Growth in neurons

Growth in neurons

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We know that neurons do not divide, but then how does it accommodate with the body as we grow taller? Do the existing ones just elongate or do they really divide?

Neurons modulate the growth of blood vessels

A team of researchers at Karlsruhe Institute of Technology (KIT) shake at the foundations of a dogma of cell biology. By detailed series of experiments, they proved that blood vessel growth is modulated by neurons and not, as assumed so far, through a control mechanism of the vessel cells among each other. The results are groundbreaking for research into and treatment of vascular diseases, tumors, and neurodegenerative diseases. The study will be published in the journal Nature Communications.

"Our work is pure basic research," Professor Ferdinand le Noble of KIT's Zoological Institute says, "but provides a completely new perspective on how blood vessels grow, branch out, or are inhibited in their growth." For decades, researchers have been looking for ways to promote or impede the formation of new blood vessels. Whereas heart attack and stroke patients would profit from new arteries, cancer patients would benefit from tumor starving by putting a stop to ingrowing blood vessels.

The key figures in the newly discovered extremely finely balanced process are signaling molecules: the brake on growth "soluble FMS-like tyrosine kinase-1," referred to as 1sFlt1, and the "vascular endothelial growth factor," referred to as VEGF. Even though, so far, it has been largely unknown how VEGF is regulated by the body, inhibition of this growth factor has been applied for years already in the treatment of cancer patients and of certain eye diseases. The therapy, however, is successful only in part of the patients and has several undesired side effects.

"So far, research assumed the blood vessels to more or less regulate their own growth," explains le Noble. "In case of oxygen deficiency," he points out, "tissue, among others, releases the growth factor VEGF, thus attracting the blood vessels carrying VEGF receptors on their surfaces. We wanted to know how this blood vessel growth is regulated at the time of a creature's birth." The team around le Noble hence studied the continuous growth of nerve tracts and circulatory vessels in zebrafish model organisms. The eggs of zebrafish are transparent and develop outside of the mother's body, allowing researchers to watch and observe the development of organs or even individual cells without injuring the growing animal.

By means of fluorescent dyes, postgraduate Raphael Wild in a first step documented colonization of neuronal stem cells and subsequent vascular budding in the vertebral canal of zebrafish. To understand the exact process, the team started a detailed biochemical and genetic analysis.

The researchers proved that at different development stages, the nerve cells of the spinal cord produce more or less sFlt1 and VEGF and, in this way, modulate the development of blood vessels. At the early development stage, neuronal sFlt1 brakes blood vessel growth by binding and inactivating the growth factor VEGF. In the spinal cord, this creates an environment poor in oxygen, which is essential to the early development of the neuronal stem cells. With increasing nerve cell differentiation, concentration of the soluble sFlt1 decreases continuously, and the brake on vascular growth is loosened because more active VEGF is now available. Subsequently, blood vessels grow into the young spinal cord to provide it with oxygen and nutrients.

In addition, Raphael Wild and his colleague Alina Klems show that the concentration of the growth factor is crucial as regards the density of the developing blood vessel network. Whereas, when the "brake" sFlt1 in nerve cells was switched off completely, a dense network of blood vessels formed which even grew into the vertebral canal, the growth of blood vessels was suppressed when sFIt1 was increased. Even small variations in substance concentration thus led to severe vascular developmental disorders.

Since vascular cells also have own forms of sFlt1 and VEGF, the question arose as to whether blood vessel growth may, to a certain degree, regulate itself. To find out, the researchers applied the still young and extremely elegant CRISPR/Cas method: Whereas there was no effect when sFlt1 was switched off only in vascular cells, an intensive growth of blood vessels was observed when the production of sFlt1 was switched off in the nerve cells only.

"From the results we conclude that by a fine modulation of sFlt1 and VEGF, nerve cells very dynamically regulate the density of their blood vessel network according to requirements or according to the respective development stage," le Noble points out. "The previous assumption that growing blood vessel cells control the succeeding vascular cells is a cell biology dogma whose foundations are being shaken."


The vertebrate central nervous system (CNS) is derived from the ectoderm—the outermost germ layer of the embryo. A part of the dorsal ectoderm becomes specified to neural ectoderm – neuroectoderm that forms the neural plate along the dorsal side of the embryo. [3] This is a part of the early patterning of the embryo (including the invertebrate embryo) that also establishes an anterior-posterior axis. [4] The neural plate is the source of the majority of neurons and glial cells of the CNS. The neural groove forms along the long axis of the neural plate, and the neural plate folds to give rise to the neural tube. [5] When the tube is closed at both ends it is filled with embryonic cerebrospinal fluid. [6] As the embryo develops, the anterior part of the neural tube expands and forms three primary brain vesicles, which become the forebrain (prosencephalon), midbrain (mesencephalon), and hindbrain (rhombencephalon). These simple, early vesicles enlarge and further divide into the telencephalon (future cerebral cortex and basal ganglia), diencephalon (future thalamus and hypothalamus), mesencephalon (future colliculi), metencephalon (future pons and cerebellum), and myelencephalon (future medulla). [7] The CSF-filled central chamber is continuous from the telencephalon to the central canal of the spinal cord, and constitutes the developing ventricular system of the CNS. Embryonic cerebrospinal fluid differs from that formed in later developmental stages, and from adult CSF it influences the behavior of neural precursors. [6] Because the neural tube gives rise to the brain and spinal cord any mutations at this stage in development can lead to fatal deformities like anencephaly or lifelong disabilities like spina bifida. During this time, the walls of the neural tube contain neural stem cells, which drive brain growth as they divide many times. Gradually some of the cells stop dividing and differentiate into neurons and glial cells, which are the main cellular components of the CNS. The newly generated neurons migrate to different parts of the developing brain to self-organize into different brain structures. Once the neurons have reached their regional positions, they extend axons and dendrites, which allow them to communicate with other neurons via synapses. Synaptic communication between neurons leads to the establishment of functional neural circuits that mediate sensory and motor processing, and underlie behavior. [8]

Some landmarks of neural development include the birth and differentiation of neurons from stem cell precursors, the migration of immature neurons from their birthplaces in the embryo to their final positions, outgrowth of axons and dendrites from neurons, guidance of the motile growth cone through the embryo towards postsynaptic partners, the generation of synapses between these axons and their postsynaptic partners, and finally the lifelong changes in synapses, which are thought to underlie learning and memory.

Typically, these neurodevelopmental processes can be broadly divided into two classes: activity-independent mechanisms and activity-dependent mechanisms. Activity-independent mechanisms are generally believed to occur as hardwired processes determined by genetic programs played out within individual neurons. These include differentiation, migration and axon guidance to their initial target areas. These processes are thought of as being independent of neural activity and sensory experience. Once axons reach their target areas, activity-dependent mechanisms come into play. Although synapse formation is an activity-independent event, modification of synapses and synapse elimination requires neural activity.

Developmental neuroscience uses a variety of animal models including the mouse Mus musculus, the fruit fly Drosophila melanogaster, the zebrafish Danio rerio, the frog Xenopus laevis, and the roundworm Caenorhabditis elegans.

Myelination, formation of the lipid myelin sheath around neuronal axons, is a process that is essential for normal brain function. The myelin sheath provides insulation for the nerve impulse when communicating between neural systems. Without it, the impulse would be disrupted and the signal would not reach its target, thus impairing normal functioning. Because so much of brain development occurs in the prenatal stage and infancy, it is crucial that myelination, along with cortical development occur properly. Magnetic resonance imaging (MRI) is a non-invasive technique used to investigate myelination and cortical maturation (the cortex is the outer layer of the brain composed of gray matter). Rather than showing the actual myelin, the MRI picks up on the myelin water fraction, a measure of myelin content. Multicomponent relaxometry (MCR) allow visualization and quantification of myelin content. MCR is also useful for tracking white matter maturation, which plays an important role in cognitive development. It has been discovered that in infancy, myelination occurs in a caudal–cranial, posterior-to-anterior pattern. Because there is little evidence of a relationship between myelination and cortical thickness, it was revealed that cortical thickness is independent of white matter. This allows various aspects of the brain to grow simultaneously, leading to a more fully developed brain. [9]

During early embryonic development of the vertebrate, the dorsal ectoderm becomes specified to give rise to the epidermis and the nervous system a part of the dorsal ectoderm becomes specified to neural ectoderm to form the neural plate which gives rise to the nervous system. [3] [10] The conversion of undifferentiated ectoderm to neuroectoderm requires signals from the mesoderm. At the onset of gastrulation presumptive mesodermal cells move through the dorsal blastopore lip and form a layer of mesoderm in between the endoderm and the ectoderm. Mesodermal cells migrate along the dorsal midline to give rise to the notochord that develops into the vertebral column. Neuroectoderm overlying the notochord develops into the neural plate in response to a diffusible signal produced by the notochord. The remainder of the ectoderm gives rise to the epidermis. The ability of the mesoderm to convert the overlying ectoderm into neural tissue is called neural induction.

In the early embryo, the neural plate folds outwards to form the neural groove. Beginning in the future neck region, the neural folds of this groove close to create the neural tube. The formation of the neural tube from the ectoderm is called neurulation. The ventral part of the neural tube is called the basal plate the dorsal part is called the alar plate. The hollow interior is called the neural canal, and the open ends of the neural tube, called the neuropores, close off. [11]

A transplanted blastopore lip can convert ectoderm into neural tissue and is said to have an inductive effect. Neural inducers are molecules that can induce the expression of neural genes in ectoderm explants without inducing mesodermal genes as well. Neural induction is often studied in Xenopus embryos since they have a simple body plan and there are good markers to distinguish between neural and non-neural tissue. Examples of neural inducers are the molecules noggin and chordin.

When embryonic ectodermal cells are cultured at low density in the absence of mesodermal cells they undergo neural differentiation (express neural genes), suggesting that neural differentiation is the default fate of ectodermal cells. In explant cultures (which allow direct cell-cell interactions) the same cells differentiate into epidermis. This is due to the action of BMP4 (a TGF-β family protein) that induces ectodermal cultures to differentiate into epidermis. During neural induction, noggin and chordin are produced by the dorsal mesoderm (notochord) and diffuse into the overlying ectoderm to inhibit the activity of BMP4. This inhibition of BMP4 causes the cells to differentiate into neural cells. Inhibition of TGF-β and BMP (bone morphogenetic protein) signaling can efficiently induce neural tissue from pluripotent stem cells. [12]

In a later stage of development the superior part of the neural tube flexes at the level of the future midbrain—the mesencephalon, at the mesencephalic flexure or cephalic flexure. Above the mesencephalon is the prosencephalon (future forebrain) and beneath it is the rhombencephalon (future hindbrain).

The alar plate of the prosencephalon expands to form the telencephalon which gives rise to the cerebral hemispheres, whilst its basal plate becomes the diencephalon. The optical vesicle (which eventually become the optic nerve, retina and iris) forms at the basal plate of the prosencephalon.

In chordates, dorsal ectoderm forms all neural tissue and the nervous system. Patterning occurs due to specific environmental conditions - different concentrations of signaling molecules

Dorsoventral axis Edit

The ventral half of the neural plate is controlled by the notochord, which acts as the 'organiser'. The dorsal half is controlled by the ectoderm plate, which flanks either side of the neural plate. [13]

Ectoderm follows a default pathway to become neural tissue. Evidence for this comes from single, cultured cells of ectoderm, which go on to form neural tissue. This is postulated to be because of a lack of BMPs, which are blocked by the organiser. The organiser may produce molecules such as follistatin, noggin and chordin that inhibit BMPs.

The ventral neural tube is patterned by sonic hedgehog (Shh) from the notochord, which acts as the inducing tissue. Notochord-derived Shh signals to the floor plate, and induces Shh expression in the floor plate. Floor plate-derived Shh subsequently signals to other cells in the neural tube, and is essential for proper specification of ventral neuron progenitor domains. Loss of Shh from the notochord and/or floor plate prevents proper specification of these progenitor domains. Shh binds Patched1, relieving Patched-mediated inhibition of Smoothened, leading to activation of the Gli family of transcription factors (GLI1, GLI2, and GLI3).

In this context Shh acts as a morphogen - it induces cell differentiation dependent on its concentration. At low concentrations it forms ventral interneurons, at higher concentrations it induces motor neuron development, and at highest concentrations it induces floor plate differentiation. Failure of Shh-modulated differentiation causes holoprosencephaly.

The dorsal neural tube is patterned by BMPs from the epidermal ectoderm flanking the neural plate. These induce sensory interneurons by activating Sr/Thr kinases and altering SMAD transcription factor levels.

Rostrocaudal (Anteroposterior) axis Edit

Signals that control anteroposterior neural development include FGF and retinoic acid, which act in the hindbrain and spinal cord. [14] The hindbrain, for example, is patterned by Hox genes, which are expressed in overlapping domains along the anteroposterior axis under the control of retinoic acid. The 3′ (3 prime end) genes in the Hox cluster are induced by retinoic acid in the hindbrain, whereas the 5′ (5 prime end) Hox genes are not induced by retinoic acid and are expressed more posteriorly in the spinal cord. Hoxb-1 is expressed in rhombomere 4 and gives rise to the facial nerve. Without this Hoxb-1 expression, a nerve similar to the trigeminal nerve arises.

Neurogenesis is the process by which neurons are generated from neural stem cells and progenitor cells. Neurons are 'post-mitotic', meaning that they will never divide again for the lifetime of the organism. [8]

Epigenetic modifications play a key role in regulating gene expression in differentiating neural stem cells and are critical for cell fate determination in the developing and adult mammalian brain. Epigenetic modifications include DNA cytosine methylation to form 5-methylcytosine and 5-methylcytosine demethylation. [15] [16] DNA cytosine methylation is catalyzed by DNA methyltransferases (DNMTs). Methylcytosine demethylation is catalyzed in several sequential steps by TET enzymes that carry out oxidative reactions (e.g. 5-methylcytosine to 5-hydroxymethylcytosine) and enzymes of the DNA base excision repair (BER) pathway. [15]

Neuronal migration is the method by which neurons travel from their origin or birthplace to their final position in the brain. There are several ways they can do this, e.g. by radial migration or tangential migration. Sequences of radial migration (also known as glial guidance) and somal translocation have been captured by time-lapse microscopy. [17]

Radial migration Edit

Neuronal precursor cells proliferate in the ventricular zone of the developing neocortex, where the principal neural stem cell is the radial glial cell. The first postmitotic cells must leave the stem cell niche and migrate outward to form the preplate, which is destined to become Cajal-Retzius cells and subplate neurons. These cells do so by somal translocation. Neurons migrating with this mode of locomotion are bipolar and attach the leading edge of the process to the pia. The soma is then transported to the pial surface by nucleokinesis, a process by which a microtubule "cage" around the nucleus elongates and contracts in association with the centrosome to guide the nucleus to its final destination. [18] Radial glial cells, whose fibers serve as a scaffolding for migrating cells and a means of radial communication mediated by calcium dynamic activity, [19] [20] act as the main excitatory neuronal stem cell of the cerebral cortex [21] [22] or translocate to the cortical plate and differentiate either into astrocytes or neurons. [23] Somal translocation can occur at any time during development. [17]

Subsequent waves of neurons split the preplate by migrating along radial glial fibres to form the cortical plate. Each wave of migrating cells travel past their predecessors forming layers in an inside-out manner, meaning that the youngest neurons are the closest to the surface. [24] [25] It is estimated that glial guided migration represents 90% of migrating neurons in human and about 75% in rodents. [26]

Tangential migration Edit

Most interneurons migrate tangentially through multiple modes of migration to reach their appropriate location in the cortex. An example of tangential migration is the movement of interneurons from the ganglionic eminence to the cerebral cortex. One example of ongoing tangential migration in a mature organism, observed in some animals, is the rostral migratory stream connecting subventricular zone and olfactory bulb.

Axophilic migration Edit

Many neurons migrating along the anterior-posterior axis of the body use existing axon tracts to migrate along this is called axophilic migration. An example of this mode of migration is in GnRH-expressing neurons, which make a long journey from their birthplace in the nose, through the forebrain, and into the hypothalamus. [27] Many of the mechanisms of this migration have been worked out, starting with the extracellular guidance cues [28] that trigger intracellular signaling. These intracellular signals, such as calcium signaling, lead to actin [29] and microtubule [30] cytoskeletal dynamics, which produce cellular forces that interact with the extracellular environment through cell adhesion proteins [31] to cause the movement of these cells.

Multipolar migration Edit

There is also a method of neuronal migration called multipolar migration. [32] [33] This is seen in multipolar cells, which in the human, are abundantly present in the cortical intermediate zone. They do not resemble the cells migrating by locomotion or somal translocation. Instead these multipolar cells express neuronal markers and extend multiple thin processes in various directions independently of the radial glial fibers. [32]

The survival of neurons is regulated by survival factors, called trophic factors. The neurotrophic hypothesis was formulated by Victor Hamburger and Rita Levi Montalcini based on studies of the developing nervous system. Victor Hamburger discovered that implanting an extra limb in the developing chick led to an increase in the number of spinal motor neurons. Initially he thought that the extra limb was inducing proliferation of motor neurons, but he and his colleagues later showed that there was a great deal of motor neuron death during normal development, and the extra limb prevented this cell death. According to the neurotrophic hypothesis, growing axons compete for limiting amounts of target-derived trophic factors and axons that fail to receive sufficient trophic support die by apoptosis. It is now clear that factors produced by a number of sources contribute to neuronal survival.

    (NGF): Rita Levi Montalcini and Stanley Cohen purified the first trophic factor, Nerve Growth Factor (NGF), for which they received the Nobel Prize. There are three NGF-related trophic factors: BDNF, NT3, and NT4, which regulate survival of various neuronal populations. The Trk proteins act as receptors for NGF and related factors. Trk is a receptor tyrosine kinase. Trk dimerization and phosphorylation leads to activation of various intracellular signaling pathways including the MAP kinase, Akt, and PKC pathways.
  • CNTF: Ciliary neurotrophic factor is another protein that acts as a survival factor for motor neurons. CNTF acts via a receptor complex that includes CNTFRα, GP130, and LIFRβ. Activation of the receptor leads to phosphorylation and recruitment of the JAK kinase, which in turn phosphorylates LIFRβ. LIFRβ acts as a docking site for the STAT transcription factors. JAK kinase phosphorylates STAT proteins, which dissociate from the receptor and translocate to the nucleus to regulate gene expression.
  • GDNF: Glial derived neurotrophic factor is a member of the TGFb family of proteins, and is a potent trophic factor for striatal neurons. The functional receptor is a heterodimer, composed of type 1 and type 2 receptors. Activation of the type 1 receptor leads to phosphorylation of Smad proteins, which translocate to the nucleus to activate gene expression.

Neuromuscular junction Edit

Much of our understanding of synapse formation comes from studies at the neuromuscular junction. The transmitter at this synapse is acetylcholine. The acetylcholine receptor (AchR) is present at the surface of muscle cells before synapse formation. The arrival of the nerve induces clustering of the receptors at the synapse. McMahan and Sanes showed that the synaptogenic signal is concentrated at the basal lamina. They also showed that the synaptogenic signal is produced by the nerve, and they identified the factor as Agrin. Agrin induces clustering of AchRs on the muscle surface and synapse formation is disrupted in agrin knockout mice. Agrin transduces the signal via MuSK receptor to rapsyn. Fischbach and colleagues showed that receptor subunits are selectively transcribed from nuclei next to the synaptic site. This is mediated by neuregulins.

In the mature synapse each muscle fiber is innervated by one motor neuron. However, during development many of the fibers are innervated by multiple axons. Lichtman and colleagues have studied the process of synapses elimination. [34] This is an activity-dependent event. Partial blockage of the receptor leads to retraction of corresponding presynaptic terminals.

CNS synapses Edit

Agrin appears not to be a central mediator of CNS synapse formation and there is active interest in identifying signals that mediate CNS synaptogenesis. Neurons in culture develop synapses that are similar to those that form in vivo, suggesting that synaptogenic signals can function properly in vitro. CNS synaptogenesis studies have focused mainly on glutamatergic synapses. Imaging experiments show that dendrites are highly dynamic during development and often initiate contact with axons. This is followed by recruitment of postsynaptic proteins to the site of contact. Stephen Smith and colleagues have shown that contact initiated by dendritic filopodia can develop into synapses.

Induction of synapse formation by glial factors: Barres and colleagues made the observation that factors in glial conditioned media induce synapse formation in retinal ganglion cell cultures. Synapse formation in the CNS is correlated with astrocyte differentiation suggesting that astrocytes might provide a synaptogenic factor. The identity of the astrocytic factors is not yet known.

Neuroligins and SynCAM as synaptogenic signals: Sudhof, Serafini, Scheiffele and colleagues have shown that neuroligins and SynCAM can act as factors that induce presynaptic differentiation. Neuroligins are concentrated at the postsynaptic site and act via neurexins concentrated in the presynaptic axons. SynCAM is a cell adhesion molecule that is present in both pre- and post-synaptic membranes.

Activity dependent mechanisms in the assembly of neural circuits Edit

The processes of neuronal migration, differentiation and axon guidance are generally believed to be activity-independent mechanisms and rely on hard-wired genetic programs in the neurons themselves. Research findings however have implicated a role for activity-dependent mechanisms in mediating some aspects of these processes such as the rate of neuronal migration, [35] aspects of neuronal differentiation [36] and axon pathfinding. [37] Activity-dependent mechanisms influence neural circuit development and are crucial for laying out early connectivity maps and the continued refinement of synapses which occurs during development. [38] There are two distinct types of neural activity we observe in developing circuits -early spontaneous activity and sensory-evoked activity. Spontaneous activity occurs early during neural circuit development even when sensory input is absent and is observed in many systems such as the developing visual system, [39] [40] auditory system, [41] [42] motor system, [43] hippocampus, [44] cerebellum [45] and neocortex. [46]

Experimental techniques such as direct electrophysiological recording, fluorescence imaging using calcium indicators and optogenetic techniques have shed light on the nature and function of these early bursts of activity. [47] [48] They have distinct spatial and temporal patterns during development [49] and their ablation during development has been known to result in deficits in network refinement in the visual system. [50] In the immature retina, waves of spontaneous action potentials arise from the retinal ganglion cells and sweep across the retinal surface in the first few postnatal weeks. [51] These waves are mediated by neurotransmitter acetylcholine in the initial phase and later on by glutamate. [52] They are thought to instruct the formation of two sensory maps- the retinotopic map and eye-specific segregation. [53] Retinotopic map refinement occurs in downstream visual targets in the brain-the superior colliculus (SC) and dorsal lateral geniculate nucleus (LGN). [54] Pharmacological disruption and mouse models lacking the β2 subunit of the nicotinic acetylcholine receptor has shown that the lack of spontaneous activity leads to marked defects in retinotopy and eye-specific segregation. [53]

In the developing auditory system, developing cochlea generate bursts of activity which spreads across the inner hair cells and spiral ganglion neurons which relay auditory information to the brain. [55] ATP release from supporting cells triggers action potentials in inner hair cells. [56] In the auditory system, spontaneous activity is thought to be involved in tonotopic map formation by segregating cochlear neuron axons tuned to high and low frequencies. [55] In the motor system, periodic bursts of spontaneous activity are driven by excitatory GABA and glutamate during the early stages and by acetylcholine and glutamate at later stages. [57] In the developing zebrafish spinal cord, early spontaneous activity is required for the formation of increasingly synchronous alternating bursts between ipsilateral and contralateral regions of the spinal cord and for the integration of new cells into the circuit. [58] In the cortex, early waves of activity have been observed in the cerebellum and cortical slices. [59] Once sensory stimulus becomes available, final fine-tuning of sensory-coding maps and circuit refinement begins to rely more and more on sensory-evoked activity as demonstrated by classic experiments about the effects of sensory deprivation during critical periods. [59]

Contemporary diffusion-weigthted MRI techniques may also uncover the macroscopic process of axonal development. The connectome can be constructed from diffusion MRI data: the vertices of the graph correspond to anatomically labelled gray matter 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 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. [60] [61] 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 the animation on the left).

It is hypothesized in [62] that the growing structure copies the axonal development of the human brain: the earliest developing connections (axonal fibers) are common at 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.

Several motorneurons compete for each neuromuscular junction, but only one survives until adulthood. [34] Competition in vitro has been shown to involve a limited neurotrophic substance that is released, or that neural activity infers advantage to strong post-synaptic connections by giving resistance to a toxin also released upon nerve stimulation. In vivo, it is suggested that muscle fibres select the strongest neuron through a retrograde signal.

Regulation of Fetal Growth

Nerve Growth Factor

Nerve growth factor (NGF) was first characterized from extracts of mouse salivary glands, but has been found in many other tissues, at least in tissue cultures. It has been detected in the human placenta. It is a large protein complex (molecular weight, 140,000) consisting of an active β subunit and regulatory γ and α subunits ( Harper and Thoenen, 1980 ).

The increase in size of sensory and sympathetic ganglia of chick embryos treated with NGF results from the enhanced survival of neurons that would otherwise degenerate. There may also be increased mitosis of glial cells. Neonatal sympathetic ganglia not only contain more NGF than adult ganglia, but they are also more responsive, causing the morphological transformation of sympathetic neuroblasts into differentiated neurons.

Some sympathetically innervated tissues synthesize NGF and it has been postulated that NGF released into surrounding tissue serves as a trophic factor for incoming axons. Nerve growth factor also stimulates the growth or regenerating noradrenergic neurons following brain lesions and hypertrophy of the adrenal medulla ( Mobley et al., 1977 ). Thus NGF appears to be important in the maturation of adrenergic neurons and the sympathetic nervous system.

Nerve growth factor receptors are present in brain tissue. The administration of thyroxine to rats increases the concentration of NGF in the liver, submaxillary glands, cerebellum, cerebral cortex, and brainstem ( Walker et al., 1979 ). The effects of NGF on axonal regeneration in the brain are similar to those of thyroid hormones. These studies suggest a mechanism by which thyroxine might exert its important effects on fetal brain development.


NGF is initially in a 7S, 130-kDa complex of 3 proteins – Alpha-NGF, Beta-NGF, and Gamma-NGF (2:1:2 ratio) when expressed. This form of NGF is also referred to as proNGF (NGF precursor). The gamma subunit of this complex acts as a serine protease, and cleaves the N-terminal of the beta subunit, thereby activating the protein into functional NGF.

The term nerve growth factor usually refers to the 2.5S, 26-kDa beta subunit of the protein, the only component of the 7S NGF complex that is biologically active (i.e. acting as signaling molecules).

As its name suggests, NGF is involved primarily in the growth, as well as the maintenance, proliferation, and survival of nerve cells (neurons). In fact, NGF is critical for the survival and maintenance of sympathetic and sensory neurons, as they undergo apoptosis in its absence. [5] However, several recent studies suggest that NGF is also involved in pathways besides those regulating the life cycle of neurons.

Neuronal proliferation Edit

NGF can drive the expression of genes such as bcl-2 by binding to the Tropomyosin receptor kinase A, which stimulates the proliferation and survival of the target neuron.

High affinity binding between proNGF, sortilin, and p75NTR can result in either survival or programmed cell death. Study results indicate that superior cervical ganglia neurons that express both p75NTR and TrkA die when treated with proNGF, [6] while NGF treatment of these same neurons results in survival and axonal growth. Survival and PCD mechanisms are mediated through adaptor protein binding to the death domain of the p75NTR cytoplasmic tail. Survival occurs when recruited cytoplasmic adaptor proteins facilitate signal transduction through tumor necrosis factor receptor members such as TRAF6, which results in the release of nuclear factor κB (NF-κB) transcription activator. [7] NF-κB regulates nuclear gene transcription to promote cell survival. Alternatively, programmed cell death occurs when TRAF6 and neurotrophin receptor interacting factor (NRIF) are both recruited to activate c-Jun N-terminal kinase (JNK) which phosphorylates c-Jun. The activated transcription factor c-Jun regulates nuclear transcription via AP-1 to increase pro-apoptotic gene transcription. [7]

Proliferation of pancreatic beta cells Edit

There is evidence that pancreatic beta cells express both the TrkA and p75NTR receptors of NGF. It has been shown that the withdrawal of NGF induces apoptosis in pancreatic beta cells, signifying that NGF may play a critical role in the maintenance and survival of pancreatic beta cells. [8]

Regulation of the immune system Edit

NGF plays a critical role in the regulation of both innate and acquired immunity. In the process of inflammation, NGF is released in high concentrations by mast cells, and induces axonal outgrowth in nearby nociceptive neurons. This leads to increased pain perception in areas under inflammation. In acquired immunity, NGF is produced by the Thymus as well as CD4+ T cell clones, inducing a cascade of maturation of T cells under infection. [9]

Ovulation Edit

NGF is abundant in seminal plasma. Recent studies have found that it induces ovulation in some mammals e.g. “induced” ovulators, such as llamas. Surprisingly, research showed that these induced animals will also ovulate when semen from on-schedule or “spontaneous” ovulators, such as cattle is used. Its significance in humans is unknown. It was previously dubbed ovulation-inducing factor (OIF) in semen before it was identified as beta-NGF in 2012. [10]

Romantic love Edit

Studies have found that the concentration of NGF in the blood plasma is significantly higher in individuals who have been in a romantic relationship for less than 12 months [227 (14) pg/ml], than those who are either not in a romantic relationship [149 (12) pg/ml] or have been in one for more than 12 months [123 (10) pg/ml]. [11]

NGF can indirectly stimulate the expression of adrenocorticotrophic hormone (ACTH) in the hypothalamic-pituitary-adrenal axis (HPA) by increasing vasopressin secretion. ACTH binds to the MC2 receptor in the zona fasciculata of the adrenal cortex, and stimulates secretion of the stress hormone cortisol. [12] This rapid increase of cortisol in the blood plasma can induce feelings of euphoria, which may explain the initial "rush" of falling in love. [13] Studies show that ACTH can in turn stimulate NGF secretion in both the cerebral cortex and the hypothalamus.

NGF binds with at least two classes of receptors: the tropomyosin receptor kinase A (TrkA) and low-affinity NGF receptor (LNGFR/p75NTR). Both are associated with neurodegenerative disorders.

When NGF binds to the TrkA receptor, it drives the homodimerization of the receptor, which in turn causes the autophosphorylation of the tyrosine kinase segment. [14] The tropomyosin receptor kinase A receptor has five extracellular domains, and the fifth domain is sufficient in binding NGF. [15] Once bound, the complex undergoes endocytosis and activates the NGF transcriptional program, following itwo major pathways, the Ras/MAPK pathway and the PI3K/Akt pathway. [14] The binding of NGF to TrkA also leads to the activation of PI 3-kinase, ras, and PLC signaling pathways. [16] Alternatively, the p75NTR receptor can form a heterodimer with TrkA, which has higher affinity and specificity for NGF.

Studies suggest that NGF circulates throughout the entire body via the blood plasma, and is important for the overall maintenance of homeostasis. [17]

Neuron survival Edit

Binding interaction between NGF and the TrkA receptor facilitates receptor dimerization and tyrosine residue phosphorylation of the cytoplasmic tail by adjacent Trk receptors. [18] Trk receptor phosphorylation sites operate as Shc adaptor protein docking sites, which undergo phosphorylation by the TrkA receptor [7] Once the cytoplasmic adaptor protein (Shc) is phosphorylated by the receptor cytoplasmic tail, cell survival is initiated through several intracellular pathways.

One major pathway leads to the activation of the serine/threonine kinase, Akt. This pathway begins with the Trk receptor complex-recruitment of a second adaptor protein called growth factor-receptor bound protein-2 (Grb2) along with a docking protein called Grb2-associated Binder-1 (GAB1). [7] Subsequently, phosphatidylinositol-3 kinase (PI3K) is activated, resulting in Akt kinase activation. [7] Study results have shown that blocking PI3K or Akt activity results in death of sympathetic neurons in culture, regardless of NGF presence. [19] However, if either kinase is constitutively active, neurons survive even without NGF. [19]

A second pathway contributing to cell survival occurs through activation of the mitogen-activated protein kinase (MAPK) kinase. In this pathway, recruitment of a guanine nucleotide exchange factor by the adaptor and docking proteins leads to activation of a membrane-associated G-protein known as Ras. [7] The guanine nucleotide exchange factor mediates Ras activation through the GDP-GTP exchange process. The active Ras protein phosphorylates several proteins, along with the serine/threonine kinase, Raf. [7] Raf in turn activates the MAPK cascade to facilitate ribosomal s6 kinase (RSK) activation and transcriptional regulation. [7]

Both Akt and RSK, components of the PI3K-Akt and MAPK pathways respectively, act to phosphorylate the cyclic AMP response element binding protein (CREB) transcription factor. [7] Phosphorylated CREB translocates into the nucleus and mediates increased expression of anti-apoptotic proteins, [7] thus promoting NGF-mediated cell survival. However, in the absence of NGF, the expression of pro-apoptotic proteins is increased when the activation of cell death-promoting transcription factors such as c-Jun are not suppressed by the aforementioned NGF-mediated cell survival pathways. [7]

Rita Levi-Montalcini and Stanley Cohen discovered NGF in the 1950s while faculty members at Washington University in St Louis. However, its discovery, along with the discovery of other neurotrophins, was not widely recognized until 1986, when it won the Nobel Prize in Physiology or Medicine. [20] [21] [22]

Studies in 1971 determined the primary structure of NGF. This eventually led to the discovery of the NGF gene.

NGF is abundant in seminal plasma. Recent studies have found that it induces ovulation in some mammals. [23] Nerve Growth Factors (NGF) were initially discovered due to their actions during development, but NGF are not known to be involved in the function throughout the life of the animal. [24]

Nerve growth factor prevents or reduces neuronal degeneration in animal models of neurodegenerative diseases and these encouraging results in animals have led to several clinical trials in humans. [25] NGF promotes peripheral nerve regeneration in rats. [26] The expression of NGF is increased in inflammatory diseases where it suppresses inflammation. [27] NGF appears to promote myelin repair. [28] Hence NGF may be useful for the treatment of multiple sclerosis. [29] NGF could also be involved in various psychiatric disorders, such as dementia, depression, schizophrenia, autism, Rett syndrome, anorexia nervosa, and bulimia nervosa. [30]

Dysregulation of NGF signaling has also been linked to Alzheimer's disease. [31] [32] [33] [34] [35] [36] Connective tissue cells genetically engineered to synthesize and secrete NGF and implanted in patients' basal forebrains reliably pumped out NGF, which enhanced the cells’ size and their ability to sprout new neural fibers. The treatment also rescued vulnerable cells, even if they already showed the trademark signs of Alzheimer's pathology. In some patients, these beneficial effects lasted almost 10 years after the treatment. Even patients who died responded positively to the therapy. Even pathological cells with protein clumps in their cell bodies and surroundings extended their fibers toward the NGF source, maintained a healthy size and activated pro-survival signals that boosted their stress resilience. Two other patients received direct injections of modified viruses containing the NGF gene directly to their basal forebrains. This allowed the gene to express longer in the brain. [37] [38]

Neurotrophins, including NGF, have been shown to affect many areas of the brain, including areas that are related to Rett syndrome, bipolar disorder, and Alzheimer's disease. Stress and/or anxiety are usually a precipitating factor in these disorders and affects levels of NGF, leading to impaired cognitive functioning.

This impaired cognitive functioning can be seen in people with schizophrenia. In treating schizophrenia, NGF levels are seen to be increased when using atypical antipsychotics, but not when using typical antipsychotics. Those using atypical medications usually report improved cognitive performance compared to those using typical antipsychotics. Higher NGF levels from the atypical antipsychotic medications may underlie the reduction in negative symptoms of schizophrenia relative to typical antipsychotics. [39]

NGF has been shown to restore learning ability in rats recovering from induced alcoholism. [40]

Rett syndrome and autism often show similar signs early in life, such as slowing development and intellectual disability. One distinguishing factor is that low levels of NGF have been found in the cerebrospinal fluid of children with Rett syndrome compared to children with Autism who have relatively normal to high levels. [41] Pharmaceutical therapies with NGF-like activity can be effective in treating Rett syndrome, including better motor and cortical functioning as well as increased social communication. [42]

Impairment of neuroplasticity and altered levels of neurotrophins are involved in bipolar disorder. NGF has been found to be decreased overall in people with bipolar disorder. More specifically, while in a manic state NGF is especially low. This leads to elevated or irritable mood with increased energy and decreased need for sleep while in a manic state. This decreased NGF may serve as a biological marker when assessing a person's present bipolar disorder state. [43] When treated with lithium, their NGF concentrations increased in the frontal cortex, limbic forebrain, hippocampus, and amygdala. [44]

An increase in cortical and subcortical NGF has been found in patients with Alzheimer's disease. Alzheimer's is a neurodegenerative disease with which dysregulation of NGF signaling has also been linked, causing impaired retrograde transport of NGF to certain areas of the brain. This impairment may be caused by an atypical production or use of receptors in the brain. [45] Stimulating NGF receptors via NGF infusion has been shown to increase blood flow and verbal episodic memory. These improvements have been longer lasting than other treatments for Alzheimer's. [42]

Also, NGF has been shown to play a role in a number cardiovascular diseases, such as coronary atherosclerosis, obesity, type 2 diabetes, and metabolic syndrome. [46] Reduced plasma levels of NGF and BDNF have been associated with acute coronary syndromes and metabolic syndromes. [47] [48] NGF is known to have insulinotropic, angiogenic, and antioxidant properties. NGF suppresses food intake. [ citation needed ]

NGF has also been shown to accelerate wound healing. There is evidence that it could be useful in the treatment of skin ulcers and cornea ulcers. [49]

A mutation in the beta gene of NGF has been seen to lead to a loss of pain perception additionally, this loss of pain is not linked with a change to CNS development or mental abilities in patients. [50] Thus, this study highlights that there may be different pathways by which the NGF gene regulates pain perception compared with other nervous system development. [50]

In some gynecological diseases, an elevated prostaglandin E2 is thought to stimulate production of NGF which contributes to the perception of pain and increased inflammation in endometriosis. [51]

Monoclonal antibodies against NGF have been used in clinical trials to modulate pain. One of these is tanezumab, another is fulranumab.

Nerve growth factor may contribute to increased longevity and mental capacity. [52] Centenarian Rita Levi-Montalcini took a daily solution in the form of eye drops, and has stated that her brain is more active now than it was four decades ago. [52] In 2014, researchers at the Medical University of South Carolina showed that NGF level is elevated in people who performed a single 20-minute yoga session involving om-chanting and thirumoolar pranayama, when compared to a control group. [53]

It has recently been suggested that NGF expression may be stimulated by dehydroepiandrosterone (DHEA). [55] DHEA may also act as an agonist of both TrkA and p75NTR and activate the pathways of NGF, demonstrating neurotrophic activities similar to that of NGF. [56]

Adrenocorticotrophic hormone (ACTH) can also upregulate NGF expression in the brain. [57]

Wiring Up the Brain: Axon Navigation

Mechanics, Adhesion, and the Extracellular Matrix

Growth cones navigate through biological terrain that is mechanically heterogeneous. Many years ago, Paul Weiss (1934) noticed that when neurons are put into a tissue culture dish that has cracks or scratches on the surface, the growing axons follow the pattern of these imperfections, suggesting that the axons were guided by mechanical cues ( Fig. 5.20 A ). There are obvious mechanical features of the environment that affect growth cone navigation, such as nerve sheathes and the outer surfaces of the brain, which form impenetrable barriers and the presence of major pathways such as tracts or commissures, which serve as bridges or major roadways from one region to another. When, for example, the corpus callosum (the huge axonal tract that connects the left and right cerebral cortices across the midline) is cut, axons will not be able to cross from one side of the brain to the other. Here, it possible to provide axons with an artificial mechanical bridge across the wound ( Silver and Ogawa, 1983 ) ( Fig. 5.20 B).

Fig. 5.20 . Axons may follow mechanical pathways. (A) The axons of neurons on a dried collagen matrix growing through the cracks. (B) Axons of the corpus callosum can use an artificial sling to grow from one side of the brain to the other.

A particular mechanical feature of the nervous system to which growth cones attend is stiffness. The stiffness of tissues can be measured by atomic force microscopy ( Franze, 2011 , 2013 Franze et al., 2013 ). Brain tissue has barely any collagen so it is extremely soft—about the consistency of cream cheese. Muscle is an order of magnitude stiffer, and bone a further two orders of magnitude stiffer. It can be shown by plating cells into culture on substrates that differ only in stiffness that this this mechanical feature has dramatic effects on growth cones and axon growth. Much of the work on growth cone cell biology has been done in tissue culture, where the plastic petri dishes on which the neurons grow are as hard as bone. Yet when grown on substrates as soft as brain, different neurons respond differently—spinal axons branch more while sensory neurons of dorsal root ganglia grow shorter axons. On such stiff substrates the axons of retinal ganglion cells tend to grow straight and often fasciculate with each other. When grown instead on substrates that are as soft as brain tissue, these axons grow in a more exploratory mode, changing directions frequently ( Koser et al., 2016 ). Within brain tissue, there is mechanical heterogeneity at a fine scale, neural cells bodies are stiffer than their processes, and ECM is stiffer than the cellular components. When grown on gradients of stiffness that mimic those in the brain, retinal growth cones tend to turn toward softer and away from harder, and this matches the way that they grow along gradients of stiffness in the embryonic brain. These growth cones sense the stiffness in the substrate through stretch-activated channels. When these channels are blocked by mutation or a particular component of spider venom, growth cones lose the ability to respond to tissue stiffness ( Koser et al., 2016 ) ( Fig. 5.21 ).

Fig. 5.21 . Mechanosensitivity of RGC axons in vitro. (A, B) Cultures of Xenopus eye primordia (asterisks) on (A) soft (0.1 kPa) and (B) stiff (1 kPa) substrates. Arrows indicate axons. (C) Eye primordium grown on a stiff substrate and treated with spider venom component GsMTx4 which blocks stretch activated mechanical sensing channels in the growth cone. Scale bar: 200 μm.

Mechanical support is necessary and its heterogeneity is influential, but for axons to grow to very specific target cells, molecular mechanisms are needed, and indeed, most investigations of axon guidance have focused on the molecules that support and guide navigating axons. A simple demonstration of the importance of molecular adhesion is that neurons plated on plain glass or tissue culture plastic, rarely put out axons with active growth cones, but when these same substrates are coated with a polycationic substrate, such as polylysine, that sticks well to negatively charged biological membranes, the neurons are much more likely to initiate axonal outgrowth. The growth cones of such neurons flatten against the substrate adhering very strongly to it and will follow adhesive versus nonadhesive tracks on the culture dish ( Letourneau, 1975 Hammarback et al., 1985 ) ( Fig. 5.22 ). Axons may use gradients of relative adhesiveness to orient during parts of their journey. For instance, in the moth, sensory neurons at the wing tip send out axons that grow proximally toward the base of the wing ( Nardi and Vernon, 1990 ). Microscopic examination of the epithelium along which these axons grow show that it becomes increasingly loaded with adhesion molecules toward the base. Transplantation experiments confirm that these axons respond to this gradient as they readily cross onto a more adhesive transplant that has been moved in the proximal to distal direction, but avoid less adhesive distal transplants that have been moved proximally ( Nardi, 1983 ).

Fig. 5.22 . Growth cones and adhesion. (A) On a very adhesive substrate growth cones are flattened, have lots of filopodia, and do not move rapidly (top). On a less adhesive substrate, growth cones are more compact, rounded, have fewer processes, and often move more quickly. (B) Neurites in culture given a choice between an adhesive and a nonadhesive substrate will tend to follow the adhesive trails.

To measure growth cone attachment to various cell adhesion molecules, culture media can be squirted at the growth cones through a pipette with a particular force in an attempt to “blast” them off the substrate ( Fig. 5.23 ). The longer the growth cone stays attached to the surface in the face of such blasts, the stronger its adhesion must be. Neurite growth rate can then be measured on these same substrates for comparison ( Lemmon et al., 1992 ). For an axon to grow quickly, the substrate must have the right amount of stickiness—too little and the growth cone will not attach, too much and the growth cone will get stuck. Indeed, the most adhesive substrates, such as the lectin Concanavalin A, do not support axon outgrowth growth cones on such a surface are exceedingly flattened and seem incapable of even retracting their filopodia.

Fig. 5.23 . Differential adhesion of growth cones. (A) To quantitate adhesivity, a measured blast of culture medium is directed at the growth cone. At a particular time, the growth cone becomes detached. (B) Growth is quantified by axon length increase over an interval time. (C) By using such tests, it can be shown that the neurons tested show a particular adhesion profile and tend to grow more slowly on more adhesive substrates.

In vivo, adhesion is regulated by Substrate Adhesion Molecules (SAMs) and Cell Adhesion Molecules (CAMs). Many SAMs that are excellent supporters of axon growth have been isolated from the extracellular matrix (ECM) ( Bixby and Harris, 1991 Tessier-Lavigne and Goodman, 1996 ). Laminin, Fibronectin, Vitronectin, and various forms of collagen, all promote axon outgrowth. Many of these ECM proteins are large and have many different functional domains. For example, Laminin has domains that bind to other components of the ECM and a domain that interacts with ECM receptors on the growth cone. Integrin is the primary cellular receptor for ECM-derived SAMs. It is composed of two subunits, alpha and beta ( Fig. 5.24 ). There are about 20 different alpha subunits and about 10 different beta subunits. Different neurons use different subunit combinations. The alpha5 subunit is particularly good at binding to Fibronectin, while the alpha6 subunit is better at binding to Laminin. Over the course of development, axons may change which Integrin subunits they express and thus change their sensitivity to a particular ECM molecule. For instance, chick retinal ganglion cells axons express alpha6 and grow well on Laminin when they are growing along the first legs of their journey in the retina and the optic tract. However, when their axons make contact with the tectum, they stop expressing this alpha6, lose their ability to respond to Laminin and head away from the ECM on the pial surface of the tectum and dive into the tectal neuropil ( Cohen and Johnson, 1991 ). Thus, the response of an axon to particular extracellular matrix molecules is largely a matter of which combination of alpha and beta Integrin subunits the growth cone is expressing at the time ( McKerracher et al., 1996 ). When the extracellular domains of Integrins bind to SAMs, their intracellular domains become capable of organizing other intracellular molecules that anchor the Integrins to the actin cables in the filopodia, thus providing a mechanical link between the ECM and the growth cone cytoskeleton.

Fig. 5.24 . The main classes of adhesion molecules expressed on the growth cone. Cadherins are calcium-dependent adhesion molecules, most are homophilic. Some members of the IgG superfamily of CAMs bind homophilically others are heterophilic. Integrins are composed of various alpha and beta subunits that bind to a variety of different extracellular matrix components with distinct affinity profiles.

The Age-Dependent Decline in Neuron Growth Potential in the CNS is Associated with an Age-Related Dysfunction of Neuronal Mitochondria

The age of incidence of Spinal Cord Injury (SCI) and the average age of people living with SCI is continuously increasing. In contrast, SCI is extensively modelled in young adult animals, hampering translation of research to clinical application. While there has been significant progress in manipulating axon growth after injury, how it is impacted by aging impacts this is still unknown. Aging is associated with a decline in mitochondrial functions, whereas mitochondria are essential to successful neurite and axon growth. Using isolation and culture of adult cortical neurons, we have analyzed mitochondrial changes in 2-, 6-, 12- and 18-month mice. We observed reduced neurite growth in older neurons. Older neurons also showed dysfunctional respiration, reduced membrane potential, and altered mitochondrial membrane transport proteins however mitochondrial DNA (mtDNA) abundance and cellular ATP were increased. Taken together, these data suggest dysfunctional mitochondria in older neurons are involved in the age-dependent reduction in neuron growth. Both normal aging and traumatic injury are associated with mitochondrial dysfunction, posing a challenge for an aging SCI population as the two elements can compound one another to worsen injury outcomes. The results of this study highlight this as an area of great interest in CNS trauma.

3. Results

This section summarizes the results and conclusions obtained by simulating the described model of growth using the two tools, NETMORPH and CX3D. A network of 100 neurons was constructed using the parameter set described in Table ​ Table1 1 and Section 2.2. Some of the parameters were varied, namely, the initial elongation rate () for axons and all types of dendrites. The proportion between the elongation rates of axons, basal, apical, and nonpyramidal dendrites is fixed and only the overall intensity of growth influencing all of them is varied. Five different parameter sets were tested for each of the simulators. The simulations reproduce the growth of neurons from the first day after plating them on a dish until the end of the third week (day 21) on the dish. The simulation step size was fixed to 0.1 h, a value sufficiently small to ensure stable simulations with both tools.

3.1. Computational Efficiency

The efficiency of the tested simulators was considerably different. In NETMORPH, the execution of one batch simulation consisting of 120 repetitions for five sets of parameters required between 2 hours and 7 days depending on the choice of model parameters. In CX3D, the same simulation required between 4 and 40 hours for a single repetition and a single set of parameters. Therefore, collecting 120 repetitions for five parameter sets would require several weeks. From the simulation efficiency point of view, NETMORPH was evidently superior to CX3D. It should be pointed out that we selected the model adjusted to NETMORPH, so the differences in performance are not surprising. In CX3D, the limiting factor that influences the efficiency is the internal dynamics associated to every model element, that is, soma and neurite segment. It is created to mimic the natural interactions between model elements, but it requires memory space and computational time. The purpose of CX3D simulator is to provide a basis for modeling and analysis of virtually unlimited set of problems. The aim of the developers was to propose a sufficiently efficient general purpose tool, which might be suboptimal when focusing on one single class of models like in this study.

3.2. Dependence of Synapse Density on Model Parameters

The first set of simulations, summarized in Figure ​ Figure3, 3 , was used to test the simulator and model properties. We focused on how well the simulators and models reproduce the synapse formation. The results obtained from the two simulators were compared with the corresponding experimental results found in the literature [21].

Synapse density. The upper row gives results for NETMORPH and the bottom row for CX3D. The curves mark the mean values, and the bars show the standard deviations. (a) shows the mean number of synapses per neuron when the elongation rate for basal dendrites takes values 1, 2, 4, 6, and 8 μm/day. (b) shows the magnified region of interest from (a), that is, the interval between 7 and 14 developmental days. The "*" mark the experimental values for the corresponding days, taken from [21]. (c) shows the synapse density obtained using CX3D, and the elongation rates for basal dendrites equal to 2, 6, 10, 14, and 22 μm/day. The experimental data (*) correspond well to the values obtained for  μm/day.

The number of postsynaptic and presynaptic sites, that is, the number of inputs and outputs, was computed for every neuron in every simulation repetition (120 repetitions in NETMORPH, 50 in CX3D). For each set of parameters, the mean and standard deviation were computed from the values obtained for 100 neurons and all the repetitions. Figures 3(a) and 3(b) show the results obtained for NETMORPH, and the bottom panel the results for CX3D. The curves on the panels connect the mean values obtained for days 4, 7, 10, 14, 16, and 21. The standard deviations are indicated with the one-side bars attached to the curves. The five curves, from blue to red, correspond to the five different values for the initial elongation rates. The chosen initial elongation rates for the basal dendrites of pyramidal neurons are indicated in the figure (see legend). For NETMORPH these values are , 2, 4, 6, and 8 μm/day, and for CX3D, they are , 6, 10, 14, and 22 μm/day. For the axons, apical dendrites, and dendrites of nonpyramidal neurons, the initial elongation rates are set to , , , respectively. Figure 3(b) is a magnification of the region of interest from Figure 3(a) , that is, for days 7� which represents the most accurately simulated phase of growth using the described model. Before day 7, the synapse formation is affected by timing of axonal and dendritic growth. It has been shown that axonal growth precedes the dendritic one [15]. This aspect of growth cannot be included in our simulation, due to the NETMORPH constraints. After day 14, the overall synapse density decreases due to the pronounced apoptosis in cultures [21]. This is, also, excluded from our model that has a fixed number of neurons.

Figures 3(a) and 3(b) , obtained for NETMORPH, indicate an exponential increase in number of synapses per neuron over time. As expected, these numbers also increase when increasing the initial elongation rate. On average, increasing the elongation rate by 1 to 2 μm/day increases the number of synapses 2-3 times for the same day of growth. All of the obtained values are significantly higher than the experimental results shown in [21]. The reported experimental values, computed as the total number of synapses divided by the total number of neurons, are around 64 synapses per neuron at day 7, 319 at day 14, 355 at day 21, and 1130 at day 28 [21]. In Figure 3(b) , the double values of these experimental data for days 7 and 14 are marked with "*". The values are doubled, since we consider every synapse twice, once for the presynaptic and once for the postsynaptic neuron. The density computed in [21] "assigns" every synapse to one neuron although it belongs to the two neurons. These values fall between the simulation results obtained for  μm/day and  μm/day. Regarding the increase in the number of synapses between days 7 and 14, it most likely resembles the curve for  μm/day. The high number of synapses may be explained by the tendency of the NETMORPH simulator to produce many synapses between the same pair of neurons.

Figure 3(c) , obtained for CX3D, shows much better agreement with the experimental results. The increase in synapse number is not so dramatic as in NETMORPH, and the maximal values stay in the range of a couple of thousands. The differences obtained for different elongation rates are not so big as in NETMORPH. Finally, the simulation results obtained for  μm/day show very good agreement with the experimental values for days 7 and 14.

3.3. Statistics of the Network Graphs

The extracted networks obtained in different phases of growth are analyzed using graph theoretic measures. The results for both simulators are illustrated in Figure ​ Figure4. 4 . The three upper rows show the statistics of in-degree distribution, shortest path length, and motifs count computed from the networks simulated in NETMORPH. The three bottom rows give these same measures evaluated for the networks simulated in CX3D. Each panel corresponds to one of days 7, 14, or 21. Different curves in the same panel show the results obtained for different values of the initial elongation rate , and the values of used for the basal dendrites are indicated in the legends. The statistics for all NETMORPH results is computed for 100 neurons in each network, and for 120 repetitions of each condition. The number of repetitions for CX3D simulations was 50.

Structural changes of the growing networks: in-degree distribution, shortest path length, and the count of motifs. Three upper rows: NETMORPH results, three lower rows: CX3D results. Different curves correspond to different initial elongation rates , and the employed values are given in the legends (1, 2, 3, 6, 8, and 10 μm/day for NETMORPH, 2, 6, 10, 14, and 22 μm/day for CX3D). Grey interrupted lines indicate motifs that are significantly more frequent than in random networks (-test, 0.01 significance level). The corresponding numbers show for which parameters this holds for example, 2 means "holds only for the two smallest values." For CX3D,  μm/day was excluded since it gives too sparse random networks.

The in-degree distribution in all the panels shifts toward higher values during growth and is higher for bigger values of growth rate. These results can be compared to the experimentally estimated connectivity in cultures, shown to be in the interval of 10�% [14, 18]. This indicates that the values and 2 μm/day give too small, while the and 10 μm/day result in too high connectivity. Taking into account the conclusions from Figure ​ Figure3, 3 , the values and 6 μm/day may give the results closest to the desired ones. A similar observation holds for the networks simulated in CX3D. Here, the overall growth of the neurites is slower due to properties of the simulator, so we used somewhat higher values for the elongation rates. The smallest tested value also gives too sparse networks, while the highest overestimated the connectivity. In CX3D, the values 10 and 14 μm/day give the connectivity closest to the expected. Similar results were observed for the out-degree distribution.

The shortest path length distribution depends on the selected initial elongation rates. The slowly growing networks ( μm/day for NETMORPH,  μm/day for CX3D) form a small number of connections until day 7. Most of the neurons are not connected or connected to a few neighbors. The shortest path is computed from this small set of short local connections, which results in a narrow distribution peaked around 0. As the network grows, new connections are established and distant pairs of neurons start to connect indirectly through other neurons. This shifts the shortest path length toward higher values. Neurons in the faster growing networks ( μm/day for NETMORPH,  μm/day for CX3D) already form direct and indirect connections at day 7. In the following days, new connections are added which continuously decreases the shortest path, since more neurons become directly connected.

The motifs count is shown as the percentage of total number of connected triplets of neurons (see Figure ​ Figure4). 4 ). The obtained counts are similar for all the parameter values, particularly in the NETMORPH examples. The peaks are visible for the motifs 2, 4, and 7. In the equivalent random networks, the motifs with two edges only (1, 2, and 4) or three edges (3, 5, 7, and 9) are the most frequent. Still, not all of them are equally represented in the simulated networks. In order to compare the simulation results with the corresponding random networks, that is, the networks with the same probability of connection, the statistical tests are done (-test, with 0.01 significance level). The results are also shown in Figure ​ Figure4, 4 , where dashed gray lines indicate the motifs that are significantly more frequent in the networks simulated using NETMORPH or CX3D than in the random networks. The number above each line shows for how many parameter values this holds, assuming that these are the smallest values from the set. In other words, number 4 indicates that a certain motif appears significantly more often in the networks simulated for the four smallest values among all the tested values, and it is either significantly smaller or not significantly different for the bigger elongation rate values. In CX3D figures, the smallest elongation rate was not considered, since it often gave very sparse random networks where motifs comparison was not possible. Expectedly, the motifs with four or more edges appear much more often in the networks simulated using NETMORPH or CX3D.

About the book


Dynamics of Degeneration and Growth in Neurons is a collection of papers presented at the International Symposium on the Dynamics of Degeneration and Growth in Neurons, held in Stockholm, Sweden, on May 16-18, 1973. Contributors explore the dynamics of degeneration and growth of central and peripheral neurons, touching on a wide range of topics such as the neurotoxic action of 6-hydroxy-dopa on central catecholamine neurons axonal transport of proteins in growing and regenerating neurons and collateral reinnervation in the central nervous system. Comprised of 50 chapters, this volume begins with an overview of degeneration processes in central and peripheral neurons. Results of microfluorimetric and neurochemical studies on degenerating and regenerating adrenergic nerves are presented. The next section is devoted to axoplasmic transport as a mechanism for axonal support and growth and includes chapters dealing with the effects of degeneration and axoplasmic transport blockade on synaptic ultrastructure, function, and protein composition the role of axoplasmic flow in trophism of skeletal muscle and proximodistal transport of acetylcholine in peripheral cholinergic neurons. The remaining chapters discuss the nerve growth factor receptor and its specific binding in sympathetic ganglia the noradrenergic innervation of cerebellar Purkinje cells and the possible role of brain and peripheral monoamines in the ontogenesis of normal and drug-induced responses in the immature mammal. This book will be of interest to physiologists and neurologists.

Dynamics of Degeneration and Growth in Neurons is a collection of papers presented at the International Symposium on the Dynamics of Degeneration and Growth in Neurons, held in Stockholm, Sweden, on May 16-18, 1973. Contributors explore the dynamics of degeneration and growth of central and peripheral neurons, touching on a wide range of topics such as the neurotoxic action of 6-hydroxy-dopa on central catecholamine neurons axonal transport of proteins in growing and regenerating neurons and collateral reinnervation in the central nervous system. Comprised of 50 chapters, this volume begins with an overview of degeneration processes in central and peripheral neurons. Results of microfluorimetric and neurochemical studies on degenerating and regenerating adrenergic nerves are presented. The next section is devoted to axoplasmic transport as a mechanism for axonal support and growth and includes chapters dealing with the effects of degeneration and axoplasmic transport blockade on synaptic ultrastructure, function, and protein composition the role of axoplasmic flow in trophism of skeletal muscle and proximodistal transport of acetylcholine in peripheral cholinergic neurons. The remaining chapters discuss the nerve growth factor receptor and its specific binding in sympathetic ganglia the noradrenergic innervation of cerebellar Purkinje cells and the possible role of brain and peripheral monoamines in the ontogenesis of normal and drug-induced responses in the immature mammal. This book will be of interest to physiologists and neurologists.

Brain Health: How Exercise Can Stimulate the Birth of New Neurons

It took decades of research to persuade scientists to give up their long-held belief that new neurons could not be formed in the brains of adults, but there is no longer any doubt about it. It is now well-established that strenuous physical exercise stimulates the birth of new neurons in part of the brain that is critical for memory, the hippocampus. The molecular and cellular details explaining how exercise stimulates the birth of new brain cells have been worked out now in great detail. Immature non-neuronal cells in the adult brain (glia) respond to protein growth factors that are generated in the body during robust physical activity. These growth factors stimulate the mother cells to spawn new neurons in the hippocampus. Amazingly, these nubile neurons then migrate through brain tissue to find their proper place in the neural circuitry. Even more remarkable, new research proves that the new neurons are then able to wire themselves into the existing network of connections to boost performance in memory, just like adding RAM chips does for a laptop. But why? Why should pumping muscles build more brain cells?

This is the question addressed by Gerd Kempermann and colleagues at Stanford, the University of Zurich and Dresden, Germany, in their recent paper published in the journal "Frontiers in Neuroscience." To understand the answer, you are going to have to suspend reality for a moment and imagine that rather than spending your day engaged in intellectual stimulation in front of your computer, you are instead living in the wild like our caveman ancestors.

Back then, human activity could be divided into two states, lounging and looking (for food). The purpose of memory back then, as it is today, is to integrate novel information that is likely to be important to our survival in the future. Back when natural selection was picking which genes our ancestors would pass down to the human race of today, searching for food was the intellectual arena of cognitive challenge. It was on these often lengthy and strenuous excursions from the familiar home site that novel information was most likely to be encountered. Our ancestors walked vast distances in search of food and better habitat, crossing through unfamiliar and dangerously challenging terrain and transcending distances that we now cover sitting on our gluteus maximus behind the wheel of a car. This, the scientists suggest, is why the body hatches new neurons in the memory region of the brain when we exercise -- to better equip us for the cognitive demands of the excursion. If their theory is correct, we should remember an excursion far better if we had peddled our way over the road rather than motored over it effortlessly nudging the wheel in the directions commanded by our GPS. "Make a legal U-turn if possible," (you've zoned out again and missed your exit).

This theory might explain the odd connection between burning calories and birthing neurons. Although the body of city-dwelling humans today was engineered to excel in the environment of our distant past, these ancient mechanisms built into our biology can be extremely useful to humans in modern times. Building brains by exercise has been shown to provide animals with an increased cognitive reserve, meaning that after brain injury or disease that kills or damages healthy neurons, animals that have been forced to do reps on the exercise wheel before a brain injury, do far better in recovering. The animals forced to work out also have much slower cognitive decline in aging compared to sedentary cage-mates, because the loss of brain cells is a normal process of aging.

Surprisingly, the same drugs used to treat chronic depression have been found to stimulate the birth of new neurons in the hippocampus. This ancient biological connection between muscle and brain can account for how pumping iron could benefit our mental health as well as our cognitive health not to mention the side effect of shaping legs and flattening bellies.

Grow those dendrites

A healthy brain cell indeed looks like a tree with a full canopy. There’s a trunk, which is the cell’s nucleus there’s a root system, embodied in a single axon and there are the branches, called dendrites.

Neurons in your brain pass signals from one to another like they’re playing an elaborate, lightning-quick game of telephone, using axons as the transmitters and dendrites as the receivers. Those signals originate in the brain and are passed throughout the body, culminating in simple actions, such as wiggling a toe, to more complex instructions, such as following through on a thought.

Just as you can judge a healthy tree by its canopy, so too can scientists judge a healthy neuron by its dendritic branches. But it had been unclear what causes dendrites to grow, and where those instructions to grow come from.

Biologists at the University of Iowa have determined a group of genes associated with neurons help regulate dendrites’ growth. But there’s a catch: These genes, called gamma-protocadherins, must be an exact match for each neuron for the cells to correctly grow dendrites.

The findings may offer a new insight into what causes aggressive or stunted dendrite growth in neurons, which could help explain the biological reasons for some mental-health diseases, as well as help researchers better understand brain development in babies born prematurely.

“Disrupted dendrite arborization is seen in the brains of people with autism and schizophrenia, so processes like the one we have uncovered here may have relevance to human disorders,” says Joshua Weiner, a molecular biologist at the UI and corresponding author on the paper, published online this month in the journal Cell Reports.

Gamma-protocadherins are called “adhesion molecules” because they stick out from a cell’s membrane to bind and hold cells together. The researchers learned about their role by giving a developing brain cell in a mouse the same gamma-protocadherin as in surrounding cells. When they did, the cells grew longer, more complex dendrites. But when the researchers outfitted a mouse neuron with a different gamma-protocadherin than the cells around it, dendritic growth was stunted.

The human brain is filled with neurons. Scientists think adults have 100 billion brain cells, each in close proximity to others and all seeking to make contact through their axons and dendrites. The denser a neuron’s dendritic network, the more apt a cell is to be in touch with another and aid in passing signals.

Gamma-protocadherins act like molecular Velcro, binding neurons together and instructing them to grow their dendrites. Weiner and his team figured out their role when they observed paltry dendritic growth in mouse brain cells where the gamma-protocadherins had been silenced.

The researchers went further in the new study. Using mice, they expressed the same type of gamma-protocadherin (labeled either as A1 or C3) in neurons in the cerebral cortex, a region of the brain that processes language and information. After five weeks, the neurons had sizeable dendritic networks, indicative of a healthy, normally functioning brain. Likewise, when they turned on a gamma-protocadherin gene in a neuron different from the gamma-protocadherin gene with the cells surrounding it, the mice had limited dendrite growth after the same time period.

That’s important because human neurons carry up to six gamma-protocadherins, meaning there are many combinations potentially in play. Yet, it seems the “grow your dendrite” signal only happens when neurons carrying the the same gamma-protocadherin gene pair up.

“The neurons actually care who they match with,” says Weiner, associate professor in the Department of Biology, part of the College of Liberal Arts and Sciences. “It takes what we knew from biochemical studies in a dish and shows that protocadherins really mediate these matching interactions in the developing brain.”

The team reports that star-looking cells called astrocytes also play a role in neurons’ dendrite development. Astrocytes are glial (Greek for “glue”) cells that help to bridge the gap between neurons and speed signals along. When the molecular binding between an astrocyte and neurons is an exact match, the neurons grow fully formed dendrites, the researchers report.

“Our data indicate that g-Pcdhs (gamma-protocadherins) act locally to promote dendrite arborization via homophilic matching and confirm that connectivity in vivo depends on molecular interactions between neurons and between neurons and astrocytes,” the authors write.

Co-authors on the paper include Michael Molumby, a graduate student in the UI’s Interdisciplinary Graduate Program in Genetics, and Austin Keeler, who earned his doctorate in the UI’s Interdisciplinary Graduate Program in Neuroscience last December. The pair helped design the experiments, collected and analyzed data, and helped write the paper.

The National Institutes of Health and the March of Dimes Foundation, a non-profit organization devoted to improving babies’ health, funded the research.

Watch the video: See a Salamander Grow From a Single Cell in this Incredible Time-lapse. Short Film Showcase (January 2023).