{'fraction_non_alphanumeric': 0.029317386231038505, 'fraction_numerical': 0.007730455075845974, 'mean_word_length': 5.722549019607843, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Predictive coding, multisensory integration, and attentional control: A multicomponent framework for lucid dreaming

Lucid dreaming (LD) is a mental state in which we realize not being awake but are dreaming while asleep. It often involves vivid, perceptually intense dream images as well as peculiar kinesthetic sensations, such as flying, levitating, or out-of-body experiences. LD is in the cross-spotlight of cognitive neuroscience and sleep research as a particular case to study consciousness, cognition, and the neural background of dream experiences. Here, we present a multicomponent framework for the study and understanding of neurocognitive mechanisms and phenomenological aspects of LD. We propose that LD is associated with prediction error signals arising during sleep and occurring at higher or lower levels of the processing hierarchy. Prediction errors are resolved by generating a superordinate self-model able to integrate ambiguous stimuli arriving from sensory periphery and higher-order cortical regions. While multisensory integration enables lucidity maintenance and contributes to peculiar kinesthetic experiences, attentional control facilitates multisensory integration by dynamically regulating the balance between the influence of top-down mental models and the precision weighting of bottom-up sensory inputs. Our novel framework aims to link neural correlates of LD with current concepts of sleep and arousal regulation and provide testable predictions on interindividual differences in LD as well as neurocognitive mechanisms inducing lucid dreams.


SUPPLEMENTARY INFORMATION
. Wake-like activity during sleep in different sleep disorders. Sleep disorders and pathological sleep conditions associated with wake-like cortical activity patterns during sleep. Wake-like activity during sleep appears to be a common denominator behind a wide variety of sleep disorders. The above table shows illustrative examples (for more extensive and complete reviews, especially for insomnia and NREM parasomnias, see (1-4).

Lucid dreaming across the lifespan: Developmental aspects
The multicomponent framework of lucid dreaming may accommodate the somewhat surprising observations of increased lucid dream frequency in children (18) and its reduction in older age groups (19). Whereas the prefrontal and frontoparietal networks (still immature in young children) may be involved in lucid dreaming, our model suggests that increased sensitivity to bottom-up signals may also facilitate lucidity. Young children are more capable to automatically extract low-level, raw probabilities (i.e., statistical rules) of the environment (and hence to detect violations of such probabilities) indicating dominantly bottom-up, model-free processing of sensory experiences compared to older individuals (20,21). On the other hand, cognitively controlled, model-based learning is gradually taking place after around 12 years of age (22). Interestingly, this shift in learning strategies corresponds to the gradual drop of lucid dream experiences from puberty to young adulthood (18). Susceptibility to low-level bottom-up inputs producing prediction error signals may play a major role in triggering lucid dream experiences in young children. Moreover, young children spend considerable time in REM sleep, and are prone to state dissociations, and parasomnias. Due to higher arousal thresholds young children are protected from abrupt awakenings (1), reducing the chance that active inference during dreaming will be associated with arousals and awakenings. In contrast, older individuals spend less time in REM sleep, and due to reduced sleep regulation are more susceptible to arousals (23,24) and sleep fragmentation limiting the possibility to reach lucidity during sleep. Taken together, the probabilistic, model-free learning period of young children may provide a reflexive attitude towards their (true) mental state (of dreaming), where higher arousal threshold can stabilize the (lucid) dream experience.
Coming to adulthood, the development of prefrontal and frontoparietal regions can provide top-down attentional control to stabilize the lucid dream state, but reducing its occurrence beforehand: In adulthood, prediction errors may be often explained away by schemes acquired during model-based learning, and rarely have the chance to (truly) update the state of consciousness itself (from wakefulness, to dreaming). Pre-lucid dreams can provide examples for stereotypical actions and state interpretations (e.g., "I recognized that I am dreaming, so I went to tell it to others" or "I understood that I can fly because my body died and now, I live as a spirit"). However, it should be pointd out that studies on dreaming in young children are scarce and to some extent questionable on methodological grounds (25). In addition, the assessment of lucid dream frequency in different age groups is only based on retrospective self-reports that are prone to memory biases. Therefore, future studies applying prospective data collection procedures or signal-verified lucid dream assessments are warranted to systematically investigate the frequency and nature of lucid dream experiences in children.

Lucid dreaming and psychopathology: relevance for psychosis
Several authors argued that reduced executive and self-reflective functions (related to hypofrontality) in dreaming resemble psychosis (26)(27)(28); they suggested that lucid dreaming is the opposite of psychosis: a state of increased self-reflection and insight due to increased frontal activity (28,29).
Nevertheless, these assumptions are challenged by empirical data indicating weak but consistent associations between lucid dream frequency and proneness to psychosis (30,31), and similar rates of lucid dream frequency in psychotic patients compared to non-psychotic controls (32). In the context of the present multicomponent framework, we may speculate that impaired sensory gating in psychotic states (33,34) facilitates the processing of bottom-up sensory afferents during sleep.
Accordingly, signs of reduced sensory gating in psychotic conditions were evidenced not only in wakefulness but also during sleep (35,36). Moreover, whereas non-psychotic individuals can easily monitor and automatically distinguish internally generated experiences (e.g., imagination during mind wandering) from veridical perception, psychosis-prone individuals often have difficulties in discriminating externally and internally generated mental representations. The frequent experience of intrusive, vivid, perceptual experiences of ambiguous origin, and the effort to discriminate hallucinations from veridical perception may "train" psychosis-prone individuals to question the sources of dreaming. (For a detailed description of the utility of the PC framework in psychosis see 115, 116).