Aristotle must have had a flower garden, and spent many happy hours watching the bees at their work, because they’re one of his favorite examples in his writings. In fact, he’s credited with first observing that bees communicate the location of food sources to other bees in the hive. Although his scientific observations were often spoiled by a lot of specious reasoning, Aristotle was right about what an amazing little creature the bee is.

The common honeybee, Apis mellifera, has a brain with less than a million neurons, with a size of about a cubic millimeter. In contrast, the human brain contains close to 100,000 times as many neurons (and as many as 10 billion times as many connections). Bee behavior is correspondingly much, much simpler than that of humans or other vertebrates, yet they are exquisitely adapted animals. They can navigate extreme distances on the basis of visual and olfactory cues, and choose flowers for food sources on the basis of flower species and the time of year. To perform these tasks requires learning, and not the simple operant and classical conditioning we all learned about in high school psychology. Food source choice, for instance, involves what cognitive science calls contextual learning: showing a preference for flower A over flower B in one context, and then in a different context preferring B over A. To see these sorts of cognitive skills, commonly thought only to be possible in vertebrates, in such a tiny brain is like striking a gold mine. The very simplicity of the bee’s behavior and wiring means it may be possible to solve some of the big picture questions that are still almost impossible to address in the complexity of the mammallian brain.

As I consider what I want to do with my life after finishing my thesis, and ever since I heard a talk by Susan Fahrbach from the University of Illinois, I’ve been giving a lot of thought to the honeybee. I came to neuroscience from a background in biochemistry, and I must confess that I saw neuroscientists using many of the same techniques and analytical methods as molecular and cell biologists, and made the mistake of assuming that neuroscience was at the same level of unity as molecular biology. What I mean by unity is this: for most so-called “hard” sciences the central dogmas have been hashed out to the point where there exists a common framework for talking about new results. New work, no matter how esoteric, always exists at the periphery of this core and can always be referenced to it. Not so, by a long long shot, with neuroscience. We still have no idea how memories are formed, how decisions are made, or how the brain creates the experience of a coherent, consistent reality from an incoherent miasma of sensory data. We work on the periphery of some dark shrouded thing, hoping to catch a glimpse of it through our various machinations, but unlike molecular biologists we have no common language, no solid reference point.

Although I’ve had a relatively successful and certainly educational experience working on a very tightly focused project here in Berkeley, what I’ve realized over the past few months is that what makes me tick as a scientist are the overarching questions about how brains generate behavior, i.e. neuroethology. The honeybee is particularly attractive because it’s so simple, and yet has the behaviors I’m interested in understanding, spatial navigation and learning.

Of course, it also doesn’t hurt that one of the big labs for honeybees is in Toulouse, France, right next to the Pyrenees!

Unrelatedly, I’ve started posting photos on flickr.com, which is totally awesome. Although for new pics you will have to wait until next month or until I pay for a pro account.