A bee line into the mind?

Speaking of the nature of consciousness, as we were last time, there’s new research into the workings of the “hive mind”

Last year, researchers showed that a bee “using a brain the size of a grass seed” can  solve the route-mapping puzzle known as “the travelling salesman’s problem” faster than can a person, or even a computer.

Now, we read that the decision-making dynamic of a beehive is remarkably similar to the process by which our brains make choices.

It’s enough to make a vain speciesist cry into his mug of mead.

It’s one thing when easily anthropomorphosizable (can that really be how that should be spelled!) chimps and gorillas demonstrate conscious behaviours that parallel our own. (The speciesist may freely substitute “mimic” for “parallel.”)

After all, if individual bees act like individual neurons, and if bee groups communicate and decide in the same ways that our own brain processes do, where is all of this material deconstruction of higher processes going to stop?

I’m sure that there are ID-ers out there who have already spun this latest report into a “proof” that there’s a Grand Designer whose Grand Design is clearly shown in the fact that two so very different processes share the same basic form. How could this have happened, if there hadn’t been a Big Guy planning it that way? This is another version of the “Fractals, therefore God” style of reasoning.

But of course it doesn’t take a designer to get design. As we considered briefly last time, in an article on the theories of Terence W. Deacon, complexity arises unbidden out of the constraints that systems acquire as they expand. One water droplet can fall anywhere, but the splash it makes when it hits the ground is similar to the splashes made by other droplets around it. And frozen water, as snowflakes and ice crystals, shows even more “random order,” more evidence of the similar effects of similar interactions on similar systems.

So it shouldn’t be much of a surprise when we find that a complex process composed of communicating units, whether those units are single bees or single neurons, tends to adopt similar dynamics. After all, they’re constrained by similar interactions.

Some of the details of this similarity are quite interesting.

The researchers report:

Honeybee swarms and complex brains show many parallels in how they make decisions. In both, separate populations of units (bees or neurons) integrate noisy evidence for alternatives and when one population exceeds a threshold the alternative it represents is chosen.

The journal article explains the essential decision-making dynamic:

The decision-making mechanisms in nervous systems and insect societies are strikingly similar. In both types of systems, the decision-making process is a competition between mutually interacting populations of excitable units (neurons or individuals) that accumulate noisy evidence for alternatives, and when one population exceeds a threshold level of activity, the corresponding alternative is chosen.

The researchers note that “an important feature of many of the models of neural decision-making is that each population of integrator neurons inhibits the activation of the others to a degree proportional to its own activation.”  They note that “it appears that the stop signals in bee swarms serve the same purpose as the inhibitory connections in models of decision-making in primate brains … to suppress the activity levels of integrators representing different alternatives.”

For neural models of decision-making, cross inhibition between integrating populations is crucial for effective decision-making, and has been shown to allow optimal decisions under some circumstances. As we have shown here, cross inhibition between integrating populations is also present in honeybee swarms, and is very important for their success when making decisions.

The article conclude with a provocative speculation:

It is tempting to think that the ability to implement a highly reliable strategy of decision-making is what underlies the astonishing convergence in the functional organization of these two distinct forms of decision-making system: a brain built of neurons and a swarm built of bees.

In Deacon’s terms, “the ability to implement a highly reliable strategy” might instead be expressed in terms of the similarities of the constraints which act on similar complex systems. Whether individual bees or individual neurons, it seems, these kinds of unit systems communicate and make decisions through the same kinds of interactions and mutual influences.

It’s intriguing to consider the possibility that maybe things aren’t the way they are because that’s how we achieve our necessary goals. Maybe theyre’ the way they are because that’s the way things like them turn out, in a burst of spontaneous organization and unplanned but inevitable complexity.

That could be one way that “Fractals, therefore God” might twist on itself enough to turn out to be a convenient fiction.