The human brain is a complex system, consisting of around 80 billion neurons and around 1000-10000 connections between each of those neurons. Enormous complexity, so much, in fact, that the brain has trouble even fathoming its very own complexity! There are even more glial cells in the brain that aid and support the neurons, and neurotransmitters, which allow the neurons to communicate. Historically, certain parts of the brain were thought to produce certain functions. This mostly originated from a field called Phrenology, where a phrenologist would identify different aspects of your personality based on the different bumps on your skull, which of course corresponded to those parts of your brain underneath. Brain research has come a long way. Today, we have moved away from a modular paradigm, in which generally single brain areas have unique functions, to a network paradigm, in which cognitive abilities (and even consciousness itself) like attention, perception, language, memory all emerge from, the complex integration of brain areas that are connected and interact with each other in very dynamic and complex ways. Likewise, problems with cognition, certain dysfunctions, or pathological conditions, are thus problems with connectivity, that is, network problems. Thus, misophonia is a network problem, a connectivity problem. Like the brain itself, the subject is complex, so let us briefly unpack these concepts: what is a complex system, what is a brain network, how do they work, and what goes wrong?
First, a complex system is a system of many interacting elements or components that are coupled in nonlinear ways which exhibit certain properties like self-organization, emergence, and pattern formation. What does this mean? Some examples: social networks composed of humans interacting, economic markets composed of people trading, weather patterns like hurricanes composed of water and air molecules, even ant colonies, a swarm of birds, or ecological systems composed of various organisms – and of course, the human brain composed of brain cells. Each of these has many, many elements which interact with each other. The interactions are nonlinear. This means, that for example, a small input into the system (from the outside) may produce a very large output! Or, like old cliché: the whole is much more than the sum of the parts; when you add up all the elements, or contributions from the elements, you do not get what you would expect. These systems are dynamic, which means that they change over time, sometimes in very surprising ways: think of for example, an economic crash, or a sudden creation of a hurricane. This is very related to the butterfly effect, where a butterfly flaps its wings in Texas, which ultimately leads to the formation of a hurricane in the Caribbean. This may be just a metaphor, but it is useful in understand something called Chaos theory, where small, tiny changes in a systems input, can lead to large unexpected changes down the road. This happens in the human brain! Also, the concept of self-organization means that there is no top-down organizational plan or structure, that comes from a designer. A good illustration is to consider an orchestra; in this case, there is a conductor, a leader, following a specific written piece of music. The brain, or a swarm of birds, is not like that: there is no conductor, somehow, all of the pieces working together organize themselves! Global patterns form, or emerge from the interactions of local components, that know nothing about what is going on from a bird’s eye view.
Starlings, for example, group together in formations that can be a mile long, and can send huge waves from one side to the other warning of danger. Ants can work together to form a bridge to cross a gap. No one ant knows about the concept of a bridge – likewise, no one neuron can experience the color red. The study of complex systems is fascinating and is relatively new field of research, and once we understand how the brain works in this manner, we can begin pinpoint the causes of disorders like autism, or misophonia.
One of the main tools to understand the brain as a complex system, is network science. Networks are composed of nodes (single brain areas), and edges, or links, that connect them. Networks can have 2 or more nodes. One well-studies brain network, called the default mode network, is active, actually, when you are not! That is, when are you are not involved in any specific task, or just daydreaming, or thinking about yourself or others, or contemplating the future, this network becomes active, and vice versa, this network suppresses itself when you then become active or involved in a task. Much research suggests that this networks does not function correctly in pathological conditions like autism or schizophrenia. Brain areas can be connected in three ways: structurally, functionally, or causally. Structural connectivity is the physical, or anatomical connections between brain areas. Certain brain areas may not be (directly) structurally connected, but yet still be functionally connected. This means that these brain areas will be active at the same time (for some event), even though they may be very, very indirectly connected. Lastly, causal connectivity refers to the information flow in the brain: one brain area may cause another brain area to become more or less active.
Where there exist problems in any of these kinds of connectivity, pathological conditions emerge. For example, in autism, studies have shown fewer long-distance connections between brain areas, compared with children without autism. Moreover, certain brain areas involved in social brain networks become active in sync, when they shouldn’t be, or should be syncing up when they do not. Research is now ongoing into the functional connectivity problems involved in misophonia. One methodology, called Dynamical Causal Modeling, is being used by Dr. Sukhbinder Kumar and his team in London, to identify which areas of the brain involved in auditory processing and emotion have a causal effect on other areas, demonstrating possible hyper (or hypo) connectivity problems. Once we understand the connectivity issues in misophonia, we can start to address how to correct them.
Last, as a neuroscientist trying to understand the brain, and a sufferer of misophonia, I am hopeful that in the future we will have a cure for this and so many other mental diseases.