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Single long axon vs serial neurons

Single long axon vs serial neurons


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Based on the comments in this post and also this chat. For discussions and speculations please comment in the chat.

The basic question is what is the advantage of having a single long axon such as that of sciatic nerve (~1m) compared to a series of neurons?

The primary advantage is surely the conduction speed which will get affected because of chemical synapses. However, gap junction synapses can reduce that delay. The larger volume of the soma of the post synaptic neuron may also reduce the conduction speed, but signal strengthening can also happen. Cell architecture can be adjusted to minimize the loss of speed.

The obvious disadvantage of having a single large cell is that there would be tremendous burden on the nucleus for the cellular maintenance. There would be delays in transfer of non-electrical signals such as biomolecules from axon termini to soma and vice versa. Long axons also means continuous transport along them which in turn demands large number of molecular motors and therefore ATP. Moreover, a small injury can disable the entire conduction channel. It can be imagined that this trait (long axons) can also be selected against; injury leading to inability to move and thereby causing perishment.

EDIT (Based on comments to Anne's answer)

Time is of course a valid advantage for having a single axon as an information conduction channel. However, the energy or the maintenance cost is the factor that I am actually interested in. Maintenance cost would increase with cell volume (in fact surface area) and having serial neurons would demand more energy (cumulative) than a single axon (including costs of maintaining a nucleus). However a long cell would need much higher number of molecular motors to maintain the traffic flow rate. All responses that require transcriptional control would be slow (such as response to injury). Moreover a single soma also imposes a limit on the number of mitochondria. There should be a limit on how long an axon can be. I am especially interested in case of big animals (with long hindlimbs) that also have a good reflex (perhaps camels, even horses).

Has someone tried to analyse the tradeoffs of having a long axon vs series of neurons connected by gap junctions? If not is this problem worth modeling or quite trivial?


Saw this in Quora:

My first thought mostly agreed with the question details, except I'm pretty sure that the dorsal root ganglion (DRG) has a longer axon than the motor information carried in the sciatic nerve (which is the longest nerve in the body, but not axon).

Does this mean that sciatic nerve has serial neurons?


First, I must clarify that a nerve is not the same as a neuron. A nerve is a collection of axons (with each axon a part of an individual neuron) in the peripheral nervous system. Thus, when you mention “single long axon such as the sciatic nerve”, this is technically an incorrect phrase as the sciatic nerve is a collection of many long axons. If one of these axons is nonfunctional, this would not severely affect the function of the entire sciatic nerve. However, you are right that if the entire sciatic nerve is severed, then there would be serious consequences downstream.

Second, the primary advantage of conduction velocity is less dependent on length and more dependent on presence and degree of myelination (directly proportional to fiber diameter) and presence of nodes of Ranvier.

With regards to the content of your question, the advantage of length is exactly what one might think--- greater distance. The sciatic nerve is the longest nerve in the body in order for our nervous system to innervate as far as the tip of our toes. Having hundreds of side-by-side series of neurons compared to hundreds of side-by-side axons seems like a far less efficient system in a couple of ways in exactly the two ways you mention: energy and time.

Energy: Having serial neurons would require an increase the number of neurons needed to transmit a message. Having more neurons requires more Na+, K+ and Na/K pumps and individual channels, requiring more energy.

Time: Having serial neurons would also require an increase in the number of synapses between neurons- either electrical or chemical. If the synapses are chemical, then time is increased many-many fold. If the synapses are electrical, then time is slightly increased by 10-fold per synapse compared to chemical synapses, but this would still take more time compared to having a single axon with myelination and nodes of Ranvier which by about 100-fold faster than a single electrical synapse.

In summary, having longer nerves made up of axons rather than serial neurons is beneficial by improving energy and time efficiency, which allows our bodies to effectively innervate structures farther away.

Ref:

  • Regarding delay of conduction: Chemical v. Electrical/Gap Ch 10 of Principles of Neuroscience- "Synaptic Integration in the Central Nervous System" (Siegelbaum, Kandel, Yuste) 5th ed. McGraw-Hill Medical, c2013.
  • Regarding conduction velocity of myelinated versus nonmyelinated cells

Regarding the ATPase absolute number increase in serial vs one long axon, I assume this will depend on the number of neurons in series. However, I read this paper, which says that increased length between each node of Ranvier has been physiologically associated with increased conduction velocity. This suggests fewer needed nodes, despite concentrated ATPases at these locations, and thus fewer ATPases. I haven't been able to find studies which compare ATPase concentration in the soma compared to nodes of Ranvier within axons.

Regarding energy use in soma vs axon, mitochondria are not only made in the soma but are concentrated in pre- and post-synaptic membranes (and growth cones). The more of these structures there are (as in serial neurons), the more presumed mitochondria. See mitochondria and neuronal activity.

Finally, my literature search could not find studies which showed longest possible energetically feasible length for myelinated or unmyelinated neurons.


Neuronal polarization

Neurons are highly polarized cells with structurally and functionally distinct processes called axons and dendrites. This polarization underlies the directional flow of information in the central nervous system, so the establishment and maintenance of neuronal polarization is crucial for correct development and function. Great progress in our understanding of how neurons establish their polarity has been made through the use of cultured hippocampal neurons, while recent technological advances have enabled in vivo analysis of axon specification and elongation. This short review and accompanying poster highlight recent advances in this fascinating field, with an emphasis on the signaling mechanisms underlying axon and dendrite specification in vitro and in vivo.


Overview of Neurons

Neurons are cells in the nervous system that can carry electrical impulses to facilitate communication between the brain and the rest of the body. There are three main types of neurons: sensory neurons, relay neurons, and motor neurons.

Motor neurons control movement, sensory neurons enable us to feel sensations, and relay neurons enable motor neurons and sensory neurons to communicate with each other.

To respond precisely to stimuli, the brain relies on information transmitted by sensory neurons. Sensory neurons record inputs from the environment, convert them into signals (electrical impulses) and forward the information to the brain and spinal cord, where a response can be generated. Different types of sensory neurons respond to different stimuli, for example some neurons sense temperature, others sense pain, and some specialize in taste.


Structure of Neuron

The tissue of nervous system consist of two types of cells, those are the Nerve cells and Glial cell. The nerve cells are called Neuron and the glial cells are called neuralgia. Among these the neurons performed the function of nervous system by transmitting information from one part of the body to another and the glial cells are supporting elements.

What is Neuron?

The Neurons are the structural and functional units of nervous system.

Structure of Neuron: -

A typical structure of neuron consist of a cell body and two processes, those are Dendron and Axon.The cell body of a neuron is like other cell of the body, consisting of a nucleus and cytoplasm covered by plasma membrane. The cytoplasm contains various organelles and inclusions. In adult nerve cells, centrosome is absent or inactive so their division is not occurred. Specialised cytoplasmic organelles called Nissl granules or Nissl body made up of riboneucleoprotein are found in the cell body except in the axon hillock region from where the axon arises. These granules are also present in dendrons but absent in axon.


In our study about the structure of neuron, the Dendrons are the short and branched afferent processes which receive stimulation from other neurons and carry the information towards the cell body. In general a neuron has many dendrons. However in some neurons, the Dendron may be only single or may be absent in case. The single long efferent process of a neuron is called axon which carries impulses away from the cell body to the next neuron or the target organ , such as muscle or gland.

Axons are usually un-branched. However, they give a few small terminal branches called telodendria having swollen ends known as terminal buttons. An axon is also called nerve fibre. A neuron possesses only one axon and variable number of dendrons. If there is only one process, it is usually the axon. In such type of neurons, the cell body receives stimulation. In some specialised neurons, the axon may be absent, such as , adrenal medullary cells and amacrine cells of retina of eye.


Single-axon tracing study of neurons of the external segment of the globus pallidus in primate †

Dr. Fumi Sato was on leave of absence from the Department of Anatomy, School of Medicine, Tokyo Medical and Dental University, Tokyo, Japan.

Abstract

Axonal projections arising from the external segment of the globus pallidus (GPe) in cynomolgus monkeys (Macaca fascicularis) were mapped after labeling small pools (5–15 cells) of neurons with biotinylated dextran amine. Seventy-six single axons were reconstructed from serial sagittal sections with a camera lucida. The majority of labeled GPe cells displayed long, aspiny, and poorly branched dendrites that arborized mostly along the sagittal plane, whereas others showed dendrites radiating in all directions. Numerous GPe axons emitted short, intranuclear collaterals that arborized close to their parent cell body. Based on their axonal targets, four distinct types of GPe projection neurons have been identified: 1) neurons that project to the internal segment of the globus pallidus (GPi), the subthalamic nucleus (STN), and the substantia nigra, pars reticulata (SNr 13.2%) 2) neurons that target the GPi and the STN (18.4%) 3) neurons that project to the STN and the SNr (52.6%) and 4) neurons that target the striatum (15.8%). Labeled GPe axons displayed large varicosities that often were closely apposed to the somata and proximal dendrites of STN, GPi, and SNr neurons. At striatal levels, however, GPe axons displayed small axonal varicosities that did not form perineuronal nets. These results suggest that the GPe is an important integrative locus in primate basal ganglia. This nucleus harbors several subtypes of projection neurons that are endowed with a highly patterned set of collaterals. This organization allows single GPe neurons to exert a multifarious effect not only on the STN, which is the claimed GPe target, but also on the two major output structures of the basal ganglia, the SNr and the GPi. J. Comp. Neurol. 417:17–31, 2000. ©2000 Wiley-Liss, Inc.


The AIS is the boundary between the axon and the cell body

The first part of the axon is specialized in many vertebrate neurons to serve as the site of action potential initiation (Bender and Trussell, 2012). The AIS has an especially low excitation threshold because its small surface area favors excitation and, most importantly, it contains a high concentration of voltage-gated Na + channels (Grubb and Burrone, 2010 Bender and Trussell, 2012). Thus, graded depolarizations that reach the AIS can initiate an action potential that propagates down the axon. AIS excitation is tightly regulated by synaptic inputs and locally clustered K + channels (Grubb and Burrone, 2010 Rasband, 2010 Bender and Trussell, 2012). Shaker (Kv1), Shab (Kv2) and KCNQ2/3 voltage-gated K + channels localized to the AIS regulate action potential threshold, duration and frequency (Rasband et al., 1998 Dodson et al., 2002 Pan et al., 2006 Goldberg et al., 2008 Johnston et al., 2008 Lorincz and Nusser, 2008 Sarmiere et al., 2008 Shah et al., 2008). The AIS ion channel complement is not fixed and can vary across neuronal cell types to facilitate distinct patterns of excitability (Lorincz and Nusser, 2008 Bender and Trussell, 2012).

In addition to its role in action potential initiation, the AIS has a specialized cytoskeletal structure that serves as a barrier for diffusion within the plasma membrane. This diffusion barrier property was discovered in 1999 by using optical tweezers to drag plasma membrane proteins along the axon they could not be dragged through the AIS (Winckler et al., 1999). Moreover, this barrier localizes to the boundary between axonal plasma membrane proteins like NgCAM and dendritic plasma membrane proteins like the transferrin receptor (Winckler et al., 1999). This diffusion barrier is constructed by a special sub-membrane skeleton that localizes to the AIS. Ankyrin-G (AnkG) is the central player in orchestrating the AIS and acts as a linker protein that bridges transmembrane proteins, including ion channels (Zhou et al., 1998 Pan et al., 2006), and β-IV-spectrin, which in turn binds actin (Grubb and Burrone, 2010 Rasband, 2010 Bennett and Lorenzo, 2013). These proteins work together to set up the electron-dense meshwork under the plasma membrane that has long been known as a distinguishing feature of the AIS (Peters et al., 1991 Jones et al., 2014). This cytoskeletal structure is particularly interesting because, like microtubules, it has the potential to influence the distribution of other proteins.


Types of Neurotransmitters

Acetylcholine &ndash stimulates ______________________________________
Monoamines &ndash Norepinephrine & Dopamine (sense of feeling good, low levels = depression)
Serotonin = ________________________________________________

Synapses are highly susceptible to drugs and fatigue

What is Curare?

Strychnine and some nerve gases inhibit or destroy acetylcholinesterase formation. Prolongs and enhances any stimulus, i.e. leads to convulsions, contraction of muscles upon the slightest stimulus.

Cocaine, morphine, alcohol, ether and chloroform anaesthetise nerve fibers. (inhibitory)

Mescaline and LSD produce their hallucinatory effect by interfering with nor-adrenaline & serotonin


Contents

Growing axons have a highly motile structure at the growing tip called the growth cone, which "sniffs out" the extracellular activities in the environment for signals that instruct the axon which direction to grow. These signals, called guidance cues, can be fixed in place or diffusible they can attract or repel axons. Growth cones contain receptors that recognize these guidance cues and interpret the signal into a chemotropic response. The general theoretical framework is that when a growth cone "senses" a guidance cue, the receptors activate various signaling molecules in the growth cone that eventually affect the cytoskeleton. If the growth cone senses a gradient of guidance cue, the intracellular signaling in the growth cone happens asymmetrically, so that cytoskeletal changes happen asymmetrically and the growth cone turns toward or away from the guidance cue. [1]

A combination of genetic and biochemical methods (see below) has led to the discovery of several important classes of axon guidance molecules and their receptors: [2]

    : Netrins are secreted molecules that can act to attract or repel axons by binding to their receptors, DCC and UNC5. : Secreted proteins that normally repel growth cones by engaging Robo (Roundabout) class receptors. : Ephrins are cell surface molecules that activate Eph receptors on the surface of other cells. This interaction can be attractive or repulsive. In some cases, Ephrins can also act as receptors by transducing a signal into the expressing cell, while Ephs act as the ligands. Signaling into both the Ephrin- and Eph-bearing cells is called "bi-directional signaling." : The many types of Semaphorins are primarily axonal repellents, and activate complexes of cell-surface receptors called Plexins and Neuropilins. : Integral membrane proteins mediating adhesion between growing axons and eliciting intracellular signalling within the growth cone. CAMs are the major class of proteins mediating correct axonal navigation of axons growing on axons (fasciculation). There are two CAM subgroups: IgSF-CAMs (belonging to the immunoglobulin superfamily) and Cadherins (Ca-dependent CAMs).

In addition, many other classes of extracellular molecules are used by growth cones to navigate properly:

  • Developmental morphogens, such as BMPs, Wnts, Hedgehog, and FGFs
  • Extracellular matrix and adhesion molecules such as laminin, tenascins, proteoglycans, N-CAM, and L1
  • Growth factors like NGF
  • Neurotransmitters and modulators like GABA

Integration of information in axon guidance Edit

Growing axons rely on a variety of guidance cues in deciding upon a growth pathway. The growth cones of extending axons process these cues in an intricate system of signal interpretation and integration, in order to ensure appropriate guidance. [3] These cues can be functionally subdivided into:

  • Adhesive cues, that provide physical interaction with the substrate necessary for axon protrusion. These cues can be expressed on glial and neuronal cells the growing axon contacts or be part of the extracellular matrix. Examples are laminin or fibronectin, in the extracellular matrix, and cadherins or Ig-family cell-adhesion molecules, found on cell surfaces.
  • Tropic cues, that can act as attractants or repellents and cause changes in growth cone motility by acting on the cytoskeleton through intracellular signaling. For example, Netrin plays a role in guiding axons through the midline, acting as both an attractant and a repellent, while Semaphorin3A helps axons grow from the olfactory epithelium to map different locations in the olfactory bulb.
  • Modulatory cues, that influence the sensitivity of growth cones to certain guidance cues. For instance, neurotrophins can make axons less sensitive to the repellent action of Semaphorin3A.

Given the abundance of these different guidance cues it was previously believed that growth cones integrate various information by simply summing the gradient of cues, in different valences, at a given point in time, to making a decision on the direction of growth. However, studies in vertebrate nervous systems of ventral midline crossing axons, has shown that modulatory cues play a crucial part in tuning axon responses to other cues, suggesting that the process of axon guidance is nonlinear. For example, commissural axons are attracted by Netrin and repelled by Slit. However, as axons approach the midline, the repellent action of Slit is suppressed by Robo-3/Rig-1 receptor. [4] Once the axons cross the midline, activation of Robo by Slit silences Netrin-mediated attraction, and the axons are repelled by Slit.

Cellular strategies of nerve tract formation Edit

Pioneer axons Edit

The formation of a nerve tract follows several basic rules. In both invertebrate and vertebrate nervous systems initial nerve tracts are formed by the pioneer axons of pioneer neurons. [5] These axons follow a reproducible pathway, stop at intermediate targets, and branch axons at certain choice points, in the process of targeting their final destination. This principle is illustrated by CNS extending axons of sensory neurons in insects.

During the process of limb development, proximal neurons are the first to form axonal bundles while growing towards the CNS. In later stages of limb growth, axons from more distal neurons fasciculate with these pioneer axons. Deletion of pioneer neurons disrupts the extension of later axons, destined to innervate the CNS. [6] At the same time, it is worth noting that in most cases pioneer neurons do not contain unique characteristics and their role in axon guidance can be substituted by other neurons. For instance, in Xenopus retinotectal connection systems, the pioneer axons of retinal ganglion cells originate from the dorsal part of the eye. However, if the dorsal half of the eye is replaced by less mature dorsal part, ventral neurons can replace the pioneer pathway of the dorsal cells, after some delay. [7] Studies in zebrafish retina showed that inhibiting neural differentiation of early retinal progenitors prevents axons from exiting the eye. The same study demonstrated aberrant growth trajectories in secondary neurons, following the growth of pioneer neurons missing a guidance receptor. [8] Thus, while the extent of guidance provided by pioneer axons is under debate and may vary from system to system, the pioneer pathways clearly provide the follower projections with guidance cues and enhance their ability to navigate to target.

Role of glia Edit

The first extending axons in a pathway interact closely with immature glia cells. In the forming corpus callosum of vertebrates, primitive glia cells first migrate to the ependymal zones of hemispheres and the dorsal septum wall to form a transient structure that the pioneer axons of the callosal fibers use to extend. [9] The signaling between glia and neurons in the developing nervous system is reciprocal. For instance, in the fly visual system, axons of photoreceptors require glia to exit the eye stalk whereas glia cells rely on signals from neurons to migrate back along axons. [10]

Guideposts Edit

The growing axons also rely on transient neuronal structures such as guidepost cells, during pathfinding. In the mouse visual system, proper optic chiasm formation depends on a V-shaped structure of transient neurons that intersect with specialized radial glia at the midline of the chiasm. The chiasm axons grow along and around this structure but do not invade it. [11] Another example is the subplate in the developing cerebral cortex that consists of transient neuronal layer under the subventricular zone and serves as a guidepost for axons entering permanent cortical layers. The subplate is similar to the chiasmatic neurons in that these cell groups disappear (or transit into other cell types) as the brain matures. [12] These findings indicate that transitory cell populations can serve an important guidance role even though they have no function in the mature nervous system.

The earliest descriptions of the axonal growth cone were made by the Spanish neurobiologist Santiago Ramón y Cajal in the late 19th century. [13] However, understanding the molecular and cellular biology of axon guidance would not begin until decades later. In the last thirty years or so, scientists have used various methods to work out how axons find their way. Much of the early work in axon guidance was done in the grasshopper, where individual motor neurons were identified and their pathways characterized. In genetic model organisms like mice, zebrafish, nematodes, and fruit flies, scientists can generate mutations and see whether and how they cause axons to make errors in navigation. In vitro experiments can be useful for direct manipulation of growing axons. A popular method is to grow neurons in culture and expose growth cones to purified guidance cues to see whether these cause the growing axons to turn. These types of experiments have often been done using traditional embryological non-genetic model organisms, such as the chicken and African clawed frog. Embryos of these species are easy to obtain and, unlike mammals, develop externally and are easily accessible to experimental manipulation.

Axon guidance model systems Edit

Several types of axon pathways have been extensively studied in model systems to further understand the mechanisms of axon guidance. Perhaps the two most prominent of these are commissures and topographic maps. Commissures are sites where axons cross the midline from one side of the nervous system to the other. Topographic maps are systems in which groups of neurons in one tissue project their axons to another tissue in an organized arrangement such that spatial relationships are maintained i.e. adjacent neurons will innervate adjacent regions of the target tissue.

Commissure formation: attraction and repulsion Edit

As described above, axonal guidance cues are often categorized as "attractive" or "repulsive." This is a simplification, as different axons will respond to a given cue differently. Furthermore, the same axonal growth cone can alter its responses to a given cue based on timing, previous experience with the same or other cues, and the context in which the cue is found. These issues are exemplified during the development of commissures. The bilateral symmetry of the nervous system means that axons will encounter the same cues on either side of the midline. Before crossing (ipsilaterally), the growth cone must navigate toward and be attracted to the midline. However, after crossing (contralaterally), the same growth cone must become repelled or lose attraction to the midline and reinterpret the environment to locate the correct target tissue.

Two experimental systems have had particularly strong impacts on understanding how midline axon guidance is regulated:

The ventral nerve cord of Drosophila Edit

The use of powerful genetic tools in Drosophila led to the identification of a key class of axon guidance cues, the Slits, and their receptors, the Robos (short for Roundabout). The ventral nerve cord looks like a ladder, with three longitudinal axon bundles (fascicles) connected by the commissures, the "rungs" of the ladder. There are two commissures, anterior and posterior, within each segment of the embryo.

The currently accepted model is that Slit, produced by midline cells, repels axons from the midline via Robo receptors. Ipsilaterally projecting (non-crossing) axons always have Robo receptors on their surface, while commissural axons have very little or no Robo on their surface, allowing them to be attracted to the midline by Netrins and, probably, other as-yet unidentified cues. After crossing, however, Robo receptors are strongly upregulated on the axon, which allows Robo-mediated repulsion to overcome attraction to the midline. This dynamic regulation of Robo is at least in part accomplished by a molecule called Comm (short for Commissureless), which prevents Robo from reaching the cell surface and targeting it for destruction. [15]

The spinal cord of mice and chickens Edit

In the spinal cord of vertebrates, commissural neurons from the dorsal regions project downward toward the ventral floor plate. Ipsilateral axons turn before reaching the floor plate to grow longitudinally, while commissural axons cross the midline and make their longitudinal turn on the contralateral side. Strikingly, Netrins, Slits, and Robos all play similar functional roles in this system as well. One outstanding mystery was the apparent lack of any comm gene in vertebrates. It now seems that at least some of Comm's functions are performed by a modified form of Robo called Robo3 (or Rig1).

The spinal cord system was the first to demonstrate explicitly the altered responsiveness of growth cones to cues after exposure to the midline. Explanted neurons grown in culture would respond to exogenously supplied Slit according to whether or not they had contacted floor plate tissue. [16]

Topographic maps: gradients for guidance Edit

As described above, topographic maps occur when spatial relationships are maintained between neuronal populations and their target fields in another tissue. This is a major feature of nervous system organization, particular in sensory systems. The neurobiologist Roger Sperry proposed a prescient model for topographic mapping mediated by what he called molecular "tags." The relative amounts of these tags would vary in gradients across both tissues. We now think of these tags as ligands (cues) and their axonal receptors. Perhaps the best understood class of tags are the Ephrin ligands and their receptors, the Ephs.

In the simplest type of mapping model, we could imagine a gradient of Eph receptor expression level in a field of neurons, such as the retina, with the anterior cells expressing very low levels and cells in the posterior expressing the highest levels of the receptor. Meanwhile, in the target of the retinal cells (the optic tectum), Ephrin ligands are organized in a similar gradient: high posterior to low anterior. Retinal axons enter the anterior tectum and proceed posteriorly. Because, in general, Eph-bearing axons are repelled by Ephrins, axons will become more and more reluctant to proceed the further they advance toward the posterior tectum. However, the degree to which they are repelled is set by their own particular level of Eph expression, which is set by the position of the neuronal cell body in the retina. Thus, axons from the anterior retina, expressing the lowest level of Ephs, can project to the posterior tectum, even though this is where Ephrins are highly expressed. Posterior retinal cells express high Eph level, and their axons will stop more anteriorly in the tectum.

The retinotectal projection of chickens, frogs and fish Edit

The large size and accessibility of the chicken embryo has made it a favorite model organism for embryologists. Researchers used the chick to biochemically purify components from the tectum that showed specific activity against retinal axons in culture. This led to the identification of Ephs and Ephrins as Sperry's hypothesized "tags."

The retinotectal projection has also been studied in Xenopus and zebrafish. Zebrafish is a potentially powerful system because genetic screens like those performed in invertebrates can be done relatively simply and cheaply. In 1996, large scale screens were conducted in zebrafish, including screens for retinal axon guidance and mapping. Many of the mutants have yet to be characterized.

Cell biology Edit

Genetics and biochemistry have identified a large set of molecules that affect axon guidance. How all of these pieces fit together is less understood. Most axon guidance receptors activate signal transduction cascades that ultimately lead to reorganization of the cytoskeleton and adhesive properties of the growth cone, which together underlie the motility of all cells. This has been well documented in mammalian cortical neurons. [17] However, this raises the question of how the same cues can result in a spectrum of response from different growth cones. It may be that different receptors activate attraction or repulsion in response to a single cue. Another possibility is the receptor complexes act as "coincidence detectors" to modify responses to one cue in the presence of another. Similar signaling "cross-talk" could occur intracellularly, downstream of receptors on the cell surface.

In fact, commissural axon growth responses have been shown to be attracted, repressed, or silenced in the presence of Netrin activated DCC receptor. [18] This variable activity is dependent on Robo or UNC-5 receptor expression at growth cones. Such that Slit activated Robo receptor, causes a silencing of Netrin’s attractive potential through the DCC receptor. While growth cones expressing UNC-5 receptor, respond in a repulsive manner to Netrin-DCC activation. These events occur as consequence of cytoplasmic interactions between the Netrin activated DCC receptor and Robo or UNC-5 receptor, which ultimately alters DCC’s cytoplasmic signaling. Thus, the picture that emerges is that growth cone advancement is highly complex and subject to plasticity from guidance cues, receptor expression, receptor interactions, and the subsequent signaling mechanisms that influence cytoskeleton remodeling.

Growth cone translation in guided axons Edit

The ability for axons to navigate and adjust responses to various extracellular cues, at long distances from the cell body, has prompted investigators to look at the intrinsic properties of growth cones. Recent studies reveal that guidance cues can influence spatiotemporal changes in axons by modulating the local translation and degradation of proteins in growth cones. [19] Furthermore, this activity seems to occur independent of distal nuclear gene expression. In fact, in retinal ganglion cells (RGCs) with soma severed axons, growth cones continue to track and innervate the tectum of Xenopus embryos. [20]

To accommodate this activity, growth cones are believed to pool mRNAs that code for receptors and intracellular signaling proteins involved in cytoskeleton remodeling. [21] In Xenopus retinotectal projection systems, the expression of these proteins has been shown to be influenced by guidance cues and the subsequent activation of local translation machinery. The attractive cue Netrin-1, stimulates mRNA transport and influence synthesis of β-Actin in filopodia of growth cones, to restructure and steer RGC growth cones in the direction of Netrin secretion. [22] While the repulsive cue, Slit, is suggested to stimulate the translation of Cofilin (an actin depolymerizing factor) in growth cones, leading to axon repulsion. [23] In addition, severed commissural axons in chicks, display the capability of translating and expressing Eph-A2 receptor during midline crossing. [24] As a result, studies suggest that local protein expression is a convenient mechanism to explain the rapid, dynamic, and autonomous nature of growth cone advancement in response to guidance molecules.

The axon growth hypothesis and the consensus connectome dynamics Edit

Contemporary diffusion-weighted MRI techniques may also uncover the macroscopical process of axonal development. The connectome, or the braingraph, can be constructed from diffusion MRI data: the vertices of the graph correspond to anatomically labelled brain areas, and two such vertices, say u and v, are connected by an edge if the tractography phase of the data processing finds an axonal fiber that connects the two areas, corresponding to u and v. Numerous braingraphs, computed from the Human Connectome Project can be downloaded from the http://braingraph.org site. The Consensus Connectome Dynamics (CCD) is a remarkable phenomenon that was discovered by continuously decreasing the minimum confidence-parameter at the graphical interface of the Budapest Reference Connectome Server. [25] [26] The Budapest Reference Connectome Server depicts the cerebral connections of n=418 subjects with a frequency-parameter k: For any k=1,2. n one can view the graph of the edges that are present in at least k connectomes. If parameter k is decreased one-by-one from k=n through k=1 then more and more edges appear in the graph, since the inclusion condition is relaxed. The surprising observation is that the appearance of the edges is far from random: it resembles a growing, complex structure, like a tree or a shrub (visualized on this animation on YouTube. It is hypothesized in [27] that the growing structure copies the axonal development of the human brain: the earliest developing connections (axonal fibers) are common in most of the subjects, and the subsequently developing connections have larger and larger variance, because their variances are accumulated in the process of axonal development.

Axon guidance is genetically associated with other characteristics or features. For example, enrichment analyses of different signaling pathways led to the discovery of a genetic association with intracranial volume. [28]


What is a Dendrite

A dendrite is a short-branched extension, which carries nerve impulses to the cell body from the synapses. Many dendrites are extended from a single cell body of a nerve cell. Dendrites are highly branched structures. This highly-branched nature increases the surface area that can receive signals from the synapses. Dendrites and axons of nerve cells are shown in figure 2.

Figure 2: Dendrites and Axons

Dendrites possess tapering ends. Since dendrites are short projections, they are not myelinated.


Know Your Neurons: How to Classify Different Types of Neurons in the Brain's Forest

Scientists have organized the cells that make up the nervous system into two broad groups: neurons, which are the primary signaling cells, and glia, which support neurons in various ways. The human brain contains around 100 billion neurons and, by most estimates, somewhere between 10 to 50 times as many glial cells.

All these cells are packed into a three-pound organ about the size of both your fists stuck together. You can think of your brain as a dense forest—the neuron forest—in which different kinds of trees grow near, around and on top of one another, their branches and roots intertwining. Just as all trees share a basic structure—roots, trunk, branches—but do not look exactly alike, all neurons are variations on a common structural theme. The diversity of structures is extraordinary and scientists are still discovering brain cells that do not really look like any brain cell they have seen before.

Different Types of Neurons (click to enlarge). A. Purkinje cell B. Granule cell C. Motor neuron D. Tripolar neuron E. Pyramidal Cell F. Chandelier cell G. Spindle neuron H. Stellate cell (Credit: Ferris Jabr based on reconstructions and drawings by Cajal)

A model neuron. Click to enlarge (Credit: LadyofHats, Wikimedia Commons)

Before exploring the brain's cellular diversity, let's look at a model neuron. A typical neuron has three main structures: the cell body, the axon and the dendrites. The cell body contains the nucleus, which stores the cell's genes the axon is a long slender cable that carries electrical signals known as action potentials away from the cell body toward other neurons and the dendrites are shorter branching fibers that receive signals from other neurons. Near its end, the axon of one neuron branches and forms connections with as many as 1,000 other neurons—but, as 19th century neuroanatomist Santiago Ramón y Cajal insisted, the end of one neuron does not fuse with the beginning of another into a seamless web. Instead, an axon's branching tips communicate with the dendrites, axons and cell bodies of other neurons across tiny gaps called synapses.

Neurons classified by structure. Click to enlarge (Credit: Ferris Jabr)

Scientists have classified neurons into four main groups based on differences in shape. Multipolar neurons are the most common neuron in the vertebrate nervous system and their structure most closely matches that of the model neuron: a cell body from which emerges a single long axon as well as a crown of many shorter branching dendrites. Unipolar neurons, the most common invertebrate neuron, feature a single primary projection that functions as both axon and dendrites. Bipolar neurons usually inhabit sensory organs like the eye and nose. Their dendrites ferry signals from those organs to the cell body and their axons send signals from the cell body to the brain and spinal cord. Pseudo-unipolar neurons, a variant of bipolar neurons that sense pressure, touch and pain, have no true dendrites. Instead, a single axon emerges from the cell body and heads in two opposite directions, one end heading for the skin, joints and muscle and the other end traveling to the spinal cord.

Neurons classified by function. Click to enlarge (Credit: Ferris Jabr)

Researchers also categorize neurons by function. Sensory neurons collect information from sensory organs—from the eyes, nose, tongue and skin, for example. Motor neurons carry signals from the brain and spinal cord to muscles. Interneurons connect one neuron to another: the long axons of projection interneuons link distant brain regions the shorter axons of local interneurons form smaller circuits between neighboring cells.

Do these basic classes account for all types of neurons? Well, just about every neuron in the human nervous system should fall into one these broad categories—but these categories do not capture the true diversity of the nervous system. Not even close. If you really want to catalogue neurons in their many forms—somewhat like the way scientists have classed living things into families and species and subspecies—you're going to need a lot more categories. Neurons differ from one another structurally, functionally and genetically, as well as in how they form connections with other cells. In some ways, it's up to you how far you want to take this. Some people are content with a few broad categories and do not see a need to identify and categorize every single type of neuron. Others are fascinated by the differences between cells in the brain and nervous system, even the subtlest distinctions. Some are fascinated for practical reasons, because some of these differences help explain, for example, why certain diseases only harm a certain population of neurons. Others are motivated by pure curiosity.

Since at least the 19th century—even before Cajal convinced the leading anatomists of the time that the nervous system was made of discrete cells—scientists recognized that not all components of the nervous system looked the same and began differentiating these components by name. In 1840, Adolphe Hannover discovered what today we call the ganglion cells of the retina, the light-sensitive tissue at the back of the eye. In 1866, Leopold August Besser named large, densely branching neurons "Purkinje cells" after their discoverer, Czech anatomist Jan Purkyně. Vladimir Alekseyevich Betz discovered the largest cells in the central nervous system, today known as Betz cells. Cajal tried out various names for different kinds of neurons, as well as their tinier features. He called little bumps along the length of dendrites espinas, the Spanish word for thorns. Today, we call them dendritic spines.

So how many different types of neurons have scientists named so far? To find out, I contacted several neuroscientists who specialize in cell biology and what you could call neuron taxonomy. Perhaps unsurprisingly, no one has an exact number, but if you count all the types and subtypes in the entire nervous system, the answer is at least in the hundreds. One great resource for exploring the cellular diversity of the nervous system is NeuroMorpho.org, a database of digitally reconstructed neurons that you can browse by species, brain region and cell type. Check out the Cell Types page and you'll encounter descriptive names like cone cell, climbing fiber, crab-like, medium spiny cell, pyramidal cell, chandelier cell and tripolar cell—each of which boasts a unique structure. 3D models of these neurons pop into view when you mouse over the file names of different reconstructions.

Gordon Shepherd of Yale University pointed me to the Neuroscience Lexicon, a database that he and his colleagues are building. Take a look for yourself at their current list of types of neurons. Here's what the Lexicon lists for distinct types of neurons in the cerebellum, an evolutionarily ancient part of the brain that helps coordinate movement:

• Cerebellum candelabrum cell

• Cerebellum nucleus reciprocal projections neuron

• Cerebellum unipolar brush cell

And that's just one region of the brain. Remember that the human brain contains around 100 billion neurons densely packed into three-pounds of tissue. Consider that the human brain is one of the most complex structures we have ever tried to understand. All those layers of fragile, excitable tissue folded upon one another. Within those folds we will surely discover new types of neurons of which we have no inkling at present.

Next time on Know Your Neurons, we meet the members of the second broadest category of nervous system cells—the glia!

Bentivoglio, M. Life and Discoveries of Santiago Ramon y Cajal. Nobelprize.org. 1998. http://www.nobelprize.org/nobel_prizes/medicine/laureates/1906/cajal-article.html

Costandi, M. The discovery of the neuron. Neurophilosopy. 2006. http://neurophilosophy.wordpress.com/2006/08/29/the-discovery-of-the-neuron/

Kandel ER, Schwartz JH, Jessell TM 2000. Principles of Neural Science, 4th ed. McGraw-Hill, New York

Mazzarello, P. A unifying concept: the history of cell theory. Nature Cell Biology 1, E13 - E15 (1999) doi :10.1038/8964

Schoonover, Carl. 2010. Portraits of Mind. Abrams.

ABOUT THE AUTHOR(S)

Ferris Jabr is a contributing writer for Scientific American. He has also written for the New York Times Magazine, the New Yorker and Outside.


Watch the video: The Neuron (December 2022).