Automatically Selecting a Suitable Integration Scheme for Systems of Differential Equations in Neuron Models

On the level of the spiking activity, the integrate-and-fire neuron is one of the most commonly used descriptions of neural activity. A multitude of variants has been proposed to cope with the huge diversity of behaviors observed in biological nerve cells. The main appeal of this class of model is that it can be defined in terms of a hybrid model, where a set of mathematical equations describes the sub-threshold dynamics of the membrane potential and the generation of action potentials is often only added algorithmically without the shape of spikes being part of the equations. In contrast to more detailed biophysical models, this simple description of neuron models allows the routine simulation of large biological neuronal networks on standard hardware widely available in most laboratories these days. The time evolution of the relevant state variables is usually defined by a small set of ordinary differential equations (ODEs). A small number of evolution schemes for the corresponding systems of ODEs are commonly used for many neuron models, and form the basis of the neuron model implementations built into commonly used simulators like Brian, NEST and NEURON. However, an often neglected problem is that the implemented evolution schemes are only rarely selected through a structured process based on numerical criteria. This practice cannot guarantee accurate and stable solutions for the equations and the actual quality of the solution depends largely on the parametrization of the model. In this article, we give an overview of typical equations and state descriptions for the dynamics of the relevant variables in integrate-and-fire models. We then describe a formal mathematical process to automate the design or selection of a suitable evolution scheme for this large class of models. Finally, we present the reference implementation of our symbolic analysis toolbox for ODEs that can guide modelers during the implementation of custom neuron models

Simulations on Consumer Tests: Systematic Evaluation of Tolerance Ranges by Model-Based Generation of Simulation Scenarios

Context: Since 2014 several modern cars were rated regarding the performances of their active safety systems at the European New Car Assessment Programme (EuroNCAP). Nowadays, consumer tests play a significant role for the OEM's series development with worldwide perspective, because a top rating is needed to underline the worthiness of active safety features from the customers' point of view. Furthermore, EuroNCAP already published their roadmap 2020 in which they outline further extensions in today's testing and rating procedures that will aggravate the current requirements addressed to those systems. Especially Autonomous Emergency Braking/Forward Collision Warning systems (AEB/FCW) are going to face a broader field of application as pedestrian detection or two-way traffic scenarios. Objective: This work focuses on the systematic generation of test scenarios concentrating on specific parameters that can vary within certain tolerance ranges like the lateral position of the vehicle-under-test (VUT) and its test velocity for example. It is of high interest to examine the effect of the tolerance ranges on the braking points in different test cases representing different trajectories and velocities because they will influence significantly a later scoring during the assessments and thus the safety abilities of the regarding car. Method: We present a formal model using a graph to represent the allowed variances based on the relevant points in time. Now, varying velocities of the VUT will be added to the model while the vehicle is approaching a target vehicle. The derived trajectories were used as test cases for a simulation environment. Selecting interesting test cases and processing them with the simulation environment, the influence on the system's performance of different test parameters will be investigated.Comment: 15 pages, 6 figures, Fahrerassistenzsysteme und Integrierte Sicherheit, VDI Berichte 2014, pp. 403-41

Report on the Aachen OCL meeting

As a continuation of the OCL workshop during the MODELS 2013 conference in October 2013, a number of OCL experts decided to meet in November 2013 in Aachen for two days to discuss possible short term improvements of OCL for an upcoming OMG meeting and to envision possible future long-term developments of the language. This paper is a sort of "minutes of the meeting" and intended to quickly inform the OCL community about the discussion topics

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

NESTML - die domänenspezifische Sprache für den NEST-Simulator neuronaler Netzwerke im Human Brain Project, 17

Domänenspezifische Sprachen erlauben gegenüber General Purpose Programmiersprachen begrenzten und problemorientierten Funktionsumfang an. Verschiedene Modellierungssprachen für die Computational Neuroscience wurden bereits vorgeschlagen. Da diese Sprachen jedoch typischerweise Simulatorunabhängigkeit anstreben, unterstützen sie oft nur eine Untermenge der vom Modellierer gewünschten Eigenschaften.Diese Arbeit präsentiert den Entwurf und die Implementierung der modularen und erweiterbaren domänenspezifischen Sprache NESTML, die Konzepte aus den Neurowissenschaften als vollwertige Sprachkonstrukte zur Verfügung stellt und Neurowissenschaftler so bei der Erstellung von Neuronemodellen für das neuronale Simulationswerkzeug NEST unterstützt.NESTML wurde mithilfe von MontiCore entwickelt. MontiCore ist eine Language Workbench zur Erstellung von domänenspezifischen Sprachen. MontiCore verwendet und erweitert das Grammatikformat von ANTLR4, das auf dem EBNF-Formalismus basiert, um zusätzliche Konzepte für die Grammatikwiederverwendung. MontiCore stellt eine modulare Infrastruktur für das Parsen von Modellen, den Aufbau der Symboltabllen und zum Prüfen der Kontextbedingungen bereit. Damit können die Entwicklungskosten von NESTML signifikant gesenkt werden

NESTML - die domänenspezifische Sprache für den NEST-Simulator neuronaler Netzwerke im Human Brain Project

Domänenspezifische Sprachen erlauben gegenüber General Purpose Programmiersprachen begrenzten und problemorientierten Funktionsumfang an. Verschiedene Modellierungssprachen für die Computational Neuroscience wurden bereits vorgeschlagen. Da diese Sprachen jedoch typischerweise Simulatorunabhängigkeit anstreben, unterstützen sie oft nur eine Untermenge der vom Modellierer gewünschten Eigenschaften.Diese Arbeit präsentiert den Entwurf und die Implementierung der modularen und erweiterbaren domänenspezifischen Sprache NESTML, die Konzepte aus den Neurowissenschaften als vollwertige Sprachkonstrukte zur Verfügung stellt und Neurowissenschaftler so bei der Erstellung von Neuronemodellen für das neuronale Simulationswerkzeug NEST unterstützt.NESTML wurde mithilfe von MontiCore entwickelt. MontiCore ist eine Language Workbench zur Erstellung von domänenspezifischen Sprachen. MontiCore verwendet und erweitert das Grammatikformat von ANTLR4, das auf dem EBNF-Formalismus basiert, um zusätzliche Konzepte für die Grammatikwiederverwendung. MontiCore stellt eine modulare Infrastruktur für das Parsen von Modellen, den Aufbau der Symboltabllen und zum Prüfen der Kontextbedingungen bereit. Damit können die Entwicklungskosten von NESTML signifikant gesenkt werden