Can Telepathy Occur During Dreams and OBEs?

  • Thread starter Thread starter Albert George
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The discussion revolves around the exploration of telepathy and out-of-body experiences (OBEs), sparked by a British documentary on sleep. Participants express varying beliefs about telepathy, questioning its scientific validity and the existence of evidence beyond anecdotal claims. A scientist shares a personal experience related to dream telepathy, emphasizing the difficulty in distinguishing between coincidence and genuine psychic phenomena. The conversation highlights the challenges of scientifically testing telepathy, with suggestions for structured experiments to assess correlation between dreams and external stimuli. Participants debate the neurological basis of OBEs, referencing studies that link them to brain function rather than paranormal activity. The need for rigorous scientific evidence is stressed, with some advocating for open-mindedness toward unexplained phenomena while others caution against dismissing established scientific explanations. Overall, the thread reflects a blend of skepticism and curiosity about the potential for telepathy and the nature of consciousness, urging for more research into these complex topics.
  • #91
Strictly me. The creepy part was this 'rift' of crackling energy that invariably 'opened' a short time into the experience. I had no desire to further explore. I agree, however, that OBE's are not scientifically useful until otherwise unobtainable knowledge is acquired by the practice.
 
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  • #92


Ivan Seeking said:
Occams razor is a rule of thumb, not a scientific principle that can be used to draw conclusions.
In its most simplified form, Occam's razor simply says that if you have two models that explain your data equally well, the model whose representation is shorter is more likely to be correct. This makes statistical sense. Suppose you have decided to choose a model from among all those that are m bits long (with some standard representation of a model as a series of bits). There are something like 2^m models that are m bits long. So the larger m is, the greater your risk of selection bias (and hence a false positive).

See also: minimum description length
 
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