Comparative electrotonic analysis of three classes of rat hippocampal neurons

Online conversion of reconstructed neural morphologies into standardized SWC format

Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).

Spatially resolved dendritic integration: towards a functional classification of neurons

The vast tree-like dendritic structure of neurons allows them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 130,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map specific and heterogeneous patterns of activity observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the number of branches connected to the soma. These are key topological factors in determining the neuron's energy consumption, firing rate, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron's firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.

Efficient Low-Pass Dendro-Somatic Coupling in the Apical Dendrite of Layer 5 Pyramidal Neurons in the Anterior Cingulate Cortex

Signal propagation in the dendrites of many neurons, including cortical pyramidal neurons in sensory cortex, is characterized by strong attenuation toward the soma. In contrast, using dual whole-cell recordings from the apical dendrite and soma of layer 5 (L5) pyramidal neurons in the anterior cingulate cortex (ACC) of adult male mice we found good coupling, particularly of slow subthreshold potentials like NMDA spikes or trains of EPSPs from dendrite to soma. Only the fastest EPSPs in the ACC were reduced to a similar degree as in primary somatosensory cortex, revealing differential low-pass filtering capabilities. Furthermore, L5 pyramidal neurons in the ACC did not exhibit dendritic Ca2+ spikes as prominently found in the apical dendrite of S1 (somatosensory cortex) pyramidal neurons. Fitting the experimental data to a NEURON model revealed that the specific distribution of Ileak, Iir, Im , and Ih was sufficient to explain the electrotonic dendritic structure causing a leaky distal dendritic compartment with correspondingly low input resistance and a compact perisomatic region, resulting in a decoupling of distal tuft branches from each other while at the same time efficiently connecting them to the soma. Our results give a biophysically plausible explanation of how a class of prefrontal cortical pyramidal neurons achieve efficient integration of subthreshold distal synaptic inputs compared with the same cell type in sensory cortices.SIGNIFICANCE STATEMENT Understanding cortical computation requires the understanding of its fundamental computational subunits. Layer 5 pyramidal neurons are the main output neurons of the cortex, integrating synaptic inputs across different cortical layers. Their elaborate dendritic tree receives, propagates, and transforms synaptic inputs into action potential output. We found good coupling of slow subthreshold potentials like NMDA spikes or trains of EPSPs from the distal apical dendrite to the soma in pyramidal neurons in the ACC, which was significantly better compared with S1. This suggests that frontal pyramidal neurons use a different integration scheme compared with the same cell type in somatosensory cortex, which has important implications for our understanding of information processing across different parts of the neocortex.

Dentate Granule Neurons Generated During Perinatal Life Display Distinct Morphological Features Compared With Later-Born Neurons in the Mouse Hippocampus

In nonhuman mammals and in particular in rodents, most granule neurons of the dentate gyrus (DG) are generated during development and yet little is known about their properties compared with adult-born neurons. Although it is generally admitted that these populations are morphologically indistinguishable once mature, a detailed analysis of developmentally born neurons is lacking. Here, we used in vivo electroporation to label dentate granule cells (DGCs) generated in mouse embryos (E14.5) or in neonates (P0) and followed their morphological development up to 6 months after birth. By comparison with mature retrovirus-labeled DGCs born at weaning (P21) or young adult (P84) stages, we provide the evidence that perinatally born neurons, especially embryonically born cells, are morphologically distinct from later-born neurons and are thus easily distinguishable. In addition, our data indicate that semilunar and hilar GCs, 2 populations in ectopic location, are generated during the embryonic and the neonatal periods, respectively. Thus, our findings provide new insights into the development of the different populations of GCs in the DG and open new questions regarding their function in the brain.

Robust emergence of sharply tuned place-cell responses in hippocampal neurons with structural and biophysical heterogeneities

Hippocampal pyramidal neurons sustain propagation of fast electrical signals and are electrotonically non-compact structures exhibiting cell-to-cell variability in their complex dendritic arborization. In this study, we demonstrate that sharp place-field tuning and several somatodendritic functional maps concomitantly emerge despite the presence of geometrical heterogeneities in these neurons. We establish this employing an unbiased stochastic search strategy involving thousands of models that spanned several morphologies and distinct profiles of dispersed synaptic localization and channel expression. Mechanistically, employing virtual knockout models (VKMs), we explored the impact of bidirectional modulation in dendritic spike prevalence on place-field tuning sharpness. Consistent with the prior literature, we found that across all morphologies, virtual knockout of either dendritic fast sodium channels or N-methyl-D-aspartate receptors led to a reduction in dendritic spike prevalence, whereas A-type potassium channel knockouts resulted in a non-specific increase in dendritic spike prevalence. However, place-field tuning sharpness was critically impaired in all three sets of VKMs, demonstrating that sharpness in feature tuning is maintained by an intricate balance between mechanisms that promote and those that prevent dendritic spike initiation. From the functional standpoint of the emergence of sharp feature tuning and intrinsic functional maps, within this framework, geometric variability was compensated by a combination of synaptic democracy, the ability of randomly dispersed synapses to yield sharp tuning through dendritic spike initiation, and ion-channel degeneracy. Our results suggest electrotonically non-compact neurons to be endowed with several degrees of freedom, encompassing channel expression, synaptic localization and morphological microstructure, in achieving sharp feature encoding and excitability homeostasis.

Simple models of quantitative firing phenotypes in hippocampal neurons: Comprehensive coverage of intrinsic diversity

Patterns of periodic voltage spikes elicited by a neuron help define its dynamical identity. Experimentally recorded spike trains from various neurons show qualitatively distinguishable features such as delayed spiking, spiking with or without frequency adaptation, and intrinsic bursting. Moreover, the input-dependent responses of a neuron not only show different quantitative features, such as higher spike frequency for a stronger input current injection, but can also exhibit qualitatively different responses, such as spiking and bursting under different input conditions, thus forming a complex phenotype of responses. In previous work, the comprehensive knowledge base of hippocampal neuron types Hippocampome.org systematically characterized various spike pattern phenotypes experimentally identified from 120 neuron types/subtypes. In this paper, we present a complete set of simple phenomenological models that quantitatively reproduce the diverse and complex phenotypes of hippocampal neurons. In addition to point-neuron models, we created compact multi-compartment models with up to four compartments, which will allow spatial segregation of synaptic integration in network simulations. Electrotonic compartmentalization observed in our compact multi-compartment models is qualitatively consistent with experimental observations. The models were created using an automated pipeline based on evolutionary algorithms. This work maps 120 neuron types/subtypes in the rodent hippocampus to a low-dimensional model space and adds another dimension to the knowledge accumulated in Hippocampome.org. Computationally efficient representations of intrinsic dynamics, along with other pieces of knowledge available in Hippocampome.org, provide a biologically realistic platform to explore the large-scale interactions of various neuron types at the mesoscopic level.

Quantifying How Staining Methods Bias Measurements of Neuron Morphologies

The process through which neurons are labeled is a key methodological choice in measuring neuron morphology. However, little is known about how this choice may bias measurements. To quantify this bias we compare the extracted morphology of neurons collected from the same rodent species, experimental condition, gender distribution, age distribution, brain region and putative cell type, but obtained with 19 distinct staining methods. We found strong biases on measured features of morphology. These were largest in features related to the coverage of the dendritic tree (e.g., the total dendritic tree length). Understanding measurement biases is crucial for interpreting morphological data.

Neuronal morphologies built for reliable physiology in a rhythmic motor circuit

It is often assumed that highly-branched neuronal structures perform compartmentalized computations. However, previously we showed that the Gastric Mill (GM) neuron in the crustacean stomatogastric ganglion (STG) operates like a single electrotonic compartment, despite having thousands of branch points and total cable length >10 mm (Otopalik et al., 2017a; 2017b). Here we show that compact electrotonic architecture is generalizable to other STG neuron types, and that these neurons present direction-insensitive, linear voltage integration, suggesting they pool synaptic inputs across their neuronal structures. We also show, using simulations of 720 cable models spanning a broad range of geometries and passive properties, that compact electrotonus, linear integration, and directional insensitivity in STG neurons arise from their neurite geometries (diameters tapering from 10-20 µm to < 2 µm at their terminal tips). A broad parameter search reveals multiple morphological and biophysical solutions for achieving different degrees of passive electrotonic decrement and computational strategies in the absence of active properties.

Differential changes to D1 and D2 medium spiny neurons in the 12-month-old Q175+/- mouse model of Huntington's Disease

Huntington's Disease (HD) is an autosomal dominant, progressive neurodegenerative disorder caused by deleterious expansion of CAG repeats in the Huntingtin gene and production of neurotoxic mutant Huntingtin protein (mHTT). The key pathological feature of HD is a profound degeneration of the striatum and a loss of cortical volume. The initial loss of indirect pathway (D2) medium spiny neuron (MSN) projections in early stages of HD, followed by a loss of direct pathway (D1) projections in advanced stages has important implications for the trajectory of motor and cognitive dysfunction in HD, but is not yet understood. Mouse models of HD have yielded important information on the effects and mechanisms of mHTT toxicity; however, whether these models recapitulate differential vulnerability of D1 vs. D2 MSNs is unknown. Here, we employed 12-month-old Q175+/- x D2-eGFP mice to examine the detailed structural and functional properties of D1 vs. D2 MSNs. While both D1 and D2 MSNs exhibited increased input resistance, depolarized resting membrane potentials and action potential threshold, only D1 MSNs showed reduced rheobase, action potential amplitude and frequency of spontaneous excitatory postsynaptic currents. Furthermore, D1 but not D2 MSNs showed marked proliferative changes to their dendritic arbors and reductions in spine density. Immunohistochemical assessment showed no loss of glutamatergic afferent inputs from cortical and subcortical sources onto identified D1 and D2 MSNs. Computational models constrained by empirical data predict that the increased dendritic complexity in Q175+/- D1 MSNs likely leads to greater dendritic filtering and attenuation of signals propagating to the soma from the dendrites. Together these findings reveal that, by twelve months, D1 and D2 MSNs exhibit distinctive responses to the presence of mHTT in this important mouse model of HD. This further highlights the need to incorporate findings from D1 and D2 MSNs independently in the context of HD models.

Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types

The diversity of intrinsic dynamics observed in neurons may enhance the computations implemented in the circuit by enriching network-level emergent properties such as synchronization and phase locking. Large-scale spiking network models of entire brain regions offer a platform to test theories of neural computation and cognitive function, providing useful insights on information processing in the nervous system. However, a systematic in-depth investigation requires network simulations to capture the biological intrinsic diversity of individual neurons at a sufficient level of accuracy. The computationally efficient Izhikevich model can reproduce a wide range of neuronal behaviors qualitatively. Previous studies using optimization techniques, however, were less successful in quantitatively matching experimentally recorded voltage traces. In this article, we present an automated pipeline based on evolutionary algorithms to quantitatively reproduce features of various classes of neuronal spike patterns using the Izhikevich model. Employing experimental data from Hippocampome.org, a comprehensive knowledgebase of neuron types in the rodent hippocampus, we demonstrate that our approach reliably fit Izhikevich models to nine distinct classes of experimentally recorded spike patterns, including delayed spiking, spiking with adaptation, stuttering, and bursting. Importantly, by leveraging the parameter-exploration capabilities of evolutionary algorithms, and by representing qualitative spike pattern class definitions in the error landscape, our approach creates several suitable models for each neuron type, exhibiting appropriate feature variabilities among neurons. Moreover, we demonstrate the flexibility of our methodology by creating multi-compartment Izhikevich models for each neuron type in addition to single-point versions. Although the results presented here focus on hippocampal neuron types, the same strategy is broadly applicable to any neural systems.

Differential processing in modality-specific Mauthner cell dendrites

KEY POINTS

The present study examines dendritic integrative processes that occur in many central neurons but have been challenging to study in vivo in the vertebrate brain. The Mauthner cell of goldfish receives auditory and visual information via two separate dendrites, providing a privileged scenario for in vivo examination of dendritic integration. The results show differential attenuation properties in the Mauthner cell dendrites arising at least partly from differences in cable properties and the nonlinear behaviour of the respective dendritic membranes. In addition to distinct modality-dependent membrane specialization in neighbouring dendrites of the Mauthner cell, we report cross-modal dendritic interactions via backpropagating postsynaptic potentials. Broadly, the results of the present study provide an exceptional example for the processing power of single neurons.

ABSTRACT

Animals process multimodal information for adaptive behavioural decisions. In fish, evasion of a diving bird that breaks the water surface depends on integrating visual and auditory stimuli with very different characteristics. How do neurons process such differential sensory inputs at the dendritic level? For that, we studied the Mauthner cells (M-cells) in the goldfish startle circuit, which receive visual and auditory inputs via two separate dendrites, both accessible for in vivo recordings. We investigated whether electrophysiological membrane properties and dendrite morphology, studied in vivo, play a role in selective sensory processing in the M-cell. The results obtained show that anatomical and electrophysiological differences between the dendrites combine to produce stronger attenuation of visually evoked postsynaptic potentials (PSPs) than to auditory evoked PSPs. Interestingly, our recordings showed also cross-modal dendritic interaction because auditory evoked PSPs invade the ventral dendrite (VD), as well as the opposite where visual PSPs invade the lateral dendrite (LD). However, these interactions were asymmetrical, with auditory PSPs being more prominent in the VD than visual PSPs in the LD. Modelling experiments imply that this asymmetry is caused by active conductances expressed in the proximal segments of the VD. The results obtained in the present study suggest modality-dependent membrane specialization in M-cell dendrites suited for processing stimuli of different time domains and, more broadly, provide a compelling example of information processing in single neurons.

Contributions of space-clamp errors to apparent time-dependent loss of Mg2+ block induced by NMDA

N-methyl-d-aspartate receptors (NMDARs) govern synaptic plasticity, development, and neuronal response to insult. Prolonged activation of NMDARs such as during an insult may activate secondary currents or modulate Mg²⁺ sensitivity, but the conditions under which these occur are not fully defined. We reexamined the effect of prolonged NMDAR activation in juvenile mouse hippocampal slices. NMDA (10 μM) elicited current with the expected negative-slope conductance in the presence of 1.2 mM Mg²⁺ However, several minutes of continued NMDA exposure elicited additional inward current at -70 mV. A higher concentration of NMDA (100 µM) elicited the current more rapidly. The additional current was not dependent on Ca²⁺, network activity, or metabotropic NMDAR function and did not persist on agonist removal. Voltage ramps revealed no alteration of either reversal potential or NMDA-elicited conductance between -30 mV and +50 mV. The result was a more linear NMDA current-voltage relationship. The current linearization was also induced in interneurons and in mature dentate granule neurons but not immature dentate granule cells, dissociated cultured hippocampal neurons, or nucleated patches excised from CA1 pyramidal neurons. Comparative simulations of NMDA application to a CA1 pyramidal neuron and to a cultured neuron revealed that linearization can be explained by space-clamp errors arising from gradual recruitment of distal dendritic NMDARs. We conclude that persistent secondary currents do not strongly contribute to NMDAR responses in juvenile mouse hippocampus and careful discernment is needed to exclude contributions of clamp artifacts to apparent secondary currents.NEW & NOTEWORTHY We report that upon sustained activation of NMDARs in juvenile mouse hippocampal neurons there is apparent loss of Mg²⁺ block at negative membrane potentials. However, the phenomenon is explained by loss of dendritic voltage clamp, leading to a linear current-voltage relationship. Our results give a specific example of how spatial voltage errors in voltage-clamp recordings can readily be misinterpreted as biological modulation.

When complex neuronal structures may not matter

Much work has explored animal-to-animal variability and compensation in ion channel expression. Yet, little is known regarding the physiological consequences of morphological variability. We quantify animal-to-animal variability in cable lengths (CV = 0.4) and branching patterns in the Gastric Mill (GM) neuron, an identified neuron type with highly-conserved physiological properties in the crustacean stomatogastric ganglion (STG) of Cancer borealis. We examined passive GM electrotonic structure by measuring the amplitudes and apparent reversal potentials (E_revs) of inhibitory responses evoked with focal glutamate photo-uncaging in the presence of TTX. Apparent E_revs were relatively invariant across sites (mean CV ± SD = 0.04 ± 0.01; 7–20 sites in each of 10 neurons), which ranged between 100–800 µm from the somatic recording site. Thus, GM neurons are remarkably electrotonically compact (estimated λ > 1.5 mm). Electrotonically compact structures, in consort with graded transmission, provide an elegant solution to observed morphological variability in the STG.

DOI:http://dx.doi.org/10.7554/eLife.23508.001

Radiation damage to neuronal cells: Simulating the energy deposition and water radiolysis in a small neural network

Radiation damage to the central nervous system (CNS) has been an on-going challenge for the last decades primarily due to the issues of brain radiotherapy and radiation protection for astronauts during space travel. Although recent findings revealed a number of molecular mechanisms associated with radiation-induced impairments in behaviour and cognition, some uncertainties exist in the initial neuronal cell injury leading to the further development of CNS malfunction. The present study is focused on the investigation of early biological damage induced by ionizing radiations in a sample neural network by means of modelling physico-chemical processes occurring in the medium after exposure. For this purpose, the stochastic simulation of incident particle tracks and water radiation chemistry was performed in realistic neuron phantoms constructed using experimental data on cell morphology. The applied simulation technique is based on using Monte-Carlo processes of the Geant4-DNA toolkit. The calculations were made for proton, ¹²C, and ⁵⁶Fe particles of different energy within a relatively wide range of linear energy transfer values from a few to hundreds of keV/μm. The results indicate that the neuron morphology is an important factor determining the accumulation of microscopic radiation dose and water radiolysis products in neurons. The estimation of the radiolytic yields in neuronal cells suggests that the observed enhancement in the levels of reactive oxygen species may potentially lead to oxidative damage to neuronal components disrupting the normal communication between cells of the neural network.

Estimation of the physical properties of neurons and glial cells using dielectrophoresis crossover frequency

We successfully determine the ranges of dielectric permittivity, cytoplasm conductivity, and specific membrane capacitance of mouse hippocampal neuronal and glial cells using dielectrophoresis (DEP) crossover frequency (CF). This methodology is based on the simulation of CF directly from the governing equation of a dielectric model of mammalian cells, as well as the measurements of DEP CFs of mammalian cells in different suspension media with different conductivities, based on a simple experimental setup. Relationships between the properties of cells and DEP CF, as demonstrated by theoretical analysis, enable the simultaneous estimation of three properties by a straightforward fitting procedure based on experimentally measured CFs. We verify the effectiveness and accuracy of this approach for primary mouse hippocampal neurons and glial cells, whose dielectric properties, previously, have not been accurately determined. The estimated neuronal properties significantly narrow the value ranges available from the literature. Additionally, the estimated glial cell properties are a valuable addition to the scarce information currently available about this type of cell. This methodology is applicable to any type of cultured cell that can be subjected to both positive and negative dielectrophoresis.

Computational Modeling of Adult Neurogenesis

The restriction of adult neurogenesis to only a handful of regions of the brain is suggestive of some shared requirement for this dramatic form of structural plasticity. However, a common driver across neurogenic regions has not yet been identified. Computational studies have been invaluable in providing insight into the functional role of new neurons; however, researchers have typically focused on specific scales ranging from abstract neural networks to specific neural systems, most commonly the dentate gyrus area of the hippocampus. These studies have yielded a number of diverse potential functions for new neurons, ranging from an impact on pattern separation to the incorporation of time into episodic memories to enabling the forgetting of old information. This review will summarize these past computational efforts and discuss whether these proposed theoretical functions can be unified into a common rationale for why neurogenesis is required in these unique neural circuits.

The Global Spike: Conserved Dendritic Properties Enable Unique Ca2+ Spike Generation in Low-Threshold Spiking Neurons

Low-threshold Ca²⁺ spikes (LTS) are an indispensible signaling mechanism for neurons in areas including the cortex, cerebellum, basal ganglia, and thalamus. They have critical physiological roles and have been strongly associated with disorders including epilepsy, Parkinson's disease, and schizophrenia. However, although dendritic T-type Ca²⁺ channels have been implicated in LTS generation, because the properties of low-threshold spiking neuron dendrites are unknown, the precise mechanism has remained elusive. Here, combining data from fluorescence-targeted dendritic recordings and Ca²⁺ imaging from low-threshold spiking cells in rat brain slices with computational modeling, the cellular mechanism responsible for LTS generation is established. Our data demonstrate that key somatodendritic electrical conduction properties are highly conserved between glutamatergic thalamocortical neurons and GABAergic thalamic reticular nucleus neurons and that these properties are critical for LTS generation. In particular, the efficiency of soma to dendrite voltage transfer is highly asymmetric in low-threshold spiking cells, and in the somatofugal direction, these neurons are particularly electrotonically compact. Our data demonstrate that LTS have remarkably similar amplitudes and occur synchronously throughout the dendritic tree. In fact, these Ca²⁺ spikes cannot occur locally in any part of the cell, and hence we reveal that LTS are generated by a unique whole-cell mechanism that means they always occur as spatially global spikes. This all-or-none, global electrical and biochemical signaling mechanism clearly distinguishes LTS from other signals, including backpropagating action potentials and dendritic Ca²⁺/NMDA spikes, and has important consequences for dendritic function in low-threshold spiking neurons.

SIGNIFICANCE STATEMENT Low-threshold Ca²⁺ spikes (LTS) are critical for important physiological processes, including generation of sleep-related oscillations, and are implicated in disorders including epilepsy, Parkinson's disease, and schizophrenia. However, the mechanism underlying LTS generation in neurons, which is thought to involve dendritic T-type Ca²⁺ channels, has remained elusive due to a lack of knowledge of the dendritic properties of low-threshold spiking cells. Combining dendritic recordings, two-photon Ca²⁺ imaging, and computational modeling, this study reveals that dendritic properties are highly conserved between two prominent low-threshold spiking neurons and that these properties underpin a whole-cell somatodendritic spike generation mechanism that makes the LTS a unique global electrical and biochemical signal in neurons.

A general homeostatic principle following lesion induced dendritic remodeling

INTRODUCTION

Neuronal death and subsequent denervation of target areas are hallmarks of many neurological disorders. Denervated neurons lose part of their dendritic tree, and are considered "atrophic", i.e. pathologically altered and damaged. The functional consequences of this phenomenon are poorly understood.

RESULTS

Using computational modelling of 3D-reconstructed granule cells we show that denervation-induced dendritic atrophy also subserves homeostatic functions: By shortening their dendritic tree, granule cells compensate for the loss of inputs by a precise adjustment of excitability. As a consequence, surviving afferents are able to activate the cells, thereby allowing information to flow again through the denervated area. In addition, action potentials backpropagating from the soma to the synapses are enhanced specifically in reorganized portions of the dendritic arbor, resulting in their increased synaptic plasticity. These two observations generalize to any given dendritic tree undergoing structural changes.

CONCLUSIONS

Structural homeostatic plasticity, i.e. homeostatic dendritic remodeling, is operating in long-term denervated neurons to achieve functional homeostasis.

Foundational dendritic processing that is independent of the cell type-specific structure in model primary neurons

It has long been known that primary neurons in the brain and spinal cord exhibit very distinctive dendritic structures. However, it remains unclear whether dendritic processing for signal propagation and channel activation over dendrites is a function of the cell type-specific dendritic structure. By applying an extended analysis of signal attenuation for the physiological distributions of synaptic inputs and active channels on dendritic branches, we first demonstrate that regardless of their specific structure, all anatomically reconstructed models of primary neurons display a similar pattern of directional signal attenuation and locational channel activation over their dendrites. Then, using a novel modeling approach that allows direct comparison of the anatomically reconstructed primary neurons with their reduced models that exclusively retain anatomical dendritic signaling without being associated with structural specificity, we show that the reduced model can accurately predict dendritic excitability of the anatomical model in both passive and active mode. These results indicate that the directional signaling, locational excitability and their relationship are foundational features of dendritic processing that are independent of the cell type-specific structure across primary neurons.

Distinct and synergistic feedforward inhibition of pyramidal cells by basket and bistratified interneurons

Feedforward inhibition (FFI) enables pyramidal cells in area CA1 of the hippocampus (CA1PCs) to remain easily excitable while faithfully representing a broad range of excitatory inputs without quickly saturating. Despite the cortical ubiquity of FFI, its specific function is not completely understood. FFI in CA1PCs is mediated by two physiologically and morphologically distinct GABAergic interneurons: fast-spiking, perisomatic-targeting basket cells and regular-spiking, dendritic-targeting bistratified cells. These two FFI pathways might create layer-specific computational sub-domains within the same CA1PC, but teasing apart their specific contributions remains experimentally challenging. We implemented a biophysically realistic model of CA1PCs using 40 digitally reconstructed morphologies and constraining synaptic numbers, locations, amplitude, and kinetics with available experimental data. First, we validated the model by reproducing the known combined basket and bistratified FFI of CA1PCs at the population level. We then analyzed how the two interneuron types independently affected the CA1PC spike probability and timing as a function of inhibitory strength. Separate FFI by basket and bistratified respectively modulated CA1PC threshold and gain. Concomitant FFI by both interneuron types synergistically extended the dynamic range of CA1PCs by buffering their spiking response to excitatory stimulation. These results suggest testable hypotheses on the precise effects of GABAergic diversity on cortical computation.

Extracellular proteolysis in structural and functional plasticity of mossy fiber synapses in hippocampus

Brain is continuously altered in response to experience and environmental changes. One of the underlying mechanisms is synaptic plasticity, which is manifested by modification of synapse structure and function. It is becoming clear that regulated extracellular proteolysis plays a pivotal role in the structural and functional remodeling of synapses during brain development, learning and memory formation. Clearly, plasticity mechanisms may substantially differ between projections. Mossy fiber synapses onto CA3 pyramidal cells display several unique functional features, including pronounced short-term facilitation, a presynaptically expressed long-term potentiation (LTP) that is independent of NMDAR activation, and NMDA-dependent metaplasticity. Moreover, structural plasticity at mossy fiber synapses ranges from the reorganization of projection topology after hippocampus-dependent learning, through intrinsically different dynamic properties of synaptic boutons to pre- and postsynaptic structural changes accompanying LTP induction. Although concomitant functional and structural plasticity in this pathway strongly suggests a role of extracellular proteolysis, its impact only starts to be investigated in this projection. In the present report, we review the role of extracellular proteolysis in various aspects of synaptic plasticity in hippocampal mossy fiber synapses. A growing body of evidence demonstrates that among perisynaptic proteases, tissue plasminogen activator (tPA)/plasmin system, β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) and metalloproteinases play a crucial role in shaping plastic changes in this projection. We discuss recent advances and emerging hypotheses on the roles of proteases in mechanisms underlying mossy fiber target specific synaptic plasticity and memory formation.

Functional consequences of age-related morphologic changes to pyramidal neurons of the rhesus monkey prefrontal cortex

Layer 3 (L3) pyramidal neurons in the lateral prefrontal cortex (LPFC) of rhesus monkeys exhibit dendritic regression, spine loss and increased action potential (AP) firing rates during normal aging. The relationship between these structural and functional alterations, if any, is unknown. To address this issue, morphological and electrophysiological properties of L3 LPFC pyramidal neurons from young and aged rhesus monkeys were characterized using in vitro whole-cell patch-clamp recordings and high-resolution digital reconstruction of neurons. Consistent with our previous studies, aged neurons exhibited significantly reduced dendritic arbor length and spine density, as well as increased input resistance and firing rates. Computational models using the digital reconstructions with Hodgkin-Huxley and AMPA channels allowed us to assess relationships between demonstrated age-related changes and to predict physiological changes that have not yet been tested empirically. For example, the models predict that in both backpropagating APs and excitatory postsynaptic currents (EPSCs), attenuation is lower in aged versus young neurons. Importantly, when identical densities of passive parameters and voltage- and calcium-gated conductances were used in young and aged model neurons, neither input resistance nor firing rates differed between the two age groups. Tuning passive parameters for each model predicted significantly higher membrane resistance (R m ) in aged versus young neurons. This R m increase alone did not account for increased firing rates in aged models, but coupling these R m values with subtle differences in morphology and membrane capacitance did. The predicted differences in passive parameters (or parameters with similar effects) are mathematically plausible, but must be tested empirically.

Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology

The branching structures of neurons are a long-standing focus of neuroscience. Axonal and dendritic morphology affect synaptic signaling, integration, and connectivity, and their diversity reflects the computational specialization of neural circuits. Altered neuronal morphology accompanies functional changes during development, experience, aging, and disease. Technological improvements continuously accelerate high-throughput tissue processing, image acquisition, and morphological reconstruction. Digital reconstructions of neuronal morphologies allow for complex quantitative analyses that are unattainable from raw images or two-dimensional tracings. Furthermore, digitized morphologies enable computational modeling of biophysically realistic neuronal dynamics. Additionally, reconstructions generated to address specific scientific questions have the potential for continued investigations beyond the original reason for their acquisition. Facilitating multiple reuse are repositories like NeuroMorpho.Org, which ease the sharing of reconstructions. Here, we review selected scientific literature reporting the reconstruction of axonal or dendritic morphology with diverse goals including establishment of neuronal identity, examination of physiological properties, and quantification of developmental or pathological changes. These reconstructions, deposited in NeuroMorpho.Org, have since been used by other investigators in additional research, of which we highlight representative examples. This cycle of data generation, analysis, sharing, and reuse reveals the vast potential of digital reconstructions in quantitative investigations of neuronal morphology.

Theta-gamma-modulated synaptic currents in hippocampal granule cells in vivo define a mechanism for network oscillations

Theta-gamma network oscillations are thought to represent key reference signals for information processing in neuronal ensembles, but the underlying synaptic mechanisms remain unclear. To address this question, we performed whole-cell (WC) patch-clamp recordings from mature hippocampal granule cells (GCs) in vivo in the dentate gyrus of anesthetized and awake rats. GCs in vivo fired action potentials at low frequency, consistent with sparse coding in the dentate gyrus. GCs were exposed to barrages of fast AMPAR-mediated excitatory postsynaptic currents (EPSCs), primarily relayed from the entorhinal cortex, and inhibitory postsynaptic currents (IPSCs), presumably generated by local interneurons. EPSCs exhibited coherence with the field potential predominantly in the theta frequency band, whereas IPSCs showed coherence primarily in the gamma range. Action potentials in GCs were phase locked to network oscillations. Thus, theta-gamma-modulated synaptic currents may provide a framework for sparse temporal coding of information in the dentate gyrus.

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Granule cells in vivo fire action potentials sparsely but often in bursts

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Granule cells are exposed to barrages of fast excitatory postsynaptic currents

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Granule cells receive theta-coherent excitation but gamma-coherent inhibition

Age-related changes to layer 3 pyramidal cells in the rhesus monkey visual cortex

The effects of normal aging on morphologic and electrophysiologic properties of layer 3 pyramidal neurons in rhesus monkey primary visual cortex (V1) were assessed with whole-cell, patch-clamp recordings in in vitro slices. In another cohort of monkeys, the ultrastructure of synapses in the layers 2-3 neuropil of V1 was assessed using electron microscopy. Distal apical dendritic branching complexity was reduced in aged neurons, as was the total spine density, due to specific loss of mushroom spines from the apical tree and of thin spines from the basal tree. There was also an age-related decrease in the numerical density of symmetric and asymmetric synapses. In contrast to these structural changes, intrinsic membrane, action potential (AP), and excitatory and inhibitory synaptic current properties were the same in aged and young neurons. Computational modeling using morphologic reconstructions predicts that reduced dendritic complexity leads to lower attenuation of voltage outward from the soma (e.g., backpropagating APs) in aged neurons. Importantly, none of the variables that changed with age differed in neurons from cognitively impaired versus unimpaired aged monkeys. In summary, there are age-related alterations to the structural properties of V1 neurons, but these are not associated with significant electrophysiologic changes or with cognitive decline.

Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices

Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. Area V1 pyramidal neurons are much smaller than dlPFC neurons, with significantly less extensive dendritic arbors and far fewer dendritic spines. Relative to dlPFC neurons, V1 neurons have a significantly higher input resistance, depolarized resting membrane potential, and higher action potential (AP) firing rates. Most V1 neurons exhibit both phasic and regular-spiking tonic AP firing patterns, while dlPFC neurons exhibit only tonic firing. Spontaneous postsynaptic currents are lower in amplitude and have faster kinetics in V1 than in dlPFC neurons, but are no different in frequency. Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA receptor and GABA(A) receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning.

A compartmental model of linear resonance and signal transfer in dendrites

Dendrites carry signals between synapses and the soma and play a central role in neural computation. Although they contain many nonlinear ion channels, their signal-transfer properties are linear under some experimental conditions. In experiments with continuous-time inputs, a resonant linear two-port model has been shown to provide a near-perfect fit to the dendrite-to-soma input-output relationship. In this study, we focused on this linear aspect of signal transfer using impedance functions that replace biophysical channel models in order to describe the electrical properties of the dendritic membrane. The membrane impedance model of dendrites preserves the accuracy of the two-port model with minimal computational complexity. Using this approach, we demonstrate two membrane impedance profiles of dendrites that reproduced the experimentally observed two-port results. These impedance profiles demonstrate that the two-port results are compatible with different computational schemes. In addition, our model highlights how dendritic resonance can minimize the location-dependent attenuation of signals at the resonant frequency. Thus, in this model, dendrites function as linear-resonant filters that carry signals between nonlinear computational units.

Somato-dendritic morphology and dendritic signal transfer properties differentiate between fore- and hindlimb innervating motoneurons in the frog Rana esculenta

Background

The location specific motor pattern generation properties of the spinal cord along its rostro-caudal axis have been demonstrated. However, it is still unclear that these differences are due to the different spinal interneuronal networks underlying locomotions or there are also segmental differences in motoneurons innervating different limbs. Frogs use their fore- and hindlimbs differently during jumping and swimming. Therefore we hypothesized that limb innervating motoneurons, located in the cervical and lumbar spinal cord, are different in their morphology and dendritic signal transfer properties. The test of this hypothesis what we report here.

Results

Discriminant analysis classified segmental origin of the intracellularly labeled and three-dimensionally reconstructed motoneurons 100% correctly based on twelve morphological variables. Somata of lumbar motoneurons were rounder; the dendrites had bigger total length, more branches with higher branching orders and different spatial distributions of branch points. The ventro-medial extent of cervical dendrites was bigger than in lumbar motoneurons. Computational models of the motoneurons showed that dendritic signal transfer properties were also different in the two groups of motoneurons. Whether log attenuations were higher or lower in cervical than in lumbar motoneurons depended on the proximity of dendritic input to the soma. To investigate dendritic voltage and current transfer properties imposed by dendritic architecture rather than by neuronal size we used standardized distributions of transfer variables. We introduced a novel combination of cluster analysis and homogeneity indexes to quantify segmental segregation tendencies of motoneurons based on their dendritic transfer properties. A segregation tendency of cervical and lumbar motoneurons was detected by the rates of steady-state and transient voltage-amplitude transfers from dendrites to soma at all levels of synaptic background activities, modeled by varying the specific dendritic membrane resistance. On the other hand no segregation was observed by the steady-state current transfer except under high background activity.

Conclusions

We found size-dependent and size-independent differences in morphology and electrical structure of the limb moving motoneurons based on their spinal segmental location in frogs. Location specificity of locomotor networks is therefore partly due to segmental differences in motoneurons driving fore-, and hindlimbs.

New insights into the role of hilar ectopic granule cells in the dentate gyrus based on quantitative anatomic analysis and three-dimensional reconstruction

The dentate gyrus is one of two main areas of the mammalian brain where neurons are born throughout adulthood, a phenomenon called postnatal neurogenesis. Most of the neurons that are generated are granule cells (GCs), the major principal cell type in the dentate gyrus. Some adult-born granule cells develop in ectopic locations, such as the dentate hilus. The generation of hilar ectopic granule cells (HEGCs) is greatly increased in several animal models of epilepsy and has also been demonstrated in surgical specimens from patients with intractable temporal lobe epilepsy (TLE). Herein we review the results of our quantitative neuroanatomic analysis of HEGCs that were filled with Neurobiotin following electrophysiologic characterization in hippocampal slices. The data suggest that two types of HEGCs exist, based on a proximal or distal location of the cell body relative to the granule cell layer, and based on the location of most of the dendrites, in the molecular layer or hilus. Three-dimensional reconstruction revealed that the dendrites of distal HEGCs can extend along the transverse and longitudinal axis of the hippocampus. Analysis of axons demonstrated that HEGCs have projections that contribute to the normal mossy fiber innervation of CA3 as well as the abnormal sprouted fibers in the inner molecular layer of epileptic rodents (mossy fiber sprouting). These data support the idea that HEGCs could function as a "hub" cell in the dentate gyrus and play a critical role in network excitability.

Cellular anatomy, physiology and epileptiform activity in the CA3 region of Dcx knockout mice: a neuronal lamination defect and its consequences

We report data on the neuronal form, synaptic connectivity, neuronal excitability and epileptiform population activities generated by the hippocampus of animals with an inactivated doublecortin gene. The protein product of this gene affects neuronal migration during development. Human doublecortin (DCX) mutations are associated with lissencephaly, subcortical band heterotopia, and syndromes of intellectual disability and epilepsy. In Dcx(-/Y) mice, CA3 hippocampal pyramidal cells are abnormally laminated. The lamination defect was quantified by measuring the extent of the double, dispersed or single pyramidal cell layer in the CA3 region of Dcx(-/Y) mice. We investigated how this abnormal lamination affected two groups of synapses that normally innervate defined regions of the CA3 pyramidal cell membrane. Numbers of parvalbumin (PV)-containing interneurons, which contact peri-somatic sites, were not reduced in Dcx(-/Y) animals. Pyramidal cells in double, dispersed or single layers received PV-containing terminals. Excitatory mossy fibres which normally target proximal CA3 pyramidal cell apical dendrites apparently contact CA3 cells of both layers in Dcx(-/Y) animals but sometimes on basilar rather than apical dendrites. The dendritic form of pyramidal cells in Dcx(-/Y) animals was altered and pyramidal cells of both layers were more excitable than their counterparts in wild-type animals. Unitary inhibitory field events occurred at higher frequency in Dcx(-/Y) animals. These differences may contribute to a susceptibility to epileptiform activity: a modest increase in excitability induced both interictal and ictal-like discharges more effectively in tissue from Dcx(-/Y) mice than from wild-type animals.

Non-homogeneous stereological properties of the rat hippocampus from high-resolution 3D serial reconstruction of thin histological sections

Integrating hippocampal anatomy from neuronal dendrites to whole system may help elucidate its relation to function. Toward this aim, we digitally traced the cytoarchitectonic boundaries of the dentate gyrus (DG) and areas CA3/CA1 throughout their entire longitudinal extent from high-resolution images of thin cryostatic sections of adult rat brain. The 3D computational reconstruction identified all isotropic 16 μm voxels with appropriate subregions and layers (http://krasnow1.gmu.edu/cn3/hippocampus3d). Overall, DG, CA3, and CA1 occupied comparable volumes (15.3, 12.2, and 18.8 mm(3), respectively), but displayed substantial rostrocaudal volumetric gradients: CA1 made up more than half of the posterior hippocampus, whereas CA3 and DG were more prominent in the anterior regions. The CA3/CA1 ratio increased from ∼0.4 to ∼1 septo-temporally because of a specific change in stratum radiatum volume. Next we virtually embedded 1.8 million neuronal morphologies stochastically resampled from 244 digital reconstructions, emulating the dense packing of granular and pyramidal layers, and appropriately orienting the principal dendritic axes relative to local curvature. The resulting neuropil occupancy reproduced recent electron microscopy data measured in a restricted location. Extension of this analysis across each layer and subregion over the whole hippocampus revealed highly non-homogeneous dendritic density. In CA1, dendritic occupancy was >60% higher temporally than septally (0.46 vs. 0.28, s.e.m. ∼0.05). CA3 values varied both across subfields (from 0.35 in CA3b/CA3c to 0.50 in CA3a) and layers (0.48, 0.34, and 0.27 in oriens, radiatum, and lacunosum-moleculare, respectively). Dendritic occupancy was substantially lower in DG, especially in the supra-pyramidal blade (0.18). The computed probability of dendrodendritic collision significantly correlated with expression of the membrane repulsion signal Down syndrome cell adhesion molecule (DSCAM). These heterogeneous stereological properties reflect and complement the non-uniform molecular composition, circuit connectivity, and computational function of the hippocampus across its transverse, longitudinal, and laminar organization.

Spatial heterogeneity of passive electrical transfer properties of neuronal dendrites due to their metrical asymmetry

The complex and diverse geometry of neuronal dendrites determines the different morphological types of neurons and influences the generation of complex and diverse discharge patterns at the cell output. The recent finding that each temporal pattern has its spatial signature in the form of a combination of high- and low-depolarization states of asymmetrical dendritic branches with active membrane properties raises the question of the nature of such characteristic spatial heterogeneity of electrical states. To answer this, we consider passive dendrites as a conventional reference case using the known current transfer functions, which we complete by corresponding parametric sensitivity functions. These functions for metrically asymmetrical bifurcations of different sizes, as the simplest elements constituting arborizations of arbitrary geometry, are analyzed under different membrane conductivity conditions related to the intensity of activation of ion channels. Characteristic relationships are obtained on the one hand among the size (branch lengths), metrical asymmetry (difference between sister branches in length and/or diameter), and membrane conductivity, and on the other hand, for the difference between the branches in their current transfer effectiveness as an indicator of their electrical asymmetry (heterogeneity). These relationships (i) allow the introduction of a biophysically based criterion for the electrical distinction between metrically asymmetrical branches, (ii) show how the difference first increases and then decreases with increasing membrane conductivity, and (iii) show that the greatest electrical heterogeneity occurs in a lower or higher range of conductivity, corresponding to larger or smaller bifurcation size. As a consequence, the characteristic low-, medium-, and high-conductance states are derived such that metrically asymmetrical parts of simple and complex trees are electrically distinct when the membrane conductivity lies in the size-related medium range, and indistinct otherwise.

Adult hippocampal neurogenesis and plasticity in the infrapyramidal bundle of the mossy fiber projection: I. Co-regulation by activity

Besides the massive plasticity at the level of synapses, we find in the hippocampus of adult mice and rats two systems with very strong macroscopic structural plasticity: adult neurogenesis, that is the lifelong generation of new granule cells, and dynamic changes in the mossy fibers linking the dentate gyrus to area CA3. In particular the anatomy of the infrapyramidal mossy fiber tract (IMF) changes in response to a variety of extrinsic and intrinsic stimuli. Because mossy fibers are the axons of granule cells, the question arises whether these two types of plasticity are linked. Using immunohistochemistry for markers associated with axonal growth and pro-opiomelanocortin (POMC)–GFP mice to visualize the post-mitotic maturation phase of adult hippocampal neurogenesis, we found that newly generated mossy fibers preferentially but not exclusively contribute to the IMF. The neurogenic stimulus of an enriched environment increased the volume of the IMF. In addition, the IMF grew with a time course consistent with axonal outgrowth from the newborn neurons after the induction of neurogenic seizures using kainate. These results indicate that two aspects of plasticity in the adult hippocampus, mossy fiber size and neurogenesis, are related and may share underlying mechanisms. In a second part of this study, published separately (Krebs et al., 2011) we have addressed the question of whether there is a shared genetics underlying both traits.

Potential Synaptic Connectivity of Different Neurons onto Pyramidal Cells in a 3D Reconstruction of the Rat Hippocampus

Most existing connectomic data and ongoing efforts focus either on individual synapses (e.g., with electron microscopy) or on regional connectivity (tract tracing). An individual pyramidal cell (PC) extends thousands of synapses over macroscopic distances (∼cm). The contrasting requirements of high-resolution and large field of view make it too challenging to acquire the entire synaptic connectivity for even a single typical cortical neuron. Light microscopy can image whole neuronal arbors and resolve dendritic branches. Analyzing connectivity in terms of close spatial appositions between axons and dendrites could thus bridge the opposite scales, from synaptic level to whole systems. In the mammalian cortex, structural plasticity of spines and boutons makes these “potential synapses” functionally relevant to learning capability and memory capacity. To date, however, potential synapses have only been mapped in the surrounding of a neuron and relative to its local orientation rather than in a system-level anatomical reference. Here we overcome this limitation by estimating the potential connectivity of different neurons embedded into a detailed 3D reconstruction of the rat hippocampus. Axonal and dendritic trees were oriented with respect to hippocampal cytoarchitecture according to longitudinal and transversal curvatures. We report the potential connectivity onto PC dendrites from the axons of a dentate granule cell, three CA3 PCs, one CA2 PC, and 13 CA3b interneurons. The numbers, densities, and distributions of potential synapses were analyzed in each sub-region (e.g., CA3 vs. CA1), layer (e.g., oriens vs. radiatum), and septo-temporal location (e.g., dorsal vs. ventral). The overall ratio between the numbers of actual and potential synapses was ∼0.20 for the granule and CA3 PCs. All potential connectivity patterns are strikingly dependent on the anatomical location of both pre-synaptic and post-synaptic neurons.

Morphometry of hilar ectopic granule cells in the rat

Granule cell (GC) neurogenesis in the dentate gyrus (DG) does not always proceed normally. After severe seizures (e.g., status epilepticus [SE]) and some other conditions, newborn GCs appear in the hilus. Hilar ectopic GCs (EGCs) can potentially provide insight into the effects of abnormal location and seizures on GC development. Additionally, hilar EGCs that develop after SE may contribute to epileptogenesis and cognitive impairments that follow SE. Thus, it is critical to understand how EGCs differ from normal GCs. Relatively little morphometric information is available on EGCs, especially those restricted to the hilus. This study quantitatively analyzed the structural morphology of hilar EGCs from adult male rats several months after pilocarpine-induced SE, when they are considered to have chronic epilepsy. Hilar EGCs were physiologically identified in slices, intracellularly labeled, processed for light microscopic reconstruction, and compared to GC layer GCs, from both the same post-SE tissue and the NeuroMorpho database (normal GCs). Consistently, hilar EGC and GC layer GCs had similar dendritic lengths and field sizes, and identifiable apical dendrites. However, hilar EGC dendrites were topologically more complex, with more branch points and tortuous dendritic paths. Three-dimensional analysis revealed that, remarkably, hilar EGC dendrites often extended along the longitudinal DG axis, suggesting increased capacity for septotemporal integration. Axonal reconstruction demonstrated that hilar EGCs contributed to mossy fiber sprouting. This combination of preserved and aberrant morphological features, potentially supporting convergent afferent input to EGCs and broad, divergent efferent output, could help explain why the hilar EGC population could impair DG function.

The mechanisms of the strong inhibitory modulation of long-term potentiation in the rat dentate gyrus

The hippocampus is essential for the formation of certain types of memory, and synaptic plasticity such as long-term potentiation (LTP) is widely accepted as a cellular basis of hippocampus-dependent memory. Although LTP in both perforant path-dentate gyrus (DG) granule cell and CA3-CA1 pyramidal cell synapses is similarly dependent on activation of postsynaptic N-methyl-D-aspartate receptors, several reports suggest that modulation of LTP by γ-aminobutyric acid (GABA) receptor-mediated inhibitory inputs is stronger in perforant path-DG granule cell synapses. However, little is known about how different the mechanism and physiological relevance of the GABAergic modulation of LTP induction are among different brain regions. We confirmed that the action of GABA(A) receptor antagonists on LTP was more prominent in the DG, and explored the mechanism introducing such difference by examining two types of GABA(A) receptor-mediated inhibition, i.e. synaptic and tonic inhibition. As synaptic inhibition, we compared inhibitory vs. excitatory monosynaptic responses and their summation during an LTP-inducing stimulus, and found that the balance of the summated postsynaptic currents was biased toward inhibition in the DG. As tonic inhibition, or sustained activation of extrasynaptic GABA(A) receptors by ambient GABA, we measured the change in holding currents of the postsynaptic cells induced by GABA(A) receptor antagonists, and found that the tonic inhibition was significantly stronger in the DG. Furthermore, we found that tonic inhibition was associated with LTP modulation. Our results suggest that both the larger tonic inhibition and the larger inhibitory/excitatory summation balance during conditioning are involved in the stronger inhibitory modulation of LTP in the DG.

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.

Degenerative abnormalities in transgenic neocortical neuropeptide Y interneurons expressing tau-green fluorescent protein

The introduction of a reporter gene into bacterial artificial chromosome (BAC) constructs allows a rapid identification of the cell type expressing the gene of interest. Here we used BAC transgenic mice expressing a tau-sapphire green fluorescent protein (GFP) under the transcriptional control of the neuropeptide Y (NPY) genomic sequence to characterize morphological and electrophysiological properties of NPY-GFP interneurons of the mouse juvenile primary somatosensory cortex. Electrophysiological whole-cell recordings and biocytin injections were performed to allow the morphological reconstruction of the recorded neurons in three dimensions. Ninety-six recorded NPY-GFP interneurons were compared with 39 wild-type (WT) NPY interneurons, from which 23 and 19 were reconstructed, respectively. We observed that 91% of the reconstructed NPY-GFP interneurons had developed an atypical axonal swelling from which emerge numerous ramifications. These abnormalities were very heterogeneous in shape and size. They were immunoreactive for the microtubule-associated protein tau and the lysosomal-associated membrane protein 1 (LAMP1). Moreover, an electron microscopic analysis revealed the accumulation of numerous autophagic and lysosomal vacuoles in swollen axons. Morphological analyses of NPY-GFP interneurons also indicated that their somata were smaller, their entire dendritic tree was thickened and presented a restricted spatial distribution in comparison with WT NPY interneurons. Finally, the morphological defects observed in NPY-GFP interneurons appeared to be associated with alterations of their electrophysiological intrinsic properties. Altogether, these results demonstrate that NPY-GFP interneurons developed dystrophic axonal swellings and severe morphological and electrophysiological defects that could be due to the overexpression of tau-coupled reporter constructs.

The role of ongoing dendritic oscillations in single-neuron dynamics

The dendritic tree contributes significantly to the elementary computations a neuron performs while converting its synaptic inputs into action potential output. Traditionally, these computations have been characterized as both temporally and spatially localized. Under this localist account, neurons compute near-instantaneous mappings from their current input to their current output, brought about by somatic summation of dendritic contributions that are generated in functionally segregated compartments. However, recent evidence about the presence of oscillations in dendrites suggests a qualitatively different mode of operation: the instantaneous phase of such oscillations can depend on a long history of inputs, and under appropriate conditions, even dendritic oscillators that are remote may interact through synchronization. Here, we develop a mathematical framework to analyze the interactions of local dendritic oscillations and the way these interactions influence single cell computations. Combining weakly coupled oscillator methods with cable theoretic arguments, we derive phase-locking states for multiple oscillating dendritic compartments. We characterize how the phase-locking properties depend on key parameters of the oscillating dendrite: the electrotonic properties of the (active) dendritic segment, and the intrinsic properties of the dendritic oscillators. As a direct consequence, we show how input to the dendrites can modulate phase-locking behavior and hence global dendritic coherence. In turn, dendritic coherence is able to gate the integration and propagation of synaptic signals to the soma, ultimately leading to an effective control of somatic spike generation. Our results suggest that dendritic oscillations enable the dendritic tree to operate on more global temporal and spatial scales than previously thought; notably that local dendritic activity may be a mechanism for generating on-going whole-cell voltage oscillations.

A central issue in biology is how local processes yield global consequences. This is especially relevant for neurons since these spatially extended cells process local synaptic inputs to generate global action potential output. The dendritic tree of a neuron, which receives most of the inputs, expresses ion channels that can generate nonlinear dynamics. A prominent phenomenon resulting from such ion channels are voltage oscillations. The distribution of the active membrane channels throughout the cell is often highly non-uniform. This can turn the dendritic tree into a network of sparsely spaced local oscillators. Here we analyze whether local dendritic oscillators can produce cell-wide voltage oscillations. Our mathematical theory shows that indeed even when the dendritic oscillators are weakly coupled, they lock their phases and give global oscillations. We show how the biophysical properties of the dendrites determine the global locking and how it can be controlled by synaptic inputs. As a consequence of global locking, even individual synaptic inputs can affect the timing of action potentials. In fact, dendrites locking in synchrony can lead to sustained firing of the cell. We show that dendritic trees can be bistable, with dendrites locking in either synchrony or asynchrony, which may provide a novel mechanism for single cell-based memory.

Quantitative transcriptional neuroanatomy of the rat hippocampus: evidence for wide-ranging, pathway-specific heterogeneity among three principal cell layers

We have used laser-capture microdissection and microarray hybridization to characterize gene expression in the three principal neuron layers of rat hippocampus. Correlative and clustering analyses revealed all three layers to be easily differentiated from one another based on gene expression profile alone. A greater disparity in gene expression exists between dentate granule and pyramidal cell layers, reflecting phenotypic and ontological differences between those cell populations. Remarkably, the level of more than 45% of expressed transcripts was significantly different among the three neuron populations, with more than a third of those (>1,000 transcripts) being at least twofold different between layers. Even CA1 and CA3 pyramidal cell layers were dramatically different on a transcriptional level with a separate analysis indicating that nearly 20% of transcripts are differentially expressed between them. Only a small number of transcripts were specific for a given hippocampal cell layer, suggesting that functional differences are more likely secondary to wide-ranging expression differences of modest magnitude rather than very large disparities in a few genes. Categorical analysis of transcript abundance revealed concerted differences in gene expression among the three cell layers referable to specific cellular pathways. For instance, transcripts encoding proteins involved in glucose metabolism are most highly expressed in the CA3 pyramidal layer, which may reflect an underlying greater metabolic rate of these neurons and partially explain their exquisite vulnerability to seizure-induced damage. Conversely, transcripts related to MAP kinase signaling pathways and transcriptional regulator activity are prominent in the dentate granule cell layer, which could contribute to its resistance to damage following seizure activity by positioning these neurons to respond to external stimuli by altering transcription. Taken together, these data suggest that unique physiological characteristics of major cell layers, such as neuronal activity, neuronal plasticity, and vulnerability to neurodegeneration, are reflected in substantial transcriptional heterogeneity within the hippocampus.

Partial kindling induces neurogenesis, activates astrocytes and alters synaptic morphology in the dentate gyrus of freely moving adult rats

A partial kindling procedure was used to investigate the correlation between focal seizure development and changes in dendritic spine morphology, ongoing neurogenesis and reactive astrogliosis in the adult rat dentate gyrus (DG). The processes of neurogenesis and astrogliosis were investigated using markers for doublecortin (DCX), 5-bromo-2-deoxyuridine (BrdU) and glial fibrillary acidic protein (GFAP). Our data demonstrate that mild focal seizures induce a complex series of cellular events in the DG one day after cessation of partial rapid kindling stimulation consisting (in comparison to control animals that were electrode implanted but unkindled), firstly, of an increase in the number of postmitotic BrdU labeled cells, and secondly, an increase in the number of DCX labeled cells, mainly in subgranular zone. Ultrastructural changes were examined using qualitative electron microscope analysis and 3-D reconstructions of both dendritic spines and postsynaptic densities. Typical features of kindling in comparison to control tissue included translocation of mitochondria to the base of the dendritic spine stalks; a migration of multivesicular bodies into mushroom dendritic spines, and most notably formation of "giant" spinules originating from the head of the spines of DG neurons. These morphological alterations arise at seizure stages 2-3 (focal seizures) in the absence of signs of the severe generalized seizures that are generally recognized as potentially harmful for neuronal cells. We suggest that an increase in ongoing neurogenesis, reactive astrogliosis and dendritic spine reorganization in the DG is the crucial step in the chain of events leading to the progressive development of seizure susceptibility in hippocampal circuits.

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.

Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells

In most neurons, Na+ channels in the axon are complemented by others localized in the soma and dendrites to ensure spike back-propagation. However, cerebellar granule cells are neurons with simplified architecture in which the dendrites are short and unbranched and a single thin ascending axon travels toward the molecular layer before bifurcating into parallel fibers. Here we show that in cerebellar granule cells, Na+ channels are enriched in the axon, especially in the hillock, but almost absent from soma and dendrites. The impact of this channel distribution on neuronal electroresponsiveness was investigated by multi-compartmental modeling. Numerical simulations indicated that granule cells have a compact electrotonic structure allowing excitatory postsynaptic potentials to diffuse with little attenuation from dendrites to axon. The spike arose almost simultaneously along the whole axonal ascending branch and invaded the hillock the activation of which promoted spike back-propagation with marginal delay (<200 micros) and attenuation (<20 mV) into the somato-dendritic compartment. These properties allow granule cells to perform sub-millisecond coincidence detection of pre- and postsynaptic activity and to rapidly activate Purkinje cells contacted by the axonal ascending branch.

Live Neuron Morphology Automatically Reconstructed From Multiphoton and Confocal Imaging Data

We have developed a fully automated procedure for extracting dendritic morphology from multiple three-dimensional image stacks produced by laser scanning microscopy. By eliminating human intervention, we ensure that the results are objective, quickly generated, and accurate. The software suite accounts for typical experimental conditions by reducing background noise, removing pipette artifacts, and aligning multiple overlapping image stacks. The output morphology is appropriate for simulation in compartmental simulation environments. In this report, we validate the utility of this procedure by comparing its performance on live neurons and test specimens with other fully and semiautomated reconstruction tools.

A classification method to distinguish cell-specific responses elicited by current pulses in hippocampal CA1 pyramidal cells

The suprathreshold electrophysiological responses of pyramidal cells have been grouped into large classes such as bursting and spiking. However, it is not known whether, within a class, response variability ranges uniformly across all cells or whether each cell has a unique and consistent profile that can be differentiated. A major difficulty when comparing suprathreshold responses is that slight variations in spike timing in otherwise very similar traces render traditional metrics ineffective. To address these issues, we developed a novel distance measure based on fiducial points to quantify the similarity among traces with trains of action potentials and applied it together with classification techniques to a set of in vitro patch clamp recordings from CA1 pyramidal cells. We tested if responses to repeated current stimulation of a given cell would cluster together yet remain distinct from those of other cells. We found that depolarizing and hyperpolarizing current pulses elicited responses in each cell that clustered and were systematically distinguishable from responses in other cells. The fiducial-point distance measure was more effective than other methods based on spike times and voltage-gradient phase planes. Depolarizing traces were more reliably differentiated than hyperpolarizing traces, and combining both scores was even more effective. These results suggest that each CA1 pyramidal cell has unique properties that can be detected and quantified with methods discussed here. This uniqueness may be due to slight variations in morphology or membrane channel densities and kinetics, or to large, coordinated variations in these elements. Ascertaining the actual sources and their degree of variability is important when constructing network models of neural function to ensure that key mechanisms are robust in the face of variations within these ranges. The analytical tools presented here can assist in constructing detailed cell models to match experimental records to elucidate the sources of electrophysiological variability in neurons.