Při endoskopické operaci jednokomorového hydrocefalu se v mezikomorovém otvoru objevil blanitý lalok chorioidálního plexu, který jako záklopka střídavě ovládal průtok likvoru skrze foramen Monroe. Toto pozorování se stalo podkladem pro konstrukci korektního matematického modelu. Jeho výsledkem je originální poznatek, že pohyb likvoru má dvojí povahu: jednak pomalý pohyb průběžný a jednak mnohonásobně rychlejší kmitavý pohyb mezi horními třemi komorami: dvěma postranními a s nimi propojenou komorou třetí. Biologický význam tohoto pohybu tkví pravděpodobně v tom, že tlumí pulzové nárazy krve do mozku a zabezpečuje tak nervové soustavě optimální prostředí. Je to asi hlavní funkce likvorového prostoru hlavy.
During an endoscopic surgery for a uni-ventricular hydrocephalus, a membranous lobe of chorioidal plexus appeared within the intraventricular opening that, as a safety valve, controlled by turns the liquor flow through Monro´s foramen. This observation became the base for constructing a proper mathematical model. It resulted in the original knowledge that the liquor motion is of two different types of nature: a slow continuous motion and much faster flutter among three upper ventricles: two lateral ones and the third ventricle connected with them. Biological importance of this motion probably consists in the fact that it absorbs pulsatory rushes of blood into the brain thus securing the optimal environment for the nervous system. This may be the main function of the liquor space within the head.
Práce pojednává omodelu systémové dynamiky aplikovaný na predikci počtu pacientů sAlzheimerovou chorobou v EU ajejí možné finanční dopady. Demence při Alzheimerově chorobě je nejrozšířenějším typem demence aje vysoce spjata s věkem člověka – pacienta. Většina lidí je Alzheimerovou chorobou diagnostikována, když jsou starší 64 let. Stárnutí populace bude aktuálním problémem ještě několik desetiletí vdůsledku nízké porodnosti akontinuálního zvyšování střední délky života. Z tohoto důvodu je proto třeba se zaměřit na predikční modely Alzheimerovy choroby ajejích dopadů nejen na ekonomiku. V článku je představen dynamický modelovací přístup systémové dynamiky. Vytvořený model populace EU apacientů s AD je v závěru rozšířen osubmodel financí, odhadující náklady na pacienty dle tří dostupných nákladových studií.
The aim of the paper is to describe asystem dynamics model applied on aprediction of the number of patients with Alzheimer's disease in the EU in the future and related financial impacts. Dementia resulting from Alzheimer's disease is the most widely spread type of dementia and is highly connected with the age of the person – the patient. Most people are diagnosed with Alzheimer's disease when they are older than 64. The ageing of population will be an ongoing problem in the next few decades due to alow birth rate and increasing life expectancy. This is areason to focus on prediction models of Alzheimer's disease and its impact on economy. The paper presents adynamic modelling approach of system dynamics. The created model of the EU population and patients with AD is expanded by afinancial submodel at the end. This submodel estimates the cost on patients from three available cost studies.
- MeSH
- Alzheimer Disease * economics epidemiology MeSH
- Models, Economic MeSH
- Epidemiologic Methods MeSH
- Humans MeSH
- Forecasting MeSH
- Aging MeSH
- Models, Statistical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
Teorie nelineárních dynamických systémů aplikovaná na biologické neuronové sítě, u nichž je prokázáno deterministicky chaotické chování, vysvětluje překvapivým způsobem ukládání a rychlé vybavovaní paměťových stop. Pomocí fázových přechodů a synchronizace oscilací lze interpretovat epileptickou aktivitu jako projev univerzálních vlastností deterministicky chaotických systémů. Modely mozkové aktivity založené na chaotických neuronech lépe vystihují skutečné chování biologických neuronů.
The theory of non-linear dynamic systems applied to biological neurone networks where a determinist chaotic behaviour was proved explains in a surprising way the deposition and rapid recollection of memory traces. By means of phasic transition and synchronization of oscillations it is possible to interpret the epileptic activity as a manifestation of universal properties of determinist chaotic systems. Models of cerebral activity based on chaotic neurones give a better idea of the actual behaviour of biological neurones.
BACKGROUND: Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. METHODS: Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. RESULTS: The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. CONCLUSION: In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population.
- MeSH
- Alzheimer Disease diagnosis epidemiology MeSH
- Models, Biological MeSH
- Humans MeSH
- Systems Analysis * MeSH
- Models, Theoretical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The ubiquitous feature of the nervous system of wide spread occurrence of complex dynamics behaviour is treated. The cardinal question concerning the nature of generators of such complex behaviour, namely if it is ad hoc random or deterministic but strongly nonlinear, is analyzed. It is proved analytically that the discrete dynamics of single neurons with the sigmoidal transfer function is potentially chaotic. As the by-product the functional gain-threshold mechanism in neurons is derived. This allows for the new interpretations of famous experiments by Miyashita on squirell monkeys. Then it is shown that the continuous dynamics of the neural circuits of two-three neurons are endowed with the potentiality of chaotic firing, too. Finally, it will be argued that the classical dogma of stochastic or the ad hoc random neural coding can be taken as the limiting case of presenting new approach of deterministic or chaotic paradigm.
