Dynamical systems analysis of spike-adding mechanisms in transient bursts

Transient bursting behaviour of excitable cells, such as neurons, is a common feature observed experimentally, but theoretically, it is not well understood. We analyse a five-dimensional simplified model of after-depolarisation that exhibits transient bursting behaviour when perturbed with a short current injection. Using one-parameter continuation of the perturbed orbit segment formulated as a well-posed boundary value problem, we show that the spike-adding mechanism is a canard-like transition that has a different character from known mechanisms for periodic burst solutions. The biophysical basis of the model gives a natural time-scale separation, which allows us to explain the spike-adding mechanism using geometric singular perturbation theory, but it does not involve actual bifurcations as for periodic bursts. We show that unstable sheets of the critical manifold, formed by saddle equilibria of the system that only exist in a singular limit, are responsible for the spike-adding transition; the transition is organised by the slow flow on the critical manifold near folds of this manifold. Our analysis shows that the orbit segment during the spike-adding transition includes a fast transition between two unstable sheets of the slow manifold that are of saddle type. We also discuss a different parameter regime where the presence of additional saddle equilibria of the full system alters the spike-adding mechanism

Artificial intelligence, bias and clinical safety

This is the final version. Available on open access from BMJ Publishing group via the DOI in this recordEngineering and Physical Sciences Research Council (EPSRC

Information Transfer via Gonadotropin-Releasing Hormone Receptors to ERK and NFAT: Sensing GnRH and Sensing Dynamics

This is the final version of the article. Available from Oxford University Press via the DOI in this record.Information theoretic approaches can be used to quantify information transfer via cell signaling networks. In this study, we do so for gonadotropin-releasing hormone (GnRH) activation of extracellular signal-regulated kinase (ERK) and nuclear factor of activated T cells (NFAT) in large numbers of individual fixed LβT2 and HeLa cells. Information transfer, measured by mutual information between GnRH and ERK or NFAT, was <1 bit (despite 3-bit system inputs). It was increased by sensing both ERK and NFAT, but the increase was <50%. In live cells, information transfer via GnRH receptors to NFAT was also <1 bit and was increased by consideration of response trajectory, but the increase was <10%. GnRH secretion is pulsatile, so we explored information gained by sensing a second pulse, developing a model of GnRH signaling to NFAT with variability introduced by allowing effectors to fluctuate. Simulations revealed that when cell–cell variability reflects rapidly fluctuating effector levels, additional information is gained by sensing two GnRH pulses, but where it is due to slowly fluctuating effectors, responses in one pulse are predictive of those in another, so little information is gained from sensing both. Wet laboratory experiments revealed that the latter scenario holds true for GnRH signaling; within the timescale of our experiments (1 to 2 hours), cell–cell variability in the NFAT pathway remains relatively constant, so trajectories are reproducible from pulse to pulse. Accordingly, joint sensing, sensing of response trajectories, and sensing of repeated pulses can all increase information transfer via GnRH receptors, but in each case the increase is small.This work was supported by Biochemical and Biophysical Science Research Council Grant BBSRC BB/J014699/1 (to C.A.M. and K.T.-A.). M.V. acknowledges the support of the Medical Research Council (a strategic skills development fellowship in biomedical informatics) and the Engineering and Physical Sciences Research Council via Grant EP/N014391/1

Separable actions of acetylcholine and noradrenaline on neuronal ensemble formation in hippocampal CA3 circuits

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. The neuromodulators acetylcholine and noradrenaline are separately proposed as saliency signals that dictate memory encoding but it is not known if they represent distinct signals with separate mechanisms. Here, we show experimentally that acetylcholine, and to a lesser extent noradrenaline, suppress feed-forward inhibition and enhance Excitatory–Inhibitory ratio in the mossy fiber pathway but CA3 recurrent network properties are only altered by acetylcholine. We explore the implications of these findings on CA3 ensemble formation using a hierarchy of models. In reconstructions of CA3 pyramidal cells, mossy fiber pathway disinhibition facilitates postsynaptic dendritic depolarization known to be required for synaptic plasticity at CA3-CA3 recurrent synapses. We further show in a spiking neural network model of CA3 how acetylcholine-specific network alterations can drive rapid overlapping ensemble formation. Thus, through these distinct sets of mechanisms, acetylcholine and noradrenaline facilitate the formation of neuronal ensembles in CA3 that encode salient episodic memories in the hippocampus but acetylcholine selectively enhances the density of memory storage

Information Transfer in Gonadotropin-releasing Hormone (GnRH) Signaling: extracellular signal-regulated kinase (ERK)-mediated feedback loops control hormone sensing

The computation model used in the study of GnRH signalling which was used to generate the data appearing in this paper is in ORE at http://hdl.handle.net/10871/27844Cell signaling pathways are noisy communication channels, and statistical measures derived from information theory can be used to quantify the information they transfer. Here we use single cell signaling measures to calculate mutual information as a measure of information transfer via gonadotropin-releasing hormone (GnRH) receptors (GnRHR) to extracellular signal-regulated kinase (ERK) or nuclear factor of activated T-cells (NFAT). This revealed mutual information values <1 bit, implying that individual GnRH-responsive cells cannot unambiguously differentiate even two equally probable input concentrations. Addressing possible mechanisms for mitigation of information loss, we focused on the ERK pathway and developed a stochastic activation model incorporating negative feedback and constitutive activity. Model simulations revealed interplay between fast (min) and slow (min-h) negative feedback loops with maximal information transfer at intermediate feedback levels. Consistent with this, experiments revealed that reducing negative feedback (by expressing catalytically inactive ERK2) and increasing negative feedback (by Egr1-driven expression of dual-specificity phosphatase 5 (DUSP5)) both reduced information transfer from GnRHR to ERK. It was also reduced by blocking protein synthesis (to prevent GnRH from increasing DUSP expression) but did not differ for different GnRHRs that do or do not undergo rapid homologous desensitization. Thus, the first statistical measures of information transfer via these receptors reveals that individual cells are unreliable sensors of GnRH concentration and that this reliability is maximal at intermediate levels of ERK-mediated negative feedback but is not influenced by receptor desensitization.This work was supported by a Biochemical and Biophysical Science Research Council award (BBSRC BB/J014699/1; to C. A. M. and K. T.-A.)

Quantitative approaches in clinical reproductive endocrinology

Understanding the human hypothalamic-pituitary-gonadal (HPG) axis presents a major challenge for medical science. Dysregulation of the HPG axis is linked to infertility and a thorough understanding of its dynamic behaviour is necessary to both aid diagnosis and to identify the most appropriate hormonal interventions. Here, we review how quantitative models are being used in the context of clinical reproductive endocrinology to: 1. analyse the secretory patterns of reproductive hormones; 2. evaluate the effect of drugs in fertility treatment; 3. aid in the personalization of assisted reproductive technology (ART). In this review, we demonstrate that quantitative models are indispensable tools enabling us to describe the complex dynamic behaviour of the reproductive axis, refine the treatment of fertility disorders, and predict clinical intervention outcomes

Factors influencing digital review of pathology test results in an inpatient setting: a cross-sectional study

This is the final version. Available from Oxford University Press via the DOI in this record.Availability of data and material: The datasets generated and/or analysed during the current study are not publicly available due to the remote possibility of targeted patient re-identification through a linkage attack. Limited data may be available from the corresponding author on reasonable request, and review by the information governance and ethics teams.BACKGROUND: Delay or failure to view test results in a hospital setting can lead to delayed diagnosis, risk of patient harm, and represents inefficiency. Factors influencing this were investigated to identify how timeliness and completeness of test review could be improved through an evidence based redesign of the use of clinical test review software. METHODS: A cross section of all abnormal haematology and biochemistry results which were published on a digital test review platform over a three year period were investigated. The time it took for clinicians to view these results, and the results that were not viewed within 30 days, were analysed relative to time of the week, the detailed type of test, and an indicator of patient record data quality. RESULTS: The majority of results were viewed within 90 minutes, and 93.9% of these results viewed on the digital platform within 30 days. There was significant variation in results review throughout the week, shown to be due to an interplay between technical and clinical workflow factors. Routine results were less likely to be reviewed, as were those with patient record data quality issues . CONCLUSION: The evidence suggests that test result review would be improved by stream-lining access to the result platform, differentiating between urgent and routine results, improving handover of responsibility for result review, and improving search for temporary patient records. Altering the timing of phlebotomy rounds, and a review of the appropriateness of routine test requests at the weekend may also improve result review rates.Engineering and Physical Sciences Research Council (EPSRC)NHS EnglandAlan Turing Institut

BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

Open Access ArticleLarge-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.Engineering and Physical Sciences Research Council (EPSRC)Biotechnology and Biological Sciences Research Council (BBSRC

Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures

This is the final version. Available from The Royal Society via the DOI in this record. Data and code supporting this article can be accessed on GitHub at the following link: https://github.com/terminological/uk-covid-datatools/tree/master/vignettes/current-rt.The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reproduction number has become an essential parameter for monitoring disease transmission across settings and guiding interventions. The UK published weekly estimates of the reproduction number in the UK starting in May 2020 which are formed from multiple independent estimates. In this paper, we describe methods used to estimate the time-varying SARS-CoV-2 reproduction number for the UK. We used multiple data sources and estimated a serial interval distribution from published studies. We describe regional variability and how estimates evolved during the early phases of the outbreak, until the relaxing of social distancing measures began to be introduced in early July. Our analysis is able to guide localized control and provides a longitudinal example of applying these methods over long timescales. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.Engineering and Physical Sciences Research Council (EPSRC)Engineering and Physical Sciences Research Council (EPSRC)Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC)National Institute for Health Research (NIHR

Domino-like transient dynamics at seizure onset in epilepsy

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: We have made publicly available the 15 epochs of human EEG data containing generalized paroxysms classified as focal onset, and all 15 epochs containing seizures from one individual used in the manuscript, 1252 EEG epochs containing seizures classified as generalized onset and the 6 mouse mEC recordings. All data and the code used for the data analysis and model simulations they can be accessed via DOI 10.17605/OSF.IO/G2EXK.The International League Against Epilepsy (ILAE) groups seizures into “focal”, “generalized” and “unknown” based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice.Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC