Post by Jon K on Nov 1, 2017 9:03:08 GMT -8
Stanislas Dehaene
Works by Stanislas Dehaene
This top level neuroscience/consciousness researcher is well worth reading – for example, on numbers and on language/reading in the context of “Consciousness and the Brain,” the title of his most recent book, and also in many other articles.
He is a total reductionist but his work over the last 20 years is very informative indeed. Through work in his lab, he has now identified four “signatures of consciousness” and gives the most detailed and up-to-date account I have seen about brain processing by assemblies of neurons (in a Global Neuronal Workspace model). He describes the extraordinary enormous amount of silent work done by “preconscious” and “subliminal” processes. He gives the unconscious its due, in a way, while at the same time dismissing the possibility of precognition.
I wonder if Dean Radin or others at IONS have or would utilize the latest versions of all three imaging techniques Dehaene uses in his lab to assess brain indicators and conscious awareness when correct remote viewing impressions are obtained. Dehaene won’t do it, but someone should.
Numbers and letters are very difficult to remote view. I first learned about two kinds of numbers from Dehaene’s book “The Number Sense”. Subitizable numbers (1 through 3 or 4) and the rest of them. The quantity of subitizable numbers is instantly known, without counting. Research indicates that the brain uses different circuits for subitizable and non-subitizable numbers.
Dehaene seems to think that mathematical modeling of neuron processes in the Global Neuronal Workspace will be the scientific answer to the issue of consciousness. His team has even constructed math models which though very simple do replicate patterns which the brain produces. However, there is plenty of evidence that this approach leaves out valid empirical data showing that consciousness has access to information not available in the immediate environment, and across time too, and that this reductionist approach cannot be the whole answer, even when the algorithms get much more complex and more closely approximate human brain functioning.
Works by Stanislas Dehaene
This top level neuroscience/consciousness researcher is well worth reading – for example, on numbers and on language/reading in the context of “Consciousness and the Brain,” the title of his most recent book, and also in many other articles.
He is a total reductionist but his work over the last 20 years is very informative indeed. Through work in his lab, he has now identified four “signatures of consciousness” and gives the most detailed and up-to-date account I have seen about brain processing by assemblies of neurons (in a Global Neuronal Workspace model). He describes the extraordinary enormous amount of silent work done by “preconscious” and “subliminal” processes. He gives the unconscious its due, in a way, while at the same time dismissing the possibility of precognition.
I wonder if Dean Radin or others at IONS have or would utilize the latest versions of all three imaging techniques Dehaene uses in his lab to assess brain indicators and conscious awareness when correct remote viewing impressions are obtained. Dehaene won’t do it, but someone should.
Numbers and letters are very difficult to remote view. I first learned about two kinds of numbers from Dehaene’s book “The Number Sense”. Subitizable numbers (1 through 3 or 4) and the rest of them. The quantity of subitizable numbers is instantly known, without counting. Research indicates that the brain uses different circuits for subitizable and non-subitizable numbers.
Dehaene seems to think that mathematical modeling of neuron processes in the Global Neuronal Workspace will be the scientific answer to the issue of consciousness. His team has even constructed math models which though very simple do replicate patterns which the brain produces. However, there is plenty of evidence that this approach leaves out valid empirical data showing that consciousness has access to information not available in the immediate environment, and across time too, and that this reductionist approach cannot be the whole answer, even when the algorithms get much more complex and more closely approximate human brain functioning.