There's More to Us Than Our Brains - So What Does The Brain Do?

I'm not that interested in the brain.

It's hard to be this way in modern psychology. Cognitive neuroscience is where it's at, and I think I come off as  a bit of a Luddite when I try to convince people fMRI is a bit of a waste of time. Not caring much about the brain is certainly a sociological reason why ecological psychology doesn't get taken very seriously; we're just the crazy people who don't think there are mental representations, based on some work from the 50s-70s. Surely modern imaging has shown us the activity of mental representations? Clearly, the brain is the source of all behavior! Popular science writing on psychology is all cognitive and representational; most of the psychology blogging I come across is neuroscientific. What else could it be?

I've certainly spent a lot of time waving the flag against the infiltration of neuro-talk into places it doesn't yet belong; but to be honest, as I get older, I've begun to worry that I'm trying to be 'fair and balanced' in the sense Fox News is fair and balanced: relentlessly playing up one side to offset a perceived imbalance elsewhere. What I actually want to do is be actually fair and balanced: I want my own discussions about these issues to be internally balanced and coherent, giving credit where credit is actually due. I want to start teasing apart a few issues I've conflated over the years, so that my strong concerns about the relevance of fMRI  and cognitive neuroscience work stop getting swallowed up in a general dismissal of the brain's role in our lives. The brain is clearly interesting, but it's not representing, and if not that, what is it doing?

This post is therefore a first swing at integrating a lot of the things I've been blogging about for a while and doing so in a way that leaves a sensible role for the brain. I'm going to need some neuroscientists to talk to, though; I'd appreciate it if people could spread the word on this a little, because there are just some things I want to go a few rounds on with people who know what they're talking about. 

What is the brain doing?
It's clearly the case that the brain is up to something; it consumes something like 20% of our body's energy (Clark & Sokoloff, 1999), and our bodies are thoroughly innervated by projections to and from the nervous system. So what, precisely, is it up to?

Incorrect Answer: Mentally representing the world

Whatever it's up to, the brain is not representing the world. My main reason for thinking this is that this argument is firmly based in the assumption of poverty of stimulus, which is entirely incorrect. My very first post on this blog was about this;  modern cognitive psychology is committed to this assumption, and everything it thinks the brain is up to stems from this assumption. In actual fact, we are embedded in a rich information flow to which we have a great deal of direct access, so representation just isn't really required any more.

A note about what I think representations are for

Cognitive psychology is dedicated to the idea that the input to the system is insufficient to support the kinds of behaviour we see. Mental representations are mediating states which have content, and this content is used to supplement the input so as to make it good enough to produce the behaviour we actually observe. But they are only required if the input is impoverished, and the point of the ecological approach is that the input is rich and specific to the environment. If this is the case, then the brain doesn't need to be mentally representing anything.

There are a couple of reasons why people think the stimulus is poor. The tipping point for the cognitive revolution in the 1960s was Chomsky's review of Skinner's Verbal Behaviour, which claimed to show that the input for language simply wasn't structured enough to support a learning story. In perception, the poverty of stimulus assumption is rooted in studying the anatomy of the eye. The retina seems to only be capable to producing an upside-down, horribly noisy and pixelated image, and so clearly this input needs serious enriching in order to support the visual experience we are all familiar with. Gibson spent some time detailing why this is ridiculous; vision is not derived from static images and the retinal image is an invention of scientists, an analytic tool, not a fact of perception. Interestingly, while Chomsky's ideas are alive and well in linguistics, psychology is getting increasingly interested in the richness of the statistical structure of linguistic input and starting to tell interesting learning stories.

So what is the brain doing then?

The brain is not some isolated, abstract executive. The idea of the brain in a vat is incoherent and a distraction; real brains are utterly integrated with a wide variety of other systems as well as the world around it, via perception. Brains have an important job to do, but they just aren't the only player in the game and there's a lot of things they simply don't need to do because some other system takes care of it. (Done carefully, this is the point of embodied, enactivist theories of cognition). To work out what the brain needs to do, one thing we have to do is understand what everything else is up to. We need job descriptions for the brain and the bodies they're embedded in.

Here's what I believe to be true:

Our behaviour emerges over time as we respond to the flow of information in our environment. We are not general purpose systems - we are, instead, at any given moment, one kind of task specific device (and importantly, not another kind). The kind of device we currently are is a function of what we've been up to recently; the specifics of the device reflect the nature of multiple subsystems and how these respond to the flow of information we are currently embedded within (more on this in a moment; bear with me).

This information flow is surprisingly stable; we are not adrift in a 'blooming, buzzing confusion' (to use the regularly misused William James quote). One consequence of this stability is that we can rely on it to do a lot of work for us, and there is plenty of evidence that we do just this. My favourite example is change-blindness, a phenomenon in which people can be easily made to not notice dramatic changes in their environment by removing the information specifying that a change has occurred. The early versions of these studies involved 2-frame animations of, say an aeroplane. In one frame, the engine was present under the wing, and in the other frame it's missing. You play this animation over and over and ask people whether anything is changing, and people take ages to find it, if ever. There's a critical trick, however: the animation has to be filtered to remove what's called a transient signal: the abrupt change in pixel values creates a blip, if you like, in the signal. If you filter this out, but still have two very different frames, then people simply often do not see the change. There are more recent and ambitious demonstrations, including some great real life examples (see this video, for example) but they all also require that something covers up the information that something has changed (a camera cut, or an intervening event).

Change blindness tells us that we do not store a representation of a scene; instead, we simply perceive the flow of information about the scene and respond. We don't see the change because the information specifying that a change has occurred has been removed - no information, no basis for noticing the difference. We float along in a flow of information and our behaviour emerges as we interact with that flow.

We aren't passive blank slates, however. At any given moment in time we are very specific measurement devices, sensitive to some information variables and not others and capable of responding in some ways and not others. We spend our days being one device, then another, then another, in response to changes in the information flow and in accordance with our capacities. The information flow alters as our location in space and time changes, and is specific to the current environment; our capacities reflect the current state of multiple subsystems, of which the brain is only one.

The kinds of devices we are

If I measure my height with a ruler calibrated in inch units, I get the number 67 out. If I do it with a ruler calibrated in centimetre units, I get 170. It's the same amount of space, but my two measurements have produced different results because they are calibrated differently.  If I want to measure area and only have a straight ruler, I have to make several independent measurements and combine them in a computation; if I have a polar planimeter, I can measure the area directly, no computation required. The 'simple' unit depends on the device and can, actually, be quite higher order (see this old post for what I still think is an excellent explanation using right angled triangles).

The moral of those two points is this: perception is an act of measurement, and the result of an act of measurement depends on the device doing the measuring. The perception-action approach claims we perceptually measure the world using measurement devices calibrated in action-relevant units; the output is therefore action-scaled without any further manipulation required and can be plugged directly into the action system in question. 

The trick here is that the actions we are attempting to perform are constantly changing, and thus the device we measure the world with needs to be regularly re-calibrated to different scales. Proffit's work on distance perception clearly demonstrates that we perceive the 'same' distance differently depending on whether we intend to traverse it by walking or throwing. This is what I mean when I say we move through the day being one device, then another, then another - as the required actions change, so must our perceptual measurement systems.

Calibration & Subsystems

We are, in turns out, very flexible devices. Healthy adults can calibrate and recalibrate swiftly and efficiently, although it takes years to be fully competent at this (hence motor development is a long, slow process). Recalibration does take time (we are physical systems with inertia and delays) but then persists for a while without active maintenance (for roughly the same reason); it can, of course, be maintained more robustly if the required information remains present. 

We build these devices out of the locally available resource dynamics; the combination of the task-related incidental dynamics and our internally available inherent dynamics (definitions and details here). We couple ourselves to incidental dynamical resources via perception (e.g. tool use); we use perception in an identical fashion for our inherent dynamics (there's no privileged access, no peeking behind the curtain - we only know what perception tells us), but these are obviously special in one sense, namely that we take them from one task to the next. 

Our inherent dynamical resources come from a variety of subsystems. Each contributes different elements to a task-specific perception-action device. Most critically, I think, these systems work at different time-scales to provide a careful balance between stability and flexibility, and this is where the brain starts to enter back into things for me. Bingham (1988) describes the following basic divisions in the inherent dynamics. These subsystems are all coupled to one another, and their basic behaviours are non-linear, as are the couplings.

1. The link-segment system: our skeleton is hooked together in a very specific way, and this arrangement enables some behaviour and rules some other behaviours out. This arrangement doesn't fundamentally change over time (barring injury, although the composition of the bones remodels in response to load-bearing exercise over long time scales), and thus it serves as a very stable basis for the other systems. The role of this system is to provide a physical substrate for the transmission of the forces involved in moving and interacting with the world, and it places useful constraints on the kind of motions that are possible.
2. The musculotendon system: the size, shape and composition of this system is partly constrained by genetics, but is of course highly responsive to use. The time course is days and weeks, and so this system is highly stable over short periods of time but flexible and responsive to demand over longer time scales. The role of this system is to generate the forces required to move the link-segment system; it's organised in ways to solve many of the 'degrees of freedom' problems inherent in controlling a complex system.
3. The circulatory system:  This system is highly responsive to current events: it only takes 10s of seconds for heart rate to accommodate current energy demands, and veins and arteries change size and shape in response. The role of this system is to deliver energy to the musculotendon system so it can generate the forces required to move the link-segment system.
4. The respiratory system: This is another highly responsive system which adapts to current requirements on very short time-scales. It's role is to provide oxygen and remove carbon dioxide, to enable the continuing metabolic processes powering the muscles.
5. Nutritional systems: this operates over longer time scales, and it's role is to provide the nutrients and energy required for the above systems. 

Finally, the nervous system. The brain and it's innervation of the body via the peripheral nervous system seems to me to be the fast response system in all this. The nervous system responds on microsecond time scales, and is in constant flux. It's connected to everything, and is, I think, the primary medium for the informational coupling between the various subsystems (not the only one; a lot of these systems have direct physical contact, for instance). 

The brain is dynamically stable, possibly (probably?) ideally edge-of-chaos stable. It exhibits a great deal of structural stability (visual cortex is in the same place in everyone), but even this stability is being actively maintained by the stability of the informational flow. Change that flow (for example, have someone pick up a tool, or provide information that you actually have three hands) and that structure smoothly alters in response. The reason visual cortex is where it is and organised the way it is, therefore, is because that's what a nervous system looks like when it is exposed to that kind of informational flow. Change the flow, change the organisation (as happens when people become blind, for instance: that cortex is 'colonised' by neighbouring functionality because it's structure as visual cortex is no longer being maintained).

Besides this actively maintained stability, the brain also ebbs and flows in fast response to changes in that flow. I remember taking Olaf Sporn's neuroscience class and watching microscope video of neurons extending and retracting axons on millisecond timescales; neurons aren't static at all, they are alive and frankly they are busy as fuck. The brain is alive and on the go and what it looks like at any given moment is a function of the information flow it is currently embedded in.

Trying to get a rigorous handle on this kind of dynamic behaviour is a daunting task. What makes me think it's possible is the fact that people are trying seriously to do it. I mentioned Olaf Sporns; he's a neuroscience professor at IU and he's about the only neuroscientist I've ever seen in person grapple seriously with the dynamic nature of the brain. He gave a talk once to the cognitive science reading group when I was there, and I came away thinking that 'yes, that's it, that's the way to do business'. I'm slowly reading his excellent book Networks of the Brain, and the purpose of that book is to connect neuroscientists with the modern science of network analysis so they can give up on 'biologically plausible neural networks' (you know, the little PDP toys we all got impressed with in the 80s and 90s) and actually try to cope somehow with the multi-scale structure of the brain. 

(One of the ideas I like a lot already is that of topological neighbours. Topology is a flavour of geometry that describes the set of possible transformations and relations possible when you relax the rules as far as you can; no need to preserve metric distances, for example. Networks can contain regions which are not physically next to one another but that are informationally coupled so that they are effectively part of the same network This informational coupling can then ebb and flow over time, so a given bit of cortex can be involved in multiple systems doing different things at different times. Of course, not all combinations are possible; there are anatomical limits on who is connected to whom and by how many steps.  It's not clear to me that fMRI based neuroscience can cope with this kind of data, and wouldn't know it was seeing it if it saw it.)

So what is the brain doing? With our clearer understanding of what's going into the total system, we can start making sensible guesses.

I think the nervous system is the fast switching system that enables us to functionally wall off resource dynamics to form task specific devices, a walling off which lasts only as long as it's supported by the flow of information. I think the nervous system routes action scaled information to the systems that can use it. In network geometry terms, I think the nervous system is a high dimensional shape that constantly changes configuration in response to information, preserving some aspects and transforming others. I think the notion of invariance-over-transformation is a geometric tool that applies equally to this network as to the optic flow Gibson applied it too; there is flux, but critically there is invariance and that invariance is information. I also think these are all very different from what most people seem to think goes on in the brain.

I don't think the brain is performing all the computations supposedly required to move a limb, given a) many of those 'computations' are actually solved by the architecture of, say, the hand, and b) not enough people seem to know about the way the nervous system actually moves limbs, namely via equilibrium point control. I don't think the nervous system is the place to look to explain stability in behaviour; the globally stable environment we live in and have perceptual contact with solves that problem.

Now all I need to do is make these slightly mad sounding ideas make more sense and hold together better. Annoying questions welcome :)

References
Bingham, G. (1988). Task-specific devices and the perceptual bottleneck. Human Movement Science, 7 (2-4), 225-264 DOI: 10.1016/0167-9457(88)90013-9  Download

Clarke, D.D., & Sokoloff, L. (1999). Circulation and energy metabolism of the brain. In Basic Neurochemistry, Molecular, Cellular and Medical Aspects (6th ed) (Agranoff,   B.W., Siegel, G. J, eds), pp. 637-670. Lippincott-Raven

Sporns, O. (2010) Networks of the Brain. Cambridge, MA: MIT Press. Amazon.co.uk