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  1. Differentiating dreaming and waking reports with automatic text analysis and Support Vector Machines.Xiaofang Zheng & Richard Schweickert - 2023 - Consciousness and Cognition 107 (C):103439.
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  • Automatic gender detection of dream reports: A promising approach.Christina Wong, Reza Amini & Joseph De Koninck - 2016 - Consciousness and Cognition 44:20-28.
  • A differentiating empirical linguistic analysis of dreamer activity in reports of EEG-controlled REM-dreams and hypnagogic hallucinations.Jana Speth, Clemens Frenzel & Ursula Voss - 2013 - Consciousness and Cognition 22 (3):1013-1021.
    We present Activity Analysis as a new method for the quantification of subjective reports of altered states of consciousness with regard to the indicated level of simulated motor activity. Empirical linguistic activity analysis was conducted with dream reports conceived immediately after EEG-controlled periods of hypnagogic hallucinations and REM-sleep in the sleep laboratory. Reports of REM-dreams exhibited a significantly higher level of simulated physical dreamer activity, while hypnagogic hallucinations appear to be experienced mostly from the point of passive observer. This study (...)
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  • Dreaming and cognition in patients with frontotemporal dysfunction.Teresa Paiva, Paulo Bugalho & Carla Bentes - 2011 - Consciousness and Cognition 20 (4):1027-1035.
    Individuals with Parkinson’s disease and temporal lobe epilepsy have hallucinations and mild cognitive dysfunction. The objective of this work was to study dreams in PD and TLE patients using a common functional model of dream production involving the limbic and paralimbic structures.Dreams were characterised in early-stage PD and TLE patients with dream diaries classified by the Hall van de Castle system and were compared with matched controls.In PD, there were significant differences between patients’ dreams and those of controls: animals, physical (...)
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  • Cognitive Phenomenology of Religious Experience in Religious Narratives, Dreams, and Nightmares.Victoria Pae, Patrick McNamara, April Minsky & Alina Gusev - 2015 - Archive for the Psychology of Religion 37 (3):343-357.
    McNamara hypothesized that a 4-step sequential decentering process characterized the phenomenology of religious and spiritual experiences and was rooted in dreams and nightmares. We content analyzed 50 RSES, 50 dreams, and 50 nightmares for presence and ordering of elements of the decentering process. Thirty-six percent of RSES, 48% of dreams, and 44% of nightmares had all four decentering elements. The sense of success occurred most frequently in RSES and least frequently in nightmares. Conversely, diminishment of agency occurred least often in (...)
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  • Mind-Object Identity: A Solution to the Hard Problem.Riccardo Manzotti - 2019 - Frontiers in Psychology 10.
  • Such stuff as dreams are made on? Elaborative encoding, the ancient art of memory, and the hippocampus.Sue Llewellyn - 2013 - Behavioral and Brain Sciences 36 (6):589-607.
    This article argues that rapid eye movement (REM) dreaming is elaborative encoding for episodic memories. Elaborative encoding in REM can, at least partially, be understood through ancient art of memory (AAOM) principles: visualization, bizarre association, organization, narration, embodiment, and location. These principles render recent memories more distinctive through novel and meaningful association with emotionally salient, remote memories. The AAOM optimizes memory performance, suggesting that its principles may predict aspects of how episodic memory is configured in the brain. Integration and segregation (...)
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  • Seeking patterns in dream content: A systematic approach to word searches.Kelly Bulkeley - 2009 - Consciousness and Cognition 18 (4):905-916.
    This paper systematizes the word search potential of DreamBank.net by formulating and testing a set of word strings that can be used as default analytic categories in future investigations. The word strings are applied to the 981 dream reports of college students gathered by Hall and Van de Castle and the 136 dream reports of an 80-year old male gathered by Bulkeley . The results show a basic compatibility with the frequencies identified by Hall and Van de Castle’s labor-intensive method (...)
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  • The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic.Hye Joo Han, Richard Schweickert, Zhuangzhuang Xi & Charles Viau-Quesnel - 2016 - Cognitive Science 40 (3):671-696.
    For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream (...)
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  • Mapping dreams in a computational space: A phrase-level model for analyzing Fight/Flight and other typical situations in dream reports.Maja Gutman Music, Pavan Holur & Kelly Bulkeley - 2022 - Consciousness and Cognition 106 (C):103428.
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  • BizarreVR: Dream-like bizarreness in immersive virtual reality induced changes in conscious experience of reality while leaving spatial presence intact.Simone Denzer, Sarah Diezig, Peter Achermann, Thomas Koenig & Fred W. Mast - 2022 - Consciousness and Cognition 99:103283.
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  • Digital dream analysis: A revised method.Kelly Bulkeley - 2014 - Consciousness and Cognition 29:159-170.
  • Will students pass a competitive exam that they failed in their dreams?Isabelle Arnulf, Laure Grosliere, Thibault Le Corvec, Jean-Louis Golmard, Olivier Lascols & Alexandre Duguet - 2014 - Consciousness and Cognition 29:36-47.
  • Word associations contribute to machine learning in automatic scoring of degree of emotional tones in dream reports.Reza Amini, Catherine Sabourin & Joseph De Koninck - 2011 - Consciousness and Cognition 20 (4):1570-1576.
    Scientific study of dreams requires the most objective methods to reliably analyze dream content. In this context, artificial intelligence should prove useful for an automatic and non subjective scoring technique. Past research has utilized word search and emotional affiliation methods, to model and automatically match human judges’ scoring of dream report’s negative emotional tone. The current study added word associations to improve the model’s accuracy. Word associations were established using words’ frequency of co-occurrence with their defining words as found in (...)
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  • The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text.Edgar Altszyler, Sidarta Ribeiro, Mariano Sigman & Diego Fernández Slezak - 2017 - Consciousness and Cognition 56:178-187.