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How are newly created neurons recruited into existing networks?

How are newly created neurons recruited into existing networks?



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As far as I understand, the basics of neurogenesis (abstracted down to the level that makes sense to a computer scientist) is as follows:

  1. Neural progenitor cells differentiate into new neurons that have zero (or very few) synaptic connections, but are sensitive to the local chemistry.
  2. (Optional) Sometimes (such as in adult neurogenesis in the olfactory bulb) these immature neurons-to-be are produced far away from where they are needed and follow standard pathways to migrate to the correct brain region
  3. The immature neuron extends dendrites towards upstream neurons and starts to develop an axon
  4. The immature neuron extends axon towards downstream neurons, and
  5. The neuron matures and becomes indistinguishable from the network it joined.

I've eliminated many of the biological details, since I want to just capture the details (more info). The part that seems to be not well described, and my question, is:

  • How do neurons select where to make their initial dendrite and axon connections?
  • How/when does a given network notify the progenitor cells that they should differentiate?

Partial results

Cecchi et al. (2001) proposed a model where the new neurons produce initial connections randomly, and then the only the ones that contribute to the function of the network end up firing frequently and surviving, and the rest die. This inspired by the observation of high death rate among immature neurons. However, there is not biological evidence to support that the initial connections are in fact random, and I hope that there has been more evidence gathered since the early work in 2001.

Notes

  • This question is motivated by the search for computational models with a biologically reasonable account of neurogenesis.

  • I am looking for some sort of abstract local explanation to my questions at-least at the rule-of-thumb level. For examples, if I was asking about plasticity of established connections (and not neurogenesis in particular), then Hebb's "neurons that fire together wire together" would be a sufficient answer, although STDP would be a better one. However, I do not need all the biological details, just the high level rule if one is known.

References

  • Cecchi GA, Retreanu LT, Alvarez-Buylla A, Magnasco MO - “Unsupervised Learning and Adaptation in a Model of Adult Neurogenesis” Journal of Computational Neuroscience; 11:175-182; 2001 [preprint]

There is a huge body of literature on axon growth cone guidance which will give you some insights into how the biology works. Unfortunately, incorporating it all into a model is probably going to make it unwieldy unless your express purpose is to model the physiology, which doesn't seem like the case.

Here are some references:

Hong K, Nishiyama M. (2010). From guidance signals to movement: signaling molecules governing growth cone turning. Neuroscientist, 16(1),65-78.

This is pertinent because it explicitly mentions adult neurogenesis, as much of the subject is devoted to the developing nervous system in models like the developing chicken.

Kolodkin AL, Tessier-Lavigne M (2011). Mechanisms and molecules of neuronal wiring: a primer. Cold Spring Harb Perspect Biol, 3(6), 1-14 Free PDF

To call Marc Tessier-Lavigne a leader in the field of neuronal growth would be an understatement. This article also covers some of the cues of synaptogenesis as well.

Simpson HD, Mortimer D, Goodhill GJ (2009).Theoretical models of neural circuit development. Curr Top Dev Biol, 87, 1-51.

Regrettably, I do not have access to this article, but it appears to be more along the lines of computationally realistic representations. It does state that their models for synaptic strengthening are based on Hebbian Learning, so that's at least in line with what you presumed that you needed.

In searching for more computational models, ephrins and integrins are two of the cell surface agents that are heavily involved in the process, so any abstractions of those would make for a good model.


For the dentate gyrus, which is probably more closely analogous to a feedforward hidden layer in a memory network, here are some answers:

  1. Axon and dendrite connectivity is essentially local and can probably be assumed to be initially random within that local region. That is, a neuron integrating into the DG at the midpoint (along the long hippocampal axis) will have its dendrite arborize in that same location, thus receiving cortex inputs from the region of the cortex that topographically projects to that area. Likewise, its axon will target CA3 neurons at the midpoint of the hippocampus. For this reason, the general connection statistics of a newborn neuron will ultimately be similar to a neighboring neuron; though the (likely) competition between young and old synapses and the high synaptic plasticity of young neurons will distinguish the two neurons computationally.

  2. In the DG, the rate of neurogenesis is regulated by some external conditions, such as running and (likely) affect/mood. These can probably be thought of as predictive indicators of future need of neurons. Network activity is probably more critical for the survival of neurons.

  3. The OB is most likely at least somewhat different on both these points. One should take into account that newborn OB neurons are not "typical" neurons (in the abstract NN sense) by any means; OB-GCs rely more on dendro-dendritic communication (no axon) and are inhibitory.


Compensatory masquerade

The second type of neuroplasticity, compensatory masquerade, can simply be described as the brain figuring out an alternative strategy for carrying out a task when the initial strategy cannot be followed due to impairment. One example is when a person attempts to navigate from one location to another. Most people, to a greater or lesser extent, have an intuitive sense of direction and distance that they employ for navigation. However, a person who suffers some form of brain trauma and impaired spatial sense will resort to another strategy for spatial navigation, such as memorizing landmarks. The only change that occurs in the brain is a reorganization of preexisting neuronal networks.


Vital Cortical Consciousness Regions: The Hindbrain and Posterior Cortical Region

By using functional magnetic resonance imaging (MRI), we are able to observe when the brain is unable to stimulate, when corresponding regions are activated, and when neurons become abnormally active. These differences were used in word stimulation and visual decision task experiments, and it was concluded that activation of the cerebral hemisphere depends on the nature of the task rather than the stimulus itself. Whether activated on the left or the right side, activation of the brain is not in the prefrontal cortex. Rather, activation is observed in the vicinity of the central sulcus and the back of the brain (Stephan et al., 2003). In patients who underwent post-traumatic surgery to remove some of brain regions, the vast majority of patients (98%) remained in a persistent vegetative state after one year if the resected section involved the posterior cortex (Boly et al., 2017). Bianchi’s research also reached a similar conclusion, and believed that lesions in the posterior cortex of the brain may lead to permanent coma (Bianchi and Sims, 2008). Neurological awareness is primarily anatomically located in the posterior cortical thermal region, including the sensory region, rather than the prefrontal network that is involved in task monitoring and reporting (Merker, 2007). Reports of patients that remain conscious after bilateral frontal lobe resection indicate that the prefrontal cortex is not essential for consciousness (Rowland and Mettler, 1949). Other parts of the cerebral hemisphere may be potential candidates for the maintenance of consciousness, including the back part of the brain.


The unique plasticity of hippocampal adult-born neurons: Contributing to a heterogeneous dentate

Kylie A. Huckleberry Department of Psychology, Northeastern University, Boston, MA, 02115, USA.

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Kylie A. Huckleberry Department of Psychology, Northeastern University, Boston, MA, 02115, USA.

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Abstract

The dentate gyrus (DG) of the hippocampus is evolutionarily conserved as one of the few sites of adult neurogenesis in mammals. Although there is clear evidence that neurogenesis is necessary for healthy hippocampal function, whether adult-born neurons are simply integrated into existing hippocampal networks to serve a similar purpose to that of developmentally born neurons or whether they represent a discrete cell population with unique functions remains less clear. In this review, we consider evidence for discrete cellular, synaptic, and structural features of adult-born DG neurons, suggesting that neurogenesis contributes to the formation of a heterogeneous DG. We therefore propose that hippocampal neurogenesis creates a specialized neuronal subpopulation that may play a key role in hippocampal functions like episodic memory. We note critical gaps in this extensive body of work, including a general failure to include female animals in relevant research and a need for more precise consideration of intrahippocampal neuroanatomy.


Transplantation of neurons or neurogenic cells

While the above approaches are rather restricted to specific brain regions, the introduction of exogenous neurons can be performed in any injured or diseased brain region. Nevertheless, some pathologies are more suitable for this approach than others, and the choice of cell source is deterministic, as discussed below.

First, focal pathologies with mainly one specific neuron subtype lost, such as the degeneration of substantia nigra pars compacta (A9) dopaminergic neurons in PD or striatal medium spiny neurons in HD are best suited for transplantation strategies given the precise brain regions to target and cell type to replace. Stroke and brain trauma are also spatially restricted, but offer greater challenges for neuronal replacement since various types of neurons die within the affected area and the formation of a glial scar is generally thought to be inhibitory to neurite outgrowth. 101 Yet, it is noteworthy that young transplanted neurons can readily extend axons and seemingly develop well when placed in scar-forming injuries, such as stroke 102 and cortical aspiration. 103 The broad and non-cell-type-specific nature of neuronal degeneration in AD render neuronal replacement strategies challenging for this disease. However, transplantation of young inhibitory interneurons, which are highly migratory, surfaces as an option since the interneuron population is dysfunctional in the AD cerebral cortex. 104 In general, transplantation of migratory cells in multifocal pathologies may benefit from pathotropism, as indeed, homing of NSCs to injury sites relies on a chemoattractant gradient of inflammatory soluble molecules released by the lesioned tissue (reviewed in Martino and Pluchino 19 ).

Second, the choice and manufacturing of the source cells is of pivotal importance and advantageous criteria include availability, expandability, easy differentiation into the desired neuron, and MHC-matching with the host. Pioneering work used cells obtained from fetal tissue (ventral midbrain, VM) that are well specified to generate dopaminergic neuronal subtype. Transplantation of these cells into experimental models of PD demonstrated good graft survival and improved motor function thereby launching the field of cell transplantation for brain repair. 105,106 A series of clinical trials followed in the next two decades, first using autologous adrenal medullary tissue 107 and then fetal VM tissue 108 to restore dopamine in the striatum of PD patients, or using fetal ganglionic eminences aiming at cell replacement in HD patients. 109,110 Fetal tissue grafts showed encouraging results in some PD and HD patients despite variability in the overall patient cohort. 111,112 For instance, some PD patients developed graft-induced dyskinesias and standardized procedures are now being implemented to reach a more controlled outcome. 111 Fetal transplants have not only been beneficial in clinical settings, but also shown a long-term survival and a remarkable level and specificity of circuit integration in the adult injured brain, as discussed next.

Primary fetal neurons

Neurons from fetal sources are superbly specified as they derive from exactly the brain region that generates the neuronal subtype subject to disease. Pioneering studies using ectopic transplantation of fetal midbrain dopaminergic neurons into the striatum of PD animal models or later in patients demonstrated survival and complete maturation into dopaminergic neurons of the correct subtype within the host parenchyma. 111,113 Newly settled dopaminergic neurons secreted dopamine to the denervated striatum and thus improved behavior. Later on, work by Macklis’ lab paved the way exploring the neuronal integration of fetal projection neurons transplanted into homotopic areas of the adult brain after injury. 114,115,116 The team of Gaillard and Jaber published a series of exciting studies that unveiled for the first time how abundantly fetal projection neurons can project through a host parenchyma primed by an injury. 117,118,119 Together these studies brought to light a remarkable capability of fetal projection neurons to overcome growth inhibitors of axonal regeneration in the adult brain and project over long distances towards the correct target areas. Interestingly, the above work also highlighted a role for the areal identity of the donor neurons on dictating their projections. 118 The potential of fetal projection neurons for neuronal replacement therapy received added impetus recently, by demonstration of a close match between the features of the lost neurons and those gradually acquired and tuned in transplanted ones 18 (Fig. 1c, d). This work showed, for the first time, a comprehensive comparison, brain-wide, of both afferents and efferents of fetal neurons transplanted in the primary visual cortex of adult mouse after an injury. It demonstrated a correct and remarkably precise circuit integration that even re-establishes geniculo-cortical topography. Moreover, the new circuits are functional and tuned in a manner resembling visual cortex neurons, as demonstrated by calcium imaging of transplanted neurons in vivo during visual stimulation.

Transplantation of inhibitory interneurons obtained from fetal ganglionic eminences has also proven successful in reversing excitotoxicity in neurological conditions like epilepsy and chronic pain. Cells from the medial ganglionic eminence (MGE) transplanted into different brain regions develop into mature GABAergic neurons that exhibit identical electrophysiological properties to regular somatostatin and parvalbumin neurons, and enhance local synaptic inhibition. 120,121,122 When transplanted into the hippocampus of epileptic mice or into the spinal cord of mice with hypersensitivity after peripheral nerve injury, these cells reduce seizure activity or neuropathic pain, respectively. 123,124,125 Moreover, AD as well as traumatic brain injury is often associated with interneuron dysfunction or loss, and consequent imbalance between excitation and inhibition. In AD, this leads to abnormal network activity in the hippocampal DG and memory deficits. Accordingly, transplantation of MGE cells into the hippocampus in an AD rodent model restores normal learning and memory. 104 MGE cells disperse particularly well from the transplantation site, a feature that may relate with their long migratory routes during development, and which may be deterministic for the success of cell therapy in disorders with widespread neuronal loss as AD. Furthermore, transplantation of fetal interneurons was applied in a few studies in rodents, as a creative strategy to reactivate plasticity at postnatal/adult stages, by reopening critical periods to restore visual perception after early postnatal deprivation 126,127 or to attenuate recurrence of fear memory. 128 Interneurons play a central role sculping neuronal circuits activity and plasticity, and by reopening developmentally transient windows of enhanced plasticity in the adult brain they may also contribute to the success of projection neurons integration mentioned above, where donor cell population includes a minority of interneurons. Along the same lines, interneuron transplantation might promote plasticity of the remaining endogenous neurons and improve rewiring or changes in synaptic strengths in the pursuit of functional compensation, discussed previously.

In summary, fetal neurons have provided most exciting results as donor cell population and have been applied in the clinical setting in PD and HD patients 111,112 (Fig. 1e, right). The achievements made hitherto hold great promise and inspired the raise of the European initiative TRANSEURO, which seeks consistency in the efficacy of fetal cell transplantation in PD patients, and to lift the concern of transplant-induced dyskinesias by careful standardization of criteria for patient selection, cells quality and delivery, and immunosuppressive treatments. 111 The limited availability of fetal neurons, however, hampers fetal neuron-based cell therapies for neurological disorders and hence efforts have been channeled towards the use of expandable cell sources.

ENSCs-derived neurons

As expandable cells sources either multipotent NSCs of embryonic origin may be used (eNSCs), or pluripotent stem cells, discussed next. Both of these cells can be expanded efficiently in vitro, but the main challenge is their differentiation into the disease-relevant neuronal subtype. Early transplantation studies from Evan Snyder and colleagues tested the immortalized C17.2 cell line, originally obtained from neonatal mouse cerebellum. These works showed neuronal and glial differentiation after transplantation, 129 neurite outgrowth, 130 and a protective role towards the host degenerating neurons. 131 Besides, C17.2 cells could be differentiated into dopaminergic neurons with high efficiency by Nurr1 overexpression and astrocyte-derived factors. 132 Concomitantly, the team of Ron McKay isolated and expanded eNSCs from E12 rat VM, using FGF2-mediated neurosphere formation. These cells were subsequently differentiated into dopaminergic neurons by withdrawal of the mitogens, and eventually transplanted in a rat model of PD 133 leading to a substantial improvement in amphetamine-induced rotation scores. An improved protocol of differentiation was proposed later by Arenas and collaborators including additional patterning factors, namely, FGF8, Shh, and Wnt5a. 134,135 Interestingly, McKay’s team also isolated expandable eNSCs from cortex or VM of human fetal brain and could generate dopaminergic neurons from both, but only the VM-derived dopaminergic neurons survived in the striatum of parkinsonian rats. 136 Others also isolated eNSC from human fetal brain tissue, so called human CNS-stem cells 137 (huCNS-SC) using fluorescence-activated cell sorting (FACS) of CD133+/CD34−/CD45− cells. These cells, highly expandable in vitro and multipotent also after transplantation, 138 were generated under GMP conditions (StemCells Inc.) and used as donors for multiple approaches in rodent models of SCI, AD, or hippocampal neuronal loss. 139,140 The research grade huCNS-SC elicited behavioral recovery as assessed in locomotor or cognitive tasks in SCI or AD models, respectively. 139,140 These findings propelled the translation into clinics and huCNS-SC were transplanted in children with the lethal lysosomal storage disorder neuronal ceroid lipofuscinosis (NCL) 141 (Fig. 1e, right). This resulted in favorable safety assessments and was followed by transplantations into thoracic SCI patients (unpublished). The mechanism that leads to the observed improvements, however, remains unclear, and seems at least partially due to a bystander effect. Recently, two studies describe efficacy failure of clinical grade huCNS-SC in rodent models of SCI and AD 142,143 and highlight the importance of testing safety and efficacy for individual clinical grade lots and of performing long-term assessments.

ESCs-derived and iPSCs-derived neurons

Since the isolation of human ESCs (hESCs) 144 great efforts were made to design and improve the generation of specific neuronal subtypes relevant for cell replacement therapy and testing their functional integration into the CNS in animal models of disease. Almost a decade later, human somatic cells were reprogrammed for the first time into iPSCs (hiPSCs) with just a handful of genes, 145 a discovery that set the stage for a new momentum in the brain regeneration field, by offering a scalable and MHC-matched source of neuronal and glial cells from equivalent ground state cells. 13,146 Substantial progress has been made on optimizing the directed differentiation of pluripotent ESCs or iPSCs toward a given neuronal fate by defined culture settings that activate or inhibit master developmental pathways (for review see Steinbeck and Studer 147 ). Alternatively, direct lineage conversion from a somatic cell, like skin fibroblasts, to a neuron of interest (induced neuron, or iN), 14,148,149 or reprogramming of somatic cells into induced neural progenitor cells (iNPC), 150,151,152 which can then be guided toward the desired fate, skip the pluripotent stem cell intermediate and thus carry no risk of tumor formation after transplantation.

Transplantations into the developing rodent brain, an environment that naturally supports neuronal maturation and synaptic integration, demonstrated the therapeutic potential of ESCs-derived and iPSCs-derived neurons. 153,154,155,156,157,158,159,160 These reports showed survival and integration into the developing host circuits by anterograde/retrograde tracing and/or electrophysiological recordings. Notably, ESCs-derived and iPSCs-derived neurons are also able to survive and extend long-range projections to target areas in the adult injured brain 103,161,162 and improve behavior in PD animal models. 163,164 Indeed, VM-patterned hESCs seem to provide functional benefits with similar efficiency to human fetal VM neurons 162 although innervating less target areas of A9 dopaminergic neurons. Recently, the correlation between gene expression profiles of various VM-patterned hESC lines and their outcome after transplantation into a rodent model of PD identified a set of caudal midbrain markers that predict enhanced dopaminergic neuron yield. 165 Moreover, single cell transcriptomics of VM Lmx1a progenitors showed that several markers routinely used for dopaminergic lineage patterning are shared with neuronal lineages from subthalamic nuclei, and propose the application of the unique dopaminergic markers to better tailor the source cells for cell replacement in PD. 166 Altogether, these findings highlight the importance of guiding cells to the very exact neuronal subtype for the best outcome upon transplantation.

Excitingly, optogenetic silencing of grafted hESCs-derived DA neurons proved for the first time a causative link between the graft synaptic transmission and improved behavioral outcome. 17 Also, hESCs-derived GABAergic projection neurons can be generated with great efficiency and integrate into HD-like degenerating circuits improving motor function. 167 Notably, hiPSCs-derived cortical neurons survive in an extremely inhospitable environment as stroke-lesioned parenchyma, 16,168 receive input from correct host brain areas including the thalamus and respond to sensory stimulation. 16 Those hiPSCs-derived grafts also improved sensorimotor function already 2 months after transplantation. 102 At this time point, the input connectome was already established with no further change for the next 4 months, 16 showing a fast formation of afferent connections. On the other hand, most of the grafted cells were still expressing the immature neuronal marker doublecortin raising the question to which extent the behavioral effects were due to circuit integration and/or bystander effects. Indeed, one limitation observed over the years is the rather protracted period of neuronal maturation from human pluripotent stem cells, which constitutes a major bottleneck for their routine and large-scale application in disease modeling or regenerative medicine. This has been facilitated by improved protocols with accelerated neuronal differentiation either using transcription factors 169,170 or small molecules. 160 Alternatively, this obstacle can be overcome by using direct conversion of human fibroblasts into the desired neurons. 14,148,149,171,172,173,174,175

Furthermore, studies to date highlight the need to sort out the remaining pluripotent stem cells to exclude tumor formation upon grafting 176 or improve the differentiation protocols efficiency to avoid those tumorigenic contaminants and other unwanted neural types. On the other hand, extensive expansion in culture is associated with increased genomic and epigenomic instability, 177,178 a hallmark of malignant cells. This concern can be tackled by the use of standardized culture settings that minimize genomic alterations. Additionally, stringent preclinical safety tests must assess both purity of the donor cell population and genomic/epigenomic integrity.

In summary, neurons derived from pluripotent cell sources have reached a stage where they become comparable to those derived from fetal brains. Indeed, preclinical assessments of hESCs or hiPSCs as sources for neuronal replacement therapy are encouraging and motivated the large-scale generation of GMP-qualified cell products for clinical use. At present, phase I/II trials have been initiated in patients with age-related macular degeneration and Stargardt macular dystrophy transplanted with hESCs-derived retinal pigment epithelium (RPE) 179,180 (Fig. 1e, right) and the next years will witness clinical translation also to PD patients (Gforce-PD). 181 In addition, autologous hiPSCs-derived RPE was transplanted in a patient with age-related macular degeneration. 182 This study was suspended due to safety concerns but it is prospected to be resumed using allogeneic MHC-matched hiPSCs.


II. Neurophysiology of the Cerebral Cortex

A. Basic Anatomy of Cortex

The human cerebral cortex consists of 3 to 6 layers of neurons. The phylogenetically oldest part of the cortex (archipallium) has 3 distinct neuronal layers, and is exemplified by the hippocampus, which is found in the medial temporal lobe. The majority of the cortex (neocortex or neopallium) has 6 distinct cell layers and covers most of the surface of the cerebral hemispheres. A particularly important cortical structure in the pathophysiology of one of the more common epilepsy syndromes is the hippocampus. This structure illustrated in Slide 3 is common in temporal lobe epilepsy. As seen in the slide, the hippocampus consists of three major regions: subiculum, hippocampus proper (Ammon's horn) and dentate gyrus. The hippocampus and dentate gyrus have a three layered cortex. The subiculum is the transition zone from the three to the six layered cortex. Important regions of the hippocampus proper include CA1, CA 2, CA3.

Slide 3

Basic Mechanisms Underlying Seizures and Epilepsy

The cortex includes two general classes of neurons. The projection, or principal, neurons (e.g., pyramidal neurons) are cells that "project" or send information to neurons located in distant areas of the brain. Interneurons (e.g., basket cells) are generally considered to be local-circuit cells which influence the activity of nearby neurons. Most principal neurons form excitatory synapses on post-synaptic neurons, while most interneurons form inhibitory synapses on principal cells or other inhibitory neurons. Recurrent inhibition can occur when a principal neuron forms synapses on an inhibitory neuron, which in turn forms synapses back on the principal cells to achieve a negative feedback loop. (Slide 4 illustrates an example of a type of interneuron-granule cell and its role in a negative feedback loop in the hippocampus.)

Slide 4

Basic Mechanisms Underlying Seizures and Epilepsy

Recent work suggests that some interneurons appear to have rather extensive axonal projections, rather than the local, confined axonal structures previously suggested. In some cases, such interneurons may provide a very strong synchronization or pacer activity to large groups of neurons.

B. Basic Neurophysiology and Neurochemistry Governing Excitability

Given that the basic mechanism of neuronal excitability is the action potential, a hyperexcitable state can result from increased excitatory synaptic neurotransmission, decreased inhibitory neurotransmission, an alteration in voltage-gated ion channels, or an alteration of intra- or extra-cellular ion concentrations in favor of membrane depolarization. A hyperexcitable state can also result when several synchronous subthreshold excitatory stimuli occur, allowing their temporal summation in the post synaptic neurons.

Action potentials occur due to depolarization of the neuronal membrane, with membrane depolarization propagating down the axon to induce neurotransmitter release at the axon terminal. The action potential occurs in an all-or-none fashion as a result of local changes in membrane potential brought about by net positive inward ion fluxes. Membrane potential thus varies with activation of ligand-gated channels, whose conductance is affected by binding to neurotransmitters or with activation of voltage-gated channels, whose conductance is affected by changes in transmembrane potential or with changes in intracellular ion compartmentalization.

Neurotransmitters are substances that are released by the presynaptic nerve terminal at a synapse and subsequently bind to specific postsynaptic receptors for that ligand. Ligand binding results in channel activation and passage of ions into or out of the cells. The major neurotransmitters in the brain are glutamate, gamma-amino-butyric acid (GABA), acetylcholine (ACh), norepinephrine, dopamine, serotonin, and histamine. Other molecules, such as neuropeptides and hormones, play modulatory roles that modify neurotransmission over longer time periods.

The major excitatory neurotransmitter is the amino acid glutamate. There are several subtypes of glutamate receptors. Glutamate receptors can be found postsynaptically on excitatory principal cells as well as on inhibitory interneurons, and have been demonstrated on certain types of glial cells. The ionotropic subclasses are the alpha-amino-2,3-dihydro-5-methyl-3-oxo-4-isoxazolepropanoic acid (AMPA), kainate receptors, and N-methyl-D-aspartate (NMDA) these allow ion influx upon activation by glutamate (Appendix A, Table 1). They are differentiated from one another by cation permeability as well as differential sensitivity to pharmacological agonists/antagonists. All ionotropic glutamate receptors are permeable to Na + and K + , and it is the influx of Na + and outflow of K + through these channels that contribute to membrane depolarization and generation of the action potential. The NMDA receptor also has a Ca ++ channel that is blocked by Mg ++ ions in the resting state, but under conditions of local membrane depolarization, Mg ++ is displaced and the channel becomes permeable to Ca ++ influx of Ca ++ tends to further depolarize the cell, and is thought also to contribute to Ca ++ mediated neuronal injury under conditions of excessive neuronal activation (such as status epilepticus and ischemia), potentially leading to cell death, a process termed excitotoxicity. The other major type of glutamate receptor is the metabotropic receptor, which functions by means of receptor-activated signal transduction involving membrane-associated G-proteins (Appendix A, Table 2). There are at least 3 subtypes of metabotropic receptors, based on differential agonist potency, mechanism of signal transduction, and pre- versus post-synaptic localization. (Slides 5 & 6)

Slide 5

Slide 6

Experimental studies using animal epilepsy models have shown that NMDA, AMPA and kainate agonists induce seizure activity, whereas their antagonists suppress seizure activity. Metabotropic agonists appear to have variable effects likely dependent upon their different location and mechanisms of signal transduction.

The major inhibitory neurotransmitter, GABA, interacts with 2 major subtypes of receptor: GABAA and GABAB receptors. GABAA receptors are found postsynaptically, while GABAB receptors are found presynaptically, and can thereby modulate synaptic release. In the adult brain, GABAA receptors are permeable to Cl − ions upon activation Cl − influx hyperpolarizes the membrane and inhibits action potentials. Therefore, substances which are GABAA receptor agonists, such as barbiturates and benzodiazepines, are well known to suppress seizure activity. GABAB receptors are associated with second messenger systems rather than Cl − channels, and lead to attenuation of transmitter release due to their presynaptic location. The second messenger systems often result in opening of K + channels, leading to a hyperpolarizing current. Certain GABAB agonists, such as baclofen, have been reported to exacerbate hyperexcitability and seizures. (Slides 7 & 8)

Slide 7

Slide 8

Relevant to epilepsy, glutamate and GABA both require active reuptake to be cleared from the synaptic cleft. Transporters for both glutamate and GABA exist on both neurons and glia (primarily astrocytes). Interference with transporter function has also been shown to activate or suppress epileptiform activity in animal models, depending on which transporter is being blocked.

C. Factors Governing Excitability of Individual Neurons

The complexity of neuronal activity is partly due to various mechanisms controlling the level of electrical activation in one or more cellular regions. These mechanisms may act inside the neuron or in the cellular environment, including other cells (e.g., neighboring neurons, glia, and vascular endothelial cells) as well as the extracellular space, to modify neuronal excitability. The former may be termed "neuronal" or "intrinsic," and the latter "extra-neuronal" or "extrinsic." (Slide 9)

Slide 9

Cellular Mechanisms of Seizure Generation

1. Examples of neuronal (intrinsic) factors include:

Slide 10

Neuronal (Intrinsic) Factors Modifying Neuronal Excitability

2. Examples of extra-neuronal (extrinsic) factors include:

Slide 11

Extra-Neuronal (Extrinsic) Factors Modifying Neuronal Excitability

D. How Network Organization Influences Neuronal Excitability

Neurons are connected together in elaborate arrays that provide additional levels of control of neuronal excitability. An example of a very basic neuronal network is the well-studied dentate gyrus and hippocampus, as shown in Slide 12. In the dentate gyrus, afferent connections to the network can directly activate the projection cell (e.g., granule cells). The input can also directly activate local interneurons (bipolar and basket cells), and these may inhibit projection cells in the vicinity (feed-forward inhibition). Also, the projection neuron may in turn activate the interneurons which in turn act on the projection neurons (feedback inhibition). Thus, changes in the function of one or more cells within a circuit can significantly affect both neighboring and distant neurons. (Slide 13). For example, sprouting of excitatory axons to make more numerous connections can increase excitability of the network of connected neurons. Alternatively, loss of inhibitory neurons will also increase the excitability of the network. Inhibitory function can also be reduced by a loss of excitatory neurons that activate or "drive" the inhibitory neurons.

Slide 12

Mechanisms of Generating Hyperexcitable Networks

Slide 13


RNA scientists identify many genes involved in neuron development

Neurons in the fruit fly brain are made by passing through various differentiation states, and are segregated into unique subtypes based on the age and cell division number of their mother cell (progenitor). The complexity of this process is modelled in the diagram above. Different RNAs play a role in these neuron formation steps. Credit: Nigel Michki

Neurons result from a highly complex and unique series of cell divisions. For example, in fruit flies, the process starts with stem cells that divide into mother cells (progenitor cells), that then divide into precursor cells that eventually become neurons.

A team of the University of Michigan (U-M), spearheaded by Nigel Michki, a graduate student, and Assistant Professor Dawen Cai in the departments of Biophysics (LS&A) and Cell and Developmental Biology at the Medical School, identified many genes that are important in fruit flies' neuron development, and that had never been described before in that context.

Since many genes are conserved across species such as between fruit flies (Drosophila), mice, and humans, what is learnt in flies can also serve as a model to better understand other species, including humans. "Now that we know which genes are involved in this form of neurogenesis in flies, we can look for them in other species and test for them. We work on a multitude of organisms at U-M and we've the potential to interrogate across organisms," explains Michki. "In my opinion, the work we did is one of the many pieces that will inform other work that will inform disease," adds Michki. "This is why we do foundational research like this one."

Flies are also commonly used in many different types of research that might benefit from having a more comprehensive list of the fly genes with their associated roles in neuron cell development.

Neurons are made from stem cells that massively multiply before becoming neurons. In the human brain, the process is extremely complex, involving billions of cells. In the fly brain, the process is much simpler, with around 200 stem cells for the entire brain. The smaller scale allows for a fine analysis of the neuronal cell division process from start to finish.

In flies, when the stem cell divides, it yields another stem cell and a progenitor cell. When this last one divides, it makes a so-called precursor cell that divides only once and gives rise to two neurons. Genes control this production process by telling the cells either to divide —and which particular type of cell to produce— or to stop dividing.

A microscope image of one of the developing fruit fly brain lobes, stained for our cells of interest (white), and 4 different RNAs: mamo (yellow), bi (magenta), data (green), and a long non-coding RNA, cherub (cyan). Credit: Nigel Michki

To this day, only a few of the genes that control this neuron development process have been identified and in this publication in Cell Reports, the scientists have characterized many more genes involved. Along the timeline of the neuron development process, the U-M team could precisely record which genes were involved and for how long.

In particular, at the progenitors' stage, the scientists identified three genes that are important at this stage for defining what 'kind' of neuron each progenitor will make these particular genes had never been described before in this context. They also validated previously known marker genes that are known to regulate the cell reproduction process.

When they applied their analysis technique to the other phases of the neuron development process, they also recorded the expression of additional genes. However, it is still unknown why these genes go up in expression at different steps of the neuron development process and what role they actually play in these different steps. "Now that many candidate genes are identified, we are investigating the roles they play in the neuron maturation and fate determination process," says Cai. "We are also excited to explore other developmental timepoints to illustrate the dynamic changes of the molecular landscape in the fly brain."

"This work provides rich information on how to program stem cell progeny into distinct neuron types as well as how to trans-differentiate non-neuronal cell types into neurons. These findings will have significant impact on the understanding of the normal brain development as well as on neuron regeneration medicine," adds Cheng-Yu Lee, a Professor from the U-M Life Sciences Institute who collaborated with the Cai Lab.

This study is mostly based on high-throughput single-cell RNA-sequencing techniques. The scientists took single cells from fruit flies' brains and sequenced the RNA, generating hundreds of gigabytes of data in only one day. From the RNA sequences, they could determine the developmental stage of each neuron. "We now have a very good understanding of how this process goes at the RNA level," says Michki.

The team also used traditional microscope observations to localize where these different RNAs are being expressed in the brain. "Combining in silico analysis and in situ exploration not only validates the quality of our sequencing results, but also restores the spatial and temporal relationship of the candidate genes, which is lost in the single cell dissociation process," says Cai.

At the beginning of their study, the scientists analyzed the large data set with open-source software. Later, they developed a portal (MiCV) that eases the use of existing computer services and allows to test for repeatability. This portal can be utilized for cell and gene data analysis from a variety of organs and does not require computer programming experience. "Tools like MiCV can be very powerful for researchers who are doing this type of research for the first time and who want to quickly generate new hypotheses from their data," says Michki. "It saves a lot of time for data analysis, as well as expenses on consultant fees. The ultimate goal is to allow scientists to focus more on their research rather than on sometimes daunting data analysis tools." The MiCV tool is currently being commercialized.


Mind, Brain, and Education

Professor Kaufer opened with a quotation: “All animals learn, very few teach” (Blakemore and Frith, The Learning Brain). She pointed out that, although the educational process involves both learning and teaching, neuroscience research usually focuses only on learning, as teaching is less common in animal models and difficult to study using neuroscience methodology. There is, however, a developing subfield within neuroscience called “Mind, Brain and Education” (MBE) that attempts to link research with teaching. MBE researchers consider how to take advantage of the natural human attention span, how to use studies about memory systems to inform lesson planning, and how to use research on the role of emotions in learning.

Research on Stress and Learning

In regard to this last point, the role of the emotions in learning, Kaufer described the “affective filter hypothesis,” the idea that how we feel influences how we are able to learn. Emotional states, particularly stress, influence learning, memory, and decision making. Neurobiologically, stress indicates activation of the amygdala, the segment of the brain connected with emotions and fear. The amygdala sends information to the hippocampus, the brain region associated with learning and memory as a result, we learn and remember differently when the amygdala is firing. The stress response — popularly known as the “fight or flight” response — is chemically understood as the production of a variety of hormones, most significantly cortisol. In brief moments of stress such as emergencies (Kaufer gave the classic example of seeing a poisonous snake), the adrenal gland releases cortisol into the brain, which helps us to combat or avoid the situation. However, when people experience chronic stress, the amygdala is constantly activated, and stress becomes an event in itself, rather than a response to a stimulus. Because the stress response has a negative impact on decision making, and decision making is a key component of learning, chronic stress decreases our ability to learn.

Cellular Biology of Learning: Neuroplasticity and Neurogenesis

Kaufer went on to describe several of the biological aspects of learning, including neuroplasticity and neurogenesis. Plasticity, the capacity of the brain to change and develop, is both synaptic and dendritic. That is, changes may occur regarding the connections between neurons (synapses) or in the neurons themselves (dendrites) — or, to put it simply, we can both reorganize our knowledge and change the quality and nature of the knowledge itself. In addition, new discoveries with regard to neurogenesis — the ability of the brain to generate new neurons — suggest that some areas of the brain, including the hippocampus, can birth new cells throughout a person’s lifetime. (This reverses an earlier hypothesis that neurogenesis ends after a certain age, that by adulthood we have all the brain cells we will ever possess and that they slowly die off.) In animal models, Kaufer explained, there are very specific aspects of learning that are dependent on neurogenesis, such as spatial learning and emotional memory. Newly generated neurons are recruited into existing networks, strengthening or developing preexisting connections in the brain.

Behaviors and conditions that influence plasticity and neurogenesis include sleep, nutrition, exercise, stress (cortisol levels), and happiness (dopamine levels). Kaufer explained that these exist in dynamic relation to one another. For example, voluntary exercise can counter the effects of stress. Kaufer also explained that the relationship between stress and cognition is a “classic inverted U-curve.”

That is, high levels of stress tend to correlate with low performance — but low levels of stress also correlate with low performance. A moderate amount of stress results in the highest performance. What constitutes a “moderate amount,” however, varies greatly between individuals.

Neurobiology and Active Learning

The value distinction between “active learning” and “passive learning,” long used in educational research and philosophy, also seems to have a neurobiological basis. Kaufer described a recently published study, “Hippocampal Brain-Network Coordination During Volitional Exploratory Behavior Enhances Learning” (Voss et al., Nature Neuroscience 14 (2011), 115-120), which concludes:

Our data support the notion that volitional control is an omnipresent determinant of exploratory behaviors that occurs whenever an organism is unconstrained in interactions with the environment.

Professor Kaufer translated and elaborated this conclusion for the non-specialist audience:

There is recruitment of multiple cortical areas (and cross talk with the hippocampus) that produces optimized learning with active learning process. Active learning (volitional control) is advantageous for learning because distinct neural systems related to executive functions (planning or predicting, attention and object processing) are dynamically activated and communicate with the hippocampus, to enhance its performance.

In addition to helping us understand why active learning is effective, neuroscience research seems to support the efficacy of tools like Bloom’s taxonomy (see diagram below), which describes cognitive tasks in ascending orders of complexity.

Kaufer explained some of her own techniques for increasing active learning in the classroom, especially the large lecture classroom in which small-group discussion may not be a viable option. She is a proponent of using polling technology such as the i-clicker, a tool that allows instructors to receive real-time feedback from students on questions posed during a lecture. She uses the i-clicker in a variety of ways in her own classroom: giving short quizzes on reading material asking a “reality check” question to make sure students are following and have grasped key information allowing students to self-evaluate and learn from their peers as they see how others answer doing in-class problem solving and as a lead-in to a class activity. She also uses other techniques, such as asking students to break into discussion pairs, and prefacing class with music, which sets the tone for students and simultaneously relaxes and stimulates them.

Learning Styles and Neural Pathways

Appealing to different learning styles is also a technique that seems to be supported by the latest neurobiological research, though not in the way that is popularly understood. Kaufer described a study entitled “Influencing Brain Networks: Implications for Education” (Posner and Rothbart, Trends in Cognitive Sciences 9.3 [March 2005], 99–103), which suggested that, although there is strong evidence of brain networks common to all human beings, there are also individual differences due to genes and experiences. The article also suggested that learning seemed to be most effective when learners were “tagging” new information to old knowledge, suggesting that prior knowledge and preconceptions are particularly important for teaching and learning.

Another article on learning styles, “The Neural Correlates of Visual and Verbal Cognitive Styles” (Kraemer et al., Journal of Neuroscience 29.12 (March 25, 2009, 3792–3798), showed that individuals who identified themselves as visual or verbal learners tended to show activation of different neural pathways while performing learning tasks. In addition, researchers observed a “translation” effect: self-characterized “verbal” learners tended to show activation of verbal-related areas of the brain when performing visual tasks, and self-characterized “visual” learners tended to show activation of visual-related areas when performing verbal tasks. This suggests that appealing to multiple learning styles is useful not in order to cater to each student’s primary mode of learning, as is often assumed, but because cross-connections are created when people perform tasks in a manner different from their “preferred” cognitive style. It’s the variety of brain regions recruited through multiple neural pathways that makes learning most effective for all learners.

Applications to Teaching

Professor Kaufer concluded by reiterating some of the ways she implements these principles in the classroom, including the i-clickers, multiple ways of presenting an important point, taking a break in a long class, encouraging a variety of forms of class participation, using music, presenting questions in a context that is personally relevant to the student (for example, phrasing questions in the second person), and encouraging students to be physically active (for example, using qigong movements during a class break).


Supplementary data

We wish to thank Xavier de Giovanni, Alain Demoya, Joël Baurberg for their valuable technical assistance, Mourad Mekaouche, Ivan Balansard, Sébastien Barniaud, Anne Duhoux and Ahmed Zellat for animal care and surgery. We also extend our sincere appreciation to Jean-François Lebas for MRI scanning, Abdelouahed Belmalih, Martine Meunier, David Thura, Amine Bentliba and Elisabetta Monfardini for help in the early phase of the study. We are very grateful to Viktor Jirsa and Andrea Brovelli for their comments on an earlier version of the article and to the anonymous reviewers for their critical and constructive reading of our article.


Mature, differentiated neurons do not divide (undergo mitosis), but apparently there is a small population of self-renewing neural stem cells in adults that can produce new neurons. Neurogenesis predominantly occurs in the subventricular and subgranular zones of the brain.

Peripheral nerves can regenerate along its axon as long as the endoneurial tube and the Schwann cells are intact. Here's a picture of a neuron regenerating.

As was pointed out by @jello differentiated neurons do not divide, instead new neurons are recruited into existing networks from undifferentiated cells. This process is called neurogenesis. A high level summary of adult neurogenesis:


Supplementary data

We wish to thank Xavier de Giovanni, Alain Demoya, Joël Baurberg for their valuable technical assistance, Mourad Mekaouche, Ivan Balansard, Sébastien Barniaud, Anne Duhoux and Ahmed Zellat for animal care and surgery. We also extend our sincere appreciation to Jean-François Lebas for MRI scanning, Abdelouahed Belmalih, Martine Meunier, David Thura, Amine Bentliba and Elisabetta Monfardini for help in the early phase of the study. We are very grateful to Viktor Jirsa and Andrea Brovelli for their comments on an earlier version of the article and to the anonymous reviewers for their critical and constructive reading of our article.


II. Neurophysiology of the Cerebral Cortex

A. Basic Anatomy of Cortex

The human cerebral cortex consists of 3 to 6 layers of neurons. The phylogenetically oldest part of the cortex (archipallium) has 3 distinct neuronal layers, and is exemplified by the hippocampus, which is found in the medial temporal lobe. The majority of the cortex (neocortex or neopallium) has 6 distinct cell layers and covers most of the surface of the cerebral hemispheres. A particularly important cortical structure in the pathophysiology of one of the more common epilepsy syndromes is the hippocampus. This structure illustrated in Slide 3 is common in temporal lobe epilepsy. As seen in the slide, the hippocampus consists of three major regions: subiculum, hippocampus proper (Ammon's horn) and dentate gyrus. The hippocampus and dentate gyrus have a three layered cortex. The subiculum is the transition zone from the three to the six layered cortex. Important regions of the hippocampus proper include CA1, CA 2, CA3.

Slide 3

Basic Mechanisms Underlying Seizures and Epilepsy

The cortex includes two general classes of neurons. The projection, or principal, neurons (e.g., pyramidal neurons) are cells that "project" or send information to neurons located in distant areas of the brain. Interneurons (e.g., basket cells) are generally considered to be local-circuit cells which influence the activity of nearby neurons. Most principal neurons form excitatory synapses on post-synaptic neurons, while most interneurons form inhibitory synapses on principal cells or other inhibitory neurons. Recurrent inhibition can occur when a principal neuron forms synapses on an inhibitory neuron, which in turn forms synapses back on the principal cells to achieve a negative feedback loop. (Slide 4 illustrates an example of a type of interneuron-granule cell and its role in a negative feedback loop in the hippocampus.)

Slide 4

Basic Mechanisms Underlying Seizures and Epilepsy

Recent work suggests that some interneurons appear to have rather extensive axonal projections, rather than the local, confined axonal structures previously suggested. In some cases, such interneurons may provide a very strong synchronization or pacer activity to large groups of neurons.

B. Basic Neurophysiology and Neurochemistry Governing Excitability

Given that the basic mechanism of neuronal excitability is the action potential, a hyperexcitable state can result from increased excitatory synaptic neurotransmission, decreased inhibitory neurotransmission, an alteration in voltage-gated ion channels, or an alteration of intra- or extra-cellular ion concentrations in favor of membrane depolarization. A hyperexcitable state can also result when several synchronous subthreshold excitatory stimuli occur, allowing their temporal summation in the post synaptic neurons.

Action potentials occur due to depolarization of the neuronal membrane, with membrane depolarization propagating down the axon to induce neurotransmitter release at the axon terminal. The action potential occurs in an all-or-none fashion as a result of local changes in membrane potential brought about by net positive inward ion fluxes. Membrane potential thus varies with activation of ligand-gated channels, whose conductance is affected by binding to neurotransmitters or with activation of voltage-gated channels, whose conductance is affected by changes in transmembrane potential or with changes in intracellular ion compartmentalization.

Neurotransmitters are substances that are released by the presynaptic nerve terminal at a synapse and subsequently bind to specific postsynaptic receptors for that ligand. Ligand binding results in channel activation and passage of ions into or out of the cells. The major neurotransmitters in the brain are glutamate, gamma-amino-butyric acid (GABA), acetylcholine (ACh), norepinephrine, dopamine, serotonin, and histamine. Other molecules, such as neuropeptides and hormones, play modulatory roles that modify neurotransmission over longer time periods.

The major excitatory neurotransmitter is the amino acid glutamate. There are several subtypes of glutamate receptors. Glutamate receptors can be found postsynaptically on excitatory principal cells as well as on inhibitory interneurons, and have been demonstrated on certain types of glial cells. The ionotropic subclasses are the alpha-amino-2,3-dihydro-5-methyl-3-oxo-4-isoxazolepropanoic acid (AMPA), kainate receptors, and N-methyl-D-aspartate (NMDA) these allow ion influx upon activation by glutamate (Appendix A, Table 1). They are differentiated from one another by cation permeability as well as differential sensitivity to pharmacological agonists/antagonists. All ionotropic glutamate receptors are permeable to Na + and K + , and it is the influx of Na + and outflow of K + through these channels that contribute to membrane depolarization and generation of the action potential. The NMDA receptor also has a Ca ++ channel that is blocked by Mg ++ ions in the resting state, but under conditions of local membrane depolarization, Mg ++ is displaced and the channel becomes permeable to Ca ++ influx of Ca ++ tends to further depolarize the cell, and is thought also to contribute to Ca ++ mediated neuronal injury under conditions of excessive neuronal activation (such as status epilepticus and ischemia), potentially leading to cell death, a process termed excitotoxicity. The other major type of glutamate receptor is the metabotropic receptor, which functions by means of receptor-activated signal transduction involving membrane-associated G-proteins (Appendix A, Table 2). There are at least 3 subtypes of metabotropic receptors, based on differential agonist potency, mechanism of signal transduction, and pre- versus post-synaptic localization. (Slides 5 & 6)

Slide 5

Slide 6

Experimental studies using animal epilepsy models have shown that NMDA, AMPA and kainate agonists induce seizure activity, whereas their antagonists suppress seizure activity. Metabotropic agonists appear to have variable effects likely dependent upon their different location and mechanisms of signal transduction.

The major inhibitory neurotransmitter, GABA, interacts with 2 major subtypes of receptor: GABAA and GABAB receptors. GABAA receptors are found postsynaptically, while GABAB receptors are found presynaptically, and can thereby modulate synaptic release. In the adult brain, GABAA receptors are permeable to Cl − ions upon activation Cl − influx hyperpolarizes the membrane and inhibits action potentials. Therefore, substances which are GABAA receptor agonists, such as barbiturates and benzodiazepines, are well known to suppress seizure activity. GABAB receptors are associated with second messenger systems rather than Cl − channels, and lead to attenuation of transmitter release due to their presynaptic location. The second messenger systems often result in opening of K + channels, leading to a hyperpolarizing current. Certain GABAB agonists, such as baclofen, have been reported to exacerbate hyperexcitability and seizures. (Slides 7 & 8)

Slide 7

Slide 8

Relevant to epilepsy, glutamate and GABA both require active reuptake to be cleared from the synaptic cleft. Transporters for both glutamate and GABA exist on both neurons and glia (primarily astrocytes). Interference with transporter function has also been shown to activate or suppress epileptiform activity in animal models, depending on which transporter is being blocked.

C. Factors Governing Excitability of Individual Neurons

The complexity of neuronal activity is partly due to various mechanisms controlling the level of electrical activation in one or more cellular regions. These mechanisms may act inside the neuron or in the cellular environment, including other cells (e.g., neighboring neurons, glia, and vascular endothelial cells) as well as the extracellular space, to modify neuronal excitability. The former may be termed "neuronal" or "intrinsic," and the latter "extra-neuronal" or "extrinsic." (Slide 9)

Slide 9

Cellular Mechanisms of Seizure Generation

1. Examples of neuronal (intrinsic) factors include:

Slide 10

Neuronal (Intrinsic) Factors Modifying Neuronal Excitability

2. Examples of extra-neuronal (extrinsic) factors include:

Slide 11

Extra-Neuronal (Extrinsic) Factors Modifying Neuronal Excitability

D. How Network Organization Influences Neuronal Excitability

Neurons are connected together in elaborate arrays that provide additional levels of control of neuronal excitability. An example of a very basic neuronal network is the well-studied dentate gyrus and hippocampus, as shown in Slide 12. In the dentate gyrus, afferent connections to the network can directly activate the projection cell (e.g., granule cells). The input can also directly activate local interneurons (bipolar and basket cells), and these may inhibit projection cells in the vicinity (feed-forward inhibition). Also, the projection neuron may in turn activate the interneurons which in turn act on the projection neurons (feedback inhibition). Thus, changes in the function of one or more cells within a circuit can significantly affect both neighboring and distant neurons. (Slide 13). For example, sprouting of excitatory axons to make more numerous connections can increase excitability of the network of connected neurons. Alternatively, loss of inhibitory neurons will also increase the excitability of the network. Inhibitory function can also be reduced by a loss of excitatory neurons that activate or "drive" the inhibitory neurons.

Slide 12

Mechanisms of Generating Hyperexcitable Networks

Slide 13


Compensatory masquerade

The second type of neuroplasticity, compensatory masquerade, can simply be described as the brain figuring out an alternative strategy for carrying out a task when the initial strategy cannot be followed due to impairment. One example is when a person attempts to navigate from one location to another. Most people, to a greater or lesser extent, have an intuitive sense of direction and distance that they employ for navigation. However, a person who suffers some form of brain trauma and impaired spatial sense will resort to another strategy for spatial navigation, such as memorizing landmarks. The only change that occurs in the brain is a reorganization of preexisting neuronal networks.


Mind, Brain, and Education

Professor Kaufer opened with a quotation: “All animals learn, very few teach” (Blakemore and Frith, The Learning Brain). She pointed out that, although the educational process involves both learning and teaching, neuroscience research usually focuses only on learning, as teaching is less common in animal models and difficult to study using neuroscience methodology. There is, however, a developing subfield within neuroscience called “Mind, Brain and Education” (MBE) that attempts to link research with teaching. MBE researchers consider how to take advantage of the natural human attention span, how to use studies about memory systems to inform lesson planning, and how to use research on the role of emotions in learning.

Research on Stress and Learning

In regard to this last point, the role of the emotions in learning, Kaufer described the “affective filter hypothesis,” the idea that how we feel influences how we are able to learn. Emotional states, particularly stress, influence learning, memory, and decision making. Neurobiologically, stress indicates activation of the amygdala, the segment of the brain connected with emotions and fear. The amygdala sends information to the hippocampus, the brain region associated with learning and memory as a result, we learn and remember differently when the amygdala is firing. The stress response — popularly known as the “fight or flight” response — is chemically understood as the production of a variety of hormones, most significantly cortisol. In brief moments of stress such as emergencies (Kaufer gave the classic example of seeing a poisonous snake), the adrenal gland releases cortisol into the brain, which helps us to combat or avoid the situation. However, when people experience chronic stress, the amygdala is constantly activated, and stress becomes an event in itself, rather than a response to a stimulus. Because the stress response has a negative impact on decision making, and decision making is a key component of learning, chronic stress decreases our ability to learn.

Cellular Biology of Learning: Neuroplasticity and Neurogenesis

Kaufer went on to describe several of the biological aspects of learning, including neuroplasticity and neurogenesis. Plasticity, the capacity of the brain to change and develop, is both synaptic and dendritic. That is, changes may occur regarding the connections between neurons (synapses) or in the neurons themselves (dendrites) — or, to put it simply, we can both reorganize our knowledge and change the quality and nature of the knowledge itself. In addition, new discoveries with regard to neurogenesis — the ability of the brain to generate new neurons — suggest that some areas of the brain, including the hippocampus, can birth new cells throughout a person’s lifetime. (This reverses an earlier hypothesis that neurogenesis ends after a certain age, that by adulthood we have all the brain cells we will ever possess and that they slowly die off.) In animal models, Kaufer explained, there are very specific aspects of learning that are dependent on neurogenesis, such as spatial learning and emotional memory. Newly generated neurons are recruited into existing networks, strengthening or developing preexisting connections in the brain.

Behaviors and conditions that influence plasticity and neurogenesis include sleep, nutrition, exercise, stress (cortisol levels), and happiness (dopamine levels). Kaufer explained that these exist in dynamic relation to one another. For example, voluntary exercise can counter the effects of stress. Kaufer also explained that the relationship between stress and cognition is a “classic inverted U-curve.”

That is, high levels of stress tend to correlate with low performance — but low levels of stress also correlate with low performance. A moderate amount of stress results in the highest performance. What constitutes a “moderate amount,” however, varies greatly between individuals.

Neurobiology and Active Learning

The value distinction between “active learning” and “passive learning,” long used in educational research and philosophy, also seems to have a neurobiological basis. Kaufer described a recently published study, “Hippocampal Brain-Network Coordination During Volitional Exploratory Behavior Enhances Learning” (Voss et al., Nature Neuroscience 14 (2011), 115-120), which concludes:

Our data support the notion that volitional control is an omnipresent determinant of exploratory behaviors that occurs whenever an organism is unconstrained in interactions with the environment.

Professor Kaufer translated and elaborated this conclusion for the non-specialist audience:

There is recruitment of multiple cortical areas (and cross talk with the hippocampus) that produces optimized learning with active learning process. Active learning (volitional control) is advantageous for learning because distinct neural systems related to executive functions (planning or predicting, attention and object processing) are dynamically activated and communicate with the hippocampus, to enhance its performance.

In addition to helping us understand why active learning is effective, neuroscience research seems to support the efficacy of tools like Bloom’s taxonomy (see diagram below), which describes cognitive tasks in ascending orders of complexity.

Kaufer explained some of her own techniques for increasing active learning in the classroom, especially the large lecture classroom in which small-group discussion may not be a viable option. She is a proponent of using polling technology such as the i-clicker, a tool that allows instructors to receive real-time feedback from students on questions posed during a lecture. She uses the i-clicker in a variety of ways in her own classroom: giving short quizzes on reading material asking a “reality check” question to make sure students are following and have grasped key information allowing students to self-evaluate and learn from their peers as they see how others answer doing in-class problem solving and as a lead-in to a class activity. She also uses other techniques, such as asking students to break into discussion pairs, and prefacing class with music, which sets the tone for students and simultaneously relaxes and stimulates them.

Learning Styles and Neural Pathways

Appealing to different learning styles is also a technique that seems to be supported by the latest neurobiological research, though not in the way that is popularly understood. Kaufer described a study entitled “Influencing Brain Networks: Implications for Education” (Posner and Rothbart, Trends in Cognitive Sciences 9.3 [March 2005], 99–103), which suggested that, although there is strong evidence of brain networks common to all human beings, there are also individual differences due to genes and experiences. The article also suggested that learning seemed to be most effective when learners were “tagging” new information to old knowledge, suggesting that prior knowledge and preconceptions are particularly important for teaching and learning.

Another article on learning styles, “The Neural Correlates of Visual and Verbal Cognitive Styles” (Kraemer et al., Journal of Neuroscience 29.12 (March 25, 2009, 3792–3798), showed that individuals who identified themselves as visual or verbal learners tended to show activation of different neural pathways while performing learning tasks. In addition, researchers observed a “translation” effect: self-characterized “verbal” learners tended to show activation of verbal-related areas of the brain when performing visual tasks, and self-characterized “visual” learners tended to show activation of visual-related areas when performing verbal tasks. This suggests that appealing to multiple learning styles is useful not in order to cater to each student’s primary mode of learning, as is often assumed, but because cross-connections are created when people perform tasks in a manner different from their “preferred” cognitive style. It’s the variety of brain regions recruited through multiple neural pathways that makes learning most effective for all learners.

Applications to Teaching

Professor Kaufer concluded by reiterating some of the ways she implements these principles in the classroom, including the i-clickers, multiple ways of presenting an important point, taking a break in a long class, encouraging a variety of forms of class participation, using music, presenting questions in a context that is personally relevant to the student (for example, phrasing questions in the second person), and encouraging students to be physically active (for example, using qigong movements during a class break).


RNA scientists identify many genes involved in neuron development

Neurons in the fruit fly brain are made by passing through various differentiation states, and are segregated into unique subtypes based on the age and cell division number of their mother cell (progenitor). The complexity of this process is modelled in the diagram above. Different RNAs play a role in these neuron formation steps. Credit: Nigel Michki

Neurons result from a highly complex and unique series of cell divisions. For example, in fruit flies, the process starts with stem cells that divide into mother cells (progenitor cells), that then divide into precursor cells that eventually become neurons.

A team of the University of Michigan (U-M), spearheaded by Nigel Michki, a graduate student, and Assistant Professor Dawen Cai in the departments of Biophysics (LS&A) and Cell and Developmental Biology at the Medical School, identified many genes that are important in fruit flies' neuron development, and that had never been described before in that context.

Since many genes are conserved across species such as between fruit flies (Drosophila), mice, and humans, what is learnt in flies can also serve as a model to better understand other species, including humans. "Now that we know which genes are involved in this form of neurogenesis in flies, we can look for them in other species and test for them. We work on a multitude of organisms at U-M and we've the potential to interrogate across organisms," explains Michki. "In my opinion, the work we did is one of the many pieces that will inform other work that will inform disease," adds Michki. "This is why we do foundational research like this one."

Flies are also commonly used in many different types of research that might benefit from having a more comprehensive list of the fly genes with their associated roles in neuron cell development.

Neurons are made from stem cells that massively multiply before becoming neurons. In the human brain, the process is extremely complex, involving billions of cells. In the fly brain, the process is much simpler, with around 200 stem cells for the entire brain. The smaller scale allows for a fine analysis of the neuronal cell division process from start to finish.

In flies, when the stem cell divides, it yields another stem cell and a progenitor cell. When this last one divides, it makes a so-called precursor cell that divides only once and gives rise to two neurons. Genes control this production process by telling the cells either to divide —and which particular type of cell to produce— or to stop dividing.

A microscope image of one of the developing fruit fly brain lobes, stained for our cells of interest (white), and 4 different RNAs: mamo (yellow), bi (magenta), data (green), and a long non-coding RNA, cherub (cyan). Credit: Nigel Michki

To this day, only a few of the genes that control this neuron development process have been identified and in this publication in Cell Reports, the scientists have characterized many more genes involved. Along the timeline of the neuron development process, the U-M team could precisely record which genes were involved and for how long.

In particular, at the progenitors' stage, the scientists identified three genes that are important at this stage for defining what 'kind' of neuron each progenitor will make these particular genes had never been described before in this context. They also validated previously known marker genes that are known to regulate the cell reproduction process.

When they applied their analysis technique to the other phases of the neuron development process, they also recorded the expression of additional genes. However, it is still unknown why these genes go up in expression at different steps of the neuron development process and what role they actually play in these different steps. "Now that many candidate genes are identified, we are investigating the roles they play in the neuron maturation and fate determination process," says Cai. "We are also excited to explore other developmental timepoints to illustrate the dynamic changes of the molecular landscape in the fly brain."

"This work provides rich information on how to program stem cell progeny into distinct neuron types as well as how to trans-differentiate non-neuronal cell types into neurons. These findings will have significant impact on the understanding of the normal brain development as well as on neuron regeneration medicine," adds Cheng-Yu Lee, a Professor from the U-M Life Sciences Institute who collaborated with the Cai Lab.

This study is mostly based on high-throughput single-cell RNA-sequencing techniques. The scientists took single cells from fruit flies' brains and sequenced the RNA, generating hundreds of gigabytes of data in only one day. From the RNA sequences, they could determine the developmental stage of each neuron. "We now have a very good understanding of how this process goes at the RNA level," says Michki.

The team also used traditional microscope observations to localize where these different RNAs are being expressed in the brain. "Combining in silico analysis and in situ exploration not only validates the quality of our sequencing results, but also restores the spatial and temporal relationship of the candidate genes, which is lost in the single cell dissociation process," says Cai.

At the beginning of their study, the scientists analyzed the large data set with open-source software. Later, they developed a portal (MiCV) that eases the use of existing computer services and allows to test for repeatability. This portal can be utilized for cell and gene data analysis from a variety of organs and does not require computer programming experience. "Tools like MiCV can be very powerful for researchers who are doing this type of research for the first time and who want to quickly generate new hypotheses from their data," says Michki. "It saves a lot of time for data analysis, as well as expenses on consultant fees. The ultimate goal is to allow scientists to focus more on their research rather than on sometimes daunting data analysis tools." The MiCV tool is currently being commercialized.


The unique plasticity of hippocampal adult-born neurons: Contributing to a heterogeneous dentate

Kylie A. Huckleberry Department of Psychology, Northeastern University, Boston, MA, 02115, USA.

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Kylie A. Huckleberry Department of Psychology, Northeastern University, Boston, MA, 02115, USA.

Behavioral Neuroscience Program, Department of Psychology, Northeastern University, Boston, Massachusetts, USA

Abstract

The dentate gyrus (DG) of the hippocampus is evolutionarily conserved as one of the few sites of adult neurogenesis in mammals. Although there is clear evidence that neurogenesis is necessary for healthy hippocampal function, whether adult-born neurons are simply integrated into existing hippocampal networks to serve a similar purpose to that of developmentally born neurons or whether they represent a discrete cell population with unique functions remains less clear. In this review, we consider evidence for discrete cellular, synaptic, and structural features of adult-born DG neurons, suggesting that neurogenesis contributes to the formation of a heterogeneous DG. We therefore propose that hippocampal neurogenesis creates a specialized neuronal subpopulation that may play a key role in hippocampal functions like episodic memory. We note critical gaps in this extensive body of work, including a general failure to include female animals in relevant research and a need for more precise consideration of intrahippocampal neuroanatomy.


Transplantation of neurons or neurogenic cells

While the above approaches are rather restricted to specific brain regions, the introduction of exogenous neurons can be performed in any injured or diseased brain region. Nevertheless, some pathologies are more suitable for this approach than others, and the choice of cell source is deterministic, as discussed below.

First, focal pathologies with mainly one specific neuron subtype lost, such as the degeneration of substantia nigra pars compacta (A9) dopaminergic neurons in PD or striatal medium spiny neurons in HD are best suited for transplantation strategies given the precise brain regions to target and cell type to replace. Stroke and brain trauma are also spatially restricted, but offer greater challenges for neuronal replacement since various types of neurons die within the affected area and the formation of a glial scar is generally thought to be inhibitory to neurite outgrowth. 101 Yet, it is noteworthy that young transplanted neurons can readily extend axons and seemingly develop well when placed in scar-forming injuries, such as stroke 102 and cortical aspiration. 103 The broad and non-cell-type-specific nature of neuronal degeneration in AD render neuronal replacement strategies challenging for this disease. However, transplantation of young inhibitory interneurons, which are highly migratory, surfaces as an option since the interneuron population is dysfunctional in the AD cerebral cortex. 104 In general, transplantation of migratory cells in multifocal pathologies may benefit from pathotropism, as indeed, homing of NSCs to injury sites relies on a chemoattractant gradient of inflammatory soluble molecules released by the lesioned tissue (reviewed in Martino and Pluchino 19 ).

Second, the choice and manufacturing of the source cells is of pivotal importance and advantageous criteria include availability, expandability, easy differentiation into the desired neuron, and MHC-matching with the host. Pioneering work used cells obtained from fetal tissue (ventral midbrain, VM) that are well specified to generate dopaminergic neuronal subtype. Transplantation of these cells into experimental models of PD demonstrated good graft survival and improved motor function thereby launching the field of cell transplantation for brain repair. 105,106 A series of clinical trials followed in the next two decades, first using autologous adrenal medullary tissue 107 and then fetal VM tissue 108 to restore dopamine in the striatum of PD patients, or using fetal ganglionic eminences aiming at cell replacement in HD patients. 109,110 Fetal tissue grafts showed encouraging results in some PD and HD patients despite variability in the overall patient cohort. 111,112 For instance, some PD patients developed graft-induced dyskinesias and standardized procedures are now being implemented to reach a more controlled outcome. 111 Fetal transplants have not only been beneficial in clinical settings, but also shown a long-term survival and a remarkable level and specificity of circuit integration in the adult injured brain, as discussed next.

Primary fetal neurons

Neurons from fetal sources are superbly specified as they derive from exactly the brain region that generates the neuronal subtype subject to disease. Pioneering studies using ectopic transplantation of fetal midbrain dopaminergic neurons into the striatum of PD animal models or later in patients demonstrated survival and complete maturation into dopaminergic neurons of the correct subtype within the host parenchyma. 111,113 Newly settled dopaminergic neurons secreted dopamine to the denervated striatum and thus improved behavior. Later on, work by Macklis’ lab paved the way exploring the neuronal integration of fetal projection neurons transplanted into homotopic areas of the adult brain after injury. 114,115,116 The team of Gaillard and Jaber published a series of exciting studies that unveiled for the first time how abundantly fetal projection neurons can project through a host parenchyma primed by an injury. 117,118,119 Together these studies brought to light a remarkable capability of fetal projection neurons to overcome growth inhibitors of axonal regeneration in the adult brain and project over long distances towards the correct target areas. Interestingly, the above work also highlighted a role for the areal identity of the donor neurons on dictating their projections. 118 The potential of fetal projection neurons for neuronal replacement therapy received added impetus recently, by demonstration of a close match between the features of the lost neurons and those gradually acquired and tuned in transplanted ones 18 (Fig. 1c, d). This work showed, for the first time, a comprehensive comparison, brain-wide, of both afferents and efferents of fetal neurons transplanted in the primary visual cortex of adult mouse after an injury. It demonstrated a correct and remarkably precise circuit integration that even re-establishes geniculo-cortical topography. Moreover, the new circuits are functional and tuned in a manner resembling visual cortex neurons, as demonstrated by calcium imaging of transplanted neurons in vivo during visual stimulation.

Transplantation of inhibitory interneurons obtained from fetal ganglionic eminences has also proven successful in reversing excitotoxicity in neurological conditions like epilepsy and chronic pain. Cells from the medial ganglionic eminence (MGE) transplanted into different brain regions develop into mature GABAergic neurons that exhibit identical electrophysiological properties to regular somatostatin and parvalbumin neurons, and enhance local synaptic inhibition. 120,121,122 When transplanted into the hippocampus of epileptic mice or into the spinal cord of mice with hypersensitivity after peripheral nerve injury, these cells reduce seizure activity or neuropathic pain, respectively. 123,124,125 Moreover, AD as well as traumatic brain injury is often associated with interneuron dysfunction or loss, and consequent imbalance between excitation and inhibition. In AD, this leads to abnormal network activity in the hippocampal DG and memory deficits. Accordingly, transplantation of MGE cells into the hippocampus in an AD rodent model restores normal learning and memory. 104 MGE cells disperse particularly well from the transplantation site, a feature that may relate with their long migratory routes during development, and which may be deterministic for the success of cell therapy in disorders with widespread neuronal loss as AD. Furthermore, transplantation of fetal interneurons was applied in a few studies in rodents, as a creative strategy to reactivate plasticity at postnatal/adult stages, by reopening critical periods to restore visual perception after early postnatal deprivation 126,127 or to attenuate recurrence of fear memory. 128 Interneurons play a central role sculping neuronal circuits activity and plasticity, and by reopening developmentally transient windows of enhanced plasticity in the adult brain they may also contribute to the success of projection neurons integration mentioned above, where donor cell population includes a minority of interneurons. Along the same lines, interneuron transplantation might promote plasticity of the remaining endogenous neurons and improve rewiring or changes in synaptic strengths in the pursuit of functional compensation, discussed previously.

In summary, fetal neurons have provided most exciting results as donor cell population and have been applied in the clinical setting in PD and HD patients 111,112 (Fig. 1e, right). The achievements made hitherto hold great promise and inspired the raise of the European initiative TRANSEURO, which seeks consistency in the efficacy of fetal cell transplantation in PD patients, and to lift the concern of transplant-induced dyskinesias by careful standardization of criteria for patient selection, cells quality and delivery, and immunosuppressive treatments. 111 The limited availability of fetal neurons, however, hampers fetal neuron-based cell therapies for neurological disorders and hence efforts have been channeled towards the use of expandable cell sources.

ENSCs-derived neurons

As expandable cells sources either multipotent NSCs of embryonic origin may be used (eNSCs), or pluripotent stem cells, discussed next. Both of these cells can be expanded efficiently in vitro, but the main challenge is their differentiation into the disease-relevant neuronal subtype. Early transplantation studies from Evan Snyder and colleagues tested the immortalized C17.2 cell line, originally obtained from neonatal mouse cerebellum. These works showed neuronal and glial differentiation after transplantation, 129 neurite outgrowth, 130 and a protective role towards the host degenerating neurons. 131 Besides, C17.2 cells could be differentiated into dopaminergic neurons with high efficiency by Nurr1 overexpression and astrocyte-derived factors. 132 Concomitantly, the team of Ron McKay isolated and expanded eNSCs from E12 rat VM, using FGF2-mediated neurosphere formation. These cells were subsequently differentiated into dopaminergic neurons by withdrawal of the mitogens, and eventually transplanted in a rat model of PD 133 leading to a substantial improvement in amphetamine-induced rotation scores. An improved protocol of differentiation was proposed later by Arenas and collaborators including additional patterning factors, namely, FGF8, Shh, and Wnt5a. 134,135 Interestingly, McKay’s team also isolated expandable eNSCs from cortex or VM of human fetal brain and could generate dopaminergic neurons from both, but only the VM-derived dopaminergic neurons survived in the striatum of parkinsonian rats. 136 Others also isolated eNSC from human fetal brain tissue, so called human CNS-stem cells 137 (huCNS-SC) using fluorescence-activated cell sorting (FACS) of CD133+/CD34−/CD45− cells. These cells, highly expandable in vitro and multipotent also after transplantation, 138 were generated under GMP conditions (StemCells Inc.) and used as donors for multiple approaches in rodent models of SCI, AD, or hippocampal neuronal loss. 139,140 The research grade huCNS-SC elicited behavioral recovery as assessed in locomotor or cognitive tasks in SCI or AD models, respectively. 139,140 These findings propelled the translation into clinics and huCNS-SC were transplanted in children with the lethal lysosomal storage disorder neuronal ceroid lipofuscinosis (NCL) 141 (Fig. 1e, right). This resulted in favorable safety assessments and was followed by transplantations into thoracic SCI patients (unpublished). The mechanism that leads to the observed improvements, however, remains unclear, and seems at least partially due to a bystander effect. Recently, two studies describe efficacy failure of clinical grade huCNS-SC in rodent models of SCI and AD 142,143 and highlight the importance of testing safety and efficacy for individual clinical grade lots and of performing long-term assessments.

ESCs-derived and iPSCs-derived neurons

Since the isolation of human ESCs (hESCs) 144 great efforts were made to design and improve the generation of specific neuronal subtypes relevant for cell replacement therapy and testing their functional integration into the CNS in animal models of disease. Almost a decade later, human somatic cells were reprogrammed for the first time into iPSCs (hiPSCs) with just a handful of genes, 145 a discovery that set the stage for a new momentum in the brain regeneration field, by offering a scalable and MHC-matched source of neuronal and glial cells from equivalent ground state cells. 13,146 Substantial progress has been made on optimizing the directed differentiation of pluripotent ESCs or iPSCs toward a given neuronal fate by defined culture settings that activate or inhibit master developmental pathways (for review see Steinbeck and Studer 147 ). Alternatively, direct lineage conversion from a somatic cell, like skin fibroblasts, to a neuron of interest (induced neuron, or iN), 14,148,149 or reprogramming of somatic cells into induced neural progenitor cells (iNPC), 150,151,152 which can then be guided toward the desired fate, skip the pluripotent stem cell intermediate and thus carry no risk of tumor formation after transplantation.

Transplantations into the developing rodent brain, an environment that naturally supports neuronal maturation and synaptic integration, demonstrated the therapeutic potential of ESCs-derived and iPSCs-derived neurons. 153,154,155,156,157,158,159,160 These reports showed survival and integration into the developing host circuits by anterograde/retrograde tracing and/or electrophysiological recordings. Notably, ESCs-derived and iPSCs-derived neurons are also able to survive and extend long-range projections to target areas in the adult injured brain 103,161,162 and improve behavior in PD animal models. 163,164 Indeed, VM-patterned hESCs seem to provide functional benefits with similar efficiency to human fetal VM neurons 162 although innervating less target areas of A9 dopaminergic neurons. Recently, the correlation between gene expression profiles of various VM-patterned hESC lines and their outcome after transplantation into a rodent model of PD identified a set of caudal midbrain markers that predict enhanced dopaminergic neuron yield. 165 Moreover, single cell transcriptomics of VM Lmx1a progenitors showed that several markers routinely used for dopaminergic lineage patterning are shared with neuronal lineages from subthalamic nuclei, and propose the application of the unique dopaminergic markers to better tailor the source cells for cell replacement in PD. 166 Altogether, these findings highlight the importance of guiding cells to the very exact neuronal subtype for the best outcome upon transplantation.

Excitingly, optogenetic silencing of grafted hESCs-derived DA neurons proved for the first time a causative link between the graft synaptic transmission and improved behavioral outcome. 17 Also, hESCs-derived GABAergic projection neurons can be generated with great efficiency and integrate into HD-like degenerating circuits improving motor function. 167 Notably, hiPSCs-derived cortical neurons survive in an extremely inhospitable environment as stroke-lesioned parenchyma, 16,168 receive input from correct host brain areas including the thalamus and respond to sensory stimulation. 16 Those hiPSCs-derived grafts also improved sensorimotor function already 2 months after transplantation. 102 At this time point, the input connectome was already established with no further change for the next 4 months, 16 showing a fast formation of afferent connections. On the other hand, most of the grafted cells were still expressing the immature neuronal marker doublecortin raising the question to which extent the behavioral effects were due to circuit integration and/or bystander effects. Indeed, one limitation observed over the years is the rather protracted period of neuronal maturation from human pluripotent stem cells, which constitutes a major bottleneck for their routine and large-scale application in disease modeling or regenerative medicine. This has been facilitated by improved protocols with accelerated neuronal differentiation either using transcription factors 169,170 or small molecules. 160 Alternatively, this obstacle can be overcome by using direct conversion of human fibroblasts into the desired neurons. 14,148,149,171,172,173,174,175

Furthermore, studies to date highlight the need to sort out the remaining pluripotent stem cells to exclude tumor formation upon grafting 176 or improve the differentiation protocols efficiency to avoid those tumorigenic contaminants and other unwanted neural types. On the other hand, extensive expansion in culture is associated with increased genomic and epigenomic instability, 177,178 a hallmark of malignant cells. This concern can be tackled by the use of standardized culture settings that minimize genomic alterations. Additionally, stringent preclinical safety tests must assess both purity of the donor cell population and genomic/epigenomic integrity.

In summary, neurons derived from pluripotent cell sources have reached a stage where they become comparable to those derived from fetal brains. Indeed, preclinical assessments of hESCs or hiPSCs as sources for neuronal replacement therapy are encouraging and motivated the large-scale generation of GMP-qualified cell products for clinical use. At present, phase I/II trials have been initiated in patients with age-related macular degeneration and Stargardt macular dystrophy transplanted with hESCs-derived retinal pigment epithelium (RPE) 179,180 (Fig. 1e, right) and the next years will witness clinical translation also to PD patients (Gforce-PD). 181 In addition, autologous hiPSCs-derived RPE was transplanted in a patient with age-related macular degeneration. 182 This study was suspended due to safety concerns but it is prospected to be resumed using allogeneic MHC-matched hiPSCs.


Vital Cortical Consciousness Regions: The Hindbrain and Posterior Cortical Region

By using functional magnetic resonance imaging (MRI), we are able to observe when the brain is unable to stimulate, when corresponding regions are activated, and when neurons become abnormally active. These differences were used in word stimulation and visual decision task experiments, and it was concluded that activation of the cerebral hemisphere depends on the nature of the task rather than the stimulus itself. Whether activated on the left or the right side, activation of the brain is not in the prefrontal cortex. Rather, activation is observed in the vicinity of the central sulcus and the back of the brain (Stephan et al., 2003). In patients who underwent post-traumatic surgery to remove some of brain regions, the vast majority of patients (98%) remained in a persistent vegetative state after one year if the resected section involved the posterior cortex (Boly et al., 2017). Bianchi’s research also reached a similar conclusion, and believed that lesions in the posterior cortex of the brain may lead to permanent coma (Bianchi and Sims, 2008). Neurological awareness is primarily anatomically located in the posterior cortical thermal region, including the sensory region, rather than the prefrontal network that is involved in task monitoring and reporting (Merker, 2007). Reports of patients that remain conscious after bilateral frontal lobe resection indicate that the prefrontal cortex is not essential for consciousness (Rowland and Mettler, 1949). Other parts of the cerebral hemisphere may be potential candidates for the maintenance of consciousness, including the back part of the brain.


Mature, differentiated neurons do not divide (undergo mitosis), but apparently there is a small population of self-renewing neural stem cells in adults that can produce new neurons. Neurogenesis predominantly occurs in the subventricular and subgranular zones of the brain.

Peripheral nerves can regenerate along its axon as long as the endoneurial tube and the Schwann cells are intact. Here's a picture of a neuron regenerating.

As was pointed out by @jello differentiated neurons do not divide, instead new neurons are recruited into existing networks from undifferentiated cells. This process is called neurogenesis. A high level summary of adult neurogenesis:


Watch the video: Πώς μπορούμε να αναπτύξουμε νέους νευρώνες στον εγκέφαλο. TED (August 2022).