Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data.

The construction of compartmental models of neurons involves tuning a set of parameters to make the model neuron behave as realistically as possible. While the parameter space of single-compartment models or other simple models can be exhaustively searched, the introduction of dendritic geometry causes the number of parameters to balloon. As parameter tuning is a daunting and time-consuming task when performed manually, reliable methods for automatically optimizing compartmental models are desperately needed, as only optimized models can capture the behavior of real neurons. Here we present a three-step strategy to automatically build reduced models of layer 5 pyramidal neurons that closely reproduce experimental data. First, we reduce the pattern of dendritic branches of a detailed model to a set of equivalent primary dendrites. Second, the ion channel densities are estimated using a multi-objective optimization strategy to fit the voltage trace recorded under two conditions - with and without the apical dendrite occluded by pinching. Finally, we tune dendritic calcium channel parameters to model the initiation of dendritic calcium spikes and the coupling between soma and dendrite. More generally, this new method can be applied to construct families of models of different neuron types, with applications ranging from the study of information processing in single neurons to realistic simulations of large-scale network dynamics

Receptor-Associated Protein (RAP) Plays a Central Role in Modulating Aβ Deposition in APP/PS1 Transgenic Mice

BACKGROUND: Receptor associated protein (RAP) functions in the endoplasmic reticulum (ER) to assist in the maturation of several membrane receptor proteins, including low density lipoprotein receptor-related protein (LRP) and lipoprotein receptor 11 (SorLA/LR11). Previous studies in cell and mouse model systems have demonstrated that these proteins play roles in the metabolism of the amyloid precursor protein (APP), including processes involved in the generation, catabolism and deposition of beta-amyloid (Abeta) peptides. METHODOLOGY/PRINCIPAL FINDINGS: Mice transgenic for mutant APPswe and mutant presenilin 1 (PS1dE9) were mated to mice with homozygous deletion of RAP. Unexpectedly, mice that were homozygous null for RAP and transgenic for APPswe/PS1dE9 showed high post-natal mortality, necessitating a shift in focus to examine the levels of amyloid deposition in APPswe/PS1dE9 that were hemizygous null for RAP. Immunoblot analysis confirmed 50% reductions in the levels of RAP with modest reductions in the levels of proteins dependent upon RAP for maturation [LRP trend towards a 20% reduction ; SorLA/LR11 statistically significant 15% reduction (p<0.05)]. Changes in the levels of these proteins in the brains of [APPswe/PS1dE9](+/-)/RAP(+/-) mice correlated with 30-40% increases in amyloid deposition by 9 months of age. CONCLUSIONS/SIGNIFICANCE: Partial reductions in the ER chaperone RAP enhance amyloid deposition in the APPswe/PS1dE9 model of Alzheimer amyloidosis. Partial reductions in RAP also affect the maturation of LRP and SorLA/LR11, which are each involved in several different aspects of APP processing and Abeta catabolism. Together, these findings suggest a central role for RAP in Alzheimer amyloidogenesis

A Fokker-Planck formalism for diffusion with finite increments and absorbing boundaries

Gaussian white noise is frequently used to model fluctuations in physical systems. In Fokker-Planck theory, this leads to a vanishing probability density near the absorbing boundary of threshold models. Here we derive the boundary condition for the stationary density of a first-order stochastic differential equation for additive finite-grained Poisson noise and show that the response properties of threshold units are qualitatively altered. Applied to the integrate-and-fire neuron model, the response turns out to be instantaneous rather than exhibiting low-pass characteristics, highly non-linear, and asymmetric for excitation and inhibition. The novel mechanism is exhibited on the network level and is a generic property of pulse-coupled systems of threshold units.Comment: Consists of two parts: main article (3 figures) plus supplementary text (3 extra figures

A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience

The CARMEN Virtual Laboratory (VL) is a cloud-based platform which allows neuroscientists to store, share, develop, execute, reproduce and publicise their work. This paper describes new functionality in the CARMEN VL: an interactive publications repository. This new facility allows users to link data and software to publications. This enables other users to examine data and software associated with the publication and execute the associated software within the VL using the same data as the authors used in the publication. The cloud-based architecture and SaaS (Software as a Service) framework allows vast data sets to be uploaded and analysed using software services. Thus, this new interactive publications facility allows others to build on research results through reuse. This aligns with recent developments by funding agencies, institutions, and publishers with a move to open access research. Open access provides reproducibility and verification of research resources and results. Publications and their associated data and software will be assured of long-term preservation and curation in the repository. Further, analysing research data and the evaluations described in publications frequently requires a number of execution stages many of which are iterative. The VL provides a scientific workflow environment to combine software services into a processing tree. These workflows can also be associated with publications and executed by users. The VL also provides a secure environment where users can decide the access rights for each resource to ensure copyright and privacy restrictions are met

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Tracking CNS and systemic sources of oxidative stress during the course of chronic neuroinflammation

The functional dynamics and cellular sources of oxidative stress are central to understanding MS pathogenesis but remain elusive, due to the lack of appropriate detection methods. Here we employ NAD(P)H fluorescence lifetime imaging to detect functional NADPH oxidases (NOX enzymes) in vivo to identify inflammatory monocytes, activated microglia, and astrocytes expressing NOX1 as major cellular sources of oxidative stress in the central nervous system of mice affected by experimental autoimmune encephalomyelitis (EAE). This directly affects neuronal function in vivo, indicated by sustained elevated neuronal calcium. The systemic involvement of oxidative stress is mirrored by overactivation of NOX enzymes in peripheral CD11b(+) cells in later phases of both MS and EAE. This effect is antagonized by systemic intake of the NOX inhibitor and anti-oxidant epigallocatechin-3-gallate. Together, this persistent hyper-activation of oxidative enzymes suggests an "oxidative stress memory" both in the periphery and CNS compartments, in chronic neuroinflammation

A Novel Zinc Finger Protein Zfp277 Mediates Transcriptional Repression of the Ink4a/Arf Locus through Polycomb Repressive Complex 1

Polycomb group (PcG) proteins play a crucial role in cellular senescence as key transcriptional regulators of the Ink4a/Arf tumor suppressor gene locus. However, how PcG complexes target and contribute to stable gene silencing of the Ink4a/Arf locus remains little understood.We examined the function of Zinc finger domain-containing protein 277 (Zfp277), a novel zinc finger protein that interacts with the PcG protein Bmi1. Zfp277 binds to the Ink4a/Arf locus in a Bmi1-independent manner and interacts with polycomb repressor complex (PRC) 1 through direct interaction with Bmi1. Loss of Zfp277 in mouse embryonic fibroblasts (MEFs) caused dissociation of PcG proteins from the Ink4a/Arf locus, resulting in premature senescence associated with derepressed p16(Ink4a) and p19(Arf) expression. Levels of both Zfp277 and PcG proteins inversely correlated with those of reactive oxygen species (ROS) in senescing MEFs, but the treatment of Zfp277(-/-) MEFs with an antioxidant restored the binding of PRC2 but not PRC1 to the Ink4a/Arf locus. Notably, forced expression of Bmi1 in Zfp277(-/-) MEFs did not restore the binding of Bmi1 to the Ink4a/Arf locus and failed to bypass cellular senescence. A Zfp277 mutant that could not bind Bmi1 did not rescue Zfp277(-/-) MEFs from premature senescence.Our findings implicate Zfp277 in the transcriptional regulation of the Ink4a/Arf locus and suggest that the interaction of Zfp277 with Bmi1 is essential for the recruitment of PRC1 to the Ink4a/Arf locus. Our findings also highlight dynamic regulation of both Zfp277 and PcG proteins by the oxidative stress pathways

Modeling convergent ON and OFF pathways in the early visual system

For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron’s response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus–response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological “linear–nonlinear” (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron’s receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data