen as experimentally advantageous (Crick and Koch, 1998). However, neuroimaging research into the neural correlates of lucid dreaming and its association with metacognitive and volitional processes has proven lucid dreaming to be a highly promising approach for the investigation of higher-order aspects of consciousness. Neural correlates of lucid dreaming show a remarkable overlap with areas and networks subserving self-reflective thought and volitional capabilities. In addition, these areas show the strongest differences between human and non-human primates, strengthening suggestions that higher-order aspects of consciousness are most pronounced in humans.

While research into lucid dreaming is currently hampered by the rarity of the phenomenon, systematic training (Stumbrys et al., 2012), and new technical approaches for its induction like transcranial direct current stimulation (tDCS; Noreika et al., 2010; Stumbrys et al., 2013) might lead to research programs beyond a collection of case studies. In such research programs, subjects might be asked to actively engage in metacognitive processes and volitional acts during lucid dreaming, thereby tracing higher-order consciousness from its state-dependent absence to the regaining of the ability to engage in higher-order conscious thought to its actual execution. Using neuroimaging methods in combination with refined measures of the degree of lucidity, e.g., by exploiting scales that assess several dimensions of volition and insight during dreams (Voss et al., 2013), the specific involvement of several brain regions in distinct higher-order aspects of consciousness may be disentangled. Such studies would further refine the neural correlates underlying the multiple facets of human consciousness.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References available at the Frontiers site

What the Brain’s Default Mode Network Reveals About Self-Reflection

From the Open Access journal Frontiers in Human Neuroscience, this cool article looks at how the brain's default network (the cortical midline structures, or CMS) participates in the creation of self-reflection or self-awareness. Here are the structured involved [emphasis added]:

The set of regions contributing to self-reflection consists primarily of the medial prefrontal cortex (mPFC), encompassing the medial surface of the medial frontal gyrus [Brodmann’s Areas (BAs) 8 and 10], and the medial parietal cortex, roughly encompassing the retrosplenial and posterior aspects of the cingulate cortex, the area bounded at the anterior by the paracentral lobule, and at the posterior by the parieto-occipital sulcus (BAs 23, 31, 7).

The authors propose three possibilities for the role of the CMS in self-reflection:

1. Self may be a powerful, but ordinary case for a cognitive system specialized for thinking about people. 2. The mPFC may serve as a processing “hub,” binding together information from all sensory modalities with internally generated information. 3. The mPFC may serve as a cortical director of thought, helping to guide moment-by-moment conscious processing. 

The authors conclude that the CMSs are "associated with social processing, are developed strongly in humans relative to other animals, and humans travel in much larger social networks than do other animals." Therefore, they speculate that the CMSs "may form the basis of a special neurocognitive system evolved for social processing."


Full Citation:
Moran JM, Kelley WM and Heatherton TF. (2013). What can the organization of the brain’s default mode network tell us about self-knowledge? Frontiers in Human Neuroscience, 7:391. doi: 10.3389/fnhum.2013.00391

What can the organization of the brain’s default mode network tell us about self-knowledge?

Joseph M. Moran 1,2, William M. Kelley 3, and Todd F. Heatherton 3

1. U.S. Army Natick Soldier Research, Development, and Engineering Center, Natick, MA, USA
2. Center for Brain Science, Harvard University, Cambridge, MA, USA
3. Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA 

Abstract

Understanding ourselves has been a fundamental topic for psychologists and philosophers alike. In this paper we review the evidence linking specific brain structures to self-reflection. The brain regions most associated with self-reflection are the posterior cingulate and medial prefrontal (mPFC) cortices, together known as the cortical midline structures (CMSs). We review evidence arguing that self-reflection is special in memory, while noting that these brain regions are often engaged when we think about others in our social worlds. Based on the CMSs’ patterns of connectivity and activity, we speculate about three possible interpretations of their role in supporting self-reflection that are somewhat overlapping, and not intended to be mutually exclusive. First, self may be a powerful, but ordinary case for a cognitive system specialized for thinking about people. Second, mPFC may serve as a processing “hub,” binding together information from all sensory modalities with internally generated information. Third, mPFC may serve as a cortical director of thought, helping to guide moment-by-moment conscious processing. Suggestions are made for future research avenues aimed at testing such possibilities.

Introduction

How do we know what we are like? How do we determine the boundaries between ourselves and the world around us? How do we know what is ours, and what is not? Questions like these have engaged philosophers for millennia, and psychological scientists throughout psychology’s relatively brief history. Great progress has been made by practitioners of these fields, who have recently been joined by neuroscientists bearing the promise of going beyond introspection, self-report, and behavior to the source of our sense of self, the brain. This work is theoretically useful in at least two ways. First, it enables characterization of how the brain implements the psychological process(es) of self-reflection, allowing for links between the neural and psychological levels of analysis. Second, it may suggest new ways to interpret and modify accounts of self-reflection at the psychological-level, allowing neural-level data to influence psychological-level theorizing. Wielding two major empirical breakthroughs, cognitive neuroscientists have made significant headway in understanding how the brain gives rise to a sense of self, revealing surprising knowledge about the organization of the neuronal networks responsible for self-reflection.

The Default Mode Network and Self-Reflection

In brief, these breakthroughs consisted first of the discovery of what has come to be known as the default mode network (Shulman et al., 1997; Raichle et al., 2001), and second of the independent identification that a subset of these brain regions are enlisted when we engage in self-reflection (Gusnard et al., 2001; Johnson et al., 2002; Kelley et al., 2002). To be clear, this network’s involvement is observed most closely during the psychological task of reflecting on one’s personalities and characteristics (self-reflection), rather than during self-recognition, thinking of the self-concept, or thinking about self-esteem, for example. As such, this paper will focus on self at the level of self-reflection and the neural networks responsible for this task. The set of regions contributing to self-reflection consists primarily of the medial prefrontal cortex (mPFC), encompassing the medial surface of the medial frontal gyrus [Brodmann’s Areas (BAs) 8 and 10], and the medial parietal cortex, roughly encompassing the retrosplenial and posterior aspects of the cingulate cortex, the area bounded at the anterior by the paracentral lobule, and at the posterior by the parieto-occipital sulcus (BAs 23, 31, 7). For ease of reference, we will refer to this medial parietal cluster together as posterior cingulate cortex (pCC). These regions have come to be known together as the cortical midline structures (CMSs) (Northoff and Bermpohl, 2004), and are the regions most closely associated with self-reflection in meta-analyses (e.g.,Northoff et al., 2006; Qin and Northoff, 2011).

The default mode network concept arose to explain the puzzling observation that when subjects rest quietly with eyes closed, CMS activity is elevated (as measured by positron emission tomography), along with that of anterior temporal lobes and lateral parietal cortices (Shulman et al., 1997). This set of regions is more active when people rest than when they are engaged in goal-directed tasks, and display functional connectivity: these regions’ activity rises and falls together during the normal course of cognitive engagement and disengagement from the external world (Greicius et al., 2003; Fox et al., 2005). This led Raichle and colleagues to propose that this set of regions formed a default mode network; a network that may serve to generate internal mental stimuli and pay attention to our stream of consciousness, but whose activity is attenuated when we turn our attention to the outside world (as in goal-directed tasks) (Gusnard et al., 2001; Raichle et al., 2001). Following these observations, several labs demonstrated direct overlap between the brain regions engaged during rest and during self-reflection (Wicker et al., 2003; D’Argembeau et al., 2005; Schneider et al., 2008; Whitfield-Gabrieli et al., 2011). This relation is further supported by a meta-analysis (Qin and Northoff, 2011), which reported that the same finding occurred across many studies.

Medial Prefrontal Cortex

Several aspects of these regions’ neuroanatomy may support these well-characterized roles. mPFC is larger than any other prefrontal region in humans (Ongur et al., 2003). By proportion, it covers more of the cortex in humans and has more space available for connections with other supramodal areas than in other primates (Semendeferi et al., 2001). It has a greater density of dendritic spines (69% more on average than primary sensory cortex) and smaller density of cell bodies on the average than other cortical regions, suggesting more complex associative processing (Jacobs et al., 2001). Finally, mPFC is almost exclusively interconnected with other heteromodal processing regions in the prefrontal cortex (Barbas and Pandya, 1989; Petrides and Pandya, 1999), anterior temporal cortex (Amaral and Price, 1984; Morán et al., 1987), and the cingulate gyrus (Morecraft and Van Hoesen, 1993; Arikuni et al., 1994). Most of these connections are reciprocal in nature (Passingham et al., 2002).

These regions are considered to be part of the “social brain”: a network implicated by neuroimaging and lesion work in representing the people that populate our social worlds (Adolphs, 2001; Heatherton, 2011; Lewis et al., 2011). mPFC’s enlargement in humans, preponderance of interconnections rather than cell bodies, and connections with other “social brain” nodes are all features that point toward a role in social abstraction, a skill for which humans are evidently selected (Dunbar, 2009). Indeed, humans form much larger social networks than do other animals (Dunbar, 1998). Lewis et al. (2011) showed further that the size of particular mPFC regions is correlated both with the degree to which we are able to represent multiple others’ viewpoints and the size of our social networks. Underscoring the role of mPFC in social processing in general, and self-processing in specific, a recent meta-analysis further subdivides mPFC into ventral and dorsal aspects (Denny et al., 2012; Wagner et al., 2012), showing that ventral mPFC responds more to self, and dorsal mPFC responds more to others.

Medial Parietal Cortex

Posterior cingulate cortex shares many reciprocal connections with mPFC. In addition, the subregions of pCC are reciprocally connected with one another in a bilateral manner (Cavanna and Trimble, 2006). Along with mPFC, pCC is disproportionately large in humans relative to non-human primates (Goldman-Rakic, 1987). pCC shares many connections with subcortical and cortical regions and serves as “association cortex,” allowing the brain to “integrate both external and self-generated information and to produce much of the mental activity that characterizes Homo sapiens” (Cavanna and Trimble, 2006, p. 568). This set of neuroanatomical features suggests that these regions would be good candidates for those able to perform the inward-focusing and self-generation of stimuli that constitute mental activity when we are not focused on the external world (Mason et al., 2007; Smallwood et al., 2008). That these regions are disproportionately developed in humans, and that humans congregate in the largest social networks, suggests that much of this mental activity at rest might be about ourselves and others.

If we were to plan to design a system that would be able to retain information about itself, to determine what is and is not self, and to update that store of information in a flexible and goal-dependent manner, we could do worse than to outfit it with the array of connections and features that are possessed by the CMS. While the neuroanatomical evidence is certainly suggestive of a set of regions that are specialized for self-reflection, stronger evidence has emerged in cognitive neuroscience. Work that we and others have done has repeatedly demonstrated that reflecting on the self engages the CMS relative to reflecting about (certain) other people, or non-social classes of stimuli (Craik et al., 1999; Johnson et al., 2002; Kelley et al., 2002; Heatherton et al., 2006; Moran et al., 2011; Whitfield-Gabrieli et al., 2011). This work has supported the idea that the self is a special cognitive structure, providing a superordinate means by which information can be encoded into memory (Fossati et al., 2004; Macrae et al., 2004). This position is further supported by neuropsychological work from Klein et al. (1999) that revealed a post-lesion dissociation in patients’ abilities to form memories about the self versus about general semantic categories. The theoretical position that self-is-special is in direct contrast to the notion that the self is a “powerful, but ordinary” structure in memory; a view which suggests that our improved memory for information encoded in reference to the self is simply a result of the greater familiarity of the self-concept (Greenwald and Banaji, 1989), but that the semantic structures of self are no different from the semantic structures of sailboats and silver jewelry. Even though the cognitive neuroscience evidence strongly supports the self-is-special view, Denny et al.’s (2012) meta-analytical finding of a dorsal-ventral axis along which mPFC appears to be differentiated for other- and self-representation appears contradictory. Why is it the case that, on the one hand, our neural representations of self and other are so closely allied, but on the other hand these representations occur in regions of the cortex distinct from (and largely anatomically disconnected from) those networks that are engaged when we reflect about non-social sources of information?

Why Does Self-Reflection Engage the Cortical Midline Structures?

We consider three possible explanations for this pattern of results that are speculative, not intended to be mutually exclusive, and are at least partially overlapping. First, one possibility is that Greenwald and Banaji (1989) may have been half-right: it may be that social information is special, and that the self is a powerful-but-ordinary social knowledge structure. Second, Heatherton (2011) has proposed that mPFC serves as a “hub,” binding together heavily processed information from secondary sensory areas from each of the senses with internally generated information to represent the conscious “workspace.” Third, mPFC may act in a meta-cognitive fashion by guiding our moment-to-moment thought processes; in essence, in deciding what to think about next. See Figure 1 for a schematic representation of each of these models.

FIGURE 1 

Figure 1. Schematic representation of three possible distinct, but not mutually exclusive models of cortical midline structure (CMS) function. Top left: the CMS are specialized for representing social information, of which the self is a powerful-but-ordinary subset. Top right: the CMS serve as a set of regions responsible for the direction of our thought processes on a moment-to-moment basis. Bottom: the CMS serve as a hub integrating information from disparate neural processing systems into a “conscious workspace.”

Is the Self a Powerful-But-Ordinary Social Construct?

On the self is a powerful-but-ordinary social construct view, the CMS could be seen as representing social information per se, and their seeming selectivity for self-relevant information might simply represent an extreme case of social information processing about a social target (the self) that by definition is more familiar than all other social targets. The overarching view of simulation theory (Gordon, 1986) is that in order to understand others we run a mental simulation of how we might act in given social situations. Conversely, the emerging discipline of neural hermeneutics (Gallotti and Frith, 2013) suggests that in order to understand ourselves, we pay close attention to the social behavior of others. Both of these viewpoints converge on the idea that the self might be a powerful, but ordinary social target.

One obvious prediction of this idea is that the CMS might be differentially engaged by the representation of (and processing about) social targets that are differentially familiar to us. Familiarity contains the concepts of both closeness and similarity: close individuals are those we feel close to (including family and friends), whereas similar individuals are those who share characteristics with us (like members of our race, political affiliation, or age group). Indeed, in Qin and Northoff’s (2011) meta-analysis, they observe that stimulus familiarity drives activation in a similar ventral mPFC region just as much as does self-reflection. In addition, Denny et al.’s (2012) meta-analysis shows that ventral aspects of mPFC are preferentially engaged by reflecting on the self versus others. If this region is sensitive to the familiarity (or “selfness”) of social information, then it should respond more to information that is more self-relevant than not. Several studies have found such a pattern of results (e.g., Phan et al., 2004; Moran et al., 2006). Indeed, Mitchell et al. (2006) observed that social targets manipulated to be similar to the self engaged this ventral mPFC region, whereas social targets manipulated to be dissimilar to the self engaged dorsal mPFC. Krienen et al. (2010) clarified Mitchell et al.’s findings by demonstrating that the driver of activation in mPFC was closeness rather than similarity per se, suggesting that the familiarity of repeated exposure to individuals drives their self-relevance.

Converging on this idea, a series of studies investigating self-reflection in different cultures have provided support for the notion that in individuals whose cultures are more interdependent, the same ventral mPFC region does not differentiate thinking about self from thinking about close family members (like participants’ own mothers) (Zhang et al., 2006; Zhu et al., 2007; Chen et al., 2013), but that this does not necessarily hold true in Western, more independent cultures (Kelley et al., 2002; Kjaer et al., 2002; Heatherton et al., 2006; Vanderwal et al., 2008). These cross-cultural findings are best interpreted in the context of recent criticisms suggesting that standard delineations between Western and Eastern cultures are not as clear-cut as has been suggested (Martinez Mateo et al., 2013). In this context, Moran et al. (2011) provide data that clarify the distinction between independent and interdependent cultures. In their paper, consideration of one’s mother’s personality traits, but not her physical characteristics produced activation levels midway between those of thinking about one’s own traits versus those of former US President, George W. Bush. To the degree that we represent the traits of a close other as being like our own (rather than their physical characteristics), this suggests again that “selfness” may be driving this difference in ventral mPFC). Considered as a unit, these lines of research reveal a quantitative dimension along which social targets of greater familiarity activate ventral mPFC to a greater degree, with the self sitting at the top as the most familiar social target of all.

A further prediction of the notion that the CMS are specialized for socialprocessing (and that the self is a powerful subset of such processing) is that we might be able to differentiate their relative contributions along lines in which thinking about ourselves and thinking about others naturally cleave. To the degree that our representations of ourselves are first-person, and our representations of others are third-person, one would imagine that neural systems implicated in social processing that preferentially receivevisual information would be more responsive to third-person representations. Based on the patterns of connectivity that we introduced at the beginning of this paper, it should be clear that the regions of pCC implicated in the default mode (and in self-reflection) are strongly linked to regions that create complex visual representations. Indeed, Raichle et al. (2001) advocate for a domain-general role for the pCC regions in providing complex visual representations to consciousness. Other work in cognitive neuroscience supports and extends this view, showing via meta-analysis that pCC regions participate in a network engaged in autobiographical memory, prospective future thinking, and navigation (Spreng et al., 2009). All such tasks require complex visual representation, and it is interesting that mPFC did not emerge in this meta-analysis. More direct evidence in support of the idea that pCC supports the third- rather than first-person representations more common in thinking about others rather than the self comes again from the meta-analysis of Denny et al. (2012). In their paper, they found across 107 studies that the precuneus was more active when participants thought about others than when they thought about themselves. Single-study evidence of the idea that visual rather than conceptual representations of people engage pCC comes from Moran et al. (2011), who showed that thinking about social targets’ appearance (e.g., Does George W. Bush have a beard?) versus thinking about their character traits (e.g., Is George W. Bush kind?) produces more activation in pCC. This relationship also held true when the social target was the self. Direct investigations of adopting third- versus first-person perspectives have also shown greater pCC involvement during third-person perspective taking (Ruby and Decety, 2001).

Is Medial Prefrontal Cortex a Hub for Integrating Internal and External Information?

Our second possibility is that the ventral mPFC region identified by Heatherton (2011) serves as a hub that integrates internal and external information into a conscious workspace. On this view, self-reflection would be the canonical task for such a region because it so strongly requires the flexible and ongoing integration of our own knowledge about ourselves with our ever-changing knowledge gained from our sense organs about how we are interacting with the environment, and about how social actors in our environment think about us. Thinking about those social actors independent from ourselves (theory of mind) would drive this machinery to a lesser degree (but still more than thinking about non-social aspects of the world) because rapid and complex integration of sensory, external, and non-sensory conceptual knowledge is required to understand others’ goals, intentions, and beliefs, whereas such dynamic processing is much less necessary for thinking about tools or cars or jewelry. This sort of integration into a conscious workspace is also a hallmark of the cognitive processes engaged during “rest,” and engendered by the default mode of brain functioning.

Is Medial Prefrontal Cortex Specialized for Directing Conscious Thought Processes?

Finally, our third possibility is that the ventral mPFC region identified in self-reflection tasks is specialized for helping to decide in which direction our thought processes should proceed. The convergence of heavily processed external sensory inputs with internally generated inputs would also support this view, which of course is not mutually exclusive with the view that mPFC serves as a hub for integration of information from disparate neural processing units. To the degree that deciding where our thoughts should go is a representational process, and that reflection on those thoughts (and our enduring personality traits) is a meta-representational version of the same process, one would imagine that a system with such functional-anatomic properties would be well-placed to perform both conscious direction of thoughts and self-reflection. That rest and self-reflection so consistently overlap (Qin and Northoff, 2011; Whitfield-Gabrieli et al., 2011) suggests that being free to direct our own thoughts (i.e., not responding directly to the environment or an experimenter-provided task) is a state that mimics the natural process observed when we are asked to reflect directly on our own selves. A prediction of this viewpoint is that decision-making might be tied to activity in the CMS, and indeed research shows that CMS activity predicts freely made decisions up to 7 s before participants indicate becoming aware of the decision having been made (Soon et al., 2008). This third possibility thus may account for the still-puzzling observation that the mPFC is perhaps the most important actor in the brain’s default mode network, which itself perhaps serves as a proxy for our ongoing conscious awareness of both our internal and external words. This conjecture awaits empirical investigation however, not least because sampling the ongoing representational processes of the default mode requires disrupting such processes.

Conclusion

In summary, we have speculated about several different explanations for the observation that the CMS are observed so consistently to participate in self-reflection. Neuroanatomical connectivity suggests that these regions are heteromodal association areas that derive much of their inputs from upstream regions associated with social information processing, and that pCC in particular gains its inputs from regions of the brain responsible for complex visual representations. Because these regions are associated with social processing, are developed strongly in humans relative to other animals, and humans travel in much larger social networks than do other animals, we speculate that they may form the basis of a special neurocognitive system evolved for social processing. More fundamental characterizations of this system suggest that the anterior midline structure, mPFC, is in fact a domain-general region dedicated as a hub of information processing about the internal and external worlds, and relatedly, that the purpose of such a confluence of representations is to direct our conscious awareness from one moment to the next, switching flexibly between representations of our internal mental life and of the world around us. On this view, mPFC’s seeming specialization for social information processing merely reflects its response to stimuli (self and others) that drive the integration of internal and external information sources more strongly than non-social stimuli.

Much research remains to be done to gain greater understanding of how and why the self, other social targets, and the default mode of thought are related to one another, and why they so reliably involve the CMS. Initial support for the idea that mPFC regions might be necessary for self-reflection comes from a study with patients with ventral mPFC damage at the site implicated by Kelley et al. (2002) as being maximally involved in self-reflection (Philippi et al., 2012). These patients did not show the self-reference effect in memory, suggesting that mPFC is necessary for encoding information in relation to oneself. Emerging advances in TMS may allow researchers to target more closely these regions for temporary, reversible lesions, or for theta-burst stimulation for temporary increases in excitability of these regions (Vernet et al., 2013). Such studies could provide more controlled evidence to determine whether these regions are necessary for reflection about self and other. In parallel, advances in real-time fMRI techniques (deCharms et al., 2004; Hinds et al., 2011) allow for the exquisite control of presentation parameters, such that we can manipulate when participants are asked to reflect on self and others to moments when activation in either mPFC or pCC are high or low, and determine with a great degree of accuracy what effects natural fluctuations in the default mode at any given moment might have on our abilities to accurately represent ourselves.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

This work was supported by a grant from the National Institutes of Health (R01MH059282) to Todd F. Heatherton.

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