Morphological homeostasis in cortical dendrites

Local Microtubule and F-Actin Distributions Fully Constrain the Spatial Geometry of Drosophila Sensory Dendritic Arbors

Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and straightness. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here, we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from the Drosophila larva encompassing multiple cell classes and genotypes. We observe that branches with a higher microtubule concentration tend to deviate less from the direction of their parent branch across all neuron types. Higher microtubule branches are also overall straighter. F-actin displays a similar effect on angular deviation and branch straightness, but not as consistently across all neuron types as microtubule. These observations raise the question as to whether the associations between cytoskeletal distributions and arbor geometry are sufficient constraints to reproduce type-specific dendritic architecture. Therefore, we create a computational model of dendritic morphology purely constrained by the cytoskeletal composition measured from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.

Reprogramming of adult human dermal fibroblasts to induced dorsal forebrain precursor cells maintains aging signatures

Introduction: With the increase in aging populations around the world, the development of in vitro human cell models to study neurodegenerative disease is crucial. A major limitation in using induced pluripotent stem cell (hiPSC) technology to model diseases of aging is that reprogramming fibroblasts to a pluripotent stem cell state erases age-associated features. The resulting cells show behaviors of an embryonic stage exhibiting longer telomeres, reduced oxidative stress, and mitochondrial rejuvenation, as well as epigenetic modifications, loss of abnormal nuclear morphologies, and age-associated features. Methods: We have developed a protocol utilizing stable, non-immunogenic chemically modified mRNA (cmRNA) to convert adult human dermal fibroblasts (HDFs) to human induced dorsal forebrain precursor (hiDFP) cells, which can subsequently be differentiated into cortical neurons. Analyzing an array of aging biomarkers, we demonstrate for the first time the effect of direct-to-hiDFP reprogramming on cellular age. Results: We confirm direct-to-hiDFP reprogramming does not affect telomere length or the expression of key aging markers. However, while direct-to-hiDFP reprogramming does not affect senescence-associated β-galactosidase activity, it enhances the level of mitochondrial reactive oxygen species and the amount of DNA methylation compared to HDFs. Interestingly, following neuronal differentiation of hiDFPs we observed an increase in cell soma size as well as neurite number, length, and branching with increasing donor age suggesting that neuronal morphology is altered with age. Discussion: We propose direct-to-hiDFP reprogramming provides a strategy for modeling age-associated neurodegenerative diseases allowing the persistence of age-associated signatures not seen in hiPSC-derived cultures, thereby facilitating our understanding of neurodegenerative disease and identification of therapeutic targets.

What programs the size of animal cells?

The human body is programmed with definite quantities, magnitudes, and proportions. At the microscopic level, such definite sizes manifest in individual cells - different cell types are characterized by distinct cell sizes whereas cells of the same type are highly uniform in size. How do cells in a population maintain uniformity in cell size, and how are changes in target size programmed? A convergence of recent and historical studies suggest - just as a thermostat maintains room temperature - the size of proliferating animal cells is similarly maintained by homeostatic mechanisms. In this review, we first summarize old and new literature on the existence of cell size checkpoints, then discuss additional advances in the study of size homeostasis that involve feedback regulation of cellular growth rate. We further discuss recent progress on the molecules that underlie cell size checkpoints and mechanisms that specify target size setpoints. Lastly, we discuss a less-well explored teleological question: why does cell size matter and what is the functional importance of cell size control?

NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity

Neuron shape and connectivity affect function. Modern imaging methods have proven successful at extracting morphological information. One potential path to achieve analysis of this morphology is through graph theory. Encoding by graphs enables the use of high throughput informatic methods to extract and infer brain function. However, the application of graph-theoretic methods to neuronal morphology comes with certain challenges in term of complex subgraph matching and the difficulty in computing intermediate shapes in between two imaged temporal samples. Here we report a novel, efficacious graph-theoretic method that rises to the challenges. The morphology of a neuron, which consists of its overall size, global shape, local branch patterns, and cell-specific biophysical properties, can vary significantly with the cell's identity, location, as well as developmental and physiological state. Various algorithms have been developed to customize shape based statistical and graph related features for quantitative analysis of neuromorphology, followed by the classification of neuron cell types using the features. Unlike the classical feature extraction based methods from imaged or 3D reconstructed neurons, we propose a model based on the rooted path decomposition from the soma to the dendrites of a neuron and extract morphological features from each constituent path. We hypothesize that measuring the distance between two neurons can be realized by minimizing the cost of continuously morphing the set of all rooted paths of one neuron to another. To validate this claim, we first establish the correspondence of paths between two neurons using a modified Munkres algorithm. Next, an elastic deformation framework that employs the square root velocity function is established to perform the continuous morphing, which, as an added benefit, provides an effective visualization tool. We experimentally show the efficacy of NeuroPath2Path, NeuroP2P, over the state of the art.

Diversity of Axonal and Dendritic Contributions to Neuronal Output

Our general understanding of neuronal function is that dendrites receive information that is transmitted to the axon, where action potentials (APs) are initiated and propagated to eventually trigger neurotransmitter release at synaptic terminals. Even though this canonical division of labor is true for a number of neuronal types in the mammalian brain (including neocortical and hippocampal pyramidal neurons or cerebellar Purkinje neurons), many neuronal types do not comply with this classical polarity scheme. In fact, dendrites can be the site of AP initiation and propagation, and even neurotransmitter release. In several interneuron types, all functions are carried out by dendrites as these neurons are devoid of a canonical axon. In this article, we present a few examples of "misbehaving" neurons (with a non-canonical polarity scheme) to highlight the diversity of solutions that are used by mammalian neurons to transmit information. Moreover, we discuss how the contribution of dendrites and axons to neuronal excitability may impose constraints on the morphology of these compartments in specific functional contexts.

Transient Hypoxemia Disrupts Anatomical and Functional Maturation of Preterm Fetal Ovine CA1 Pyramidal Neurons

Children who survive premature birth often exhibit reductions in hippocampal volumes and deficits in working memory. However, it is unclear whether synaptic plasticity and cellular mechanisms of learning and memory can be elicited or disrupted in the preterm fetal hippocampus. CA1 hippocampal neurons were exposed to two common insults to preterm brain: transient hypoxia-ischemia (HI) and hypoxia (Hx). We used a preterm fetal sheep model using both sexes in twin 0.65 gestation fetuses that reproduces the spectrum of injury and abnormal growth in preterm infants. Using Cavalieri measurements, hippocampal volumes were reduced in both Hx and HI fetuses compared with controls. This volume loss was not the result of neuronal cell death. Instead, morphometrics revealed alterations in both basal and apical dendritic arborization that were significantly associated with the level of systemic hypoxemia and metabolic stress regardless of etiology. Anatomical alterations of CA1 neurons were accompanied by reductions in probability of presynaptic glutamate release, long-term synaptic plasticity and intrinsic excitability. The reduction in intrinsic excitability was in part due to increased activity of the channels underlying the fast and slow component of the afterhyperpolarization in Hx and HI. Our studies suggest that even a single brief episode of hypoxemia can markedly disrupt hippocampal maturation. Hypoxemia may contribute to long-term working memory disturbances in preterm survivors by disrupting neuronal maturation with resultant functional disturbances in hippocampal action potential throughput. Strategies directed at limiting the duration or severity of hypoxemia during brain development may mitigate disturbances in hippocampal maturation.SIGNIFICANCE STATEMENT Premature infants commonly sustain hypoxia-ischemia, which results in reduced hippocampal growth and life-long disturbances in learning and memory. We demonstrate that the circuitry related to synaptic plasticity and cellular mechanisms of learning and memory (LTP) are already functional in the fetal hippocampus. Unlike adults, the fetal hippocampus is surprisingly resistant to cell death from hypoxia-ischemia. However, the hippocampus sustains robust structural and functional disturbances in the dendritic maturation of CA1 neurons that are significantly associated with the magnitude of a brief hypoxic stress. Since transient hypoxic episodes occur commonly in preterm survivors, our findings suggest that the learning problems that ensue may be related to the unique susceptibility of the hippocampus to brief episodes of hypoxemia.

Modelling brain-wide neuronal morphology via rooted Cayley trees

Neuronal morphology is an essential element for brain activity and function. We take advantage of current availability of brain-wide neuron digital reconstructions of the Pyramidal cells from a mouse brain, and analyze several emergent features of brain-wide neuronal morphology. We observe that axonal trees are self-affine while dendritic trees are self-similar. We also show that tree size appear to be random, independent of the number of dendrites within single neurons. Moreover, we consider inhomogeneous branching model which stochastically generates rooted 3-Cayley trees for the brain-wide neuron topology. Based on estimated order-dependent branching probability from actual axonal and dendritic trees, our inhomogeneous model quantitatively captures a number of topological features including size and shape of both axons and dendrites. This sheds lights on a universal mechanism behind the topological formation of brain-wide axonal and dendritic trees.

Morphological determinants of dendritic arborization neurons in Drosophila larva

Pairing in vivo imaging and computational modeling of dendritic arborization (da) neurons from the fruit fly larva provides a unique window into neuronal growth and underlying molecular processes. We image, reconstruct, and analyze the morphology of wild-type, RNAi-silenced, and mutant da neurons. We then use local and global rule-based stochastic simulations to generate artificial arbors, and identify the parameters that statistically best approximate the real data. We observe structural homeostasis in all da classes, where an increase in size of one dendritic stem is compensated by a reduction in the other stems of the same neuron. Local rule models show that bifurcation probability is determined by branch order, while branch length depends on path distance from the soma. Global rule simulations suggest that most complex morphologies tend to be constrained by resource optimization, while simpler neuron classes privilege path distance conservation. Genetic manipulations affect both the local and global optimal parameters, demonstrating functional perturbations in growth mechanisms.

Intra-neuronal Competition for Synaptic Partners Conserves the Amount of Dendritic Building Material

Brain development requires correct targeting of multiple thousand synaptic terminals onto staggeringly complex dendritic arbors. The mechanisms by which input synapse numbers are matched to dendrite size, and by which synaptic inputs from different transmitter systems are correctly partitioned onto a postsynaptic arbor, are incompletely understood. By combining quantitative neuroanatomy with targeted genetic manipulation of synaptic input to an identified Drosophila neuron, we show that synaptic inputs of two different transmitter classes locally direct dendrite growth in a competitive manner. During development, the relative amounts of GABAergic and cholinergic synaptic drive shift dendrites between different input domains of one postsynaptic neuron without affecting total arbor size. Therefore, synaptic input locally directs dendrite growth, but intra-neuronal dendrite redistributions limit morphological variability, a phenomenon also described for cortical neurons. Mechanistically, this requires local dendritic Ca²⁺ influx through Dα7nAChRs or through LVA channels following GABA_AR-mediated depolarizations. VIDEO ABSTRACT.

Delayed feedback model of axonal length sensing

A fundamental question in cell biology is how the sizes of cells and organelles are regulated at various stages of development. Size homeostasis is particularly challenging for neurons, whose axons can extend from hundreds of microns to meters (in humans). Recently, a molecular-motor-based mechanism for axonal length sensing has been proposed, in which axonal length is encoded by the frequency of an oscillating retrograde signal. In this article, we develop a mathematical model of this length-sensing mechanism in which advection-diffusion equations for bidirectional motor transport are coupled to a chemical signaling network. We show that chemical oscillations emerge due to delayed negative feedback via a Hopf bifurcation, resulting in a frequency that is a monotonically decreasing function of axonal length. Knockdown of either kinesin or dynein causes an increase in the oscillation frequency, suggesting that the length-sensing mechanism would produce longer axons, which is consistent with experimental findings. One major prediction of the model is that fluctuations in the transport of molecular motors lead to a reduction in the reliability of the frequency-encoding mechanism for long axons.

A frequency-dependent decoding mechanism for axonal length sensing

We have recently developed a mathematical model of axonal length sensing in which a system of delay differential equations describe a chemical signaling network. We showed that chemical oscillations emerge due to delayed negative feedback via a Hopf bifurcation, resulting in a frequency that is a monotonically decreasing function of axonal length. In this paper, we explore how frequency-encoding of axonal length can be decoded by a frequency-modulated gene network. If the protein output were thresholded, then this could provide a mechanism for axonal length control. We analyze the robustness of such a mechanism in the presence of intrinsic noise due to finite copy numbers within the gene network.

Amacrine cell subtypes differ in their intrinsic neurite growth capacity

PURPOSE

Amacrine cell neurite patterning has been extensively studied in vivo, and more than 30 subpopulations with varied morphologies have been identified in the mammalian retina. It is not known, however, whether the complex amacrine cell morphology is determined intrinsically, is signaled by extrinsic cues, or both.

METHODS

Here we purified rat amacrine cell subpopulations away from their retinal neighbors and glial-derived factors to ask questions about their intrinsic neurite growth ability. In defined medium strongly trophic for amacrine cells in vitro, we characterized survival and neurite growth of amacrine cell subpopulations defined by expression of specific markers.

RESULTS

We found that a series of amacrine cell subtype markers are developmentally regulated, turning on through early postnatal development. Subtype marker expression was observed in similar fractions of cultured amacrine cells as was observed in vivo, and was maintained with time in culture. Overall, amacrine cell neurite growth followed principles very similar to those in postnatal retinal ganglion cells, but embryonic retinal ganglion cells demonstrated different features, relating to their rapid axon growth. Surprisingly, the three subpopulations of amacrine cells studied in vitro recapitulated quantitatively and qualitatively the varied morphologies they have in vivo.

CONCLUSIONS

Our data suggest that cultured amacrine cells maintain intrinsic fidelity to their identified in vivo subtypes, and furthermore, that cell-autonomous, intrinsic factors contribute to the regulation of neurite patterning.

Digital reconstruction and morphometric analysis of human brain arterial vasculature from magnetic resonance angiography

Characterization of the complex branching architecture of cerebral arteries across a representative sample of the human population is important for diagnosing, analyzing, and predicting pathological states. Brain arterial vasculature can be visualized by magnetic resonance angiography (MRA). However, most MRA studies are limited to qualitative assessments, partial morphometric analyses, individual (or small numbers of) subjects, proprietary datasets, or combinations of the above limitations. Neuroinformatics tools, developed for neuronal arbor analysis, were used to quantify vascular morphology from 3T time-of-flight MRA high-resolution (620 μm isotropic) images collected in 61 healthy volunteers (36/25 F/M, average age=31.2 ± 10.7, range=19-64 years). We present in-depth morphometric analyses of the global and local anatomical features of these arbors. The overall structure and size of the vasculature did not significantly differ across genders, ages, or hemispheres. The total length of the three major arterial trees stemming from the circle of Willis (from smallest to largest: the posterior, anterior, and middle cerebral arteries; or PCAs, ACAs, and MCAs, respectively) followed an approximate 1:2:4 proportion. Arterial size co-varied across individuals: subjects with one artery longer than average tended to have all other arteries also longer than average. There was no net right-left difference across the population in any of the individual arteries, but ACAs were more lateralized than MCAs. MCAs, ACAs, and PCAs had similar branch-level properties such as bifurcation angles. Throughout the arterial vasculature, there were considerable differences between branch types: bifurcating branches were significantly shorter and straighter than terminating branches. Furthermore, the length and meandering of bifurcating branches increased with age and with path distance from the circle of Willis. All reconstructions are freely distributed through a public database to enable additional analyses and modeling (cng.gmu.edu/brava).

Cell length sensing for neuronal growth control

Neurons exhibit great size differences, and must coordinate biosynthesis rates in cell bodies with the growth needs of different lengths of axons. Classically, axon growth has been viewed mainly as a consequence of extrinsic influences. However, recent publications have proposed at least two different intrinsic axon growth-control mechanisms. We suggest that these mechanisms form part of a continuum of axon growth-control mechanisms, wherein initial growth rates are pre-programmed by transcription factor levels, and subsequent elongating growth is dependent on feedback from intrinsic length-sensing enabled by bidirectional motor-dependent oscillating signals. This model might explain intrinsic limits on elongating neuronal growth and provides a mechanistic framework for determining the connections between genome expression and cellular growth rates in neurons.

A motor-driven mechanism for cell-length sensing

Size homeostasis is fundamental in cell biology, but it is not clear how large cells such as neurons can assess their own size or length. We examined a role for molecular motors in intracellular length sensing. Computational simulations suggest that spatial information can be encoded by the frequency of an oscillating retrograde signal arising from a composite negative feedback loop between bidirectional motor-dependent signals. The model predicts that decreasing either or both anterograde or retrograde signals should increase cell length, and this prediction was confirmed upon application of siRNAs for specific kinesin and/or dynein heavy chains in adult sensory neurons. Heterozygous dynein heavy chain 1 mutant sensory neurons also exhibited increased lengths both in vitro and during embryonic development. Moreover, similar length increases were observed in mouse embryonic fibroblasts upon partial downregulation of dynein heavy chain 1. Thus, molecular motors critically influence cell-length sensing and growth control.

Digital morphometry of rat cerebellar climbing fibers reveals distinct branch and bouton types

Cerebellar climbing fibers (CFs) provide powerful excitatory input to Purkinje cells (PCs), which represent the sole output of the cerebellar cortex. Recent discoveries suggest that CFs have information-rich signaling properties important for cerebellar function, beyond eliciting the well known all-or-none PC complex spike. CF morphology has not been quantitatively analyzed at the same level of detail as its biophysical properties. Because morphology can greatly influence function, including the capacity for information processing, it is important to understand CF branching structure in detail, as well as its variability across and within arbors. We have digitally reconstructed 68 rat CFs labeled using biotinylated dextran amine injected into the inferior olive and comprehensively quantified their morphology. CF structure was considerably diverse even within the same anatomical regions. Distinctly identifiable primary, tendril, and distal branches could be operationally differentiated by the relative size of the subtrees at their initial bifurcations. Additionally, primary branches were more directed toward the cortical surface and had fewer and less pronounced synaptic boutons, suggesting they prioritize efficient and reliable signal propagation. Tendril and distal branches were spatially segregated and bouton dense, indicating specialization in signal transmission. Furthermore, CFs systematically targeted molecular layer interneuron cell bodies, especially at terminal boutons, potentially instantiating feedforward inhibition on PCs. This study offers the most detailed and comprehensive characterization of CF morphology to date. The reconstruction files and metadata are publicly distributed at NeuroMorpho.org.

Effects of aging on properties of the local circuit in rat primary somatosensory cortex (S1) in vitro

During aging receptive field properties degrade, the ability of the circuit to process temporal information is impaired and behaviors mediated by the circuit can become impaired. These changes are mediated by changes in the properties of neural circuits, particularly the balance of excitation and inhibition, the intrinsic properties of neurons, and the anatomy of connections in the circuit. In this study, properties of thalamorecipient pyramidal neurons in layer 3 were examined in the hindpaw region of rat primary somatosensory cortex (S1) in vitro. Excitatory and inhibitory postsynaptic currents (IPSCs) resulting from trains of electrical stimulation of thalamocortical afferents were recorded. Excitatory postsynaptic currents were larger in old S1, but showed no difference in temporal dynamics; IPSCs showed significantly less suppression across the train in old S1, partly due to a decrease in GABAB signaling. Neurons in old S1 were more likely to exhibit burst firing, due to an increase in T-current. Significant differences in dendritic morphology were also observed in old S1, accompanied by a decrease in dendritic spine density. These data directly demonstrate changes in the properties of the thalamorecipient circuit in old S1 and help to explain the changes observed in responses during aging.

Sensory deprivation differentially impacts the dendritic development of pyramidal versus non-pyramidal neurons in layer 6 of mouse barrel cortex

Early postnatal sensory experience can have profound impacts on the structure and function of cortical circuits affecting behavior. Using the mouse whisker-to-barrel system we chronically deprived animals of normal sensory experience by bilaterally trimming their whiskers every other day from birth for the first postnatal month. Brain tissue was then processed for Golgi staining and neurons in layer 6 of barrel cortex were reconstructed in three dimensions. Dendritic and somatic parameters were compared between sensory-deprived and normal sensory experience groups. Results demonstrated that layer 6 non-pyramidal neurons in the chronically deprived group showed an expansion of their dendritic arbors. The pyramidal cells responded to sensory deprivation with increased somatic size and basilar dendritic arborization but overall decreased apical dendritic parameters. In sum, sensory deprivation impacted on the neuronal architecture of pyramidal and non-pyramidal neurons in layer 6, which may provide a substrate for observed physiological and behavioral changes resulting from whisker trimming.

The balance between excitation and inhibition and functional sensory processing in the somatosensory cortex

The balance between excitation and inhibition (E/I balance) is tightly regulated in adult cortices to maintain proper nervous system function. Disturbed E/I balance is associated with numerous neuropsychological disorders, such as autism, epilepsy and schizophrenia. The present review will discuss aspects of Hebbian and homeostatic mechanisms regulating excitatory and inhibitory balance related to sensory processing in somatosensory cortex of rodents. Additionally, changes in the E/I balance during sensory manipulation will be discussed.

Morphofunctional changes in goldfish Mauthner neurons after application of beta-amyloid

The effects of applying aggregated beta-amyloid peptide fragment 25-35 on the three-dimensional structure and volume of Mauthner neurons (MN) and on motor asymmetry were assessed in goldfish using reconstructions based on serial histological sections. These experiments showed that the motor asymmetry of the fish was stable in the intact state and in controls and correlated tightly with structural asymmetry of neurons. beta-Amyloid produced large changes or inversion in motor asymmetry, which did not coincide with or even contradicted the structural asymmetry of MN. This occurred as a result of marked dystrophy or, conversely, hypertrophy of individual neurons and their individual dendrites, with changes in their proportions. It is suggested that the harmful action of beta-amyloid on MN structure and the discordant ("incorrect") behavior of the fish may result from mechanical deformation evoked by its tape-like fibrils. Overall, the results lead to the conclusion that MN provide a suitable system for studying the structural aspects of amyloidosis.

Stabilization of mauthner neuron structure on adaptation of goldfish to contralateral optokinetic stimulation

We have previously shown that contralateral optokinetic (visual) stimulation (COS) evokes inversion of motor asymmetry in goldfish and three-fold reductions in the volume of the ventral dendrite of the ipsilateral Mauthner neuron (MN). A training regime consisting of repeated daily sessions of COS induced resistance of the motor behavior of the fish to this treatment. We report here our studies of the effects of training sessions of COS on the structure of MN and their components. Daily visual training was found to stabilize the sizes of the dorsal dendrites of MN, significantly increasing their resistance to single prolonged sessions of COS. Thus, repeated stimulation of an individual dendrite induces an adaptive morphological state in the dendrite and in the neuron as a whole. This allows more detailed studies of the role of the individual dendrite in modifying the functional activity of the whole neuron in the mechanisms of adaptation and memory at the cellular level to be performed.

Impact of dendritic size and dendritic topology on burst firing in pyramidal cells

Neurons display a wide range of intrinsic firing patterns. A particularly relevant pattern for neuronal signaling and synaptic plasticity is burst firing, the generation of clusters of action potentials with short interspike intervals. Besides ion-channel composition, dendritic morphology appears to be an important factor modulating firing pattern. However, the underlying mechanisms are poorly understood, and the impact of morphology on burst firing remains insufficiently known. Dendritic morphology is not fixed but can undergo significant changes in many pathological conditions. Using computational models of neocortical pyramidal cells, we here show that not only the total length of the apical dendrite but also the topological structure of its branching pattern markedly influences inter- and intraburst spike intervals and even determines whether or not a cell exhibits burst firing. We found that there is only a range of dendritic sizes that supports burst firing, and that this range is modulated by dendritic topology. Either reducing or enlarging the dendritic tree, or merely modifying its topological structure without changing total dendritic length, can transform a cell's firing pattern from bursting to tonic firing. Interestingly, the results are largely independent of whether the cells are stimulated by current injection at the soma or by synapses distributed over the dendritic tree. By means of a novel measure called mean electrotonic path length, we show that the influence of dendritic morphology on burst firing is attributable to the effect both dendritic size and dendritic topology have, not on somatic input conductance, but on the average spatial extent of the dendritic tree and the spatiotemporal dynamics of the dendritic membrane potential. Our results suggest that alterations in size or topology of pyramidal cell morphology, such as observed in Alzheimer's disease, mental retardation, epilepsy, and chronic stress, could change neuronal burst firing and thus ultimately affect information processing and cognition.

Longitudinal in vivo imaging reveals balanced and branch-specific remodeling of mature cortical pyramidal dendritic arbors after stroke

The manner in which fully mature peri-infarct cortical dendritic arbors remodel after stroke, and thus may possibly contribute to stroke-induced changes in cortical receptive fields, is unknown. In this study, we used longitudinal in vivo two-photon imaging to investigate the extent to which brain ischemia can trigger dendritic remodeling of pyramidal neurons in the adult mouse somatosensory cortex, and to determine the nature by which remodeling proceeds over time and space. Before the induction of stroke, dendritic arbors were relatively stable over several weeks. However, after stroke, apical dendritic arbor remodeling increased significantly (dendritic tip growth and retraction), particularly within the first 2 weeks after stroke. Despite a threefold increase in structural remodeling, the net length of arbors did not change significantly over time because dendrite extensions away from the stroke were balanced by the shortening of tips near the infarct. Therefore, fully mature cortical pyramidal neurons retain the capacity for extensive structural plasticity and remodel in a balanced and branch-specific manner.

Neocortical axon arbors trade-off material and conduction delay conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal's conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations.

Within the grey matter of cerebral cortex is a complex network formed by a dense tangle of individual branching axons mostly of cortical origin. Yet remarkably when presented with a barrage of complex, noisy sensory stimuli this convoluted network architecture computes accurately and rapidly. How does such a highly interconnected though jumbled forest of axonal trees process vital information so quickly? Pioneering neuroscientist Ramón y Cajal thought the size and shape of individual neurons was governed by simple rules to save cellular material and to reduce signal conduction delay. In this study, we investigated how these rules applied to whole axonal trees in neocortex by comparing their 3D structure to equivalent artificial arbors optimized for these rules. We discovered that neocortical axonal trees achieve a balance between these two rules so that a little more cellular material than necessary was used to substantially reduce conduction delays. Importantly, we suggest the nature of arbor branching balances time and material so that neocortical axons may communicate with a high degree of temporal precision, enabling accurate and rapid computation within local cortical networks. This approach could be applied to other neural structures to better understand the functional principles of brain design.

Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models

In neurodegenerative disorders, such as Alzheimer's disease, neuronal dendrites and dendritic spines undergo significant pathological changes. Because of the determinant role of these highly dynamic structures in signaling by individual neurons and ultimately in the functionality of neuronal networks that mediate cognitive functions, a detailed understanding of these changes is of paramount importance. Mutant murine models, such as the Tg2576 APP mutant mouse and the rTg4510 tau mutant mouse have been developed to provide insight into pathogenesis involving the abnormal production and aggregation of amyloid and tau proteins, because of the key role that these proteins play in neurodegenerative disease. This review showcases the multidimensional approach taken by our collaborative group to increase understanding of pathological mechanisms in neurodegenerative disease using these mouse models. This approach includes analyses of empirical 3D morphological and electrophysiological data acquired from frontal cortical pyramidal neurons using confocal laser scanning microscopy and whole-cell patch-clamp recording techniques, combined with computational modeling methodologies. These collaborative studies are designed to shed insight on the repercussions of dystrophic changes in neocortical neurons, define the cellular phenotype of differential neuronal vulnerability in relevant models of neurodegenerative disease, and provide a basis upon which to develop meaningful therapeutic strategies aimed at preventing, reversing, or compensating for neurodegenerative changes in dementia.

A time for atlases and atlases for time

Advances in neuroanatomy and computational power are leading to the construction of new digital brain atlases. Atlases are rising as indispensable tools for comparing anatomical data as well as being stimulators of new hypotheses and experimental designs. Brain atlases describe nervous systems which are inherently plastic and variable. Thus, the levels of brain plasticity and stereotypy would be important to evaluate as limiting factors in the context of static brain atlases. In this review, we discuss the extent of structural changes which neurons undergo over time, and how these changes would impact the static nature of atlases. We describe the anatomical stereotypy between neurons of the same type, highlighting the differences between invertebrates and vertebrates. We review some recent experimental advances in our understanding of anatomical dynamics in adult neural circuits, and how these are modulated by the organism's experience. In this respect, we discuss some analogies between brain atlases and the sequenced genome and the emerging epigenome. We argue that variability and plasticity of neurons are substantially high, and should thus be considered as integral features of high-resolution digital brain atlases.

Cooperative synapse formation in the neocortex

Neuron morphology plays an important role in defining synaptic connectivity. Clearly, only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, such axo-dendritic oppositions, termed potential synapses, must be bridged by dendritic spines to form synaptic connections. To explore the rules by which synaptic connections are formed within the constraints imposed by neuron morphology, we compared the distributions of the numbers of actual and potential synapses between pre- and postsynaptic neurons forming different laminar projections in rat barrel cortex. Quantitative comparison explicitly ruled out the hypothesis that individual synapses between neurons are formed independently of each other. Instead, the data are consistent with a cooperative scheme of synapse formation where multiple-synaptic connections between neurons are stabilized while neurons that do not establish a critical number of synapses are not likely to remain synaptically coupled.

Quantitative morphometry of electrophysiologically identified CA3b interneurons reveals robust local geometry and distinct cell classes

The morphological and electrophysiological diversity of inhibitory cells in hippocampal area CA3 may underlie specific computational roles and is not yet fully elucidated. In particular, interneurons with somata in strata radiatum (R) and lacunosum-moleculare (L-M) receive converging stimulation from the dentate gyrus and entorhinal cortex as well as within CA3. Although these cells express different forms of synaptic plasticity, their axonal trees and connectivity are still largely unknown. We investigated the branching and spatial patterns, plus the membrane and synaptic properties, of rat CA3b R and L-M interneurons digitally reconstructed after intracellular labeling. We found considerable variability within but no difference between the two layers, and no correlation between morphological and biophysical properties. Nevertheless, two cell types were identified based on the number of dendritic bifurcations, with significantly different anatomical and electrophysiological features. Axons generally branched an order of magnitude more than dendrites. However, interneurons on both sides of the R/L-M boundary revealed surprisingly modular axodendritic arborizations with consistently uniform local branch geometry. Both axons and dendrites followed a lamellar organization, and axons displayed a spatial preference toward the fissure. Moreover, only a small fraction of the axonal arbor extended to the outer portion of the invaded volume, and tended to return toward the proximal region. In contrast, dendritic trees demonstrated more limited but isotropic volume occupancy. These results suggest a role of predominantly local feedforward and lateral inhibitory control for both R and L-M interneurons. Such a role may be essential to balance the extensive recurrent excitation of area CA3 underlying hippocampal autoassociative memory function.

Mice lacking doublecortin and doublecortin-like kinase 2 display altered hippocampal neuronal maturation and spontaneous seizures

Mutations in doublecortin (DCX) are associated with intractable epilepsy in humans, due to a severe disorganization of the neocortex and hippocampus known as classical lissencephaly. However, the basis of the epilepsy in lissencephaly remains unclear. To address potential functional redundancy with murin Dcx, we targeted one of the closest homologues, doublecortin-like kinase 2 (Dclk2). Here, we report that Dcx; Dclk2-null mice display frequent spontaneous seizures that originate in the hippocampus, with most animals dying in the first few months of life. Elevated hippocampal expression of c-fos and loss of somatostatin-positive interneurons were identified, both known to correlate with epilepsy. Dcx and Dclk2 are coexpressed in developing hippocampus, and, in their absence, there is dosage-dependent disrupted hippocampal lamination associated with a cell-autonomous simplification of pyramidal dendritic arborizations leading to reduced inhibitory synaptic tone. These data suggest that hippocampal dysmaturation and insufficient receptive field for inhibitory input may underlie the epilepsy in lissencephaly, and suggest potential therapeutic strategies for controlling epilepsy in these patients.

The electrotonic structure of pyramidal neurons contributing to prefrontal cortical circuits in macaque monkeys is significantly altered in aging

Whereas neuronal numbers are largely preserved in normal aging, subtle morphological changes occur in dendrites and spines, whose electrotonic consequences remain unexplored. We examined age-related morphological alterations in 2 types of pyramidal neurons contributing to working memory circuits in the macaque prefrontal cortex (PFC): neurons in the superior temporal cortex forming "long" projections to the PFC and "local" projection neurons within the PFC. Global dendritic mass homeostasis, measured by 3-dimensional scaling analysis, was conserved with aging in both neuron types. Spine densities, dendrite diameters, lengths, and branching complexity were all significantly reduced in apical dendrites of long projection neurons with aging, but only spine parameters were altered in local projection neurons. Despite these differences, voltage attenuation due to passive electrotonic structure, assuming equivalent cable parameters, was significantly reduced with aging in the apical dendrites of both neuron classes. Confirming the electrotonic analysis, simulated passive backpropagating action potential efficacy was significantly higher in apical but not basal dendrites of old neurons. Unless compensated by changes in passive cable parameters, active membrane properties, or altered synaptic properties, these effects will increase the excitability of pyramidal neurons, compromising the precisely tuned activity required for working memory, ultimately resulting in age-related PFC dysfunction.

Quantification of local morphodynamics and local GTPase activity by edge evolution tracking

Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6–8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.

Morphological change is a key indicator of various cellular functions such as migration and construction of specific structures. Time-lapse image microscopy permits the visualization of changes in morphology and spatio-temporal protein activity related to dynamic cellular functions. However, an unsolved problem is the development of an automated analytical method to handle the vast amount of associated image data. This article describes a novel approach for analysis of time-lapse microscopy data. We automated the quantification of morphological change and cell edge protein activity and then performed statistical analysis to explore the relationship between local morphological change and spatio-temporal protein activity. Our results reveal that morphological change precedes specific protein activity by 6–8 min, which prompts a new hypothesis for cellular morphodynamics regulated by molecular signaling. Use of our method thus allows for detailed analysis of time-lapse images emphasizing the value of computer-assisted high-throughput analysis for time-lapse microscopy images and statistical analysis of morphological properties.

Quantifying neuronal size: summing up trees and splitting the branch difference

Neurons vary greatly in size, shape, and complexity depending on their underlying function. Overall size of neuronal trees affects connectivity, area of influence, and other biophysical properties. Relative distributions of neuronal extent, such as the difference between subtrees at branch points, are also critically related to function and activity. This review covers neuromorphological research that analyzes shape and size to elucidate their functional role for different neuron types. We also introduce a novel morphometric, "caulescence", capturing the extent to which trees exhibit a main path. Neuronal tree types differ vastly in caulescence, suggesting potential neurocomputational correlates of this property.

Homeostatically regulated synchronized oscillations induced by short-term tetrodotoxin treatment in cultured neuronal network

Homeostatic plasticity plays a critical role in the stability of neuronal activities. Here, with high-density hippocampal networks cultured on multi-electrode arrays (MEAs), the transformation of spontaneous neuronal firing patterns induced by 1microM tetrodotoxin was clarified. Once tetrodotoxin was washed out after a 4-h treatment, spontaneous activities rose significantly with spike rate increasing approximately three times, and synchronized burst oscillations appeared throughout the network, with the cross-correlation coefficient between the active sites rising from 0.06+/-0.03 to 0.27+/-0.05. The long-term recording showed that the oscillations lasted for more than 4h before the network recovered. These results suggest that short-term treatment by tetrodotoxin may induce the homeostatically enhanced neuronal excitability, and that the spontaneous synchronized oscillations should be an indicator of homeostatic plasticity in cultured neuronal network. Furthermore, the non-invasive and long-term recording with MEAs as a novel sensing system is identified to be appropriate for pharmacological investigations of neuronal plasticity at the network level.

Dendritic excitability and synaptic plasticity

Most synaptic inputs are made onto the dendritic tree. Recent work has shown that dendrites play an active role in transforming synaptic input into neuronal output and in defining the relationships between active synapses. In this review, we discuss how these dendritic properties influence the rules governing the induction of synaptic plasticity. We argue that the location of synapses in the dendritic tree, and the type of dendritic excitability associated with each synapse, play decisive roles in determining the plastic properties of that synapse. Furthermore, since the electrical properties of the dendritic tree are not static, but can be altered by neuromodulators and by synaptic activity itself, we discuss how learning rules may be dynamically shaped by tuning dendritic function. We conclude by describing how this reciprocal relationship between plasticity of dendritic excitability and synaptic plasticity has changed our view of information processing and memory storage in neuronal networks.

A comparative computer simulation of dendritic morphology

Computational modeling of neuronal morphology is a powerful tool for understanding developmental processes and structure-function relationships. We present a multifaceted approach based on stochastic sampling of morphological measures from digital reconstructions of real cells. We examined how dendritic elongation, branching, and taper are controlled by three morphometric determinants: Branch Order, Radius, and Path Distance from the soma. Virtual dendrites were simulated starting from 3,715 neuronal trees reconstructed in 16 different laboratories, including morphological classes as diverse as spinal motoneurons and dentate granule cells. Several emergent morphometrics were used to compare real and virtual trees. Relating model parameters to Branch Order best constrained the number of terminations for most morphological classes, except pyramidal cell apical trees, which were better described by a dependence on Path Distance. In contrast, bifurcation asymmetry was best constrained by Radius for apical, but Path Distance for basal trees. All determinants showed similar performance in capturing total surface area, while surface area asymmetry was best determined by Path Distance. Grouping by other characteristics, such as size, asymmetry, arborizations, or animal species, showed smaller differences than observed between apical and basal, pointing to the biological importance of this separation. Hybrid models using combinations of the determinants confirmed these trends and allowed a detailed characterization of morphological relations. The differential findings between morphological groups suggest different underlying developmental mechanisms. By comparing the effects of several morphometric determinants on the simulation of different neuronal classes, this approach sheds light on possible growth mechanism variations responsible for the observed neuronal diversity.

Neurons in the brain have a variety of complex arbor shapes that help determine both their interconnectivity and functional roles. Molecular biology is beginning to uncover important details on the development of these tree-like structures, but how and why vastly different shapes arise is still largely unknown. We developed a novel set of computer models of branching in which measurements of real nerve cell structures digitally traced from microscopic imaging are resampled to create virtual trees. The different rules that the models use to create the most similar virtual trees to the real data support specific hypotheses regarding development. Surprisingly, the arborizations that differed most in the optimal rules were found on opposite sides of the same type of neuron, namely apical and basal trees of pyramidal cells. The details of the rules suggest that pyramidal cell trees may respond in unique and complex ways to their external environment. By better understanding how these trees are formed in the brain, we can learn more about their normal function and why they are often malformed in neurological diseases.

Successes and rewards in sharing digital reconstructions of neuronal morphology

The computer-assisted three-dimensional reconstruction of neuronal morphology is becoming an increasingly popular technique to quantify the arborization patterns of dendrites and axons. The resulting digital files are suitable for comprehensive morphometric analyses as well as for building anatomically realistic compartmental models of membrane biophysics and neuronal electrophysiology. The digital tracings acquired in a lab for a specific purpose can be often re-used by a different research group to address a completely unrelated scientific question, if the original investigators are willing to share the data. Since reconstructing neuronal morphology is a labor-intensive process, data sharing and re-analysis is particularly advantageous for the neuroscience and biomedical communities. Here we present numerous cases of "success stories" in which digital reconstructions of neuronal morphology were shared and re-used, leading to additional, independent discoveries and publications, and thus amplifying the impact of the "source" study for which the data set was first collected. In particular, we overview four main applications of this kind of data: comparative morphometric analyses, statistical estimation of potential synaptic connectivity, morphologically accurate electrophysiological simulations, and computational models of neuronal shape and development.

Neuronal firing sensitivity to morphologic and active membrane parameters

Both the excitability of a neuron's membrane, driven by active ion channels, and dendritic morphology contribute to neuronal firing dynamics, but the relative importance and interactions between these features remain poorly understood. Recent modeling studies have shown that different combinations of active conductances can evoke similar firing patterns, but have neglected how morphology might contribute to homeostasis. Parameterizing the morphology of a cylindrical dendrite, we introduce a novel application of mathematical sensitivity analysis that quantifies how dendritic length, diameter, and surface area influence neuronal firing, and compares these effects directly against those of active parameters. The method was applied to a model of neurons from goldfish Area II. These neurons exhibit, and likely contribute to, persistent activity in eye velocity storage, a simple model of working memory. We introduce sensitivity landscapes, defined by local sensitivity analyses of firing rate and gain to each parameter, performed globally across the parameter space. Principal directions over which sensitivity to all parameters varied most revealed intrinsic currents that most controlled model output. We found domains where different groups of parameters had the highest sensitivities, suggesting that interactions within each group shaped firing behaviors within each specific domain. Application of our method, and its characterization of which models were sensitive to general morphologic features, will lead to advances in understanding how realistic morphology participates in functional homeostasis. Significantly, we can predict which active conductances, and how many of them, will compensate for a given age- or development-related structural change, or will offset a morphologic perturbation resulting from trauma or neurodegenerative disorder, to restore normal function. Our method can be adapted to analyze any computational model. Thus, sensitivity landscapes, and the quantitative predictions they provide, can give new insight into mechanisms of homeostasis in any biological system.

Homeostasis is a process that allows a system to maintain a certain level of output over a long time, even though the inputs controlling the output are changing. Recently, studies of neurons and neuronal networks have shown that the “active” parameters that describe the movement of ions across the cell membrane contribute to homeostasis, since these parameters can be combined in different ways to maintain a specific output. There is also evidence that the physical shape (“morphology”) of the neuron may play a role in homeostasis, but this possibility has not been explored in computational models. We have developed a method that uses sensitivity analysis to evaluate how different kinds of parameters, like active and morphologic ones, affect model output. Across a multi-dimensional parameter space, we identified both local and global trends in parameter sensitivities that indicate regions where different parameters, even morphologic ones, contribute strongly to homeostasis. Significantly, the authors used sensitivities to predict which parameters should change, and by how much, to compensate for changes in another parameter to restore normal function. These predictions may prove important to neuronal aging, disease, and trauma research, but the method can be used to analyze any computational model.

Homeostatic plasticity studied using in vivo hippocampal activity-blockade: synaptic scaling, intrinsic plasticity and age-dependence

Homeostatic plasticity is thought to be important in preventing neuronal circuits from becoming hyper- or hypoactive. However, there is little information concerning homeostatic mechanisms following in vivo manipulations of activity levels. We investigated synaptic scaling and intrinsic plasticity in CA1 pyramidal cells following 2 days of activity-blockade in vivo in adult (postnatal day 30; P30) and juvenile (P15) rats. Chronic activity-blockade in vivo was achieved using the sustained release of the sodium channel blocker tetrodotoxin (TTX) from the plastic polymer Elvax 40W implanted directly above the hippocampus, followed by electrophysiological assessment in slices in vitro. Three sets of results were in general agreement with previous studies on homeostatic responses to in vitro manipulations of activity. First, Schaffer collateral stimulation-evoked field responses were enhanced after 2 days of in vivo TTX application. Second, miniature excitatory postsynaptic current (mEPSC) amplitudes were potentiated. However, the increase in mEPSC amplitudes occurred only in juveniles, and not in adults, indicating age-dependent effects. Third, intrinsic neuronal excitability increased. In contrast, three sets of results sharply differed from previous reports on homeostatic responses to in vitro manipulations of activity. First, miniature inhibitory postsynaptic current (mIPSC) amplitudes were invariably enhanced. Second, multiplicative scaling of mEPSC and mIPSC amplitudes was absent. Third, the frequencies of adult and juvenile mEPSCs and adult mIPSCs were increased, indicating presynaptic alterations. These results provide new insights into in vivo homeostatic plasticity mechanisms with relevance to memory storage, activity-dependent development and neurological diseases.

Coregulation of natively expressed pertussis toxin-sensitive muscarinic receptors with G-protein-activated potassium channels

Many inhibitory neurotransmitters in the brain activate Kir3 channels by stimulating pertussis toxin (PTX)-sensitive G-protein-coupled receptors. Here, we investigated the regulation of native muscarinic receptors and Kir3 channels expressed in NGF-differentiated PC12 cells, which are similar to sympathetic neurons. Quantitative reverse transcription-PCR and immunocytochemistry revealed that NGF treatment significantly upregulated mRNA and protein for m2 muscarinic receptors, PTX-sensitive G alpha(o) G-proteins, and Kir3.2c channels. Surprisingly, these upregulated muscarinic receptor/Kir3 signaling complexes were functionally silent. Ectopic expression of m2 muscarinic receptors or Kir3.2c channels was unable to produce muscarinic receptor-activated Kir3 currents with oxotremorine. Remarkably, pretreatment with muscarinic (m2/m4) receptor antagonists resulted in robust oxotremorine-activated Kir3 currents. Thus, sustained cholinergic stimulation of natively expressed m2/m4 muscarinic receptors controlled cell surface expression and functional coupling of both receptors and Kir3 channels. This new pathway for controlling Kir3 signaling could help limit the potential harmful effects of excessive Kir3 activity in the brain.

Changes in the structural complexity of the aged brain

Structural changes of neurons in the brain during aging are complex and not well understood. Neurons have significant homeostatic control of essential brain functions, including synaptic excitability, gene expression, and metabolic regulation. Any deviations from the norm can have severe consequences as seen in aging and injury. In this review, we present some of the structural adaptations that neurons undergo throughout normal and pathological aging and discuss their effects on electrophysiological properties and cognition. During aging, it is evident that neurons undergo morphological changes such as a reduction in the complexity of dendrite arborization and dendritic length. Spine numbers are also decreased, and because spines are the major sites for excitatory synapses, changes in their numbers could reflect a change in synaptic densities. This idea has been supported by studies that demonstrate a decrease in the overall frequency of spontaneous glutamate receptor-mediated excitatory responses, as well as a decrease in the levels of alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid and N-methyl-d-aspartate receptor expression. Other properties such as gamma-aminobutyric acid A receptor-mediated inhibitory responses and action potential firing rates are both significantly increased with age. These findings suggest that age-related neuronal dysfunction, which must underlie observed decline in cognitive function, probably involves a host of other subtle changes within the cortex that could include alterations in receptors, loss of dendrites, and spines and myelin dystrophy, as well as the alterations in synaptic transmission. Together these multiple alterations in the brain may constitute the substrate for age-related loss of cognitive function.

Hippocampal granule cells in normal aging: insights from electrophysiological and functional imaging experiments

Normal aging, in the absence of neurodegenerative disease, can provide important insights into the mechanisms by which the brain can maintain cognitive abilities across the lifespan. Hippocampal-dependent memory processes can become vulnerable as age advances. The focus of this chapter is the contribution of hippocampal granule cells to cognitive impairments that are observed during aging. A number of alterations in structure, function, and gene expression have been observed in aged granule cells, any of which may lead to adaptive, compensatory or detrimental consequences to hippocampal function. As the average life span of humans continues to increase, those who reach 100 years or beyond is more common. Individuals that have aged successfully, and exhibit high levels of cognitive ability can provide useful clues into the enormous potential possessed by the mammalian brain.

Akt1 deficiency affects neuronal morphology and predisposes to abnormalities in prefrontal cortex functioning

There is accumulating evidence that AKT signaling plays a role in the pathogenesis of schizophrenia. We asked whether Akt1 deficiency in mice results in structural and functional abnormalities in prefrontal cortex (PFC). Exploratory transcriptional profiling revealed concerted alterations in the expression of PFC genes controlling synaptic function, neuronal development, myelination, and actin polymerization, and follow-up ultrastructural analysis identified consistent changes in the dendritic architecture of pyramidal neurons. Behavioral analysis indicated that Akt1-mutant mice have normal acquisition of a PFC-dependent cognitive task but abnormal working memory retention under neurochemical challenge of three distinct neurotransmitter systems. Thus, Akt1 deficiency creates a context permissive for gene-gene and gene-environment interactions that modulate PFC functioning and contribute to the disease risk associated with this locus, the severity of the clinical syndrome, or both.