Here is what we know about the brain in very general terms. Basically there are neurons throughout the nervous system that are wired to talk to each other. These wiring patterns are established during early development, and, as an individual ages, life experiences can modify these preexisting “circuits.” Such modifications can abolish certain circuits, enhance preexisting ones or even form entirely new ones. Activity within these neural circuits leads to computations that encode information from the external world. This information is then further used by neural circuits to generate some form of output, be it taking your hands off a burning stove or reacting to a melody. What is the neural language that encodes these sensory experiences and generates appropriate output?
According to what is currently known, neural language occurs on two different levels — microscopic and macroscopic.
The microscopic level of neural language deals with a single neuron. Due to certain electrochemical properties, this single neuron can “fire.” The formal definition of this neural firing is the production of “action potential.”
The physical meaning of an action potential is a very fast, rapid and reversible change in the neuron’s electrochemical properties. Therefore a neuron can use action potentials as codes by varying the patterns at which it fires. The neuron can fire more or less often. It can also fire the same number of action potentials in a period of time, but a neuron might additionally change the patterns in between these action potentials (for example it could emit five spikes in the first two seconds, pause for two seconds and fire another three spikes within one second).
An easy-to-understand example of neural language operating at the single neuron level is auditory processing. One property of sound is that it can be perceived as “loud” or “quiet.” Loudness is defined by a measure of “sound pressure level.”
Neurons in the auditory system contain an intensity code of sound pressure level. When the sound pressure level increases, an auditory neuron fires more action potentials. At a lower sound pressure level, the auditory neuron fires fewer action potentials.
In addition to single neurons firing action potentials, these neurons communicate together at a macroscopic population level. Let’s go back to the auditory processing example. As the sound pressure level increases, individual auditory neurons fire more frequently, and more auditory neurons are recruited to start firing. Therefore many neurons can fire action potentials, and these large populations of neurons can work together to encode information.
The intensity code of auditory processing is a relatively simple example of neural language that occurs at the single-neuron level and at the network level. For more abstract computations, this neural language gets a lot more complicated.
One such example is decision-making that is based on learned information about the world. It has been found that during specialized modes of decision-making, in which the organism seemingly abandons previous beliefs about the world to explore novel options, there is an intricate network “reset” in the area of the brain known as the anterior cingulate cortex. Unlike the simple intensity code of auditory processing, in which more neurons start firing when sound volume increases, this network reset in the anterior cingulate cortex does not involve any net changes in overall activity. Instead some neurons fire more, and some fire less. The true functional understanding of a reset is largely unknown.
Where does the field currently stand in terms of understanding neural language? To summarize, we have figured out that the neural language seems to be constructed from patterns of neural firing, which can occur at a single neuron level and at a network level. There have been more studies regarding neural language at the single neuron level, whereas the idea of “network” communication is new, due to the recent emergence of recording technologies that enable investigations of neural activity across several different neurons. To put it simply, we have a basic understanding of the neural language in very simple cases, such as coding sound volume level.
Yet when it comes to more complicated computations, such as mood determination and decision-making, we still have absolutely no functional understanding of the precise ways in which these phenomena take place. Understanding the functional significance of neural activity across a defined network is one central goal of contemporary neuroscience. Gaining this understanding could potentially lead us toward developing the first “dictionary” of the brain’s neural language.
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