Cliodhna O’Connor and Helene Joffe at UCL in London have just published in-depth interviews with 48 members of the British public and their main finding is that people mostly feel that neuroscience is irrelevant to them. O’Connor and Joffe said a particular feature of the interviews was the participants’ initial bemusement and discomfort about the topic. People said brain science is interesting, but 71 per cent thought it wasn’t salient in their lives…Pushed to elaborate on the field’s irrelevance, many answered that they simply saw brain research as a branch of science, which for them was a remote world.
Although most participants saw brain science as irrelevant, the exception to this rule was when they had personal experience of neurological or psychiatric illness, or they had fears about such illnesses. In this way, the brain for many was a source of anxiety – an organ that was usually ignored but which becomes suddenly salient when it goes wrong. For these people, brain research was essentially seen as a branch of medicine. Indeed, they used terms like brain science and brain surgery, and brain scientist and brain surgeon, interchangeably. There were particular fears about dementia, brain cancer and stroke.
So the public doesn’t really think neuroscience is relevant to them, and when they do it’s because they think it’s a branch of medicine. Also, it scares them to think about it. Great!
Not that should be that big of a surprise; how many people, after struggling to explain their science to a friend just end up shrugging and say, “it’s basic science”? How much of the neuroscience that the public reads about could just be summarized as, “we sent some surveys to see what people thought/how they behaved, and then we found out that the brain is involved“?
In systems neuroscience, we like to say that the goal of the visual system is to extract as much information about the world as possible. We start in the retina with points of light; those points are correlated (look around you: the color of one part of the visual world is often very similar to the color right next to it). So then the next set of neurons represent sudden changes in the brightness (ON/OFF neurons) to decorrelate. In the first stage of visual cortex, we find neurons that respond to edges – areas where you could put a several ON/OFF receptive fields in a row (see above). The responses of the visual neurons get successively more unrelated to each other as you go deeper into cortex – they start representing more abstract shapes and then, say, individual faces. But our guiding principle through this all is that the visual neurons are trying to present as much information about the visual world as possible.
But now let’s look at the nervous system from a broader view. What is it trying to accomplish? If we were economists, we might say that the nervous system is trying to maximize the ‘utility’ of the animal; an ecologist might say that it is trying to maximize the reproductive success of an animal (or: of an animal’s offspring, or its genes).
Is this a reasonable view of the ‘goal’ of the nervous system? If so, where do the goals of the input and the output meet? When do neurons in the visual system of the animal begin representing value, or utility, at some level? Is there some principle from computer science that has something to say about value and sensory representation?
Our brain works through a series of chemical messaging systems: payloads of neurotransmitters cross synapses, ions whizz through directly-connected gap junctions, molecular cascades tumble through cells. And on a gross level we have large chunks of grubby grey matter whose fluctuating electrical potentials draw in blood when we see beauty. Yet the phenomenon of beauty is not solely based on the level of blood flow in our brains; rather, it is the precise matrix of neurons and proteins and peptides that are in flux at the right moment that creates our emergent feelings of aesthetics. The beauty of a sunset is not the beauty of literature is not the beauty of an equation, despite what our burbling blood whispers to the thrumming MRI machines.
Anyway, despite the ‘poetics’, the point is real. There is a lot of cynicism among certain in the neuroscience community about the utility of fMRI. This certainly isn’t helped by dead-salmon studies of the ilk that Neuroskeptic or Neurocritic often point out. But that doesn’t mean it isn’t useful! Because of the reward function in science, labs are motivated to oversell their findings – and the media et al help them get away with it, because they don’t really understand what’s going on and like pretty pictures of brains. Yet even when the result is simply finding that some area of the brain ‘lights up’ to some stimulus, that still tells us something about the underlying circuitry, and where to go check for more details.
I recently got a quadcopter and in pockets of my spare time I’ve been attempting to make it an autonomous drone. Yet reading this article on unmanned drones has me returning to some thoughts I’ve had while working on the project. Basically: is neuroscience useful? Much of the utility from drones comes from their autonomy and adaptability. In my naive fantasies, I think that the work we do to understand the nervous system should inspire drone makers, hiring neuroscientists left and right to implant the lessons we’ve learned from the nervous system into these machines.
And yet – and yet I’m not aware of anyone doing this. There are whispers and rumors emanating from the Brain Corporation that this is their mission but I have yet to see anything concrete come out of that (to be fair, they’re a relatively new company). But even more we should be asking ourselves: are we going to be leap-frogged by those who are working in computer sciences – artificial intelligence, machine learning, vision processing?
That the drones are living in a newly created ecosystem, interacting and invading new niches, is undeniable. Presumably an enterprising young scientist in ecology, neuroscience, (economic) decision-making should be perfectly suited to at least consulting on these projects. I guess the question is: does that actually happen? Outside of ‘explaining the brain’ for ‘medicine’, do we do anything that’s actually useful? Or is that up to the engineers?