Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

(Table 1) Active-layer thickness as measured by the Biocomplexity Experiment (BE) for the flooded, drained and control sections in Barrow, Alaska

A continuous time series of annual soil thaw records, extending from 1994 to 2009, is available for comparison with the records of thaw obtained from the Biocomplexity Experiment (BE) for the period 2006-2009. Discontinuous records of thaw at Barrow from wet tundra sites date back to the 1960s. Comparisons between the longer records with the BE observations reveal strong similarities. Records of permafrost temperature, reflecting changes in the annual surface energy exchange, are available from the 1950s for comparison with results from measurement programs begun in 2002. The long-term systematic geocryological investigations at Barrow indicate an increase in permafrost temperature, especially during the last several years. The increase in near-surface permafrost temperature is most pronounced in winter. Marked trends are not apparent in the active-layer record, although subsidence measurements on the North Slope indicate that penetration into the ice-rich layer at the top of permafrost has occurred over the past decade. Active-layer thickness values from the 1960s are generally higher than those from the 1990s, and are very similar to those of the 2000s. Analysis of spatial active-layer observations at representative locations demonstrates significant variations in active-layer thickness between different landscape types, reflecting the influence of vegetation, substrate, microtopography, and, especially, soil moisture. Landscape-specific differences exist in the response of active-layer thickness to climatic forcing. These differences are attributable to the existence of localized controls related to combinations of surface and subsurface characteristics. The geocryological records at Barrow illustrate the importance and effectiveness of sustained, well organized monitoring efforts to document long-term trends.

Field data on methane fluxes, temperature, soil gas profiles and microbial activities in ponds of the northeast Siberian polygonal tundra

The data files give the basic field and laboratory data on five ponds in the northeast Siberian Arctic tundra on Samoylov. The files contain water and soil temperature data of the ponds, methane fluxes, measured with closed chambers in the centres without vascular plants and the margins with vascular plants, the contribution of plant mediated fluxes on total methane fluxes, the gas concentrations (methane and dissolved inorganic carbon, oxygen) in the soil and the water column of the ponds, microbial activities (methane production, methane oxidation, aerobic and anaerobic carbon dioxide production), total carbon pools in the different horizons of the bottom soils, soil bulk density, soil substance density, and soil porosity.

Flux data of NU2_trap (Table A1)

Flux of bulk components, carbonate- and silicate-bearing skeleton organisms, and the d15N-isotopic signal were investigated on a 1-year time-series sediment trap deployed at the pelagic NU mooring site (Namibia Upwelling, ca. 29°S, 13°E) in the central Benguela System. The flux of bulk components mostly shows bimodal seasonality with major peaks in austral summer and winter, and moderate to low export in austral fall and spring. The calcium carbonate fraction dominates the export of particulates throughout the year, followed by lithogenic and biogenic opal. Planktonic foraminifera and coccolithophorids are major components of the carbonate fraction, while diatoms clearly dominate the biogenic opal fraction. Bulk d15N isotopic composition of particulate matter is positively correlated with the total mass flux during summer and fall, while negatively correlated during winter and spring. Seasonal changes in the intensity of the main oceanographic processes affecting the NU site are inferred from variations in bulk component flux, and in the flux and diversity patterns of individual species or group of species. Influence from the Namaqua (Hondeklip) upwelling cell through offshore migration of chlorophyll filaments is stronger in summer, while the winter flux maximum seems to reflect mainly in situ production, with less influence from the coastal and shelf upwelling areas. On a yearly basis, dominant microorganisms correspond well with the flora and fauna of tropical/subtropical waters, with minor contribution of near-shore organisms. The simultaneous occurrence of species with different ecological affinities mirrors the fact that the mooring site was located in a transitional region with large hydrographic variability over short-time intervals.

Particle fluxes of the bathypelagic sediment trap CVOO-3 in the eastern tropical North Atlantic for the period December 2009 until May 2011

Particle fluxes at the Cape Verde Ocean Observatory (CVOO) in the eastern tropical North Atlantic for the period December 2009 until May 2011 are discussed based on bathypelagic sediment trap time-series data collected at 1290 and 3439 m water depth. The typically oligotrophic particle flux pattern with weak seasonality is modified by the appearance of a highly productive and low oxygen (minimum concentration below 2 µmol kg**-1 at 40 m depth) anticyclonic modewater eddy (ACME) in winter 2010. The eddy passage was accompanied by unusually high mass fluxes of up to 151 mg m**-2 d**-1, lasting from December 2009 to May 2010. Distinct biogenic silica (BSi) and organic carbon flux peaks of ~15 and 13.3 mg m**-2 d**-1, respectively, were observed in February-March 2010 when the eddy approached the CVOO. The flux of the lithogenic component, mostly mineral dust, was well correlated with that of organic carbon, in particular in the deep trap samples, suggesting a tight coupling. The lithogenic ballasting obviously resulted in high particle settling rates and, thus, a fast transfer of epi-/meso-pelagic signatures to the bathypelagic traps. We suspect that the two- to three-fold increase in particle fluxes with depth as well as the tight coupling of mineral dust and organic carbon in the deep trap samples might be explained by particle focusing processes within the deeper part of the eddy. Molar C : N ratios of organic matter during the ACME passage were around 18 and 25 for the upper and lower trap samples, respectively. This suggests that some productivity under nutrient (nitrate) limitation occurred in the euphotic zone of the eddy in the beginning of 2010 or that a local nitrogen recycling took place. The d15N record showed a decrease from 5.21 to 3.11 per mil from January to March 2010, while the organic carbon and nitrogen fluxes increased. The causes of enhanced sedimentation from the eddy in February/March 2010 remain elusive, but nutrient depletion and/or an increased availability of dust as a ballast mineral for organic-rich aggregates might have contributed. Rapid remineralisation of sinking organic-rich particles could have contributed to oxygen depletion at shallow depth. Although the eddy formed in the West African coastal area in summer 2009, no indications of coastal flux signatures (e.g. from diatoms) were found in the sediment trap samples, confirming the assumption that the suboxia developed within the eddy en route. However, we could not detect biomarkers indicative of the presence of anammox (anaerobic ammonia oxidation) bacteria or green sulfur bacteria thriving in photic zone suboxia/hypoxia, i.e. ladderane fatty acids and isorenieratene derivatives, respectively. This could indicate that suboxic conditions in the eddy had recently developed and/or the respective bacterial stocks had not yet reached detection thresholds. Another explanation is that the fast-sinking organic-rich particles produced in the surface layer did not interact with bacteria from the suboxic zone below. Carbonate fluxes dropped from -52 to 21.4 mg m**-2 d**-1 from January to February 2010, respectively, mainly due to reduced contribution of shallow-dwelling planktonic foraminifera and pteropods. The deep-dwelling foraminifera Globorotalia menardii, however, showed a major flux peak in February 2010, most probably due to the suboxia/hypoxia. The low oxygen conditions forced at least some zooplankton to reduce diel vertical migration. Reduced "flux feeding" by zooplankton in the epipelagic could have contributed to the enhanced fluxes of organic materials to the bathypelagic traps during the eddy passage. Further studies are required on eddy-induced particle production and preservation processes and particle focusing.

Biogeochemical properties of sinking particles intercepted at three depths on the NW Atlantic margin

Three conical sediment were deployed at three depths 968 m (top trap), 1976 m (middletrap), and 2938 m (50mabove the bottom, bottom trap) - from June 27, 2004 to April 27, 2005 on the NW Atlantic margin at a water depth of 2988 m. The sediment trap carousels were programmed to open each collection cup for 23.4 days for the top trap and 14.5 days for the other two traps, resulting in total 13 samples from the top trap and 21 samples each from the middle and bottom traps. The samples were analyzed for the biogeochemical properties with various methods. Frequent occurrences of higher fluxes in deep relative to shallower sediment traps and low delta 14C values of sinking POC together provide strong evidence for significant lateral transport of aged organic matter over the margin. Comparison of biogeochemical properties such as aluminum concentration and flux, and iron concentration between samples intercepted at different depths shows that particles collected by the deepest trap had more complex sources than the shallower ones. These data also suggest that at least two modes of lateral transport exist over the New England margin. Based on radio carbon mass balance, about 30% (± 10%) of sinking POC in all sediment traps is estimated to be derived from lateral transport of re-suspended sediment. A strong correlation between delta 14C values and aluminum concentrations suggests that the aged organic matter is associated with lithogenic particles.

Distributed Extremum-Seeking Control with Applications to High-Altitude Balloons

The real-time optimization of large-scale systems is a difficult problem due to the need for complex models involving uncertain parameters and the high computational cost of solving such problems by a decentralized approach. Extremum-seeking control (ESC) is a model-free real-time optimization technique which can estimate unknown parameters and can optimize nonlinear time-varying systems using only a measurement of the cost function to be minimized. In this thesis, we develop a distributed version of extremum-seeking control which allows large-scale systems to be optimized without models and with minimal computing power. First, we develop a continuous-time distributed extremum-seeking controller. It has three main components: consensus, parameter estimation, and optimization. The consensus provides each local controller with an estimate of the cost to be minimized, allowing them to coordinate their actions. Using this cost estimate, parameters for a local input-output model are estimated, and the cost is minimized by following a gradient descent based on the estimate of the gradient. Next, a similar distributed extremum-seeking controller is developed in discrete-time. Finally, we consider an interesting application of distributed ESC: formation control of high-altitude balloons for high-speed wireless internet. These balloons must be steered into a favourable formation where they are spread out over the Earth and provide coverage to the entire planet. Distributed ESC is applied to this problem, and is shown to be effective for a system of 1200 ballons subjected to realistic wind currents. The approach does not require a wind model and uses a cost function based on a Voronoi partition of the sphere. Distributed ESC is able to steer balloons from a few initial launch sites into a formation which provides coverage to the entire Earth and can maintain a similar formation as the balloons move with the wind around the Earth.

Two-Path All-pass Based Half-Band Infinite Impulse Response Decimation Filters and the Effects of Their Non-Linear Phase Response on ECG Signal Acquisition

This paper is based on the novel use of a very high fidelity decimation filter chain for Electrocardiogram (ECG) signal acquisition and data conversion. The multiplier-free and multi-stage structure of the proposed filters lower the power dissipation while minimizing the circuit area which are crucial design constraints to the wireless noninvasive wearable health monitoring products due to the scarce operational resources in their electronic implementation. The decimation ratio of the presented filter is 128, working in tandem with a 1-bit 3rd order Sigma Delta (ΣΔ) modulator which achieves 0.04 dB passband ripples and -74 dB stopband attenuation. The work reported here investigates the non-linear phase effects of the proposed decimation filters on the ECG signal by carrying out a comparative study after phase correction. It concludes that the enhanced phase linearity is not crucial for ECG acquisition and data conversion applications since the signal distortion of the acquired signal, due to phase non-linearity, is insignificant for both original and phase compensated filters. To the best of the authors’ knowledge, being free of signal distortion is essential as this might lead to misdiagnosis as stated in the state of the art. This article demonstrates that with their minimal power consumption and minimal signal distortion features, the proposed decimation filters can effectively be employed in biosignal data processing units.

Evolutionary dynamics under various modes of reproduction

Thesis (Ph.D.)--University of Washington, 2016-08

Likelihood-Based Inference for Partially Observed Multi-Type Markov Branching Processes

Thesis (Ph.D.)--University of Washington, 2016-08

A path-based framework for analyzing large markov models

Reliability and dependability modeling can be employed during many stages of analysis of a computing system to gain insights into its critical behaviors. To provide useful results, realistic models of systems are often necessarily large and complex. Numerical analysis of these models presents a formidable challenge because the sizes of their state-space descriptions grow exponentially in proportion to the sizes of the models. On the other hand, simulation of the models requires analysis of many trajectories in order to compute statistically correct solutions. This dissertation presents a novel framework for performing both numerical analysis and simulation. The new numerical approach computes bounds on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. This relationship makes it possible for the approach to explore multiple paths at the same time,· thus significantly increasing the number of paths that can be explored in a given amount of time. Furthermore, the use of a structured representation for the state space and the direct computation of the desired reward measure (without ever storing the solution vector) allow it to analyze very large models using a very small amount of storage. Often, path-based techniques must compute many paths to obtain tight bounds. In addition to presenting the basic path-based approach, we also present algorithms for computing more paths and tighter bounds quickly. One resulting approach is based on the concept of path composition whereby precomputed subpaths are composed to compute the whole paths efficiently. Another approach is based on selecting important paths (among a set of many paths) for evaluation. Many path-based techniques suffer from having to evaluate many (unimportant) paths. Evaluating the important ones helps to compute tight bounds efficiently and quickly.

Queueuing system with failures and priorities

Queueing theory provides models, structural insights, problem solutions and algorithms to many application areas. Due to its practical applicability to production, manufacturing, home automation, communications technology, etc, more and more complex systems requires more elaborated models, tech- niques, algorithm, etc. need to be developed. Discrete-time models are very suitable in many situations and a feature that makes the analysis of discrete time systems technically more involved than its continuous time counterparts. In this paper we consider a discrete-time queueing system were failures in the server can occur as-well as priority messages. The possibility of failures of the server with general life time distribution is considered. We carry out an extensive study of the system by computing generating functions for the steady-state distribution of the number of messages in the queue and in the system. We also obtain generating functions for the stationary distribution of the busy period and sojourn times of a message in the server and in the system. Performance measures of the system are also provided.