28 February 2013

The brains of rats...

Go better together!  Curious story today in the Guardian, "Brains of rats connected to allow them to share information via internet" by Ian Sample (Feb 28, 2013).  The internet part of it seems pretty gimmicky, not sure why that's important, and it's a little unclear to me what is really going on here.  The substantive portion is described like this:
The scientists first demonstrated that rats can share, and act on, each other's sensory information by electrically connecting their brains via tiny grids of electrodes that reach into the motor cortex, the brain region that processes movement.

The rats were trained to press a lever when a light went on above it. When they performed the task correctly, they got a drink of water. To test the animals' ability to share brain information, they put the rats in two separate compartments. Only one compartment had a light that came on above the lever. When the rat pressed the lever, an electronic version of its brain activity was sent directly to the other rat's brain. In trials, the second rat responded correctly to the imported brain signals 70% of the time by pressing the lever.

Remarkably, the communication between the rats was two-way. If the receiving rat failed at the task, the first rat was not rewarded with a drink, and appeared to change its behaviour to make the task easier for its partner.
So it sounds like impulses from one rat, which were generated upon a certain movement, were sent in some format into the other rat's brain, into its motor cortex.  That in turn seemed to influence the movements/'decisions' of the receiving rat.

Some questions I have about this - (1) how much of a learning period was involved? 2) how many notable movement/decision options did the receiving rat actually have?  3) was there some timing boundary within which the rat had to take action to be seen as successful communication? 4) what was the success rate? Maybe it's all answered in the paper.

For me it raises the question of whether essentially any patterned impulses received by certain brain areas could be successfully 'interpreted' - and to what level of discrimination.  In this case the receiver may be doing little more than using the reception as a timing signal to make a movement, but perhaps it can go deeper than that.

The article ends with a good reminder that there's plenty we don't know in this area:
Very little is known about how thoughts are encoded and how they might be transmitted into another person's brain – so that is not a realistic prospect any time soon. And much of what is in our minds is what Sandberg calls a "draft" of what we might do. "Often, we don't want to reveal those drafts, that would be embarrassing and confusing. And a lot of those drafts are changed before we act. Most of the time I think we'd be very thankful not to be in someone else's head."
(H/t to twitterers @pourmecoffee and @neurophilosophy)

Update:  Here's another report from NYT:  "One Rat Thinks, and Another Reacts"

27 February 2013

Knowing vs. Understanding

Came across this Slate post "Explain it to me again, computer" by Samuel Arbesman (Feb 25, 2013).  Here's the initial question:
But whether or not science is always moving forward or whether we think we have the final view of how the world works (which we almost certainly do not), we pride ourselves on our ability to understand our universe. Whatever its complexity, we believe that we can write down equations that will articulate the universe in all its grandeur.

But what if this intuition is wrong? What if there are not only practical limits to our ability to understand the laws of nature, but theoretical ones?
I don't think I concur with this intuition, but here's the interesting twist:
A computer program known as Eureqa that was designed to find patterns and meaning in large datasets not only has recapitulated fundamental laws of physics but has also found explanatory equations that no one really understands. And certain mathematical theorems have been proven by computers, and no one person actually understands the complete proofs, though we know that they are correct.
I think in some ways technology moves ahead in this way, by finding 'true' behavior (rules that work in the world), and exploiting it to enable new techniques.  Science can often come along later with theoretical justification and explanation.  But to think that we may never really understand some of these findings, and just accept them, does feel a little de-stabilizing.

(H/t Andrew Sullivan)