Structure (the details of how a function is implemented) is important, there is no doubt. But I see two related arguments about putting function first, or at least giving it the driver's seat in our science.
Argument 1: Function provides the job description required to constrain our understanding of brain activity
The first argument in favour of function is that cognitive neuroscience is essentially in the business of uncovering the neural implementations of the things cognitive science has identified need doing. Cognitive science provides the 'job description' for the brain; the functional analysis of what the brain is up to that guides the interpretation of the structural analysis that comes out of neuroscience. See this new paper in Cognition making this argument in more detail. Without this theory, all neuroscience can tell you is that bit is currently talking to that bit. With the theory, it can talk about why they are talking to one another and what thtat talk is achieving.
My problem, of course, is that I think radical embodied cognition is working to overturn the current functional analysis that guides modern neuroscience. If REC is right, then there are implications for how we do neuroscience, and I worry that a lot of neuroscience might go away; who needs to know where in the brain object representations live if there are no such things? I therefore think we need to get the functional story right first.
Argument 2: Biological systems work to preserve function, not structureThe second argument in favour of function is that the evidence strongly suggests that perception-action and neural systems work to maintain function and not structure. That is, in a very real sense, these systems don't care what they have to do or what shape they have to take so long as they fulfill the relevant task demand. This supports the idea in Argument 1 that it's the functional analysis that defines what the system will look like.
Perception-action: When you reach to grasp an object you don't try to maintain a particular form of the movement, you tailor the spatial and temporal characteristics of the movement to the current situation. We can do this because perception-action systems typically have access to more degrees of freedom (things that can change state) than required to solve the task. This fact is typically presented as a control problem (anything that can change state must be controlled and that control gets very hard, very fast as you increase the number of things that can change). It can also be framed as a feature, not a bug; the 'bliss of motor abundance', in Latash's excellent phrase. Our ability to reconfigure our actions to account for local conditions is the thing that enables our successful, functional interactions with the environment.
Neural systems: The brain has preferred ways of doing things, as does the perception-action system. But it has remarkable resilience in the face of damage, disease, atypical development and, presumably, the day-to-day variation in the conditions under which you have to exhibit the "same" behaviours. In neural systems this gets referred to as degeneracy; the ability of two networks with different configurations ('wiring') to produce the same function. It is again a feature, and not a bug. My favorite example of this is Eve Marder's work demonstrating how there are 452,516 biologically plausible different ways to hook up the neurons in a lobster gut and still have it output the critical pyloric rhythm that moves food through that gut (Prinz et al, 2004; blogged in detail here).
Can't we just do them both in parallel?This is the most common question I get about this topic; can't we pursue functional questions and structural questions at the same time? My answer is sure, you can, but it's risky. If you get the functional analysis wrong, then you will have spent a bunch of time asking pointless questions about the structure of the nervous system. (We think this has already happened.)
Surely the neuroscience data will tell us which way to jump, function wise? Well, partly. But there is no such thing as theory free data. Your guiding theory (the functional analysis) dictates what questions you ask and which ones you don't ask, and how to interpret the results. This is ok, it's what theory is for. But that means that structural data collected under the assumptions of one functional analysis can't tell us much about how useful the other functional analysis might be. Until neuroscience collects some data under the assumptions of REC, we don't have the ability to compare and contrast the results (anyone who knows of useful work, please tell us about it in the comments!)
(Of course, evidence (from neuroscience and elsewhere) can feed back into the functional analysis. A famous example is Freeman and Skarda (1990) who detail how they spent a long time trying to understand olfaction in the brain from a representational stance and discovered that their data simply did not support that kind of functional analysis. So in principle, these two threads can inform one another. But in practice, my suspicion is that the functional analysis dominates for the reasons laid out above).
Further ReadingFreeman, W. J., & Skarda, C. A. (1990). Representations: Who needs them. Brain organization and memory: Cells, systems, and circuits, 375-380. Download
Prinz, A., Bucher, D., & Marder, E. (2004). Similar network activity from disparate circuit parameters Nature Neuroscience, 7 (12), 1345-1352. Download
Related Blog PostsThere's More Than One Way to Rhythmically Move a Lobster