Validity and reliability of the DANU sports system for walking and running gait assessment.

Objective. Gait assessments have traditionally been analysed in laboratory settings, but this may not reflect natural gait. Wearable technology may offer an alternative due to its versatility. The purpose of the study was to establish the validity and reliability of temporal gait outcomes calculated by the DANU sports system, against a 3D motion capture reference system.Approach. Forty-one healthy adults (26 M, 15 F, age 36.4 ± 11.8 years) completed a series of overground walking and jogging trials and 60 s treadmill walking and running trials at various speeds (8-14 km hr-1), participants returned for a second testing session to repeat the same testing.Main results. For validity, 1406 steps and 613 trials during overground and across all treadmill trials were analysed respectively. Temporal outcomes generated by the DANU sports system included ground contact time, swing time and stride time all demonstrated excellent agreement compared to the laboratory reference (intraclass correlation coefficient (ICC) > 0.900), aside from ground contact time during overground jogging which had good agreement (ICC = 0.778). For reliability, 666 overground and 511 treadmill trials across all speeds were examined. Test re-test agreement was excellent for all outcomes across treadmill trials (ICC > 0.900), except for swing time during treadmill walking which had good agreement (ICC = 0.886). Overground trials demonstrated moderate to good test re-test agreement (ICC = 0.672-0.750), which may be due to inherent variability of self-selected (rather than treadmill set) pacing between sessions.Significance. Overall, this study showed that temporal gait outcomes from the DANU Sports System had good to excellent validity and moderate to excellent reliability in healthy adults compared to an established laboratory reference.

Assessing the robustness of time-to-event models for estimating unmarked wildlife abundance using remote cameras.

Recently developed methods, including time-to-event and space-to-event models, estimate the abundance of unmarked populations from encounter rates with camera trap arrays, addressing a gap in noninvasive wildlife monitoring. However, estimating abundance from encounter rates relies on assumptions that can be difficult to meet in the field, including random movement, population closure, and an accurate estimate of movement speed. Understanding how these models respond to violation of these assumptions will assist in making them more applicable in real-world settings. We used simulated walk models to test the effects of violating the assumptions of the time-to-event model under four scenarios: (1) incorrectly estimating movement speed, (2) violating closure, (3) individuals moving within simplified territories (i.e., movement restricted to partially overlapping circles), (4) and individuals clustering in preferred habitat. The time-to-event model was robust to closure violations, territoriality, and clustering when cameras were placed randomly. However, the model failed to estimate abundance accurately when movement speed was incorrectly estimated or cameras were placed nonrandomly with respect to habitat. We show that the time-to-event model can provide unbiased estimates of abundance when some assumptions that are commonly violated in wildlife studies are not met. Having a robust method for estimating the abundance of unmarked populations with remote cameras will allow practitioners to monitor a more diverse array of populations noninvasively. With the time-to-event model, placing cameras randomly with respect to animal movement and accurately estimating movement speed allows unbiased estimation of abundance. The model is robust to violating the other assumptions we tested.

A Neanderthal Sodium Channel Increases Pain Sensitivity in Present-Day Humans.

The sodium channel Nav1.7 is crucial for impulse generation and conduction in peripheral pain pathways [1]. In Neanderthals, the Nav1.7 protein carried three amino acid substitutions (M932L, V991L, and D1908G) relative to modern humans. We expressed Nav1.7 proteins carrying all combinations of these substitutions and studied their electrophysiological effects. Whereas the single amino acid substitutions do not affect the function of the ion channel, the full Neanderthal variant carrying all three substitutions, as well as the combination of V991L with D1908G, shows reduced inactivation, suggesting that peripheral nerves were more sensitive to painful stimuli in Neanderthals than in modern humans. We show that, due to gene flow from Neanderthals, the three Neanderthal substitutions are found in ∼0.4% of present-day Britons, where they are associated with heightened pain sensitivity.

Competition and specialization in an African forest carnivore community.

Globally, human activities have led to the impoverishment of species assemblages and the disruption of ecosystem function. Determining whether this poses a threat to future ecosystem stability necessitates a thorough understanding of mechanisms underpinning community assembly and niche selection. Here, we tested for niche segregation within an African small carnivore community in Kibale National Park, Uganda. We used occupancy modeling based on systematic camera trap surveys and fine-scale habitat measures, to identify opposing preferences between closely related species (cats, genets, and mongooses). We modeled diel activity patterns using kernel density functions and calculated the overlap of activity periods between related species. We also used co-occupancy modeling and activity overlap analyses to test whether African golden cats Caracal aurata influenced the smaller carnivores along the spatial and/or temporal axes. There was some evidence that related species segregated habitat and activity patterns. Specialization was particularly strong among forest species. The cats and genets partitioned habitat, while the mongooses partitioned both habitat and activity period. We found little evidence for interference competition between African golden cats and other small carnivores, although weak interference competition was suggested by lower detection probabilities of some species at stations where African golden cats were present. This suggests that community assembly and coexistence in this ecosystem are primarily driven by more complex processes. The studied carnivore community contains several forest specialists, which are typically more prone to localized extinction. Preserving the observed community assemblage will therefore require the maintenance of a large variety of habitats, with a particular focus on those required by the more specialized carnivores.

Synaptic proximity enables NMDAR signalling to promote brain metastasis.

Metastasis-the disseminated growth of tumours in distant organs-underlies cancer mortality. Breast-to-brain metastasis (B2BM) is a common and disruptive form of cancer and is prevalent in the aggressive basal-like subtype, but is also found at varying frequencies in all cancer subtypes. Previous studies revealed parameters of breast cancer metastasis to the brain, but its preference for this site remains an enigma. Here we show that B2BM cells co-opt a neuronal signalling pathway that was recently implicated in invasive tumour growth, involving activation by glutamate ligands of N-methyl-D-aspartate receptors (NMDARs), which is key in model systems for metastatic colonization of the brain and is associated with poor prognosis. Whereas NMDAR activation is autocrine in some primary tumour types, human and mouse B2BM cells express receptors but secrete insufficient glutamate to induce signalling, which is instead achieved by the formation of pseudo-tripartite synapses between cancer cells and glutamatergic neurons, presenting a rationale for brain metastasis.

GKAP Acts as a Genetic Modulator of NMDAR Signaling to Govern Invasive Tumor Growth.

Genetic linkage analysis previously suggested that GKAP, a scaffold protein of the N-methyl-D-aspartate receptor (NMDAR), was a potential modifier of invasion in a mouse model of pancreatic neuroendocrine tumor (PanNET). Here, we establish that GKAP governs invasive growth and treatment response to NMDAR inhibitors of PanNET via its pivotal role in regulating NMDAR pathway activity. Combining genetic knockdown of GKAP and pharmacological inhibition of NMDAR, we implicate as downstream effectors FMRP and HSF1, which along with GKAP demonstrably support invasiveness of PanNET and pancreatic ductal adenocarcinoma cancer cells. Furthermore, we distilled genome-wide expression profiles orchestrated by the NMDAR-GKAP signaling axis, identifying transcriptome signatures in tumors with low/inhibited NMDAR activity that significantly associate with favorable patient prognosis in several cancer types.

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution - Application to the jaguar (Panthera onca).

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species' entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world's jaguar population at 173,000 (95% CI: 138,000-208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions.

Relationships between humans and ungulate prey shape Amur tiger occurrence in a core protected area along the Sino-Russian border.

Large carnivore populations are globally threatened by human impacts. Better protection could benefit carnivores, co-occurring species, and the ecosystems they inhabit. The relationship between carnivores and humans, however, is not always consistent in areas of high human activities and is often mediated through the effects of humans on their ungulate prey. To test assumptions regarding how prey abundance and humans affect carnivore occurrence, density, and daily activity patterns, we assessed tiger-prey-human spatiotemporal patterns based on camera-trapping data in Hunchun Nature Reserve, a promising core area for tiger restoration in China. Our study area contained seasonally varying levels of human disturbance in summer and winter. We used N-mixture models to predict the relative abundance of ungulate prey considering human and environmental covariates. We estimated tiger spatial distribution using occupancy models and models of prey relative abundance from N-mixture models. Finally, we estimated temporal activity patterns of tigers and prey using kernel density estimates to test for temporal avoidance between tigers, prey, and humans. Our results show that human-related activities depressed the relative abundance of prey at different scales and in different ways, but across species, the relative abundance of prey directly increased tiger occupancy. Tiger occupancy was strongly positively associated with the relative abundance of sika deer in summer and winter. The crepuscular and nocturnal tigers also apparently synchronized their activity with that of wild boar and roe deer. However, tigers temporally avoided human activity without direct spatial avoidance. Our study supports the effects of humans on tigers through human impacts on prey populations. Conservation efforts may not only target human disturbance on predators, but also on prey to alleviate human-carnivore conflict.

Kv4.2 channel activity controls intrinsic firing dynamics of arcuate kisspeptin neurons.

KEY POINTS: Neurons in the hypothalamus of the brain which secrete the peptide kisspeptin are important regulators of reproduction, and normal reproductive development. Electrical activity, in the form of action potentials, or spikes, leads to secretion of peptides and neurotransmitters, influencing the activity of downstream neurons; in kisspeptin neurons, this activity is highly irregular, but the mechanism of this is not known. In this study, we show that irregularity depends on the presence of a particular type of potassium ion channel in the membrane, which opens transiently in response to electrical excitation. The results contribute to understanding how kisspeptin neurons generate and time their membrane potential spikes, and how reliable this process is. Improved understanding of the activity of kisspeptin neurons, and how it shapes their secretion of peptides, is expected to lead to better treatment for reproductive dysfunction and disorders of reproductive development. ABSTRACT: Kisspeptin neurons in the hypothalamus are critically involved in reproductive function, via their effect on GnRH neuron activity and consequent gonadotropin release. Kisspeptin neurons show an intrinsic irregularity of firing, but the mechanism of this remains unclear. To address this, we carried out targeted whole-cell patch-clamp recordings of kisspeptin neurons in the arcuate nucleus (Kiss1Arc ), in brain slices isolated from adult male Kiss-Cre:tdTomato mice. Cells fired irregularly in response to constant current stimuli, with a wide range of spike time variability, and prominent subthreshold voltage fluctuations. In voltage clamp, both a persistent sodium (NaP) current and a fast transient (A-type) potassium current were apparent, activating at potentials just below the threshold for spiking. These currents have also previously been described in irregular-spiking cortical interneurons, in which the A-type current, mediated by Kv4 channels, interacts with NaP current to generate complex dynamics of the membrane potential, and irregular firing. In Kiss1Arc neurons, A-type current was blocked by phrixotoxin, a specific blocker of Kv4.2/4.3 channels, and consistent expression of Kv4.2 transcripts was detected by single-cell RT-PCR. In addition, firing irregularity was correlated to the density of A-type current in the membrane. Using conductance injection, we demonstrated that adding Kv4-like potassium conductance (gKv4 ) to a cell produces a striking increase in firing irregularity, and excitability is reduced, while subtracting gKv4 has the opposite effects. Thus, we propose that Kv4 interacting dynamically with NaP is a key determinant of the irregular firing behaviour of Kiss1Arc neurons, shaping their physiological function in gonadotropin release.

Fluctuation Analysis in Nonstationary Conditions: Single Ca2+ Channel Current in Pyramidal Neurons.

Fluctuation analysis is a method that allows measurement of the single-channel current of ion channels even when it is too small to be resolved directly with the patch-clamp technique. This is the case for voltage-gated calcium channels. They are present in all mammalian central neurons, controlling presynaptic release of transmitter, postsynaptic signaling, and synaptic integration. The amplitudes of their single-channel currents in a physiological concentration of extracellular calcium, however, are small and not well determined. But measurement of this quantity is essential for estimating numbers of functional voltage-gated calcium channels in the membrane and the size of channel-associated calcium signaling domains, and for understanding the stochastic nature of calcium signaling. Here, we recorded the voltage-gated calcium channel current in nucleated patches from layer 5 pyramidal neurons in rat neocortex, in physiological external calcium (1-2 mM). The ensemble-averaging of current responses required for conventional fluctuation analysis proved impractical because of the rapid rundown of calcium channel currents. We therefore developed a more robust method, using mean current fitting of individual current responses and band-pass filtering. Furthermore, voltage-ramp stimulation proved useful. We validated the accuracy of the method by analyzing simulated data. At an external calcium concentration of 1 mM, and a membrane potential of -20 mV, we found that the average single-channel current amplitude was ∼0.04 pA, increasing to 0.065 pA at 2 mM external calcium, and 0.12 pA at 5 mM. The relaxation time constant of the fluctuations was in the range 0.2-0.8 ms. The results are relevant to understanding the stochastic properties of dendritic Ca2+ spikes in neocortical layer 5 pyramidal neurons. With the reported method, single-channel current amplitude of native voltage-gated calcium channels can be resolved accurately despite conditions of unstable rundown.

Autocrine, paracrine and necrotic NMDA receptor signalling in mouse pancreatic neuroendocrine tumour cells.

N-Methyl-d-aspartate receptor (NMDAR) activation is implicated in the malignant progression of many cancer types, as previously shown by the growth-inhibitory effects of NMDAR antagonists. NMDAR-mediated calcium influx and its downstream signalling depend critically, however, on the dynamics of membrane potential and ambient glutamate concentration, which are poorly characterized in cancer cells. Here, we have used low-noise whole-cell patch-clamp recording to investigate the electrophysiology of glutamate signalling in pancreatic neuroendocrine tumour (PanNET) cells derived from a genetically-engineered mouse model (GEMM) of PanNET, in which NMDAR signalling is known to promote cancer progression. Activating NMDARs caused excitation and intracellular calcium elevation, and intracellular perfusion with physiological levels of glutamate led to VGLUT-dependent autocrine NMDAR activation. Necrotic cells, which are often present in rapidly-growing tumours, were shown to release endogenous cytoplasmic glutamate, and necrosis induced by mechanical rupture of the plasma membrane produced intense NMDAR activation in nearby cells. Computational modelling, based on these results, predicts that NMDARs in cancer cells can be strongly activated in the tumour microenvironment by both autocrine glutamate release and necrosis.

Flexibility in the duration of parental care: Female leopards prioritise cub survival over reproductive output.

Deciding when to terminate care of offspring is a key consideration for parents. Prolonging care may increase fitness of current offspring, but it can also reduce opportunities for future reproduction. Despite its evolutionary importance, few studies have explored the optimal duration of parental care, particularly among large carnivores. We used a 40-year dataset to assess the trade-offs associated with the length of maternal care in leopards in the Sabi Sand Game Reserve, South Africa. We compared the costs imposed by care on the survival and residual reproductive value of leopard mothers against the benefits derived from maternal care in terms of increased offspring survival, recruitment and reproduction. We also examined the demographic and ecological factors affecting the duration of care in the light of five explanatory hypotheses: litter size, sex allocation, resource limitation, timing of independence and terminal investment. Duration of care exhibited by female leopards varied markedly, from 9 to 35 months. Mothers did not appear to suffer any short- or long-term survival costs from caring for cubs, but extending care reduced the number of litters that mothers could produce during their lifetimes. Interestingly, the duration of care did not appear to affect the post-independence survival or reproductive success of offspring (although it may have indirectly affected offspring survival by influencing dispersal distance). However, results from generalised linear mixed models showed that mothers prolonged care during periods of prey scarcity, supporting the resource limitation hypothesis. Female leopards also cared for sons longer than daughters, in line with the sex-allocation hypothesis. Cub survival is an important determinant of the lifetime reproductive success in leopards. By buffering offspring against environmental perturbation without jeopardising their own survivorship, female leopards apparently "hedge their bets" with current offspring rather than gamble on future offspring which have a small probability of surviving. In many species, parents put their own needs before that of their offspring. Leopard mothers appear sensitive to their offspring's demands, and adjust levels of care accordingly.

Stochastic and deterministic dynamics of intrinsically irregular firing in cortical inhibitory interneurons.

Most cortical neurons fire regularly when excited by a constant stimulus. In contrast, irregular-spiking (IS) interneurons are remarkable for the intrinsic variability of their spike timing, which can synchronize amongst IS cells via specific gap junctions. Here, we have studied the biophysical mechanisms of this irregular spiking in mice, and how IS cells fire in the context of synchronous network oscillations. Using patch-clamp recordings, artificial dynamic conductance injection, pharmacological analysis and computational modeling, we show that spike time irregularity is generated by a nonlinear dynamical interaction of voltage-dependent sodium and fast-inactivating potassium channels just below spike threshold, amplifying channel noise. This active irregularity may help IS cells synchronize with each other at gamma range frequencies, while resisting synchronization to lower input frequencies.

Estimating abundance and density of Amur tigers along the Sino-Russian border.

As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China.

Intrinsic Cornu Ammonis Area 1 Theta-Nested Gamma Oscillations Induced by Optogenetic Theta Frequency Stimulation.

Gamma oscillations (30-120 Hz) are thought to be important for various cognitive functions, including perception and working memory, and disruption of these oscillations has been implicated in brain disorders, such as schizophrenia and Alzheimer's disease. The cornu ammonis area 1 (CA1) of the hippocampus receives gamma frequency inputs from upstream regions (cornu ammonis area 3 and medial entorhinal cortex) and generates itself a faster gamma oscillation. The exact nature and origin of the intrinsic CA1 gamma oscillation is still under debate. Here, we expressed channel rhodopsin-2 under the CaMKIIα promoter in mice and prepared hippocampal slices to produce a model of intrinsic CA1 gamma oscillations. Sinusoidal optical stimulation of CA1 at theta frequency was found to induce robust theta-nested gamma oscillations with a temporal and spatial profile similar to CA1 gamma in vivo The results suggest the presence of a single gamma rhythm generator with a frequency range of 65-75 Hz at 32 °C. Pharmacological analysis found that the oscillations depended on both AMPA and GABAA receptors. Cell-attached and whole-cell recordings revealed that excitatory neuron firing slightly preceded interneuron firing within each gamma cycle, suggesting that this intrinsic CA1 gamma oscillation is generated with a pyramidal-interneuron circuit mechanism. SIGNIFICANCE STATEMENT: This study demonstrates that the cornu ammonis area 1 (CA1) is capable of generating intrinsic gamma oscillations in response to theta input. This gamma generator is independent of activity in the upstream regions, highlighting that CA1 can produce its own gamma oscillation in addition to inheriting activity from the upstream regions. This supports the theory that gamma oscillations predominantly function to achieve local synchrony, and that a local gamma generated in each area conducts the signal to the downstream region.

Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large carnivore species where landscape-scale resource selection data already exist.

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology.

Mortality of Amur tigers: The more things change, the more they stay the same.

Poaching as well as loss of habitat and prey are identified as causes of tiger population declines. Although some studies have examined habitat requirements and prey availability, few studies have quantified cause-specific mortality of tigers. We used cumulative incidence functions (CIFs) to quantify cause-specific mortality rates of tigers, expanding and refining earlier studies to assess the potential impact of a newly emerging disease. To quantify changes in tiger mortality over time, we re-examined data first collected by Goodrich et al. (; study period 1: 1992-2004) as well as new telemetry data collected since January 2005 (study period 2: 2005-2012) using a total of 57 tigers (27 males and 30 females) monitored for an average of 747 days (range 26-4718 days). Across the entire study period (1992 to 2012) we found an estimated average annual survival rate of 0.75 for all tigers combined. Poaching was the primary cause of mortality during both study periods, followed by suspected poaching, distemper and natural/unknown causes. Since 2005, poaching mortality has remained relatively constant and, if combined with suspected poaching, may account for a loss of 17-19% of the population each year. Canine distemper virus (CDV) may be an additive form of mortality to the population, currently accounting for an additional 5%. Despite this relatively new source of mortality, poaching remains the main threat to Amur tiger survival and, therefore, population growth.

Density of voltage-gated potassium channels is a bifurcation parameter in pyramidal neurons.

Several types of intrinsic dynamics have been identified in brain neurons. Type 1 excitability is characterized by a continuous frequency-stimulus relationship and, thus, an arbitrarily low frequency at threshold current. Conversely, Type 2 excitability is characterized by a discontinuous frequency-stimulus relationship and a nonzero threshold frequency. In previous theoretical work we showed that the density of Kv channels is a bifurcation parameter, such that increasing the Kv channel density in a neuron model transforms Type 1 excitability into Type 2 excitability. Here we test this finding experimentally, using the dynamic clamp technique on Type 1 pyramidal cells in rat cortex. We found that increasing the density of slow Kv channels leads to a shift from Type 1 to Type 2 threshold dynamics, i.e., a distinct onset frequency, subthreshold oscillations, and reduced latency to first spike. In addition, the action potential was resculptured, with a narrower spike width and more pronounced afterhyperpolarization. All changes could be captured with a two-dimensional model. It may seem paradoxical that an increase in slow K channel density can lead to a higher threshold firing frequency; however, this can be explained in terms of bifurcation theory. In contrast to previous work, we argue that an increased outward current leads to a change in dynamics in these neurons without a rectification of the current-voltage curve. These results demonstrate that the behavior of neurons is determined by the global interactions of their dynamical elements and not necessarily simply by individual types of ion channels.

libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment.