State of understanding is a long way off

There are many ways in which the brain is visualized. Each may be useful in some situations but all are misleading in others.

 

First example: the action of the brain is the result of the balance of neurotransmitters. Is there too much or too little dopamine? There is no doubt that the neurotransmitters and their receptors are very important but not in so simplistic a form. A while ago there was a posting by Neuroskeptic (here) where the metaphor of soup was used.

The concept of a ‘chemical imbalance’ in the human brain is one of the most fantastic oversimplifications in science, and one of the worst legacies of the modern pharmaceutical industry. … A bowl of soup could have a chemical imbalance. …Our technology for investigating the chemistry of the brain is comically crude.

 

Second example: the action of the brain is the result of specialized ‘areas for x’. Is there an area for love? Of course, it is true that there is a good deal of localization of various types of processing but this is a long way from ‘areas for x’. Some call it the ‘new phrenology’ and (here) is Michael Shermer’s take.

Today a popular metaphor is that the brain is like a Swiss Army knife, with specialized modules for vision, language, facial recognition, cheating detection, risk taking, spirituality and even God.

Modularity metaphors have been fueled by a new brain-scanning technology called functional magnetic resonance imaging (fMRI). We have all seen scans with highlighted (usually in red) areas where your brain “lights up” when thinking about X (money, sex, God, and so on)… There is a skeptical movement afoot to curtail abuses of the metaphor, however, and it is being driven by neuroscientists themselves.

 

Third example: the action of the brain is the result for a few networks, groups of local areas across the brain that act together. The favorite approach lately has been to contrast the default network and the task oriented network. This seems a very productive approach but a long way from a clear theory. The problem is that as studies look closer there are variations in the network components and overlaps depending on the type of task or rest etc. Much that is said about networks appears simplistic. G. deMarco pointed out the complications (here)

The concept supposes the existence of a dynamic interaction between interconnected, active areas and that the brain areas are expressed as networks within integrated systems. In such a system, localized areas are included in networks which become dynamic according to the cognitive task. Brain areas underlie several functions and can belong successively to several different functional networks. In other words, a given brain area does not have a single function; its resources can be exploited in several different cognitive strategies.

 

There are many more examples. Now the big idea is the connectome. If we knew all the connections between neurons we would know how the brain operated. The mantra is ‘you are your connectome’. To date the only connectome that has been documented is of a tiny worm with exactly 302 neurons in its nervous system. It does not seem that the connectome resulted in a complete understanding of C. elegans’ behaviour. This is because its neurons are not interchangeable widgets. A NeuroDojo post reviews the fight over the usefulness of the connectome project (here).

In one sense, the theory is trivially true. But in another sense, the theory omits so much that it doesn’t end up telling us anything we wanted to know.

 

So we have a lot of useful but incomplete ways to look at brain activity. Understanding is not right around the corner. But on the other hand, it is not impossible either. We should not settle for simplistic theories and we should not lose hope of a strong theory someday.