This brain imbalance, can and has been imaged via fMRI.
I put this first because it is the easiest to address. I’ve run many, many fMRI studies and not only do they lack all the pretty colors we see in ads and so forth (these are added in after imaging based on statistical signal processing, voxel size, BOLD levels, etc.), but they absolutely cannot tell us anything about any “imbalance” that has anything to do with receptors or neurotransmitters or that does anything other than to indicate the extent to which neuronal activity is characterized by nonlinearity (
imbalance), complex dynamics (nonlinearity over time), and widely-divergent activity among similar populations at levels far, far below functional brain regions such as the PFC, hippocampus, V1, etc.
The brain itself runs on chemicals (neurotransmitters and such)
I know. However, it is the fact that such chemical levels have no balance, no resting state, nor even really local fixed points that are attractors/sinks. Rather, it is defined by unbalance. The term "chaos" in so-called "chaos theory" (which has undergone various iterations and their accompanying names, such as catastrophe theory) is widely misunderstood. The intuitive sense of chaos has to do with complete unpredictability. The system is in a particular state and one point and then a completely different at another and then yet
another complete different state. In fact, chaotic systems are special because they are a kind of "controlled" chaos. It may be, for example, that the phase space of the system can be modelled fairly well (even exactly, given the necessary initial conditions and the application of suitably precise physical laws), and in fact it is more typical for chaotic systems to have such graphs. What makes them special (or rather, two things that do), is first the obvious sensitivity to arbitrary changes in parameters. Take a pyramidal neuron receiving input from some 100,000 or 200,000 other neurons while it changes what its "fuzzy" threshold is (if it has one). This neuron alone is receiving input from the axons of a hundred thousand neurons or two, and fundamental to this input is the inter-neural communication governed by neurotransmitters.
Consider now a few dozen of these, which may or may not share input but all of which are part of localized networks (which we would define arbitrarily in most cases given the scale even for cognitive neuroimaging studies, let alone neuronal models). Tiny changes in just a few ions in select places can influence a neuron's spike train (simplistically, sequences of firing rates). Most importantly,
it is absolutely fundamental that no balance exist, especially for the primary chemicals which enable neural dynamics/communication. Otherwise, you couldn’t learn, retain memories, or really do much of anything. The brain isn’t just a dynamical system but an information processing unit that, unlike a computer, has no distinction between processor and memory (memory here is used simply as encoded/stored data, not RAM vs. CPU cache vs. hard-drive space). Levels of everything from potassium ions to serotonin fluctuate wildly in every brain, but these fluctuations are governed to some extent by reinforced patternings within and even among local neural populations. However, the topological properties which best approximate some localized network don’t actually reflect the graph-theoretic properties of directed networks, first because of the internal dynamics but far more importantly because such networks synchronize nonlocally and nearly instantaneously.
So when a population of neurons which includes neurons attached to tens or hundreds of thousands of others within a local population/within a local “network” responds nearly instantaneously and continuously in response to nonlocal dynamics of other such networks, the idea of “balance” isn’t just empirically unsupported and theoretically without merit or even just nonsense; it’s a violation of physics.
To this we can add that nobody has ever detected or has any idea of what chemical “balance” of any sort would look like, other than to note that changes resulting from what we have good reason to believe are changes of neurotransmitter levels affect mood/behavior. This is true in general, though, and to identify neurotransmitters implicated in depression, bipolar disorder, schizophrenia, or that wonderful, new addition to the DSM V – “Internet Gaming Disorder”- as the cause of such disorders is not only to posit that a relationship exists between particular neurotransmitters and a cluster of symptoms that serves as the ENTIRE foundation for our diagnostic schemata, but to make the fundamental mistake of confusing correlation with a particular direction of causation.
As an addict, I have exceptionally high activity in my D2 receptors, which means I reuptake dopamine at a rapid rate, in turn not feeling pleasure the same way as the rest of the " normal" population.
Ignoring the lack of any “normal” population understood or modelled within relevant fields such that there is any “normal” dynamics to which we could compare any “abnormal” levels of neurotransmitter activity (which we can’t even measure), I have to ask: Are you aware of how many other disorders are characterized in precisely the same way?