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- 06/09/2010: Worms and us
- 03/09/2010: Cognitive science and Neurobiology
- 02/09/2010: Going under and coming to
- 01/09/2010: Memristors
- 28/08/2010: Synchrony in social interaction
- 25/08/2010: Connectome
- 22/08/2010: The sounds we hear
- 19/08/2010: Reverse engineering the brain
- 16/08/2010: Communication
- 13/08/2010: Botox
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Property of Consciousness 1
What have we found at the end of a year and a bit? I’ll look at that in the next few posts.
It would seem to me that one idea has been fairly convincingly shown: that consciousness predicts the near future from the near past in order to give us an experienced ‘now’. The possible advantages of this constructed ‘now’ are obvious: we experience life in the present, we have a fluid passage through future-present-past, and most importantly, we can register the error between what we predict will happen and what does happen and use this error signal to correct our actions and perceptions. Further, the error signal can provide input to the ‘reward’ system, input to learning systems and input to controlling the focus of attention. How immensely useful this prediction is!!!
Whether the system is mathematically Bayesian or not, it is certainly philosophically Bayesian. We are creating a high-probability scenario of what the future holds from the ‘priors’ we find in the past.
So…
Property/function of consciousness #1 – Consciousness predicts the near future from the near past in order to give us an experienced ‘now’ which is compared with current sensory input. This comparison gives more accuracy to movements and perceptions, and it facilitates appropriate emotional reactions, learning and attention.
Here are some previous postings indicating the predictive nature of consciousness.
I assume there will be more research to come in the next year that will further elaborate this property.
06/08/2009 at 10:55 am
I like a lot your proposed genereal model of consciousness
I do not think the error provides imput to the reward system, I think it inhibits the input of the reward system to enter it
I think that the system whether it is matematically bayesian or another one might probably have a fuzzy logic
part in it.
Bye j
JanetK: I think the error signal is complicated and so is the reward system. Firth says that if the error is good (we get something we like but didn’t expect) the dopamine goes up and if there is no error the dopamine stays the same and if there is a negative error (we expected something good and it didn’t happen) the dopamine goes down.