Translating network models to parallel hardware in NEURON.

The increasing complexity of network models poses a growing computational burden. At the same time, computational neuroscientists are finding it easier to access parallel hardware, such as multiprocessor personal computers, workstation clusters, and massively parallel supercomputers. The practical question is how to move a working network model from a single processor to parallel hardware. Here we show how to make this transition for models implemented with NEURON, in such a way that the final result will run and produce numerically identical results on either serial or parallel hardware. This allows users to develop and debug models on readily available local resources, then run their code without modification on a parallel supercomputer.

Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex.

Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium (Ca(2+)) regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. The network contained 776 compartmental neurons arranged in the cortical layers, connected using synapses containing AMPA/NMDA/GABAA/GABAB receptors. Metabotropic glutamate receptors (mGluR) produced inositol triphosphate (IP3) which caused the release of Ca(2+) from endoplasmic reticulum (ER) stores, with reuptake by sarco/ER Ca(2+)-ATP-ase pumps (SERCA), and influence on HCN channels. Stimulus-induced depolarization led to Ca(2+) influx via NMDA and voltage-gated Ca(2+) channels (VGCCs). After a delay, mGluR activation led to ER Ca(2+) release via IP3 receptors. These factors increased HCN channel conductance and produced firing lasting for ∼1min. The model displayed inter-scale synergies among synaptic weights, excitation/inhibition balance, firing rates, membrane depolarization, Ca(2+) levels, regulation of HCN channels, and induction of persistent activity. The interaction between inhibition and Ca(2+) at the HCN channel nexus determined a limited range of inhibition strengths for which intracellular Ca(2+) could prepare population-specific persistent activity. Interactions between metabotropic and ionotropic inputs to the neuron demonstrated how multiple pathways could contribute in a complementary manner to persistent activity. Such redundancy and complementarity via multiple pathways is a critical feature of biological systems. Mediation of activation at different time scales, and through different pathways, would be expected to protect against disruption, in this case providing stability for persistent activity.

NEURON: a tool for neuroscientists.

NEURON is a simulation environment for models of individual neurons and networks of neurons that are closely linked to experimental data. NEURON provides tools for conveniently constructing, exercising, and managing models, so that special expertise in numerical methods or programming is not required for its productive use. This article describes two tools that address the problem of how to achieve computational efficiency and accuracy.

Parallel network simulations with NEURON.

The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.

The role of distal dendritic gap junctions in synchronization of mitral cell axonal output.

One of the first and most important stages of odor processing occurs in the glomerular units of the olfactory bulb and most likely involves mitral cell synchronization. Using a detailed model constrained by a number of experimental findings, we show how the intercellular coupling mediated by intraglomerular gap junctions (GJs) in the tuft dendrites could play a major role in sychronization of mitral cell action potential output in spite of their distal dendritic location. The model suggests that the high input resistance and active properties of the fine tuft dendrites are instrumental in generating local spike synchronization and an efficient forward and backpropagation of action potentials between the tuft and the soma. The model also gives insight into the physiological significance of long primary dendrites in mitral cells, and provides evidence against the use of reduced single compartmental models to investigate network properties of cortical pyramidal neurons.

The NEURON simulation environment.

The moment-to-moment processing of information by the nervous system involves the propagation and interaction of electrical and chemical signals that are distributed in space and time. Biologically realistic modeling is needed to test hypotheses about the mechanisms that govern these signals and how nervous system function emerges from the operation of these mechanisms. The NEURON simulation program provides a powerful and flexible environment for implementing such models of individual neurons and small networks of neurons. It is particularly useful when membrane potential is nonuniform and membrane currents are complex. We present the basic ideas that would help informed users make the most efficient use of NEURON.

Expanding NEURON's repertoire of mechanisms with NMODL.

Neuronal function involves the interaction of electrical and chemical signals that are distributed in time and space. The mechanisms that generate these signals and regulate their interactions are marked by a rich diversity of properties that precludes a "one size fits all" approach to modeling. This article presents a summary of how the model description language NMODL enables the neuronal simulation environment NEURON to accommodate these differences.

Simulating the spread of membrane potential changes in arteriolar networks.

OBJECTIVE: Our aim was to simulate the spread of membrane potential changes in microvascular trees and then make the simulation programs accessible to other researchers. We have applied our simulations to demonstrate the implications of electrical coupling between arteriolar smooth muscle and endothelium. METHODS: A two-layered, cable-like model of an arteriole was used, and the assumptions involved in the approach explicitly stated. Several common experimental situations that involve the passive spread of membrane potential changes in microvascular trees were simulated. The calculations were performed using NEURON, a well-established computer simulation program that we have modified for use with vascular trees. RESULTS: Simulated results show that membrane potential changes would probably not spread as far in the endothelium as they would in the smooth muscle of arterioles. Where feed arteries are connected to larger distributing arteries, passive spread alone may not explain the physiologically observed spread of diameter changes. CONCLUSIONS: Simulated results suggest that the morphology of an arteriole, in which the muscle layer is much thicker than the endothelium, favors electrical conduction along smooth muscle rather than the endothelium. However, it seems that passive electrical spread is insufficient to explain the apparent spread of membrane potential changes in experimental situations. Active responses involving voltage-dependent conductances may be involved, and these can also be included in our simulation.

Computational analysis of action potential initiation in mitral cell soma and dendrites based on dual patch recordings.

In olfactory mitral cells, dual patch recordings show that the site of action potential initiation can shift between soma and distal primary dendrite and that the shift is dependent on the location and strength of electrode current injection. We have analyzed the mechanisms underlying this shift, using a model of the mitral cell that takes advantage of the constraints available from the two recording sites. Starting with homogeneous Hodgkin-Huxley-like Na(+)-K(+) channel distribution in the soma-dendritic region and much higher sodium channel density in the axonal region, the model's channel kinetics and density were adjusted by a fitting algorithm so that the model response was virtually identical to the experimental data. The combination of loading effects and much higher sodium channel density in the axon relative to the soma-dendritic region results in significantly lower "voltage threshold" for action potential initiation in the axon; the axon therefore fires first unless the voltage gradient in the primary dendrite is steep enough for it to reach its higher threshold. The results thus provide a quantitative explanation for the stimulus strength and position dependence of the site of action potential initiation in the mitral cell.

Conformation studies of histone H1(0) in comparison with histones H1 and H5.

The class of lysine-rich histones, H1, found in most eukaryotic cells is largely replaced by another class of lysine-rich histones, H5, in avian and other erythrocytes. Erythrocytes are transcriptionally inert and this state has been attributed to the presence of H5. Although there are many sequence differences between H1 and H5 both molecules have very similar structures with three well-defined domains: a flexible basic N-terminal region, an apolar globular central region and a flexible basic C-terminal region. The lengths of the N-terminal regions are different for H1 and H5 whereas the lengths of the central and C-terminal regions are very similar. Considerable interest attaches to the findings that another type of mammalian lysine-rich histone H1(0) has an apolar region exhibiting considerable sequence homology (70%) with the central globular region of H5. The abundance of H1 in cells has been found to correlate inversely with their mitotic activities. Conformational studies using high-resolution nuclear magnetic resonance and optical spectroscopy have been made of H1 and its conformational behaviour has been compared with those of H1 and H5. H1 has been found to contain a central globular region of similar size to those found in H1 and H5. However, the conformation and stability of the globular domain of H1 are very similar to the globular region of H5 rather than H1. H1 appears to be a hybrid containing a major feature of the H5 histone. The globular regions of H1 and H5 are known to bind to a specific site on the nucleosome sealing off two turns of DNA. It is proposed that H1 binds to the same site.