Neuro Science  

 

 

 

Neuron

A neuron is a cell that functions a bulding block of Nervous System. Everybody would know that most of biological organisms (e.g, plants and animals) is made up of a basic structural and functional units called a cell. If you go into a higher plants or animals (e.g, human), the individual is made up of various organs (e.g, heart, kidney, brain etc) and each of those organ is made up of its own structural and functional units called a cell. A neuron is a special type of cell that is building block of a nervous system.

Structure of a Neuron

A typical structure of a neuron can be illustrated as below. You might have seen this kind of picture from almost any text and videos explain about basic neuroscience. Don't try to memorize this picture... you would get familiar or even memorize the picture if you draw it on paper by hand a few times.

Labelled drawing of a neuron, from dendrites through the cell body and axon to the synaptic end bulbs

The drawing labels nine parts, and they are easiest to hold in mind by following the direction a signal travels. Input arrives at the dendrites, is gathered at the cell body, and leaves along the axon. The magnified inset at the top left enlarges one dendrite branch so that the spines on it become visible.

  • Dendrite : the branching input structure, drawn spreading above the cell body.
  • Dendritic spine : the small knobs along a dendrite. They are what the inset at the top left enlarges.
  • Cell body (SOMA) : the shaded centre where the inputs are gathered.
  • Axon Hillock : the junction where the cell body narrows into the axon.
  • Axon : the single long output fibre running down the middle of the drawing.
  • Myelin Sheath : the segmented covering drawn around the axon.
  • Node of Ranvier : the gap between two neighbouring sheath segments.
  • Axon Terminal : the branching at the far end of the axon.
  • Synaptic End Bulb (Synaptic knob) : the filled dot at the tip of each terminal branch.

NOTE : Most of the labeled part can be seen under the microscope relatively easy, but some part (especially Axon Hillock) would not easily be observable.

NOTE : Regarding the functionality of labled part (especially Dendrite spine, Synaptic knob etc), refer to the note about Signaling.

Two asymmetries in the drawing carry most of its meaning. A neuron has many dendrites and exactly one axon, so it collects from many sources and answers with a single output. The axon is also the only part wearing a sheath, and that sheath is interrupted rather than continuous.

  • Input branches and output does not : many dendrites converge on one cell body, and a single axon leaves it.
  • The axon hillock is where the two halves meet : it is the narrowing between cell body and axon, and it is the part the note above calls hard to observe.
  • The sheath is interrupted on purpose : the Nodes of Ranvier are gaps between myelin segments, not gaps in the drawing.
  • Spines sit on dendrites, not on the axon : the inset enlarges them because they are too small to read at the scale of the main figure.

How do the parts of a neuron turn input into output ?

The structure drawing names each part, but the labels do not explain the handoff between them. The important question is where variable input becomes a standard electrical output.

Signals arriving at dendrites usually change the local membrane potential. These graded potentials can be excitatory or inhibitory, and their amplitudes vary with input strength. They weaken as they spread toward the cell body, where nearby dendrites and the soma combine their effects across both space and time.

An excitatory effect moves the membrane potential toward threshold, whereas an inhibitory effect opposes that movement or reduces an existing excitation. Therefore inputs from many synapses compete before the neuron produces an output signal.

The decisive region is usually the axon initial segment, beside the axon hillock. Voltage-gated ion channels generate an action potential only if the combined membrane potential reaches threshold. Otherwise, the graded change decays instead of continuing along the axon. Each action potential is all-or-none, so stronger sustained input usually increases firing rate rather than spike size.

Figure 1 follows the conversion from dendritic input to synaptic output and separates graded signals from the action potential they may trigger.

One neuron's input-to-output sequence Dendrites graded inputs excitatory + inhibitory Cell body spatial + temporal summation Axon initial segment threshold decision action potential starts Axon action potential propagates Axon terminals Ca2+ entry transmitter release Below threshold: graded change decays At threshold: an action potential begins

Figure 1. Threshold separates local computation from long-distance transmission. Only a sufficient combined input starts an action potential.

Myelin changes how that action potential travels along the axon. In a myelinated axon, current spreads rapidly beneath myelin and the signal is regenerated mainly at each Node of Ranvier. This propagation pattern is called saltatory conduction. An unmyelinated axon instead regenerates the signal along successive regions of membrane.

At the axon terminals, the action potential opens voltage-gated calcium channels, and calcium entry triggers synaptic vesicles to release neurotransmitter. Thus the electrical signal inside the neuron becomes a chemical signal across most synapses. The detailed ion movements and synaptic sequence are covered in Signaling.

  • Dendrites and the cell body handle graded input : excitation and inhibition are combined across space and time.
  • The axon initial segment applies the threshold : a sufficient combined input starts an all-or-none action potential.
  • Input strength is usually represented by firing rate : stronger sustained input does not enlarge each action potential.
  • Myelin changes the propagation path : the action potential is regenerated mainly at the Nodes of Ranvier.
  • Axon terminals convert the signal again : calcium entry links the electrical action potential to chemical transmitter release.

Types of Neuron

Even though the sturcture of a neuron is explained by a typical / single type of neuron, there are many different types of neurons in our nervous system. Some of examples are shown below.

Five neuron shapes side by side, labelled Unipolar, Pseudo-Unipolar, Bipolar, Multipolar and Pyramidal

The five drawings differ in one thing, which is how many processes leave the cell body. That count is what most of the names encode. Reading from left to right, the cell body starts at one end of the cell, moves towards the middle, and then grows branches of its own.

  • Unipolar : one process leaves the cell body, which sits at the top. That single process branches only at the far end.
  • Pseudo-Unipolar : the cell body hangs to one side on a short stalk. The process it joins runs straight through and branches at both ends.
  • Bipolar : the cell body sits in the middle of the cell, with one process leaving from each end.
  • Multipolar : the cell body is drawn as a star, with several dendrites radiating from it and one axon leaving downwards.
  • Pyramidal : the cell body is triangular. One prominent dendrite rises from the apex and branches widely, and smaller branches sit around the base.

Usually depending on locations, layers of the cortex or types of sensory organs (e.g, retinal, sensory neursons) etc, the dominant types of neuron varies.  For example, Bipolar neuron is dominantly observable in retina and Pysamidal neuron is frequently observable in specific layers of brain cortex.

  • Most of the names count the processes : unipolar has one, bipolar has two, and multipolar has many.
  • Pseudo-unipolar looks unipolar and works like bipolar : a single stalk leaves the cell body and then splits into two branches running opposite ways.
  • Pyramidal is named for its shape rather than its count : it has many processes, and the triangular cell body with an apical dendrite is what sets it apart.
  • The dominant type follows the location : bipolar cells in the retina and pyramidal cells in particular cortical layers, as this section notes.

Functional Types of Neuron

The previous section sorts neurons by shape. There is a second sorting that most textbooks give first, and it asks a different question. Not what the cell looks like, but which way the signal travels through it.

By that measure there are three kinds. A sensory neuron carries information inward, from the world into the nervous system. A motor neuron carries it outward, to a muscle, a gland or an organ. An interneuron sits between the two and connects them to each other.

The two sortings are not independent, and the link is worth writing down because Types of Neuron already draws it without saying so. Most sensory neurons are pseudounipolar, which is the second shape in that drawing. One axon leaves the cell body and splits into two branches. Motor neurons are multipolar, each with one axon and several dendrites, and interneurons are multipolar as well.

< The three functional types, and the shape each usually takes >

Functional type

Direction of the signal

Usual shape

What it connects

Sensory, or afferent

inward, into the nervous system

pseudounipolar

A sensory receptor at one end. It is activated by sensory input from the environment.

Motor, or efferent

outward, out of the nervous system

multipolar

A muscle, gland or organ at one end. Lower motor neurons run from the spinal cord to a muscle, and upper motor neurons run between brain and spinal cord.

Interneuron

internal, neither end leaves

multipolar

Other neurons at both ends. Interneurons connect spinal motor and sensory neurons, and they also communicate with each other.

The interneuron is the easiest of the three to overlook, and it is the one that does the interesting work. A sensory neuron and a motor neuron each have one end outside the nervous system, at a receptor or at a muscle. An interneuron has neither end outside. Everything it touches is another neuron, and interneurons wired to each other form circuits of various complexity.

  • Shape and function are two separate sortings : the previous section counts the processes leaving the cell body, and this one follows the direction of the signal.
  • Most sensory neurons are pseudounipolar : one axon leaves the cell body and then splits into two branches.
  • Motor neurons and interneurons are both multipolar : one axon and several dendrites, which is the most common body plan for a nerve cell.
  • Only the interneuron keeps both ends inside : it connects sensory and motor neurons, and interneurons also connect to one another.

Glial Cells

Look again at the drawing in Structure of a Neuron. It labels a Myelin Sheath around the axon, and Nodes of Ranvier where that wrapping stops. Nothing in the picture says what builds the sheath. The answer is that the neuron does not build it, and another kind of cell does.

Those other cells are the glia. The mature central nervous system has three kinds of them. Astrocytes maintain, in a variety of ways, an appropriate chemical environment for neuronal signaling. Oligodendrocytes lay down a laminated, lipid-rich wrapping called myelin around some, but not all, axons. Microglial cells are primarily scavenger cells that remove cellular debris from sites of injury or normal cell turnover.

So the sheath in the drawing is the work of an oligodendrocyte, as long as the axon is in the brain or the spinal cord. Outside them, in the peripheral nervous system, the cells that elaborate myelin are called Schwann cells instead. The Nodes of Ranvier are the gaps left between one wrapping cell and the next.

One number attached to glia deserves care, because you will meet it often and it is usually wrong. Older texts put glia at ten times the number of neurons, and some put the figure at three to one. Counting the cells directly gives about 86 billion neurons against about 85 billion non-neuronal cells in the human brain, which is close to one to one. A later review of 150 years of cell counting found no published study that supports the ten to one figure at all.

A single whole-brain ratio also hides a wide regional spread, so it is worth less than it looks. The ratio runs at roughly 3.76 to 1 in the cerebral cortex and roughly 1 to 4.3 in the cerebellum. The cerebellum, in other words, holds more neurons than glia.

One thing glia do not do is signal the way a neuron signals. Glia do not participate directly in synaptic interactions and electrical signaling. Their supportive functions do help define synaptic contacts and maintain the signaling abilities of neurons, which is a different kind of contribution.

  • The sheath in the figure is not built by the neuron : an oligodendrocyte builds it in the central nervous system, and a Schwann cell does so in the peripheral nervous system.
  • Three kinds of glia in the mature CNS : astrocytes for the chemical environment, oligodendrocytes for myelin, and microglia for clearing debris.
  • The ten to one ratio is a myth : direct counting gives about 86 billion neurons against about 85 billion non-neuronal cells.
  • A whole-brain ratio hides the regional spread : about 3.76 to 1 in the cerebral cortex, and about 1 to 4.3 in the cerebellum.
  • Glia do not signal the way neurons do : they take no direct part in synaptic interactions or electrical signalling.

Special Neurons

In this section, I want to talk about some examples of neurons that perform a specific funtions. That is, it is about the aspect of functionalities, not about the aspect of structure/Anatomy. The special neurons/cells introduced here plays a specific role in a bigger brain functionality (e.g, memory formation, perception etc) and would be mentioned in other notes (e.g, Memory/Learning), but I am trying to consolidate all of these special neurons in one place.

Place Neuron/Place Cell

Place Neuron (or Place cell) is the type of neuron that fires only when an animal is located in a specific place.

  • It is discoverd in 1971 by John OKeefe and located in Hippocampus (Refer to This)
  • It is a pyramidal type neuron

As shown in the illustration below as an example, the electrical activities (neuronal firsing) of a specific neuron is being measured while the object (a mouse) wondering around in 2 dimensional plane. As you see, the neuron fires only when the mouse is at a specific place (e.g, the position (C) in this example) and does not firue when the mouse is at other places.

A mouse wandering a 2D arena, with spike trains at five points and dense firing only at point C

The image on the right in following picture indicates the brain region where place cells located. It is Hippocampus.

Firing map of a place cell in an arena beside a rat head showing the hippocampus

Image Source : Scientific Background - The Brains Navigational Place and Grid Cell System

Does the place neuron exists only for a certain position in 2D plane ?  According to recent studies, it is discovered that the place neuron exists for specific position in 3D space as well.

The 970 mm lattice cube used to test place cells in three dimensions, with cameras and a rat inside it

Image Source : The place-cell representation of volumetric space in rats - Nature (2020)

Three recorded cells shown as 3D spike clouds with XY, XZ and YZ spike maps and rate maps

Two more recorded cells as 3D spike clouds and rate maps, with the path and spike legend

Image Source : The place-cell representation of volumetric space in rats - Nature (2020)

NOTE : In this section we saw a specific type of neurons that fires for a specific places. Does it mean that memory for a specific location is stored within a specific nerve cell ?  that is different story. It may be related to the place neuron, but thoe whole story of the memory formation for a certain place would be much more complicated and we still don't have the full / detailed picture of it.

Grid Cell

Grid cells are specialized neurons in the entorhinal cortex that fire when an animal occupies specific locations in its environment. These cells form a hexagonal grid pattern, enabling the animal to represent and navigate through space. Grid cells work in conjunction with place cells and head direction cells to create a cognitive map of the environment.

Space in the brain: how the hippocampal formation supports spatial cognition states

  • Grid cell was identified in 2005 by May-Britt and Edvard Mose (Refer to This)
  • Grid cells were first identified in medial entorhinal cortex (MEC) and have since been found in preand parasubiculum
  • Like place cells, they fire at specific locations in the environment, but unlike place cells each grid cell has multiple firing fields which tessellate the environment with a strikingly regular triangular pattern
  • The grid field can be characterized in terms of three properties:
    • scale (determined by the distance between adjacent firing rate peaks),
    • orientation (of grid axes relative to some reference direction)
    • spatial phase (i.e. the two-dimensional offset of the grid relative to an external reference point).

Following picture shows an example of grid cell. As shown on the left, the same cell fires at multiple places which are arranged in the form of grid (in haxagonal pattern) and on the right shows the brain region where grid cells are located. These cells are located in the region of entorhinal cortex (EC) which is right outside of hippocampus.

Grid cell firing at hexagonally arranged locations in an arena, beside a rat head showing the entorhinal cortex

Image Source : Scientific Background - The Brains Navigational Place and Grid Cell System

Head Direction Cell

Head direction cells are neurons found in the brain that specifically fire in response to an animal's directional heading. They create an internal compass, enabling spatial navigation and orientation. These cells are primarily located in the limbic system, with high concentrations in the postsubiculum and the entorhinal cortex.

Space in the brain: how the hippocampal formation supports spatial cognition states :

  • HD(Head Direction) cells provide a representation of allocentric heading independent of location.
  • Each HD cell has a preferred direction corresponding to a compass direction. It fires rapidly whenever the animal is facing in the preferred direction and only weakly otherwise
  • Place cells rely on directional information from the HD system
  • Lesioning the HD system disrupts the ability of visual cues to control the orientation of place fields within a cylinder
  • HD cells are found in the dorsal presubiculum and entorhinal cortex, but also, it should be noted, outside the hippocampal formation; for example, in anterior dorsal thalamic nucleus and retrosplenial cortex.

Mirror Neuron

Mirror Neuron is a type of neuron that fires not only when an animal really act but also when the animal just observe a certain action done by others without aciting itself. In other words, it is the type of neuron that mirror a certain action done by others.

Since it was found for the first time in late 1980s, it have had become one of the most famous type of neuron for a few decades. So many scientist (even not professionals) have tried to explain many animal/human behavior with the concept of mirror neuron even when it cannot be proven by strict scientific experiment or observation.

For more detailed understandings on mirror neuron, let's look into some examples of mirror neuron published in a few research papers. Take closer look at the examples illustrated below a few times until you get clearer image about the concept (function) of mirror neuron.

Let's take a loot at the first example shown below. Check if you can describe each of the picture in your own words before looking at my explanation.

Monkey grabbing an object in A and watching a person grab in B, with the F5 cortex area marked in C

 

Image Source : Mirror neurons and their clinical relevance - ResearchGate (2009)

In [A], you see a monkey is grabbing an object and the cortex area that is associated with the motor activity gets fired. This is expected neuronal activity. There is nothing surprising.

In [B], the same neurons are being measured. This time, the monkey is not doing anything (i.e, not grabbing anything) and it just watch a person grabbing the object. Here comes the strange part. The neurons (same neurons as in [A]) are firing even when the monkey is not doing anything. It means that these neurons are mirroring a certain action.

[C] shows the exact location of the cortex area being measured in this test, meaning that this is where the mirror neurons for the grabbing activity are located.

Now let's take a look at another paper showing a little bit more details about the same mirror neurons as in the previous example. Again, try to take a look at the pictures and try to explain it in your own words.

Four mirror neuron recording conditions a to d, with the grabbing part hidden in b and d

 

Image Source : THE MIRROR-NEURON SYSTEM - Giacomo Rizzolatti1 and Laila Craighero (2004)

In [a], You see the typical activity of mirror neuron. They fires when the monkey just observes the grabbing activity done by a person. The person reaches out his hand and grabs the object.

In [c], you see the subject (monkey) is observing the motion of grabbing done by a person, but the person is just showing the motion without really grabbing the object. The neuron still fires but the level of the fire is much lower than the case [a]

In [b], The human subject is doing the same motion(reaching out a hand and grabbing the object) as in [a] but the later part of the motion (i.e, the grabbing part) is hidden from the mokey (i.e, not visible to monkey). But neurons still fires at the same intensity as in [a].

In [d], The human subject is doing the same motion(reaching out a hand and grabbing the object) as in [c] but the later part of the motion (i.e, the fake grabbing part) is hidden from the mokey (i.e, not visible to monkey). In this case, the neuron does not fire (or fires at negligigle intensity)

NOTE : The four panels are laid out with [a] and [c] on the top row and [b] and [d] below them, so the letters do not run left to right. Reading down the left column gives the two cases where the person really grabs the object, and the right column gives the two cases where the grab is only mimed.

Concept Cell

The NOTE closing the place cell part asks whether the memory of a place lives inside one nerve cell. A separate line of work asks the same question about people and objects, and it gets closer to an answer than you might expect.

The subjects were eight patients with pharmacologically intractable epilepsy who had been implanted with depth electrodes to localize the focus of seizure onset. The recordings covered the hippocampus, amygdala, entorhinal cortex and parahippocampal gyrus. Two of those four are the same structures the place cell and grid cell parts of this section describe.

993 units were recorded across 21 sessions, and 132 of them, about 14 percent, responded to at least one picture. The responses were narrow. Among the units that responded at all, an average of only 2.8 percent of the pictures shown produced a response.

One unit in the left posterior hippocampus is the example everybody quotes. It fired to all pictures of the actress Jennifer Aniston alone, but not, or only very weakly, to other famous and non-famous faces, landmarks, animals or objects. It did not fire to pictures of Jennifer Aniston together with the actor Brad Pitt. In 18 of the 21 sessions the team also presented letter strings with the names of individuals or objects, and in some cases the written name alone was enough.

The conclusion the paper draws is careful, and worth quoting rather than paraphrasing. The results suggest an invariant, sparse and explicit code, which might be important in the transformation of complex visual percepts into long-term and more abstract memories. That is a statement about how a concept is coded. It is not a statement that one cell holds one memory.

  • A concept cell answers to an identity, not to a picture : the same unit fired to strikingly different images of one person.
  • The written name can work as well as the face : letter strings carrying a name triggered some of the same units.
  • The code is sparse : responsive units answered to only about 2.8 percent of the pictures they were shown.
  • These are the structures the earlier parts describe : the recordings covered hippocampus, amygdala, entorhinal cortex and parahippocampal gyrus.
  • Sparse is not one cell per memory : the finding is an invariant, sparse and explicit code, and the claim stops there.

Purkinje Cell

Every other cell in this section earns its place by what it responds to. The Purkinje cell earns its place by what it looks like, which makes it the extreme case for the two sections at the top of this note.

Purkinje cell bodies make up the middle Purkinje cell layer of the cerebellar cortex. From each cell body rises a large, flat, highly branched dendritic tree, set perpendicular to the folds in the cerebellar cortex. Flat is the word to hold on to. The tree spreads through a plane rather than through a ball, so neighbouring Purkinje cells stack like pages in a book.

The output side is the opposite of the input side. Against that very large dendritic tree there is a single long axon, and it forms an inhibitory projection to the cerebellar nuclei. The transmitter it releases is GABA. The cell therefore gathers across an enormous surface and answers with one inhibitory line, which is the asymmetry from Structure of a Neuron taken to its limit.

  • The Purkinje cell is the multipolar plan at its extreme : a very large branched dendritic tree against one axon.
  • The dendritic tree is flat rather than spherical : it sits perpendicular to the folds of the cerebellar cortex.
  • Its single output is inhibitory : the axon projects to the cerebellar nuclei and releases GABA.
  • It shows the input and output asymmetry at full stretch : a huge collecting surface answered by one line.

YouTube

Reference