Neuron
Rodolfo Llinas (2008), Scholarpedia, 3(8):1490. | doi:10.4249/scholarpedia.1490 | revision #91571 [link to/cite this article] |
Neurons are the principal cellular elements that underlie the function of the nervous system including the brain, spinal cord, peripheral sensory systems and enteric (gut) nervous system. The anatomical variation of these neurons is large, but the general morphology and their electrical and ligand dependent responsiveness allows these cells to be classed as neurons (coined in 1891 by Wilhelm von Waldeyer). Other cellular types are also present in the central nervous system (CNS), most particularly several types of glial elements, initially considered a glue type cell serving as a support matrix for the neuronal circuits. It is now known that these cell types are essential in the maintenance of the neuronal network, in neuronal migration during development and in the generation of myelin. Their electrical response dynamics, being slow compared with that of neurons place them mostly in a modulatory role. Their ability to regulate extracellular background synaptic transmitter levels makes them, however, essential for CNS function.
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Neuronal form
Neurons are generically characterized by a central cell body or soma that comes in different shapes. The soma houses the cell nucleus and most of the genomic expression and synthetic machinery that elaborates the proteins, lipids, and sugars that constitute the neuronal cytoplasm and membranes. The membranous system bounds and defines different intracellular compartments and includes the outer cell membrane (the plasmalemma) that encompasses the global compartment defining cellularity itself.
Associated with the plasmalemma (but also with other intracellular elements) are transmembrane macromolecules that control the functionality of nerve cells (voltage and ligand activated ionic channels, ionic pumps, non-gated ‘leakage’ channels) and the machinery that keeps the cells alive by continuously taking up and replacing the molecular modules that constitute the cell’s functional matrix.
In general terms neurons are viewed as having an input and an output pole. Early in the evolution of CNS, and during development, such cells were devoid of any plasmalemmal extensions. These bald neurons may be found in present day forms as receptors cells in, for instance, the carotid glomus, in gustatory system in vertebrate tongue or as photoreceptors in the retina. The point being that neurons can have many types of branching or, in fact, no branches at all. For the majority of neurons, however,
- the receiving or input pole generally consists of extensively branching tree-like extensions of the soma membrane known as dendrites (coined in 1889 by William His from dendros (Greek) meaning tree) which arise in vertebrate neurons directly from the cell body (the body is also a receiving site in most neurons). With invertebrate neurons the dendrites arise most commonly from the axon (see Figure 3).
- the output pole, called the axon (coined in 1896 by Rudolph Albert von Kolliker; red in Figure 1), arises as a single structure from the soma (and occasionally from a dendrite). The axon conducts propagating electrochemical signals termed action potentials (usually initiated at the axon hillock, green in Figure 2B) away from the soma. There are some dendrites that also serve as output systems (see dendro dendritic synapses by G. Shepherd).
There are, however, exceptions to these general rules of neuronal organization. In some neurons, e.g. peripheral sensory neurons, the input occurs via axons.
Examples of the great variety of neuronal form are shown in Figure 1-Figure 6. Those in images Figure 2-Figure 6 have been made using more recent staining techniques. This set of images represents the common variety of neurons as well as the extremes of morphology to illustrate the enormous variety neurons can generate morphologically.
Neuronal function
Their electrophysiological properties are as rich as their morphology, and endow neurons with a vast set of electrical properties and functional styles. The voltage and ligand dependent ionic conductances that generate and modulate such excitability can implement autorhythmic properties either as single cell oscillators or resonators that ultimately dictate network oscillatory properties. Early electrophysiological results from the study of motoneurons led to the view that neurons do precious little, other than integrate and fire. Intelligence is in the network was the initial credo in those early years. Many other newer parameters have entered electrophysiology over the last three decades. Plasticity (mostly as Long Term Potentiation and Long Term Depression) and intrinsic electrical properties have been particularly significant.
Neurons are characterized by four main functional properties; a) electrical excitability (mostly across the plasmalemma), b) secretion (mostly vesicular and peptide extruding channel dependent), c) molecular synthesis (mostly proteins), and d) growth and plasticity.
This short review will deal mainly with electrical excitability. Secretion, mostly as the mechanism responsible for excitatory or inhibitory synaptic transmission, will be dealt in other entries.
Electrical excitability
When considering neuronal function, electrical excitability is indeed one of the main themes of concern.
Passive electrical properties
Passive properties refer to the capacitative and resistive aspects inherent in neuronal membranes, along with the resistivity inherent in the cytoplasm and the extracellular milieu. Together, these properties provide an electrical resemblance between neuronal processes (axons and dendrites) and conduction in electrical cables and hence are termed cable properties. Across this capacitive/resistive membrane an electric field and a voltage difference is maintained by the action of selective ion pumps. While the basic assumption of most electrophysiologists is that the membrane potential may be initially considered as having a resting value (the resting potential) that is uniformly distributed along neuronal compartments, this is an oversimplification, as the ionic conductances (and pumps) which are responsible for setting the resting potential need not have a fixed density throughout the neuronal membrane. Even so, isopotentiality is inherent in most initial cable property assumptions. The value of the electrical field (in mV) is related to the driving force (emf) for each of the ionic species that can move across the membrane and the magnitude of the conductance for each ionic species (i.e. the number of permeable channels available for any ion species at any given moment multiplied by the single channel conductance). While a more or less uniform permeability may be found for the leakage channels (a constantly open channel permeable to potassium), voltage gated channels allowing sodium, potassium, calcium, and chloride ions across the plasmalemma also contribute to the membrane potential to the extent of the magnitude of their conductance at a given time. Note however that these latter conductances, because they are voltage-gated, deviate from the simple passive character of the leakage channel.
Because of the complexity afforded by the branching pattern of the dendritic tree, the passive electrical properties of neurons were initially difficult to envision without a proper mathematical model. In the mid sixties of last century Wilfred Rall (see Rall Model) was the first to define the electrotonic cable properties of branching dendritic trees and to show the importance of such branching patterns on synaptic summation at different sites in the dendritic arbor.
Neurons conduct waves of membrane potential passively (electrotonically) a short distance along their processes as the result of currents that flow intracellularly along the longitudinal resistance and simultaneously across the plasmalemmal membrane as resistive or capacitative current. When active properties are engaged these changes can travel the entire length of these processes.
Active electrical properties
By active electrical properties it is meant that the electrical potentials across the plasma membrane may be affected by the activation of voltage, ligand, or second messenger gated transmembrane ionic channels. The generation of action potentials is an example of electrical properties brought about by active, voltage-dependent means. Here the electric field across the membrane will act on the voltage sensors of transmembrane ionic channels (channel sites with dipole moment properties that will trigger conformational changes, often allosteric, that will change channel ionic conductance). In the specific case of action potentials voltage-gated channels, the inflow of sodium or calcium ions depolarizes the plasma membrane. In turn, opening voltage-gated potassium channels and the resulting current flow repolarizes the plasma membrane. Although the conductance of most voltage-gated channels are increased by membrane depolarization, the conductance of some channels is increased when the membrane is hyperpolarized.
Other examples of active electrical properties are those brought about by ligand-gated ionic conductances, where the binding of a neurotransmitter will gate ionic conductances allowing the generation of excitatory or inhibitory synaptic potentials. Yet another form of electrical activity is represented by intrinsic subthreshold oscillations, where the excitability of the cell is gated in such a fashion that the membrane potential is not uniform but rather in a state of continuous fluctuation, generating an oscillatory sinusoidal-like membrane profile—often with phase reset properties indicating chaotic, dynamic kinetics.
Neuronal integration
In an active neuron the superposition of passive and active electrical properties serves to allow the cell the possibility of summing the transmembrane potential either linearly or non-linearly and to reach depolarization levels sufficiently high to trigger action potentials. These can be conducted either along the length of the axon or dendritic tree, in an all-or-none continuous manner, in a saltatory fashion, or in a decremental mode.
Axonal spike
Neurons have but one axon, that is, a single process leaving the soma or a dendrite. However, axons branch either in the form of collaterals along the axonal length or at a terminal arborization known as the telodendrion (distal dendrite). These terminals are usually the site of presynaptic boutons that establish synaptic contacts with other neurons, muscles, or glands.
Because they originate from a single initial segment axons send very similar spike sequences to all their branches. However, spike failure at branch points or changes in conduction velocity, secondary to changes in axonal diameter after branching, can reset conduction patterns and conduction times. A good example is the isochrony of spike conduction time found in the axons from the inferior olive that terminate in the cerebellum as what is called climbing fibers.
Dendritic spikes
In addition to action potentials in axons, dendrites may also generate regenerative events. For the most part these potentials decrement with distance but may reach the most distal dendritic branches (See Figure 7). Such action potentials can be centripetal (towards the soma) or centrifugal (back propagating away from the soma) depending on the dendritic morphology and the distribution and density of voltage gated ionic channels over the dendritic tree. For more information, see Dendrites, Dendritic spikes, and Dendritic processing.
Intrinsic electrical properties and subthreshold oscillations
Beyond action potentials and synaptic transmission there is the question of the electrical activity generated autonomously by neurons. In most cases the autonomous intrinsic activity results in a modulation of the resting potential and so the overall state of the neuron in the sense not only of synaptic modulation or the modulation produced by peptidergic, hormonal and metabolic activity, but also of other parameters such as pH and free radical (NO and CO) activity modulation.
Beyond modulation, the parameter that is most relevant in defining intrinsic activity, other than resting potential, is the types and distributions of plasma membrane channels and second messenger activated modulation of channels.
Subthreshold oscillatory activity was originally discovered in the inferior olive and then found in many other central nervous system neurons (Llinas 1988). In addition to the olive such neurons have been found in: entorhinal cortex layer 2 and 3, thalamus, cortical inhibitory interneurons, neostriatum, olfactory bulb, primary sensory ganglion, hippocampus pyramids in CA1 and CA3, dorsal column, globus pallidus, mesencephalic V, supraoptic nucleus, substantia nigra, locus coeruleus, subthalamus, pedunculo-pontine nucleus, layer V and VI pyramids, amygdala, and cingulus, among others. These oscillations are supported by persistent sodium currents and calcium current (Cav3 and Cav1 subunits), in conjunction with voltage and calcium gated potassium currents. The frequency of these oscillations can vary from high gamma band (80 Hz), Mu (25 Hz), beta (15 Hz), alpha (10 Hz), theta (6 Hz,) delta (3 Hz) and slow sleep oscillation bellow 1Hz.
These oscillations are viewed as supporting time-locked neuronal coherence and resonance. As such they are thought to be of significance in determining large functional brain states such as sleep, wakefulness, and dreaming and abnormal states such as epilepsy and thalamocortical dysrhythmia.
Non-uniformity in channels density
Finally, the electrical signature of neurons is defined by the passive integrative properties of the dendrites and soma and the non-linear electrical properties superimposed by the presence of voltage, ligand, second messenger, and metabotropic conductances supported by specialized ionic plasma membrane bound channels. These modulate excitability by their number, functional phenotype, and distribution over the dendritic, somatic and axonal neuronal segments.
While certain characteristic properties can be assigned to given cellular phenotypes, the fact is that every neuron is unique both in its individually detailed shape and its connectivity. Perhaps it is the diversity of such parameters that allow the CNS to be as reliable as it actually is. It was von Neumann who first realized the genesis of reliability from unreliable elements as one of the central character of “neuron-ness”.
A little history
Neurons evolved from primitive cells that are capable of sensitivity (irritability) and contractility (exercising force by changing shape) as drawn by Parker in 1919 ( Figure 4Aa) (also see Meech & Mackie 2007). The initial differentiation of these cells into true neurons or muscle cells precedes the further differentiation of nerve cells into sensory neurons (in communication relation to the external world) or motor neurons (in direct communication with muscles or glands) ( Figure 4Ab). The final stage occurs with the development of interneurons (establishing contacts between sensory and motor neurons) ( Figure 4Ac). The latter represent the vast majority of neurons in the brain and ganglia.
The first central nervous system neurons were described by J.E. Purkinje in the cerebellum and named by him gangliosen zellen (1837) ( Figure 4B). These cells were found to have a cell body (soma), and fine processes by simple macroscopic inspection of freshly hand-dissected motoneurons (Deiters, 1865) ( Figure 4C). However, the true variety and organization of these cells was not realized until the development of the silver impregnation technique by Camillo Golgi (1873). Golgi recognized that neurons were cells characterized by a cell body and a set of thin filamentous extensions. Golgi believed these extensions fused, making the central nervous system a continuous connectivity network. Concerning their general form, Golgi divided neurons into two main categories.
- Type I were large projection neurons, each with a long axon that projected to places distant from its site of origin on the cell body (see Figure 3A,B, and Figure 6A, B, J).
- Type II neurons projected locally at short distances from their cell body (see Figure 6I, C and Figure 3C).
In contrast, Ramon y Cajal (1888) demonstrated that neurons were individual separate elements that communicated specifically with each other and viewed the nervous system as being organized with nerve conduction going from the dendrites to the soma and axon to the next cell in the network ( Figure 1A and others). This allowed him to establish the network direction of conduction and the possibility of understanding CNS function as an orderly unidirectional information processing system. It is now know that the unidirectionality of network conduction is due to the unidirectional nature of synaptic transmission (see Synapse). Wilhem His made an important contribution to the neuron theory in 1886 with his discovery that each nerve fiber stems from a single nerve cell.
References
- Baker P.F, Hodgkin A.L. and Shaw T.I. Replacement of the axoplasm of giant nerve fibers with artificial solutions. J. Physiol. 164: 330-354, 1962.
- Cajal, R (1888) La estructura de los centros nerviosos de las aves. Rev. Trimest. Histol.1:305-315. (Structure of neural centers in birds.)
- Deiters, OFK (1865) Untersuchungen über und Rückenmark des Menshen und der Säugetiere, Braunschweig, Berlin. (Investigations of the Brain and Spinal Cord of Humans and Mammals.)
- Gascoigne, L and McVean, A (1991) Water Movement Sensitive Cells in Leech CNS. Philosophical Transactions: Biological Sciences, Vol. 332, No. 1264. pp. 261-270, Fig. 2(b)(i).
- Golgi, C (1873) Untersuchungen über den feineren Bau des Centralen und peripherischen Nervensystems. Gazzetta Medica Italian, Lombardia, 6:244-246. (Investigations on the fine structure of the central and peripheral nervous systems.)
- His, W (1886) Zur Geschichte der menschlichen Rückenmarkes und der Nervenwurzeln (1886). Abhandlungen der Königlichen sächsischen Gesellschaft der Wissenschaften (1886), 1887. Mathematisch-physische Classe, Leipzig 13: 477-514.
- Llinas, R. (1988) The intrinsic electrophysiological properties of mammalian neurons: A new insight into CNS function. Science 242, 1654-1664.
- Llinás, R. and Sugimori, M (1980) Electrophysiological properties of in vitro Purkinje cell dendrites in mammalian cerebellar slices. J. Physiol. (London) 305: 197-213.
- Meech, R and Mackie, G (2007) Evolution of excitability in lower metazoans in Invertebrate Neurobiology edited by North, G and Greenspan, Cold Spring Harbor Laboratory Press. Chapter 26.
- Parker, G. H. (1919) The Elementary Nervous System. Lippincott, Philadelphia.
- Purkinje, JE (1837) Bericht über die Versammlung deutscher Naturforscher und Aerzte in Prague Anat. Physiol. Ver. 3:177-180. (Report on the conference of German scientists and doctors in Prague.)
Internal references
- Joseph E. LeDoux (2008) Amygdala. Scholarpedia, 3(4):2698.
- Peter Redgrave (2007) Basal ganglia. Scholarpedia, 2(6):1825.
- Valentino Braitenberg (2007) Brain. Scholarpedia, 2(11):2918.
- Olaf Sporns (2007) Complexity. Scholarpedia, 2(10):1623.
- Roger D. Traub (2006) Fast oscillations. Scholarpedia, 1(12):1764.
- Giovanni Gallavotti (2008) Fluctuations. Scholarpedia, 3(6):5893.
- Almut Schüz (2008) Neuroanatomy. Scholarpedia, 3(3):3158.
- Jeff Moehlis, Kresimir Josic, Eric T. Shea-Brown (2006) Periodic orbit. Scholarpedia, 1(7):1358.
- John Dowling (2007) Retina. Scholarpedia, 2(12):3487.
- Ichiji Tasaki (2007) Saltatory conduction. Scholarpedia, 2(6):3354.
- Robert E. Burke (2008) Spinal cord. Scholarpedia, 3(4):1925.
- S. Murray Sherman (2006) Thalamus. Scholarpedia, 1(9):1583.
Recommended reading
- Bullock T. H. , Bennett M. V. L., Johnston D., Josephson R., Marder R, Fields R. D. (2005) The Neuron Doctrine, Redux. Science. 310(5749): 791 - 793.
External links
See also
Brain, Dendrites, Dendritic processing, Models of neurons, Neuroanatomy, Synapse, Synaptic plasticity