Applying a Dynamical Systems Model and Network Theory to Major Depressive Disorder

Mental disorders like major depressive disorder can be seen as complex dynamical systems. In this study we investigate the dynamic behaviour of individuals to see whether or not we can expect a transition to another mood state. We introduce a mean field model to a binomial process, where we reduce a dynamic multidimensional system (stochastic cellular automaton) to a one-dimensional system to analyse the dynamics. Using maximum likelihood estimation, we can estimate the parameter of interest which, in combination with a bifurcation diagram, reflects the expectancy that someone has to transition to another mood state. After validating the proposed method with simulated data, we apply this method to two empirical examples, where we show its use in a clinical sample consisting of patients diagnosed with major depressive disorder, and a general population sample. Results showed that the majority of the clinical sample was categorized as having an expectancy for a transition, while the majority of the general population sample did not have this expectancy. We conclude that the mean field model has great potential in assessing the expectancy for a transition between mood states. With some extensions it could, in the future, aid clinical therapists in the treatment of depressed patients.Comment: arXiv admin note: text overlap with arXiv:1610.0504

Reproductive Management of the Dairy Goat Doe

With the slow but steady increase in interest in dairy goats, our profession finds itself facing the problems of this unique species with increasing frequency. This creates a special challenge for us in two respects. First, our medical knowledge about the goat is still sparse and is just now beginning to expand due to an increased interest within the veterinary profession

ESMvis:a tool for visualizing individual Experience Sampling Method (ESM) data

PURPOSE: The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data. METHODS: We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive-compulsive disorder with comorbid depression. RESULTS: We provided personalized feedback, in which both the overall trajectory and specific time moments were captured in a movie format. Two relapses during the study period could be visually determined, and subsequently confirmed by the therapist. The therapist and patient evaluated ESMvis as an insightful add-on tool to care-as-usual. CONCLUSION: ESMvis is a showcase on providing personalized feedback by dynamic visualization of ESM time-series data. Our tool is freely available and adjustable, making it widely applicable. In addition to potential applications in clinical practice, ESMvis can work as an exploratory tool that can lead to new hypotheses and inform more complex statistical techniques

Contribution of mixing to upward transport across the tropical tropopause layer (TTL)

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board the high-altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the entire TTL region roughly extending between 350 and 420 K. Here, analysis of transport across the TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by meteorological analysis winds and heating/cooling rates derived from a radiation calculation. Below the tropopause, the model smoothly transforms from the isentropic to the hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the vertical wind of the meteorological analysis. As in previous CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observations and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the tropical flanks of the subtropical jets and, to some extent, in the the outflow regions of the large-scale convection, offers an explanation for the upward transport of trace species from the main convective outflow at around 350 K up to the tropical tropopause around 380 K

Contribution of mixing to the upward transport across the TTL

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board of the high altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the TTL region roughly extending between 350 and 420 K. Analysis of transport across TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by ECMWF winds and heating/cooling rates derived from a radiation calculation. Below the tropopause the model smoothly transforms from the isentropic to hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the ECMWF vertical wind. As with other CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observation and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the outflow regions of the large-scale convection and in the vicinity of the subtropical jets, is necessary to understand the upward transport of the tropospheric air from the main convective outflow around 350 K up to the tropical tropopause around 380 K. This mechanism is most effective if the outflow of the mesoscale convective systems interacts with the subtropical jets

Contribution of mixing to the upward transport across the TTL

During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board of the high altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the TTL region roughly extending between 350 and 420 K. Analysis of transport across TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by ECMWF winds and heating/cooling rates derived from a radiation calculation. Below the tropopause the model smoothly transforms from the isentropic to hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the ECMWF vertical wind. As with other CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observation and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the outflow regions of the large-scale convection and in the vicinity of the subtropical jets, is necessary to understand the upward transport of the tropospheric air from the main convective outflow around 350 K up to the tropical tropopause around 380 K. This mechanism is most effective if the outflow of the mesoscale convective systems interacts with the subtropical jets

Temporal associations between salivary cortisol and emotions in clinically depressed individuals and matched controls:A dynamic time warp analysis

Depression can be understood as a complex dynamic system where depressive symptoms interact with one another. Cortisol is suggested to play a major role in the pathophysiology of depression, but knowledge on the temporal interplay between cortisol and depressive symptoms is scarce. We aimed to analyze the temporal connectivity between salivary cortisol and momentary affective states in depressed individuals and controls. Thirty pair-matched depressed and non-depressed participants completed questionnaires on momentary positive (PA) and negative (NA) affect and collected saliva three times a day for 30 days. The association between cortisol and affect was analyzed by dynamic time warp (DTW) analyses. These analyses involved lag-1 backward to lag-1 forward undirected analyses and lag-0 and lag-1 forward directed analyses. Large inter- and intra-individual variability in the networks were found. At the group level, with undirected analysis PA and NA were connected in the networks in depressed individuals and in controls. Directed analyses indicated that increases in cortisol preceded specific NA items in controls, but tended to follow upon specific affect items increase in depressed individuals. To conclude, at group level, changes in cortisol levels in individuals diagnosed with a depression may be a result of changes in affect, rather than a cause.</p

A qualitative approach to guide choices for designing a diary study

Background: Electronic diaries are increasingly used in diverse disciplines to collect momentary data on experienced feelings, cognitions, behavior and social context in real life situations. Choices to be made for an effective and feasible design are however a challenge. Careful and detailed documentation of argumentation of choosing a particular design, as well as general guidelines on how to design such studies are largely lacking in scientific papers. This qualitative study provides a systematic overview of arguments for choosing a specific diary study design (e.g. time frame) in order to optimize future design decisions. Methods: During the first data assessment round, 47 researchers experienced in diary research from twelve different countries participated. They gave a description of and arguments for choosing their diary design (i.e., study duration, measurement frequency, random or fixed assessment, momentary or retrospective assessment, allowed delay to respond to the beep). During the second round, 38 participants (81%) rated the importance of the different themes identified during the first assessment round for the different diary design topics. Results: The rationales for diary design choices reported during the first round were mostly strongly related to the research question. The rationales were categorized into four overarching themes: nature of the variables, reliability, feasibility, and statistics. During the second round, all overarching themes were considered important for all diary design topics. Conclusions: We conclude that no golden standard for the optimal design of a diary study exists since the design depends heavily upon the research question of the study. The findings of the current study are helpful to explicate and guide the specific choices that have to be made when designing a diary study

ACTman:Automated preprocessing and analysis of actigraphy data

Objectives: To introduce a novel software-library called Actigraphy Manager (ACTman) which automates labor-intensive actigraphy data preprocessing and analyses steps while improving transparency, reproducibility, and scalability over software suites traditionally used in actigraphy research practice. Design: Descriptive. Methods: Use cases are described for performing a common actigraphy task in ACTman and alternative actigraphy software. Important inefficiencies in actigraphy workflow are identified and their consequences are described. We explain how these hinder the feasibility of conducting studies with large groups of athletes and/or longer data collection periods. Thereafter, the information flow through the ACTman software is described and we explain how it alleviates aforementioned inefficiencies. Furthermore, transparency, reproducibility, and scalability issues of commonly used actigraphy software packages are discussed and compared with the ACTman package. Results: It is shown that from an end-user perspective ACTman offers a compact workflow as it automates many preprocessing and analysis steps that otherwise have to be performed manually. When considering transparency, reproducibility, and scalability the design of the ACTman software is found to outperform proprietary and open-source actigraphy software suites. As such, ACTman alleviates important bottlenecks within actigraphy research practice. Conclusions: ACTman facilitates the current transition towards larger datasets containing data of multiple athletes by automating labor-intensive preprocessing and analyses steps within actigraphy research. Furthermore, ACTman offers many features which enhance user-convenience and analysis customization, such as moving window functionality and period selection options. ACTman is open-source and thus fully verifiable, in contrast with many proprietary software packages which remain a black box for researchers