Passive electrotonic properties of rat hippocampal CA3 interneurones

Unveiling the capabilities of bipolar conical channels in neuromorphic iontronics

Conical channels filled with an aqueous electrolyte have been proposed as promising candidates for iontronic neuromorphic circuits. This is facilitated by a novel analytical model for the internal channel dynamics [T. M. Kamsma, W. Q. Boon, T. ter Rele, C. Spitoni and R. van Roij, Phys. Rev. Lett., 2023, 130(26), 268401], the relative ease of fabrication of conical channels, and the wide range of achievable memory retention times by varying the channel lengths. In this work, we demonstrate that the analytical model for conical channels can be generalized to channels with an inhomogeneous surface charge distribution, which we predict to exhibit significantly stronger current rectification and more pronounced memristive properties in the case of bipolar channels, i.e. channels where the tip and base carry a surface charge of opposite sign. Additionally, we show that the use of bipolar conical channels in a previously proposed iontronic circuit features hallmarks of neuronal communication, such as all-or-none action potentials and spike train generation. Bipolar channels allow, however, for circuit parameters in the range of their biological analogues, and exhibit membrane potentials that match well with biological mammalian action potentials, further supporting their potential biocompatibility.

Seeing beyond the spikes: reconstructing the complete spatiotemporal membrane potential distribution from paired intra- and extracellular recordings

Although electrophysiologists have been recording intracellular neural activity routinely ever since the ground-breaking work of Hodgkin and Huxley, and extracellular multichannel electrodes have also been used frequently and extensively, a practical experimental method to track changes in membrane potential along a complete single neuron is still lacking. Instead of obtaining multiple intracellular measurements on the same neuron, we propose an alternative method by combining single-channel somatic patch-clamp and multichannel extracellular potential recordings. In this work, we show that it is possible to reconstruct the complete spatiotemporal distribution of the membrane potential of a single neuron with the spatial resolution of an extracellular probe during action potential generation. Moreover, the reconstruction of the membrane potential allows us to distinguish between the two major but previously hidden components of the current source density (CSD) distribution: the resistive and the capacitive currents. This distinction provides a clue to the clear interpretation of the CSD analysis, because the resistive component corresponds to transmembrane ionic currents (all the synaptic, voltage-sensitive and passive currents), whereas capacitive currents are considered to be the main contributors of counter-currents. We validate our model-based reconstruction approach on simulations and demonstrate its application to experimental data obtained in vitro via paired extracellular and intracellular recordings from a single pyramidal cell of the rat hippocampus. In perspective, the estimation of the spatial distribution of resistive membrane currents makes it possible to distiguish between active and passive sinks and sources of the CSD map and the localization of the synaptic input currents, which make the neuron fire. KEY POINTS: A new computational method is introduced to calculate the unbiased current source density distribution on a single neuron with known morphology. The relationship between extracellular and intracellular electric potential is determined via mathematical formalism, and a new reconstruction method is applied to reveal the full spatiotemporal distribution of the membrane potential and the resistive and capacitive current components. The new reconstruction method was validated on simulations. Simultaneous and colocalized whole-cell patch-clamp and multichannel silicon probe recordings were performed from the same pyramidal neuron in the rat hippocampal CA1 region, in vitro. The method was applied in experimental measurements and returned precise and distinctive characteristics of various intracellular phenomena, such as action potential generation, signal back-propagation and the initial dendritic depolarization preceding the somatic action potential.

A multimodal 3D neuro-microphysiological system with neurite-trapping microelectrodes

Three-dimensional cell technologies as pre-clinical models are emerging tools for mimicking the structural and functional complexity of the nervous system. The accurate exploration of phenotypes in engineered 3D neuronal cultures, however, demands morphological, molecular and especially functional measurements. Particularly crucial is measurement of electrical activity of individual neurons with millisecond resolution. Current techniques rely on customized electrophysiological recording set-ups, characterized by limited throughput and poor integration with other readout modalities. Here we describe a novel approach, using multiwell glass microfluidic microelectrode arrays, allowing non-invasive electrical recording from engineered 3D neural tissues. We demonstrate parallelized studies with reference compounds, calcium imaging and optogenetic stimulation. Additionally, we show how microplate compatibility allows automated handling and high-content analysis of human induced pluripotent stem cell-derived neurons. This microphysiological platform opens up new avenues for high-throughput studies on the functional, morphological and molecular details of neurological diseases and their potential treatment by therapeutic compounds.

Prediction of Neural Diameter From Morphology to Enable Accurate Simulation

Accurate neuron morphologies are paramount for computational model simulations of realistic neural responses. Over the last decade, the online repository NeuroMorpho.Org has collected over 140,000 available neuron morphologies to understand brain function and promote interaction between experimental and computational research. Neuron morphologies describe spatial aspects of neural structure; however, many of the available morphologies do not contain accurate diameters that are essential for computational simulations of electrical activity. To best utilize available neuron morphologies, we present a set of equations that predict dendritic diameter from other morphological features. To derive the equations, we used a set of NeuroMorpho.org archives with realistic neuron diameters, representing hippocampal pyramidal, cerebellar Purkinje, and striatal spiny projection neurons. Each morphology is separated into initial, branching children, and continuing nodes. Our analysis reveals that the diameter of preceding nodes, Parent Diameter, is correlated to diameter of subsequent nodes for all cell types. Branching children and initial nodes each required additional morphological features to predict diameter, such as path length to soma, total dendritic length, and longest path to terminal end. Model simulations reveal that membrane potential response with predicted diameters is similar to the original response for several tested morphologies. We provide our open source software to extend the utility of available NeuroMorpho.org morphologies, and suggest predictive equations may supplement morphologies that lack dendritic diameter and improve model simulations with realistic dendritic diameter.

Small universal spiking neural P systems with dendritic/axonal delays and dendritic trunk/feedback

In spiking neural P (SN P) systems, neurons are interconnected by means of synapses, and they use spikes to communicate with each other. However, in biology, the complex structure of dendritic tree is also an important part in the communication scheme between neurons since these structures are linked to advanced neural process such as learning and memory formation. In this work, we present a new variant of the SN P systems inspired by diverse dendrite and axon phenomena such as dendritic feedback, dendritic trunk, dendritic delays and axonal delays, respectively. This new variant is referred to as a spiking neural P system with dendritic and axonal computation (DACSN P system). Specifically, we include experimentally proven biological features in the current SN P systems to reduce the computational complexity of the soma by providing it with stable firing patterns through dendritic delays, dendritic feedback and axonal delays. As a consequence, the proposed DACSN P systems use the minimum number of synapses and neurons with simple and homogeneous standard spiking rules. Here, we study the computational capabilities of a DACSN P system. In particular, we prove that DACSN P systems with dendritic and axonal behavior are universal as both number-accepting/generating devices. In addition, we constructed a small universal SN P system using 39 neurons with standard spiking rules to compute any Turing computable function.

Functional expression of TrkB receptors on interneurones and pyramidal cells of area CA3 of the rat hippocampus

The dentate gyrus and hippocampal area CA3 region of the mammalian brain contains the highest levels of brain-derived neurotrophic factor (BDNF) and its canonical membrane receptor, tropomyosin-related kinase B (TrkB). Therefore, the present study examines the expression and physiological responses triggered by activation of TrkB on hippocampal area CA3 interneurones and pyramidal cells of the rat hippocampus. Triple immunolabelling for TrkB, glutamate decarboxylase 67, and the calcium-binding proteins parvalbumin, calbindin or calretinin confirms the somatic expression of TrkB in all CA3 sublayers. TrkB-positive interneurones with fast-spiking discharge are restricted to strata oriens and lucidum, whereas regular-spiking interneurones are found in the strata lucidum, radiatum and lacunosum-moleculare. Activation of TrkB receptors with 7,8-dihydroxyflavone (DHF) modulates amplitude and frequency of spontaneous synaptic currents recorded from CA3 interneurones. Furthermore, the isolated excitatory postsynaptic currents (EPSC) of CA3 interneurones evoked by the mossy fibres (MF) or commissural/associational (C/A) axons, show input-specific synaptic potentiation in response to TrkB stimulation. On CA3 pyramidal cells, stimulation with DHF potentiates the MF synaptic transmission and increases the MF-EPSP - spike coupling. The latter exhibits a dramatic increase when picrotoxin is bath perfused after DHF, indicating that local interneurones restrain the excitability mediated by activation of TrkB. Therefore, we propose that release of BDNF on area CA3 reshapes the output of this hippocampal region by simultaneous activation of TrkB on GABAergic interneurones and pyramidal cells.

Flexible neural connectivity under constraints on total connection strength

Neural computation is determined by neurons’ dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron’s total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.

High-throughput electron microscopic anatomical experiments have begun to yield detailed maps of neural circuit connectivity. Uncovering the principles that govern these circuit structures is a major challenge for systems neuroscience. Healthy neural circuits must be able to perform computational tasks while satisfying physiological constraints. Those constraints can restrict a neuron’s possible connectivity, and thus potentially restrict its computation. Here we examine simple models of constraints on total synaptic weights, and calculate the number of circuit configurations they allow: a simple measure of their computational flexibility. We propose probabilistic models of connectivity that weight the number of synaptic partners according to computational flexibility under a constraint and test them using recent wiring diagrams from a learning center, the mushroom body, in the fly brain. We compare constraints that fix or bound a neuron’s total connection strength to a simple random wiring null model. Of these models, the fixed total connection strength matched the overall connectivity best in mushroom bodies from both larval and adult flies. We also provide evidence suggesting that neural circuits are more flexible in early stages of development and lose this flexibility as they grow towards specialized function.

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.

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.

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.

Using a Semi-Automated Strategy to Develop Multi-Compartment Models That Predict Biophysical Properties of Interneuron-Specific 3 (IS3) Cells in Hippocampus

Determining how intrinsic cellular properties govern and modulate neuronal input–output processing is a critical endeavor for understanding microcircuit functions in the brain. However, lack of cellular specifics and nonlinear interactions prevent experiments alone from achieving this. Building and using cellular models is essential in these efforts. We focus on uncovering the intrinsic properties of mus musculus hippocampal type 3 interneuron-specific (IS3) cells, a cell type that makes GABAergic synapses onto specific interneuron types, but not pyramidal cells. While IS3 cell morphology and synaptic output have been examined, their voltage-gated ion channel profile and distribution remain unknown. We combined whole-cell patch-clamp recordings and two-photon dendritic calcium imaging to examine IS3 cell membrane and dendritic properties. Using these data as a target reference, we developed a semi-automated strategy to obtain multi-compartment models for a cell type with unknown intrinsic properties. Our approach is based on generating populations of models to capture determined features of the experimental data, each of which possesses unique combinations of channel types and conductance values. From these populations, we chose models that most closely resembled the experimental data. We used these models to examine the impact of specific ion channel combinations on spike generation. Our models predict that fast delayed rectifier currents should be present in soma and proximal dendrites, and this is confirmed using immunohistochemistry. Further, without A-type potassium currents in the dendrites, spike generation is facilitated at more distal synaptic input locations. Our models will help to determine the functional role of IS3 cells in hippocampal microcircuits.

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.

Functional evidence for a direct excitatory projection from the lateral habenula to the ventral tegmental area in the rat

The lateral habenula, a phylogenetically conserved epithalamic structure, is activated by aversive stimuli and reward omission. Excitatory efferents from the lateral habenula predominately inhibit midbrain dopamine neuronal firing through a disynaptic, feedforward inhibitory mechanism involving the rostromedial tegmental nucleus. However, the lateral habenula also directly targets dopamine neurons within the ventral tegmental area, suggesting that opposing actions may result from increased lateral habenula activity. In the present study, we tested the effect of habenular efferent stimulation on dopamine and nondopamine neurons in the ventral tegmental area of Sprague-Dawley rats using a parasagittal brain slice preparation. Single pulse stimulation of the fasciculus retroflexus excited 48% of dopamine neurons and 51% of nondopamine neurons in the ventral tegmental area of rat pups. These proportions were not altered by excision of the rostromedial tegmental nucleus and were evident in both cortical- and striatal-projecting dopamine neurons. Glutamate receptor antagonists blocked this excitation, and fasciculus retroflexus stimulation elicited evoked excitatory postsynaptic potentials with a nearly constant onset latency, indicative of a monosynaptic, glutamatergic connection. Comparison of responses in rat pups and young adults showed no significant difference in the proportion of neurons excited by fasciculus retroflexus stimulation. Our data indicate that the well-known, indirect inhibitory effect of lateral habenula activation on midbrain dopamine neurons is complemented by a significant, direct excitatory effect. This pathway may contribute to the role of midbrain dopamine neurons in processing aversive stimuli and salience.

Separation and assisted patterning of hippocampal neurons from glial cells using positive dielectrophoresis

In this work, we describe the separation of embryonic mouse hippocampal neurons from glial cells using a positive dielectrophoresis (DEP) process. Here, we have implemented a cell trapping-favorable, cell suspension solution with low conductivity. It enables positive dielectrophoresis for hippocampal neurons (thereby attracting them to the electrodes), while resulting in negative dielectrophoresis for glial cells (repelling them from the electrodes). We have systematically performed a mathematical simulation and analysis to anticipate the DEP frequency at which hippocampal neurons and glial cells are separated. Simulated DEP crossover frequencies have been experimentally verified, and new, refined glial dielectric and physical properties are suggested that better reflect the experimental results obtained. DEP movements of neurons and glial cells in targeted separation media were experimentally analyzed, under the specified electric signal. Additionally, we have confirmed our modeling results by selectively trapping neurons over electrodes on a custom-made, multi-electrode array (MEA), resulting in active recruitment of neurons over the stimulation and recording sites. This technique is a valuable addition to the toolbox for creating more functional and versatile multi-electrode arrays.

Tonically active NMDA receptors--a signalling mechanism critical for interneuronal excitability in the CA1 stratum radiatum

In contrast to tonic extrasynaptic γ-aminobutyric acid (GABA)A receptor-mediated signalling, the physiological significance of tonic extrasynaptic N-methyl-D-aspartate (NMDA) receptor (NMDAR)-mediated signalling remains uncertain. In this study, reversible open-channel blockers of NMDARs, memantine and phencyclidine (PCP) were used as tools to examine tonic NMDAR-mediated signalling in rat hippocampal slices. Memantine in concentrations up to 10 μM had no effect on synaptically evoked NMDAR-mediated responses in pyramidal neurons or GABAergic interneurons. On the other hand, 10 μM memantine reduced tonic NMDAR-mediated currents in GABAergic interneurons by approximately 50%. These tonic NMDAR-mediated currents in interneurons contributed significantly to the excitability of the interneurons as 10 μM memantine reduced the disynaptic inhibitory postsynaptic current in pyramidal cells by about 50%. Moreover, 10 μM memantine, but also PCP in concentrations ≤ 1 μM, increased the magnitude of the population spike, likely because of disinhibition. The relatively higher impact of tonic NMDAR-mediated signalling in interneurons was at least partly explained by the expression of GluN2D-containing NMDARs, which was not observed in mature pyramidal cells. The current results are consistent with the idea that low doses of readily reversible NMDAR open-channel blockers preferentially inhibit tonically active extrasynaptic NMDARs, and they suggest that tonically active NMDARs contribute more prominently to the intrinsic excitation in GABAergic interneurons than in pyramidal cells. It is proposed that this specific difference between interneurons and pyramidal cells can explain the disinhibition caused by the Alzheimer's disease medication memantine.

Topological characterization of neuronal arbor morphology via sequence representation: I--motif analysis

BACKGROUND

The morphology of neurons offers many insights into developmental processes and signal processing. Numerous reports have focused on metrics at the level of individual branches or whole arbors; however, no studies have attempted to quantify repeated morphological patterns within neuronal trees. We introduce a novel sequential encoding of neurite branching suitable to explore topological patterns.

RESULTS

Using all possible branching topologies for comparison we show that the relative abundance of short patterns of up to three bifurcations, together with overall tree size, effectively capture the local branching patterns of neurons. Dendrites and axons display broadly similar topological motifs (over-represented patterns) and anti-motifs (under-represented patterns), differing most in their proportions of bifurcations with one terminal branch and in select sub-sequences of three bifurcations. In addition, pyramidal apical dendrites reveal a distinct motif profile.

CONCLUSIONS

The quantitative characterization of topological motifs in neuronal arbors provides a thorough description of local features and detailed boundaries for growth mechanisms and hypothesized computational functions.

Functional properties of GABA synaptic inputs onto GABA neurons in monkey prefrontal cortex

In rodent cortex GABAA receptor (GABAAR)-mediated synapses are a significant source of input onto GABA neurons, and the properties of these inputs vary among GABA neuron subtypes that differ in molecular markers and firing patterns. Some features of cortical interneurons are different between rodents and primates, but it is not known whether inhibition of GABA neurons is prominent in the primate cortex and, if so, whether these inputs show heterogeneity across GABA neuron subtypes. We thus studied GABAAR-mediated miniature synaptic events in GABAergic interneurons in layer 3 of monkey dorsolateral prefrontal cortex (DLPFC). Interneurons were identified on the basis of their firing pattern as fast spiking (FS), regular spiking (RS), burst spiking (BS), or irregular spiking (IS). Miniature synaptic events were common in all of the recorded interneurons, and the frequency of these events was highest in FS neurons. The amplitude and kinetics of miniature inhibitory postsynaptic potentials (mIPSPs) also differed between DLPFC interneuron subtypes in a manner correlated with their input resistance and membrane time constant. FS neurons had the fastest mIPSP decay times and the strongest effects of the GABAAR modulator zolpidem, suggesting that the distinctive properties of inhibitory synaptic inputs onto FS cells are in part conferred by GABAARs containing α1 subunits. Moreover, mIPSCs differed between FS and RS interneurons in a manner consistent with the mIPSP findings. These results show that in the monkey DLPFC GABAAR-mediated synaptic inputs are prominent in layer 3 interneurons and may differentially regulate the activity of different interneuron subtypes.

Synapse-specific compartmentalization of signaling cascades for LTP induction in CA3 interneurons

Inhibitory interneurons with somata in strata radiatum and lacunosum-molecular (SR/L-M) of hippocampal area CA3 receive excitatory input from pyramidal cells via the recurrent collaterals (RCs), and the dentate gyrus granule cells via the mossy fibers (MFs). Here we demonstrate that Hebbian long-term potentiation (LTP) at RC synapses on SR/L-M interneurons requires the concomitant activation of calcium-impermeable AMPARs (CI-AMPARs) and N-methyl-d-aspartate receptors (NMDARs). RC LTP was prevented by voltage clamping the postsynaptic cell during high-frequency stimulation (HFS; 3 trains of 100 pulses delivered at 100 Hz every 10s), with intracellular injections of the Ca(2+) chelator BAPTA (20mM), and with the NMDAR antagonist D-AP5. In separate experiments, RC and MF inputs converging onto the same interneuron were sequentially activated. We found that RC LTP induction was blocked by inhibitors of the calcium/calmodulin-dependent protein kinase II (CaMKII; KN-62, 10 μM or KN-93, 10 μM) but MF LTP was CaMKII independent. Conversely, the application of the protein kinase A (PKA) activators forskolin/IBMX (50 μM/25 μM) potentiated MF EPSPs but not RC EPSPs. Together these data indicate that the aspiny dendrites of SR/L-M interneurons compartmentalize synapse-specific Ca(2+) signaling required for LTP induction at RC and MF synapses. We also show that the two signal transduction cascades converge to activate a common effector, protein kinase C (PKC). Specifically, LTP at RC and MF synapses on the same SR/LM interneuron was blocked by postsynaptic injections of chelerythrine (10 μM). These data indicate that both forms of LTP share a common mechanism involving PKC-dependent signaling modulation.

Modelling extracellular electrical stimulation: part 4. Effect of the cellular composition of neural tissue on its spatio-temporal filtering properties

OBJECTIVE

The objective of this paper is to present a concrete application of the cellular composite model for calculating the membrane potential, described in an accompanying paper.

APPROACH

A composite model that is used to determine the membrane potential for both longitudinal and transverse modes of stimulation is demonstrated.

MAIN RESULTS

Two extreme limits of the model, near-field and far-field for an electrode close to or distant from a neuron, respectively, are derived in this paper. Results for typical neural tissue are compared using the composite, near-field and far-field models as well as the standard isotropic volume conductor model. The self-consistency of the composite model, its spatial profile response and the extracellular potential time behaviour are presented. The magnitudes of the longitudinal and transverse components for different values of electrode-neurite separations are compared.

SIGNIFICANCE

The unique features of the composite model and its simplified versions can be used to accurately estimate the spatio-temporal response of neural tissue to extracellular electrical stimulation.

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.

Modeling extracellular electrical stimulation: I. Derivation and interpretation of neurite equations

Neuroprosthetic devices, such as cochlear and retinal implants, work by directly stimulating neurons with extracellular electrodes. This is commonly modeled using the cable equation with an applied extracellular voltage. In this paper a framework for modeling extracellular electrical stimulation is presented. To this end, a cylindrical neurite with confined extracellular space in the subthreshold regime is modeled in three-dimensional space. Through cylindrical harmonic expansion of Laplace's equation, we derive the spatio-temporal equations governing different modes of stimulation, referred to as longitudinal and transverse modes, under types of boundary conditions. The longitudinal mode is described by the well-known cable equation, however, the transverse modes are described by a novel ordinary differential equation. For the longitudinal mode, we find that different electrotonic length constants apply under the two different boundary conditions. Equations connecting current density to voltage boundary conditions are derived that are used to calculate the trans-impedance of the neurite-plus-thin-extracellular-sheath. A detailed explanation on depolarization mechanisms and the dominant current pathway under different modes of stimulation is provided. The analytic results derived here enable the estimation of a neurite's membrane potential under extracellular stimulation, hence bypassing the heavy computational cost of using numerical methods.

Regulation of AMPA and NMDA receptor-mediated EPSPs in dendritic trees of thalamocortical cells

Two main excitatory synapses are formed at the dendritic arbor of first-order nuclei thalamocortical (TC) neurons. Ascending sensory axons primarily establish contacts at large proximal dendrites, whereas descending corticothalamic fibers form synapses on thin distal dendrites. With the use of a multicomparment computational model based on fully reconstructed TC neurons from the ventroposterolateral nucleus of the cat, we compared local responses at the site of stimulation as well as somatic responses induced by both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and N-methyl-D-aspartate receptor (NMDAR)-mediated currents. We found that AMPAR-mediated responses, when synapses were located at proximal dendrites, induced a larger depolarization at the level of soma, whereas NMDAR-mediated responses were more efficient for synapses located at distal dendrites. The voltage transfer and transfer impedance were higher for NMDAR than for AMPAR activation at any location. For both types of synaptic current and for both input locations at the dendritic arbor, somatic responses were characterized by a low variability despite the large variability found in local responses in dendrites. The large neurons had overall smaller somatic responses than small neurons, but this relation was not found in local dendritic responses. We conclude that in TC cells, the dendritic location of small synaptic inputs does not play a major role in the amplitude of a somatic response, but the size of the neuron does. The variability of response amplitude between cells was much larger than the variability within cells. This suggests possible functional segregation of TC neurons of different size.

Fast recruitment of recurrent inhibition in the cat visual cortex

Neurons of the same column in L4 of the cat visual cortex are likely to share the same sensory input from the same region of the visual field. Using visually-guided patch clamp recordings we investigated the biophysical properties of the synapses of neighboring layer 4 neurons. We recorded synaptic connections between all types of excitatory and inhibitory neurons in L4. The E–E, E–I, and I–E connections had moderate CVs and failure rates. However, E–I connections had larger amplitudes, faster rise-times, and shorter latencies. Identification of the sites of putative synaptic contacts together with compartmental simulations on 3D reconstructed cells, suggested that E–I synapses tended to be located on proximal dendritic branches, which would explain their larger EPSP amplitudes and faster kinetics. Excitatory and inhibitory synapses were located at the same distance on distal dendrites of excitatory neurons. We hypothesize that this co-localization and the fast recruitment of local inhibition provides an efficient means of modulating excitation in a precisely timed way.

Burst firing transitions in two-compartment pyramidal neuron induced by the perturbation of membrane capacitance

Neuronal membrane capacitance C (m) is one of the prominent factors in action potential initiation and propagation and then influences the firing patterns of neurons. Exploring the roles that C (m) plays in different firing patterns can facilitate the understanding of how different factors might influence neuronal firing behaviors. However, the impacts of variations in C (m) on neuronal firing patterns have been only partly explored until now. In this study, the influence of C (m) on burst firing behaviors of a two-compartment pyramidal neuron (including somatic compartment and dendritic compartment) was investigated by means of computer simulation, the value of C (m) in each compartment was denoted as C (m,s) and C (m,d), respectively. Two cases were considered, in the first case, we let C (m,s) =C (m,d), and then changed them simultaneously. While in the second case, we assumed C (m,s) ≠C (m,d), and then changed them, respectively. From the simulation results obtained from these two cases, it was found that the variation of C (m) in the somatic compartment and the dendritic compartment show much difference, simulated results obtained from the variation of C (m,d) have much more similarities than that of C (m,s) when comparing with the results obtained in the first case under which C (m,s) =C (m,d). These different effects of C (m,s) and C (m,d) on neuronal firing behaviors may result from the different topology and functional roles of soma and dendrites. Numerical results demonstrated in this paper may give us some inspiration in understanding the possible roles of C (m) in burst firing patterns, especially their transitions in compartmental neurons.

A multi-compartment model for interneurons in the dorsal lateral geniculate nucleus

GABAergic interneurons (INs) in the dorsal lateral geniculate nucleus (dLGN) shape the information flow from retina to cortex, presumably by controlling the number of visually evoked spikes in geniculate thalamocortical (TC) neurons, and refining their receptive field. The INs exhibit a rich variety of firing patterns: Depolarizing current injections to the soma may induce tonic firing, periodic bursting or an initial burst followed by tonic spiking, sometimes with prominent spike-time adaptation. When released from hyperpolarization, some INs elicit rebound bursts, while others return more passively to the resting potential. A full mechanistic understanding that explains the function of the dLGN on the basis of neuronal morphology, physiology and circuitry is currently lacking. One way to approach such an understanding is by developing a detailed mathematical model of the involved cells and their interactions. Limitations of the previous models for the INs of the dLGN region prevent an accurate representation of the conceptual framework needed to understand the computational properties of this region. We here present a detailed compartmental model of INs using, for the first time, a morphological reconstruction and a set of active dendritic conductances constrained by experimental somatic recordings from INs under several different current-clamp conditions. The model makes a number of experimentally testable predictions about the role of specific mechanisms for the firing properties observed in these neurons. In addition to accounting for the significant features of all experimental traces, it quantitatively reproduces the experimental recordings of the action-potential- firing frequency as a function of injected current. We show how and why relative differences in conductance values, rather than differences in ion channel composition, could account for the distinct differences between the responses observed in two different neurons, suggesting that INs may be individually tuned to optimize network operation under different input conditions.

Properties and functional implications of I (h) in hippocampal area CA3 interneurons

The present study examines the biophysical properties and functional implications of I (h) in hippocampal area CA3 interneurons with somata in strata radiatum and lacunosum-moleculare. Characterization studies showed a small maximum h-conductance (2.6 ± 0.3 nS, n = 11), shallow voltage dependence with a hyperpolarized half-maximal activation (V (1/2) = -91 mV), and kinetics characterized by double-exponential functions. The functional consequences of I (h) were examined with regard to temporal summation and impedance measurements. For temporal summation experiments, 5-pulse mossy fiber input trains were activated. Blocking I (h) with 50 μM ZD7288 resulted in an increase in temporal summation, suggesting that I (h) supports sensitivity of response amplitude to relative input timing. Impedance was assessed by applying sinusoidal current commands. From impedance measurements, we found that I (h) did not confer theta-band resonance, but flattened the impedance-frequency relations instead. Double immunolabeling for hyperpolarization-activated cyclic nucleotide-gated proteins and glutamate decarboxylase 67 suggests that all four subunits are present in GABAergic interneurons from the strata considered for electrophysiological studies. Finally, a model of I (h) was employed in computational analyses to confirm and elaborate upon the contributions of I (h) to impedance and temporal summation.

Modeling neuronal current MRI signal with human neuron

Up to date, no consensus has been achieved regarding the possibility of detecting neuronal currents by MRI (ncMRI) in human brain. To evaluate the detectability of ncMRI, an effective way is to simulate ncMRI signal with the realistic neuronal geometry and electrophysiological processes. Unfortunately, previous realistic ncMRI models are based on rat and monkey neurons. The species difference in neuronal morphology and physiology would prevent these models from simulating the ncMRI signal accurately in human subjects. The aim of this study is to bridge this gap by establishing a realistic ncMRI model specifically for human cerebral cortex. In this model, the ncMRI signal was simulated using anatomically reconstructed human pyramidal neurons and their biophysical properties. The modeling results showed that the amplitude of ncMRI signal significantly depends on the density of synchronously firing neurons and imaging conditions such as position of imaging voxel, direction of main magnetic field (B(0) ) relative to the cortical surface and echo time. The results indicated that physiologically-evoked ncMRI signal is too weak to be detected (magnitude/phase change ≤ -1.4 × 10(-6) /0.02°), but the phase signal induced by spontaneous activity may reach a detectable level (up to 0.2°) in favorable conditions.

Passive and active shaping of unitary responses from associational/commissural and perforant path synapses in hippocampal CA3 pyramidal cells

Although associational/commissural (A/C) and perforant path (PP) inputs to CA3b pyramidal cells play a central role in hippocampal mnemonic functions, the active and passive processes that shape A/C and PP AMPA and NMDA receptor-mediated unitary EPSP/EPSC (AMPA and NMDA uEPSP/uEPSC) have not been fully characterized yet. Here we find no differences in somatic amplitude between A/C and PP for either AMPA or NMDA uEPSPs. However, larger AMPA uEPSCs were evoked from proximal than from distal A/C or PP. Given the space-clamp constraints in CA3 pyramidal cells, these voltage clamp data suggest that the location-independence of A/C and PP AMPA uEPSP amplitudes is achieved in part through the activation of voltage dependent conductances at or near the soma. Moreover, similarity in uEPSC amplitudes for distal A/C and PP points to the additional participation of unclamped active conductances. Indeed, the pharmacological blockade of voltage-dependent conductances eliminates the location-independence of these inputs. In contrast, the location-independence of A/C and PP NMDA uEPSP/uEPSC amplitudes is maintained across all conditions indicating that propagation is not affected by active membrane processes. The location-independence for A/C uEPSP amplitudes may be relevant in the recruitment of CA3 pyramidal cells by other CA3 pyramidal cells. These data also suggest that PP excitation represents a significant input to CA3 pyramidal cells. Implication of the passive data on local synaptic properties is further investigated in the companion paper with a detailed computational model.

Role of microcircuit structure and input integration in hippocampal interneuron recruitment and plasticity

The proper operation of cortical neuronal networks depends on the temporally precise recruitment of GABAergic inhibitory interneurons. Inhibitory cells receive convergent excitatory inputs from afferent pathways, as well as local collaterals of principal cells, and provide feedforward or feedback inhibition within the circuitry. Accumulating evidence indicates that recruitment of GABAergic cells is highly diverse among interneuron types. Differences in the properties of input synapses, dendritic architecture and membrane properties, as well as the rich repertoire of plasticity mechanisms contribute to this diversity. Efficient and precise recruitment of interneurons is thought to depend on the coincident occurrence of rapid synaptic responses and their faithful propagation to the action potential initiation site. However, slow inputs can also play important roles by facilitating the activation of interneurons by rapid synaptic inputs and supporting associative synaptic plasticity. Here we review how the diversity in the synaptic and integrative properties as well as dendritic geometry of hippocampal inhibitory cells impact on their activation. We further discuss how the various modes of interneuron recruitment can support the versatile cell type- and input-specific computational functions which appear to be adapted to the structure and the function of the network they are embedded in. This article is part of a Special Issue entitled 'Synaptic Plasticity & Interneurons'.

Multiple forms of long-term synaptic plasticity at hippocampal mossy fiber synapses on interneurons

The hippocampal mossy fiber (MF) pathway originates from the dentate gyrus granule cells and provides a powerful excitatory synaptic drive to neurons in the dentate gyrus hilus and area CA3. Much of the early work on the MF pathway focused on its electrophysiological properties, and ability to drive CA3 pyramidal cell activity. Over the last ten years, however, a new focus on the synaptic interaction between granule cells and inhibitory interneurons has emerged. These data have revealed an immense heterogeneity of long-term plasticity at MF synapses on various interneuron targets. Interestingly, these studies also indicate that the mechanisms of MF long-term plasticity in some interneuron subtypes may be more similar to pyramidal cells than previously appreciated. In this review, we first define the synapse types at each of the interneuron targets based on the receptors present. We then describe the different forms of long-term plasticity observed, and the mechanisms underlying each form as they are currently understood. Finally we highlight various open questions surrounding MF long-term plasticity in interneurons, focusing specifically on the induction and maintenance of LTP, and what the functional impact of persistent changes in efficacy at MF-interneuron synapses might be on the emergent properties of the inhibitory network dynamics in area CA3. This article is part of a Special Issue entitled 'Synaptic Plasticity & Interneurons'.

Distinct nonuniform cable properties optimize rapid and efficient activation of fast-spiking GABAergic interneurons

Fast-spiking, parvalbumin-expressing basket cells (BCs) play a key role in feedforward and feedback inhibition in the hippocampus. However, the dendritic mechanisms underlying rapid interneuron recruitment have remained unclear. To quantitatively address this question, we developed detailed passive cable models of BCs in the dentate gyrus based on dual somatic or somatodendritic recordings and complete morphologic reconstructions. Both specific membrane capacitance and axial resistivity were comparable to those of pyramidal neurons, but the average somatodendritic specific membrane resistance (R(m)) was substantially lower in BCs. Furthermore, R(m) was markedly nonuniform, being lowest in soma and proximal dendrites, intermediate in distal dendrites, and highest in the axon. Thus, the somatodendritic gradient of R(m) was the reverse of that in pyramidal neurons. Further computational analysis revealed that these unique cable properties accelerate the time course of synaptic potentials at the soma in response to fast inputs, while boosting the efficacy of slow distal inputs. These properties will facilitate both rapid phasic and efficient tonic activation of BCs in hippocampal microcircuits.

Anatomical and electrophysiological comparison of CA1 pyramidal neurons of the rat and mouse

The study of learning and memory at the single-neuron level has relied on the use of many animal models, most notably rodents. Although many physiological and anatomical studies have been carried out in rats, the advent of genetically engineered mice has necessitated the comparison of new results in mice to established results from rats. Here we compare fundamental physiological and morphological properties and create three-dimensional compartmental models of identified hippocampal CA1 pyramidal neurons of one strain of rat, Sprague-Dawley, and two strains of mice, C57BL/6 and 129/SvEv. We report several differences in neuronal physiology and anatomy among the three animal groups, the most notable being that neurons of the 129/SvEv mice, but not the C57BL/6 mice, have higher input resistance, lower dendritic surface area, and smaller spines than those of rats. A surprising species-specific difference in membrane resonance indicates that both mouse strains have lower levels of the hyperpolarization-activated nonspecific cation current I(h). Simulations suggest that differences in I(h) kinetics rather than maximal conductance account for the lower resonance. Our findings indicate that comparisons of data obtained across strains or species will need to account for these and potentially other physiological and anatomical differences.

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.

Effect of voltage sensitive fluorescent proteins on neuronal excitability

Fluorescent protein voltage sensors are recombinant proteins that are designed as genetically encoded cellular probes of membrane potential using mechanisms of voltage-dependent modulation of fluorescence. Several such proteins, including VSFP2.3 and VSFP3.1, were recently reported with reliable function in mammalian cells. They were designed as molecular fusions of the voltage sensor of Ciona intestinalis voltage sensor containing phosphatase with a fluorescence reporter domain. Expression of these proteins in cell membranes is accompanied by additional dynamic membrane capacitance, or "sensing capacitance", with feedback effect on the native electro-responsiveness of targeted cells. We used recordings of sensing currents and fluorescence responses of VSFP2.3 and of VSFP3.1 to derive kinetic models of the voltage-dependent signaling of these proteins. Using computational neuron simulations, we quantitatively investigated the perturbing effects of sensing capacitance on the input/output relationship in two central neuron models, a cerebellar Purkinje and a layer 5 pyramidal neuron. Probe-induced sensing capacitance manifested as time shifts of action potentials and increased synaptic input thresholds for somatic action potential initiation with linear dependence on the membrane density of the probe. Whereas the fluorescence signal/noise grows with the square root of the surface density of the probe, the growth of sensing capacitance is linear. We analyzed the trade-off between minimization of sensing capacitance and signal/noise of the optical read-out depending on kinetic properties and cellular distribution of the probe. The simulation results suggest ways to reduce capacitive effects at a given level of signal/noise. Yet, the simulations indicate that significant improvement of existing probes will still be required to report action potentials in individual neurons in mammalian brain tissue in single trials.

Distinct classes of pyramidal cells exhibit mutually exclusive firing patterns in hippocampal area CA3b

It is thought that CA3 pyramidal neurons communicate mainly through bursts of spikes rather than so-called trains of regular firing action potentials. Reports of both burst firing and nonburst firing CA3 cells suggest that they may fire with more than one output pattern. With the use of whole-cell recording methods we studied the firing properties of rat hippocampal pyramidal neurons in vitro within the CA3b subregion and found three distinct types of firing patterns. Approximately 37% of cells were regular firing where spikes generated by minimal current injection (rheobase) were elicited with a short latency and with stronger current intensities trains of spikes exhibited spike frequency adaptation (SFA). Another 46% of neurons exhibited a delayed onset at rheobase with a weakly-adapting firing pattern upon stronger stimulation. The remaining 17% of cells showed a burst-firing pattern, though only elicited in response to strong current injection and spontaneous bursts were never observed. Control experiments indicated that the distinct firing patterns were not due to our particular slicing methods or recording techniques. Finally, computer modeling was used to identify how relative differences in K+ conductances, specifically K(C), K(M), and K(D), between cells contribute to the different characteristics of the three types of firing patterns observed experimentally.

Coincidence detection of convergent perforant path and mossy fibre inputs by CA3 interneurons

We performed whole-cell recordings from CA3 s. radiatum (R) and s. lacunosum-moleculare (L-M) interneurons in hippocampal slices to examine the temporal aspects of summation of converging perforant path (PP) and mossy fibre (MF) inputs. PP EPSPs were evoked from the s. lacunosum-moleculare in area CA1. MF EPSPs were evoked from the medial extent of the suprapyramidal blade of the dentate gyrus. Summation was strongly supralinear when examining PP EPSP with MF EPSP in a heterosynaptic pair at the 10 ms ISI, and linear to sublinear at longer ISIs. This pattern of nonlinearities suggests that R and L-M interneurons act as coincidence detectors for input from PP and MF. Summation at all ISIs was linear in voltage clamp mode demonstrating that nonlinearities were generated by postsynaptic voltage-dependent conductances. Supralinearity was not detected when the first EPSP in the pair was replaced by a simulated EPSP injected into the soma, suggesting that the conductances underlying the EPSP boosting were located in distal dendrites. Supralinearity was selectively eliminated with either Ni2+ (30 microm), mibefradil (10 microm) or nimodipine (15 microm), but was unaffected by QX-314. This pharmacological profile indicates that supralinearity is due to recruitment of dendritic T-type Ca2+channels by the first subthreshold EPSP in the pair. Results with the hyperpolarization-activated (Ih) channel blocker ZD 7288 (50 microm) revealed that Ih restricted the time course of supralinearity for coincidently summed EPSPs, and promoted linear to sublinear summation for asynchronous EPSPs. We conclude that coincidence detection results from the counterbalanced activation of T-type Ca2+ channels and inactivation of Ih.

Optimization principles of dendritic structure

Background

Dendrites are the most conspicuous feature of neurons. However, the principles determining their structure are poorly understood. By employing cable theory and, for the first time, graph theory, we describe dendritic anatomy solely on the basis of optimizing synaptic efficacy with minimal resources.

Results

We show that dendritic branching topology can be well described by minimizing the path length from the neuron's dendritic root to each of its synaptic inputs while constraining the total length of wiring. Tapering of diameter toward the dendrite tip – a feature of many neurons – optimizes charge transfer from all dendritic synapses to the dendritic root while housekeeping the amount of dendrite volume. As an example, we show how dendrites of fly neurons can be closely reconstructed based on these two principles alone.

Fitting experimental data to models that use morphological data from public databases

Ideally detailed neuron models should make use of morphological and electrophysiological data from the same cell. However, this rarely happens. Typically a modeler will choose a cell morphology from a public database, assign standard values for Ra, Cm, and other parameters and then do the modeling study. The assumption is that the model will produce results representative of what might be obtained experimentally. To test this assumption we developed models of CA1 hippocampal pyramidal neurons using 4 different morphologies obtained from 3 public databases. The multiple run fitter in NEURON was used to fit parameter values in each of the 4 morphological models to match experimental data recorded from 19 CA1 pyramidal cells. Fits with fixed standard parameter values produced results that were generally not representative of our experimental data. However, when parameter values were allowed to vary, excellent fits were obtained in almost all cases, but the fitted parameter values were very different among the 4 reconstructions and did not match standard values. The differences in fitted values can be explained by very different diameters, total lengths, membrane areas and volumes among the reconstructed cells, reflecting either cell heterogeneity or issues with the reconstruction data. The fitted values compensated for these differences to make the database cells and experimental cells more similar electrotonically. We conclude that models using fully reconstructed morphologies need to be calibrated with experimental data (even when morphological and electrophysiological data come from the same cell), model results should be generated with multiple reconstructions, morphological and experimental cells should come from the same strain of animal at the same age, and blind use of standard parameter values in models that use reconstruction data may not produce representative experimental results.

Caloric restriction prevents aging-associated changes in spike-mediated Ca2+ accumulation and the slow afterhyperpolarization in hippocampal CA1 pyramidal neurons

In hippocampal pyramidal neurons from aged animals voltage-gated Ca2+ entry and the slow, post-burst afterhyperpolarization are enhanced. As a result, there is a decrease in neuronal excitability and, in turn, an alteration in synaptic plasticity. Restricting the caloric intake of a rodent is a well-known paradigm for increasing lifespan and ameliorating a number of neurodegenerative features of aging, including deficits in synaptic plasticity and cognition. Here we show in rat CA1 pyramidal neurons from aged animals (18-20 months old) that a restricted diet prevents the enhancement of dendritic spike-mediated Ca2+ accumulation. In contrast, no significant changes in the rates of Ca2+ recovery were observed suggesting that Ca2+ clearance mechanisms are not affected by aging or caloric restriction. Lastly, we found that caloric restriction also prevented the aging-associated increase in the slow, post-burst afterhyperpolarization. Our results suggest that caloric restriction-sensitive changes in Ca2+ accumulation and membrane excitability may in part account for the protective effects of dietary restriction on synaptic plasticity and learning deficits in aged animals.

Synaptic integration in dendritic trees

Most neurons have elaborate dendritic trees that receive tens of thousands of synaptic inputs. Because postsynaptic responses to individual synaptic events are usually small and transient, the integration of many synaptic responses is needed to depolarize most neurons to action potential threshold. Over the past decade, advances in electrical and optical recording techniques have led to new insights into how synaptic responses propagate and interact within dendritic trees. In addition to their passive electrical and morphological properties, dendrites express active conductances that shape individual synaptic responses and influence synaptic integration locally within dendrites. Dendritic voltage-gated Na(+) and Ca(2+) channels support action potential backpropagation into the dendritic tree and local initiation of dendritic spikes, whereas K(+) conductances act to dampen dendritic excitability. While all dendrites investigated to date express active conductances, different neuronal types show specific patterns of dendritic channel expression leading to cell-specific differences in the way synaptic responses are integrated within dendritic trees. This review explores the way active and passive dendritic properties shape synaptic responses in the dendrites of central neurons, and emphasizes their role in synaptic integration.

Factors mediating powerful voltage attenuation along CA1 pyramidal neuron dendrites

We performed simultaneous patch-electrode recordings from the soma and apical dendrite of CA1 pyramidal neurons in hippocampal slices, in order to determine the degree of voltage attenuation along CA1 dendrites. Fifty per cent attenuation of steady-state somatic voltage changes occurred at a distance of 238 microm from the soma in control and 409 microm after blocking the hyperpolarization-activated (H) conductance. The morphology of three neurons was reconstructed and used to generate computer models, which were adjusted to fit the somatic and dendritic voltage responses. These models identify several factors contributing to the voltage attenuation along CA1 dendrites, including high axial cytoplasmic resistivity, low membrane resistivity, and large H conductance. In most cells the resting membrane conductances, including the H conductances, were larger in the dendrites than the soma. Simulations suggest that synaptic potentials attenuate enormously as they propagate from the dendrite to the soma, with greater than 100-fold attenuation for synapses on many small, distal dendrites. A prediction of this powerful EPSP attenuation is that distal synaptic inputs are likely only to be effective in the presence of conductance scaling, dendritic excitability, or both.

Structural mechanisms to produce differential dendritic gains

The axons of sacral parasympathetic preganglionic neurons (PGNs) originate on a primary dendrite between 10 and 110 mum from the soma. Therefore, it was hypothesized that the location of the axon origin would impact the relative efficacy of ipsilateral and contralateral synaptic inputs. The morphology of two PGNs was reconstructed, and the transfer impedance was used to quantify the influence of synaptic inputs on the transmembrane potential at the axon initial segment. The ratio of ipsilateral transfer impedance to contralateral transfer impedance (termed the relative gain) was increased by 14-29% for axons originating from the dendrite vs. axons originating from the soma. The addition of 50 synchronized "gating" synapses on the proximal dendrites increased the relative gain by 17-38% when the axon originated from the dendrite, but only by 11-15% when the axon originated from the soma. The efficacy of synaptic inputs and the ability of proximal gating synapses to regulate synaptic efficacy were strongly influenced by the site of origin of the axon. The position of axon origin is an effective structural mechanism to regulate the relative efficacy of synaptic inputs arriving at different locations on the dendritic tree.

The prefrontal cortex regulates lateral amygdala neuronal plasticity and responses to previously conditioned stimuli

The amygdala plays a role in learning and memory processes that involve an emotional component. However, neural structures that regulate these amygdala-dependent processes are unknown. Previous studies indicate that regulation of affect may be imposed by the prefrontal cortex (PFC) and its efferents to the amygdala. The presentation of conditioned affective stimuli enhances activity of neurons in the lateral nucleus of the amygdala (LAT), which is thought to drive conditioned affective responses. Moreover, plasticity of LAT neuronal responses to stimuli during the course of conditioning is believed to underlie affective learning. This study examines the role of the PFC in the regulation of affective behaviors by evaluating how the PFC affects LAT neuronal plasticity and activity that is evoked by previously conditioned stimuli. In vivo intracellular recordings were performed from the LAT of anesthetized rats during pavlovian conditioning and during the presentation of stimuli that were conditioned in the awake rat before recording. Train stimulation of the PFC suppressed LAT neuronal activity that was evoked by both previously conditioned and neutral stimuli. In addition, PFC stimulation blocked LAT neuronal plasticity associated with an affective conditioning procedure. These results indicate that the PFC has the potential to regulate affective processes by inhibition of the LAT. Patients with disruptions of the PFC-LAT interaction often display an inability to regulate affective responses. This may be attributable to the loss of PFC-imposed inhibition of the emotional response to a stimulus but may also include the formation or diminished extinction of inappropriate associations.

Interneuron diversity series: containing the detonation--feedforward inhibition in the CA3 hippocampus

Feedforward inhibitory circuits are involved both in the suppression of excitability and timing of action potential generation in principal cells. In the CA3 hippocampus, a single mossy fiber from a dentate gyrus granule cell forms giant boutons with multiple release sites, which are capable of detonating CA3 principal cells. By contrast, mossy fiber terminals form a larger number of Lilliputian-sized synapses with few release sites onto local circuit interneurons, with distinct presynaptic and postsynaptic properties. This dichotomy between the two synapse types endows the circuit with exquisite control over pyramidal cell discharge. Under pathological conditions where feedforward inhibition is compromised, focal excitation is no longer contained, rendering the circuit susceptible to hyperexcitability.

The prefrontal cortex regulates lateral amygdala neuronal plasticity and responses to previously conditioned stimuli

The amygdala plays a role in learning and memory processes that involve an emotional component. However, neural structures that regulate these amygdala-dependent processes are unknown. Previous studies indicate that regulation of affect may be imposed by the prefrontal cortex (PFC) and its efferents to the amygdala. The presentation of conditioned affective stimuli enhances activity of neurons in the lateral nucleus of the amygdala (LAT), which is thought to drive conditioned affective responses. Moreover, plasticity of LAT neuronal responses to stimuli during the course of conditioning is believed to underlie affective learning. This study examines the role of the PFC in the regulation of affective behaviors by evaluating how the PFC affects LAT neuronal plasticity and activity that is evoked by previously conditioned stimuli. In vivo intracellular recordings were performed from the LAT of anesthetized rats during pavlovian conditioning and during the presentation of stimuli that were conditioned in the awake rat before recording. Train stimulation of the PFC suppressed LAT neuronal activity that was evoked by both previously conditioned and neutral stimuli. In addition, PFC stimulation blocked LAT neuronal plasticity associated with an affective conditioning procedure. These results indicate that the PFC has the potential to regulate affective processes by inhibition of the LAT. Patients with disruptions of the PFC-LAT interaction often display an inability to regulate affective responses. This may be attributable to the loss of PFC-imposed inhibition of the emotional response to a stimulus but may also include the formation or diminished extinction of inappropriate associations.

Comparison of the morphological and electrotonic properties of Renshaw cells, Ia inhibitory interneurons, and motoneurons in the cat

The morphological and electrotonic properties of 4 motoneurons, 8 Ia inhibitory interneurons, and 4 Renshaw cells were compared. The morphological analysis, based on 3-D reconstructions of the cells, revealed that dendrites of motoneurons are longer and more extensively branched. Renshaw cells have dendrites that are shorter and simpler in structure. Dendrites of Ia inhibitory interneurons could be as long as those of motoneurons but the branching structure resembled that of Renshaw cells. Compartmental models were used to determine the electrotonic properties of the paths from each dendritic terminal to the soma. The attenuations of steady-state voltage changes in motoneurons were 3 and 7 times larger than in Ia inhibitory interneurons and Renshaw cells, respectively. The same relative order was observed for current attenuation and electrotonic length. The dendritic input resistances in Renshaw cells were 2 and 4 times larger than in Ia inhibitory interneurons and motoneurons, respectively. The difference in these electrotonic properties increased during higher synaptic activity as modeled by a decrease of Rm. The peak amplitudes of voltage transients at sites of brief, synaptic-like changes in conductance were highly dependent on cell class and were largest in Renshaw cells and smallest in motoneurons. In combination with class-specific differences in the attenuation of transient voltage signals, this led to large differences in the peak amplitudes of somatic voltage transients. Differences in the rise times and half-widths of the voltage transients were observed as well. Thus, based on passive properties, each cell class has a unique set of input/output properties.