New IIT article

I don't think there is too much that is new in here, but figured it might be worth a look:

Giulio Tononi’s "integrated information theory" might solve neuroscience’s biggest puzzle

David Robson

Measures of the brain’s responses to the TMS also seem to predict the consciousness of patients in a non-communicative and vegetative state – a finding with potentially profound clinical applications.

Using previous techniques, the time taken to measure information integration across a network increases “super exponentially” with the number of nodes you are considering – meaning that, even with the best technology, the computation could last longer than the lifespan of the universe. But Toker has recently proposed an ingenious shortcut for these calculations that may bring that down to a couple of minutes, which he has tested with measurements from a couple of macaques. This could be one first step to putting the theory on a much firmer experimental footing. “We’re really in the early stages of all this,” says Toker.

And should information integration theory be right, it would be truly game changing – with implications far beyond neuroscience and medicine. Proof of consciousness in a creature, such as a lobster, could transform the fight for animal rights, for instance.

It would also answer some long-standing questions about artificial intelligence. Tononi argues that the basic architecture of the computers we have today – made from networks of transistors – preclude the necessary level of information integration that is necessary for consciousness. So even if they can be programmed to behave like a human, they would never have our rich internal life.

Of course the question of what "information" is exactly would also need to be answered I think?

I don't think there is too much that is new in here, but figured it might be worth a look:

Giulio Tononi’s "integrated information theory" might solve neuroscience’s biggest puzzle

David Robson

Of course the question of what "information" is exactly would also need to be answered I think?

There is some new (and exciting) info.

 It all comes down to mathematics. Using previous techniques, the time taken to measure information integration across a network increases “super exponentially” with the number of nodes you are considering – meaning that, even with the best technology, the computation could last longer than the lifespan of the universe. But Toker has recently proposed an ingenious shortcut for these calculations that may bring that down to a couple of minutes, which he has tested with measurements from a couple of macaques. This could be one first step to putting the theory on a much firmer experimental footing. “We’re really in the early stages of all this,” says Toker.

There is some new (and exciting) info.

What do you think is exciting about it?

(I'm not trying to rain on your parade, I just didn't think it was that big a deal so curious why you'd disagree.)

What do you think is exciting about it?

(I'm not trying to rain on your parade, I just didn't think it was that big a deal so curious why you'd disagree.)

 My push is for understandable (simple) process models, which are usually gained by collecting and sorting data patterns for correlations.  It is through empirical measurements that we come in contact with the data to gain a logical basis for these models.


Tononi needs hard facts to move forward.  A heuristic approach to aid in data processing - where patterns can be discovered and reviewed faster, should move things forward a a better pace.  Tononi et all, haven't had any real news in a while.

In particular, the idea of measuring ITT in collective intelligence vs ITT in an individual - is another route of measuring, analyzing and comparing patterns.  It should reveal another perspective on the natural activity of how information is working.

The article wonders if a lobster has consciousness and whether the developing technology could measure it.

I think that lobsters are alive and have a mind.  So, sorry Mr. Lobster.  While not eating red-meat, I am a lobster predator.