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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Neuron | 6/8 | https://en.wikipedia.org/wiki/Neuron | reference | science, encyclopedia | 2026-05-05T07:31:09.374333+00:00 | kb-cron |
The conduction of nerve impulses is an example of an all-or-none response. In other words, if a neuron responds at all, then it must respond completely. Greater intensity of stimulation, like brighter image/louder sound, does not produce a stronger signal but can increase firing frequency. Receptors respond in different ways to stimuli. Slowly adapting or tonic receptors respond to a steady stimulus and produce a steady rate of firing. Tonic receptors most often respond to increased stimulus intensity by increasing their firing frequency, usually as a power function of stimulus plotted against impulses per second. This can be likened to an intrinsic property of light where greater intensity of a specific frequency (color) requires more photons, as the photons cannot become "stronger" for a specific frequency. Other receptor types include quickly adapting or phasic receptors, where firing decreases or stops with a steady stimulus; examples include skin which, when touched causes neurons to fire, but if the object maintains even pressure, the neurons stop firing. The neurons of the skin and muscles that are responsive to pressure and vibration have filtering accessory structures that aid their function. The pacinian corpuscle is one such structure. It has concentric layers like an onion, which form around the axon terminal. When pressure is applied and the corpuscle is deformed, mechanical stimulus is transferred to the axon, which fires. If the pressure is steady, the stimulus ends; thus, these neurons typically respond with a transient depolarization during the initial deformation and again when the pressure is removed, which causes the corpuscle to change shape again. Other types of adaptation are important in extending the function of several other neurons. Although neurons have long been assumed to always give a stereotyped maximal response or none at all, there is a body of research that argues that this is only partially correct, and that while it is true that Neurons either fire an Action Potential or do not, the amplitude and duration of the Action Potentials that a Neuron fires can vary greatly, allowing the Neuron to encode information in at least the strength of the Action Potential. Additionally, the analog information carried in the Action Potential has been shown to be able to survive and travel distances originally not thought to be possible. This has been proposed to be a highly effective way to encode information compared to the usual rate and temporal coding theories commonly seen in the literature, with the ability to transfer around 4 times more information than current wisdom would suggest.
== Etymology and spelling == The German anatomist Heinrich Wilhelm Waldeyer introduced the term neuron in 1891, based on the ancient Greek νεῦρον neuron 'sinew, cord, nerve'. The word was adopted in French with the spelling neurone. That spelling was also used by many writers in English, but has now become rare in American usage and uncommon in British usage. Some previous works used nerve cell (cellule nervose), as adopted in Camillo Golgi's 1873 paper on the discovery of the silver staining technique used to visualize nervous tissue under light microscopy.
== History ==
The neuron's place as the primary functional unit of the nervous system was first recognized in the late 19th century through the work of the Spanish anatomist Santiago Ramón y Cajal. To make the structure of individual neurons visible, Ramón y Cajal improved a silver staining process that had been developed by Camillo Golgi. The improved process involves a technique called "double impregnation" and is still in use. In 1888 Ramón y Cajal published a paper about the bird cerebellum. In this paper, he stated that he could not find evidence for anastomosis between axons and dendrites and called each nervous element "an autonomous canton." This became known as the neuron doctrine, one of the central tenets of modern neuroscience. In 1891, the German anatomist Heinrich Wilhelm Waldeyer wrote a highly influential review of the neuron doctrine in which he introduced the term neuron to describe the anatomical and physiological unit of the nervous system. The silver impregnation stains are a useful method for neuroanatomical investigations because, for reasons unknown, it stains only a small percentage of cells in a tissue, exposing the complete micro structure of individual neurons without much overlap from other cells.
=== Neuron doctrine ===
The neuron doctrine is the now fundamental idea that neurons are the basic structural and functional units of the nervous system. The theory was put forward by Santiago Ramón y Cajal in the late 19th century. It held that neurons are discrete cells (not connected in a meshwork), acting as metabolically distinct units. Later discoveries yielded refinements to the doctrine. For example, glial cells, which are non-neuronal, play an essential role in information processing. Also, electrical synapses are more common than previously thought, comprising direct, cytoplasmic connections between neurons; In fact, neurons can form even tighter couplings: the squid giant axon arises from the fusion of multiple axons. Ramón y Cajal also postulated the Law of Dynamic Polarization, which states that a neuron receives signals at its dendrites and cell body and transmits them, as action potentials, along the axon in one direction: away from the cell body. The Law of Dynamic Polarization has important exceptions; dendrites can serve as synaptic output sites of neurons and axons can receive synaptic inputs.
=== Compartmental modelling of neurons === Although neurons are often described as "fundamental units" of the brain, they perform internal computations. Neurons integrate input within dendrites, and this complexity is lost in models that assume neurons to be a fundamental unit. Dendritic branches can be modeled as spatial compartments, whose activity is related to passive membrane properties, but may also be different depending on input from synapses. Compartmental modelling of dendrites is especially helpful for understanding the behavior of neurons that are too small to record with electrodes, as is the case for Drosophila melanogaster.