The Moon is not Made of Cheese and Other Hypotheses
I haven’t really spent too much time in these pages taking on the arguments of specific commenters about the BRAIN Initiative. I’ve certainly addressed some of the issues implicitly, and in fact I have agreed with some of the more serious criticisms of the project (such as overselling the connection to clinical medicine). I’m also just not a big fan of blogs as long-form flame wars, where authors try to show their intellectual skills by teasing out logical/factual inconsistencies in other people’s writing, with the inevitable result: thousands of words of snarky semantic quibbling. Nevertheless, a recent post on Live Science by Donald Stein embodies one strain of opposition to the BRAIN proposal that I think is misguided, and while I’ve alluded to some of these issues in previous posts, it seems like it is a good time to lay out some specific arguments. I mean no specific disrespect to Dr. Stein, rather I’m using his relatively articulate arguments as a proxy for many others who have staked out similar ground.
The crux of Stein’s argument is that the BRAIN Initiative is too open-ended. This has been a recurring theme for many writers as the plan developed from the early outline as the Brain Activity Map, so I’ll step through his particular arguments, given that they reflect the viewpoints of other commenters as well. First, he argues that, unlike the Human Genome Project for instance, the project has no clear end-point. I think that he, like many others, has mistaken the symbolic milestones of the previous big science attempts for a Specific Aim of an NIH grant proposal. Yes, the hallmark event of the lunar exploration program was landing a man on the moon, the goal of the HGP was sequencing an entire individual genome, and presumably characterizing the Higg’s boson was the target for the Large Hadron Collider. But the fact that these ‘goals’ were mostly symbolic is proven by the fact that none of them was shut down once the attainment was made. It’s not as though the moon shot was driven by the hypothesis that the moon was made of cheese. Putting a man on the moon was simply the publicity stunt meant to get the Cold War era public behind a large-scale investment in research/development of (mostly military) infrastructure. So, I’ll agree that the BRAINI team has not developed a good elevator pitch that will entice an increasingly deficit-shy public into a major brain science investment, but that is not really what this project is really about. In fact, as I’ve written before, the attempts to justify the plan as leading to cures for human diseases are the most far-fetched, and I worry that trying to sell basic science as clinical science may sour the public on both pursuits. Nonetheless, the BRAIN Initiative is not (and doesn’t need to be) a hypothesis-driven project; it is a basic science infrastructure development initiative meant to provide tools and technologies not for one Specific Aim in one lab, but for hundreds. In some sense the plan suffers from having too many goals, rather than too few, and in fact it is the charge of the new planning committee to pare down to the essentials in the next year. Perhaps when that process is closer to completion we can begin to ask the tough questions posed by Stein about whether this project is more important than “finding a cure for AIDS” or “beating cancer.” My personal opinion is that in almost any form, it is more important than another B2 Bomber or Joint Strike Fighter, but that’s just me.
The second thrust of Stein’s argument is rather novel among recent criticisms of the BRAINI, though as he mentions, there is some echo of it in Partha Mitra’s qualms about what was then called BAM. Stein asserts that the entire concept of brain mapping is itself so mired in the intellectual baggage of 19th century thinking, that it cannot produce an intellectually coherent result. I will concede that popular accounts of fMRI studies have often taken on the ring of phrenology, that prototypical pseudoscience of the Dickens era that claimed to divine “mental faculties” by the size of brain regions (as assessed by the shape of the skull). Most of the time, when science journalists talk about discrete areas of the brain as responsible for higher level functions, like executive planning or craving chocolate cake, they are just being lazy or stupid. But to confuse that sort of nonsense with the kind of mapping that goes on in systems neuroscience labs is either a complete category error or a classic straw man (which, like the Scarecrow, has no brain). I challenge Stein point out actual evidence of this blinding conceptual bias in the research of scientists like Michael Hasselmo, or György Buzsáki, or Eve Marder, or Terry Sejnowski (just to pick a few).
Stein tries to make this argument more concrete by making rather dramatic claims about neuroplasticity, arguing that “it is well established that the connections between dendrites and synapses in the brain are in a state of constant change,” and claiming that the territory of the brain is so dynamic as to make the entire concept of mapping it untenable. On the surface, depending on the time scale of ‘constant,’ you could say this statement is superficially true. We’ve all been surprised in the last 10-20 years by the amount of global, brain-level plasticity discovered in human brains, and since Stein studies traumatic brain injury, he no doubt sees this glass as half full. Still, to suggest that brains are such an amorphous ooze as to be completely unmappable is completely ridiculous. It’s also contradicted by hundreds of studies coming out every month. Recent discoveries that, for example, adult human brains may grow new brain cells in some very restricted conditions are surprising exactly because they are the exception that proves the rule. Long-term imaging experiments in Karel Svoboda’s lab have shown, for instance, that neocortical dendritic structure is basically stable over weeks, with a subset of synapses forming and disconnecting over shorter time periods. Even this plasticity takes place on the background of basically stable cell types in basically stable arrangements in basically stable cortical layers in basically stable cortical regions subserving basically stable sensory-motor functions. If it weren’t for this stability, structural brain mapping, let alone functional brain mapping, would be impossible. In fact, Partha Mitra’s arguments against the BAM/BRAIN proposal is based not on the impossibility of mapping in general, but on the prematurity of doing functional mapping before you have a good structural map. It is precisely this structural map that his Brain Architecture Project is trying to achieve1.
The third leg of Stein’s argument is that neuroscientists lack consensus about what aspect of brain activity warrants mapping. He claims that we don’t know whether we should be looking at biochemical cascades, genetic expression or structural changes, to name a few. It is true that a variety of people with “neuroscientist” on their business card study all these types of brain activity when trying to understand the brain as a general biological system or a locus for pathology. But those that study brains as information processing systems (called systems or computational neuroscientists) generally agree that action potentials are where the money is. Does that mean that gene expression or glial activity or neuromodulators or biochemical cascades are not important for our brains? Absolutely not. But more than 100 years of research suggests that if you want to know how brains encode, transform and compute information, you need to at least start with the electrochemical impulses neurons use to communicate. If you want to understand the internet, it’s best to start with the data packets and not the chemical composition of the paint on the server racks.
Finally, Stein props up Mitra’s argument that we wouldn’t know what to do with data from a recording of all the action potentials in a particular neural system if we had it. He suggests that we wouldn’t be able to tie that information to the underlying neural structure or to the relevant behavior/perception. Hogwash and balderdash, I say! I can assure Stein that if I had complete action potential data from the brainstem networks that I studied for my Ph.D., I could answer decades of disputed questions with a handful of experiments. This is equally true for my colleagues who study olfactory coding, bird song systems, motor control, cortical rhythms, tactile coding, auditory function, etc. The fact is systems neuroscientists know how to relate neural activity to behavior, perception, and even to network structure because they’ve been doing that for years.
1 Not to be accused of erecting my own straw man, I’m aware that there may be a lot of dynamic reconfiguration occurring in neural systems on the substrate of the structural network. How could we investigate that possibility? Exactly the methods proposed by the BRAIN Initiative.
Figure: One example of map organization in rat neocortex. 3D Reconstruction and Standardization of the Rat Vibrissal Cortex for Precise Registration of Single Neuron Morphology. PLOS Computational Biology. December 2012.