A train or chain of action potentials (Spike train) is a sequence of time registers in which a neuron triggers electrical signals or nerve impulses. This particular form of communication between neurons is the subject of interest and study by the neuroscientific community, even if there are still many answers to be provided.
In this article, we will see what these action potential trains are, their duration and structure, what the concept of neural coding is all about and what is the current state of research in this area.
What is an action potential train?
To understand what action potential trains are, let’s first see what an action potential is.
Our brains contain approximately one hundred billion neurons emitting signals to communicate with each other constantly. These signals are electrochemical in nature and travel from the cell body of one neuron, through its axon or neurite, to the next neuron.
Each of these electrical signals or impulses is called an action potential. Action potentials occur in response to stimuli or spontaneously, and each hit typically lasts 1 millisecond.
A train of action potentials is simply a combined sequence of planes and non-planes. To be better understood: imagine a numerical sequence of zeros and ones, as in a binary system; we would assign a 1 for the move and a 0 for the no-move. In this case, a train of action potentials could be encoded as a numeric sequence, as follows: 00111100. The first two zeros would represent the latency time between the presentation of the stimulus and the first blow or action potential.
Trains of action potentials can be generated by direct sensory stimuli from sight, touch, sound or smell; I they can also be induced by abstract stimuli triggered by the use of cognitive processes such as memory (By evoking memories, for example).
Duration and structure
The duration and structure of a train of action potentials generally depend on the intensity and duration of the stimulus. These types of action potentials generally last and remain “active” as long as the stimulus is present.
However, some neurons have special electrical properties that cause a prolonged response to a very short stimulus. In this type of neuron, the most intense stimuli usually cause longer trains of action potentials..
When action potentials are repeatedly recorded from a neuron in response to changing stimuli (or when an organism generates different behaviors), they tend to maintain a relatively stable shape. However, the triggering pattern of each train of action potentials varies as the stimulus changes; Usually, the firing speed (rate of fire) changes according to different conditions.
Action potential trains they have been and continue to interest the neuroscientific community, Given its peculiarities. Many researchers are trying to discover in their studies the type of information encoded by these action potentials and how neurons are able to decode them.
Neural coding is an area of neuroscience that studies how sensory information is represented in our brains through neural networks. Researchers often find it very difficult to try to decipher trains of action potentials.
It’s hard to think of an action potential train as if it were a purely binary output device. Neurons have a minimum activation threshold and are only triggered if the intensity of the stimulus is greater than this threshold. If a constant stimulus is presented, a train of action potentials will be generated. However, the activation threshold will increase over time.
The latter, which is called sensory adaptation, is the result of processes such as synaptic desensitization, A decrease in the response to the constant stimulus produced at the synapse (the chemical connection between two neurons).
This result will lead to a reduction in the traits associated with the stimulus, which will eventually decrease to zero. This process it helps the brain not to overload itself with information from the environment that remains unchanged. For example, when after a while we stop smelling the perfume we have applied or when we adapt to background noise that bothers us at first.
As we already know, neurons communicate through the generation of action potentials, which can spread from one neuron (transmitter or presynaptic) to another (receptor or postsynaptic) via the synapse. So when the presynaptic neuron generates the action potential, the postsynaptic neuron is able to receive it and generate a response that can eventually produce a new action potential, in this case postsynaptic.
Different sequences or trains of presynaptic action potentials generally produce different chains of postsynaptic action potentials. That is why the neuroscientific community believes that there is a “neural code” associated with the temporality of action potentials; that is, the same neuron could use several different action potential sequences to, in turn, encode different types of information.
On another side, the electrical activity of a neuron is generally certainly variable, And is rarely determined in its entirety by the stimulus. Faced with successive repetitions of the same stimulus, the neuron will respond each time with a different chain of action potentials. To date, researchers have not been able to characterize the response of neurons to stimuli, nor has it been possible to clearly determine how information is encoded.
What we had thought so far was that all the information stored in a train of action potentials was encoded in its frequency; that is, in the number of action potentials that occur per unit of time. But in recent years, research has been underway on the possibility that the precise times when each action potential occurs contains critical, if not critical, information. a “neuronal signature”; that is, a sort of temporal model that would identify the emitting neuron.
The most recent research indicates the design of a new method that would characterize a chain of action potentials based on the times of each of the action potentials of the same. By applying this procedure, it would be possible to align the different sequences and determine which action potentials are equivalent in each of the chains. And with this information, we could calculate the statistical distribution which follows each action potential in a hypothetical “ideal train”.
This train of ideal action potentials would represent the common model, of which each of the real trains is only a concrete realization. Once characterized, it would be possible to know if a new chain of action potentials could adapt or not to the distribution, and therefore if it codifies the same information. This ideal train concept could have interesting implications for the study and interpretation of the neural code, as well as for strengthening the theory of neural signatures.
- Strong, SP, Koberle, R., by Ruyter van Steveninck. RR, Bialek, W. (1998). Entropy and information in neural rush trains. Phys Rev Lett; 80: pages 197 to 200.