What checkers actually check:an eye tracking study of inhibitory control and working memory

Background - Not only is compulsive checking the most common symptom in Obsessive Compulsive Disorder (OCD) with an estimated prevalence of 50–80% in patients, but approximately ~15% of the general population reveal subclinical checking tendencies that impact negatively on their performance in daily activities. Therefore, it is critical to understand how checking affects attention and memory in clinical as well as subclinical checkers. Eye fixations are commonly used as indicators for the distribution of attention but research in OCD has revealed mixed results at best. Methodology/Principal Finding - Here we report atypical eye movement patterns in subclinical checkers during an ecologically valid working memory (WM) manipulation. Our key manipulation was to present an intermediate probe during the delay period of the memory task, explicitly asking for the location of a letter, which, however, had not been part of the encoding set (i.e., misleading participants). Using eye movement measures we now provide evidence that high checkers’ inhibitory impairments for misleading information results in them checking the contents of WM in an atypical manner. Checkers fixate more often and for longer when misleading information is presented than non-checkers. Specifically, checkers spend more time checking stimulus locations as well as locations that had actually been empty during encoding. Conclusions/Significance - We conclude that these atypical eye movement patterns directly reflect internal checking of memory contents and we discuss the implications of our findings for the interpretation of behavioural and neuropsychological data. In addition our results highlight the importance of ecologically valid methodology for revealing the impact of detrimental attention and memory checking on eye movement patterns.

Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans

Because of attentional limitations, the human visual system can process for awareness and response only a fraction of the input received. Lesion and functional imaging studies have identified frontal, temporal, and parietal areas as playing a major role in the attentional control of visual processing, but very little is known about how these areas interact to form a dynamic attentional network. We hypothesized that the network communicates by means of neural phase synchronization, and we used magnetoencephalography to study transient long-range interarea phase coupling in a well studied attentionally taxing dual-target task (attentional blink). Our results reveal that communication within the fronto-parieto-temporal attentional network proceeds via transient long-range phase synchronization in the beta band. Changes in synchronization reflect changes in the attentional demands of the task and are directly related to behavioral performance. Thus, we show how attentional limitations arise from the way in which the subsystems of the attentional network interact. The human brain faces an inestimable task of reducing a potentially overloading amount of input into a manageable flow of information that reflects both the current needs of the organism and the external demands placed on it. This task is accomplished via a ubiquitous construct known as “attention,” whose mechanism, although well characterized behaviorally, is far from understood at the neurophysiological level. Whereas attempts to identify particular neural structures involved in the operation of attention have met with considerable success (1-5) and have resulted in the identification of frontal, parietal, and temporal regions, far less is known about the interaction among these structures in a way that can account for the task-dependent successes and failures of attention. The goal of the present research was, thus, to unravel the means by which the subsystems making up the human attentional network communicate and to relate the temporal dynamics of their communication to observed attentional limitations in humans. A prime candidate for communication among distributed systems in the human brain is neural synchronization (for review, see ref. 6). Indeed, a number of studies provide converging evidence that long-range interarea communication is related to synchronized oscillatory activity (refs. 7-14; for review, see ref. 15). To determine whether neural synchronization plays a role in attentional control, we placed humans in an attentionally demanding task and used magnetoencephalography (MEG) to track interarea communication by means of neural synchronization. In particular, we presented 10 healthy subjects with two visual target letters embedded in streams of 13 distractor letters, appearing at a rate of seven per second. The targets were separated in time by a single distractor. This condition leads to the “attentional blink” (AB), a well studied dual-task phenomenon showing the reduced ability to report the second of two targets when an interval <500 ms separates them (16-18). Importantly, the AB does not prevent perceptual processing of missed target stimuli but only their conscious report (19), demonstrating the attentional nature of this effect and making it a good candidate for the purpose of our investigation. Although numerous studies have investigated factors, e.g., stimulus and timing parameters, that manipulate the magnitude of a particular AB outcome, few have sought to characterize the neural state under which “standard” AB parameters produce an inability to report the second target on some trials but not others. We hypothesized that the different attentional states leading to different behavioral outcomes (second target reported correctly or not) are characterized by specific patterns of transient long-range synchronization between brain areas involved in target processing. Showing the hypothesized correspondence between states of neural synchronization and human behavior in an attentional task entails two demonstrations. First, it needs to be demonstrated that cortical areas that are suspected to be involved in visual-attention tasks, and the AB in particular, interact by means of neural synchronization. This demonstration is particularly important because previous brain-imaging studies (e.g., ref. 5) only showed that the respective areas are active within a rather large time window in the same task and not that they are concurrently active and actually create an interactive network. Second, it needs to be demonstrated that the pattern of neural synchronization is sensitive to the behavioral outcome; specifically, the ability to correctly identify the second of two rapidly succeeding visual targets

The application of counter immunoelectrophoresis (CIE) in ocular protein studies. Part I:time dependent deposition patterns of immunoregulatory proteins on anionic hydrogel contact lenses

This paper focuses on the effects of wear regime on the deposition pattern of important immunoregulatory proteins on FDA Group IV etafilcon-A lenses. Specifically, the aim was to assess the extent to which the daily disposable wear modality produces a different deposition of proteins from the conventional daily wear regime which is coupled with cleaning and disinfection. Counter immunoelectrophoresis (CIE) was employed to detect individual proteins in lens extracts from individual patients and focused on the analysis of five proteins, IgA, IgG, lactoferrin, albumin and kininogen. Deposition was monitored as a function of time; significantly lower deposition was detected on the daily disposable lenses. cr 2002 British Contact Lens Association. Published by Elsevier Science Ltd. All rights reserved.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

A probabilistic indirect adaptive control for systems with input-dependent noise

A probabilistic indirect adaptive controller is proposed for the general nonlinear multivariate class of discrete time system. The proposed probabilistic framework incorporates input–dependent noise prediction parameters in the derivation of the optimal control law. Moreover, because noise can be nonstationary in practice, the proposed adaptive control algorithm provides an elegant method for estimating and tracking the noise. For illustration purposes, the developed method is applied to the affine class of nonlinear multivariate discrete time systems and the desired result is obtained: the optimal control law is determined by solving a cubic equation and the distribution of the tracking error is shown to be Gaussian with zero mean. The efficiency of the proposed scheme is demonstrated numerically through the simulation of an affine nonlinear system.

A comparative study of life history and gene flow in darters (Pisces: Percidae)

Gene flow, or the exchange of genes between populations, is important because it determines the evolutionary trajectory of a species, including the relative influences of genetic drift and natural selection in the process of population differentiation. Gene flow differs among species because of variation in dispersal capability and abundances across taxa, and historical forces related to geological or lineage history. Both history and ecology influence gene flow in potentially complicated ways, and accounting for their effects remains an important problem in evolutionary biology. This research is a comparative study of gene flow and life-history in a monophyletic group of stream fishes, the darters. As a first step in disentangling historical and ecological effects, I reconstructed the phylogenetic relationships of the study species from nucleotide sequences in the mtDNA control region. I then used this phylogeny and regional glaciation history to infer historical effects on life-history evolution and gene flow in 15 species of darters. Gene flow was estimated indirectly, using information from 20 resolvable and polymorphic allozyme loci. When I accounted for historical effects, comparisons across taxa revealed that gene flow rates were closely associated with differences in clutch sizes and reproductive investment patterns. I hypothesized that differences in larval dispersal among taxa explained this relationship. Results from a field study of larval drift were consistent with this hypothesis. Finally, I asked whether there was an interaction between species' ecology and genetic differentiation across biogeographically distinct regions. Information from allozymes and mtDNA sequences revealed that life history plays an important role in the magnitude of species divergence across biogeographic boundaries. These results suggested an important association between life histories and rates of speciation following an allopatric isolation event. This research, along with other studies from the literature, further illustrates the enormous potential of North American freshwater fishes as a system for studying speciation processes. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Automated detection of hematological abnormalities through classification of flow cytometric data patterns

Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

A conceptual model of ecological interactions in the mangrove estuaries of the Florida Everglades

A brackish water ecotone of coastal bays and lakes, mangrove forests, salt marshes, tidal creeks, and upland hammocks separates Florida Bay, Biscayne Bay, and the Gulf of Mexico from the freshwater Everglades. The Everglades mangrove estuaries are characterized by salinity gradients that vary spatially with topography and vary seasonally and inter-annually with rainfall, tide, and freshwater flow from the Everglades. Because of their location at the lower end of the Everglades drainage basin, Everglades mangrove estuaries have been affected by upstream water management practices that have altered the freshwater heads and flows and that affect salinity gradients. Additionally, interannual variation in precipitation patterns, particularly those caused to El Nin˜o events, control freshwater inputs and salinity dynamics in these estuaries. Two major external drivers on this system are water management activities and global climate change. These drivers lead to two major ecosystem stressors: reduced freshwater flow volume and duration, and sea-level rise. Major ecological attributes include mangrove forest production, soil accretion, and resilience; coastal lake submerged aquatic vegetation; resident mangrove fish populations; wood stork (Mycteria americana) and roseate spoonbill (Platelea ajaja) nesting colonies; and estuarine crocodilian populations. Causal linkages between stressors and attributes include coastal transgression, hydroperiods, salinity gradients, and the ‘‘white zone’’ freshwater/estuarine interface. The functional estuary and its ecological attributes, as influenced by sea level and freshwater flow, must be viewed as spatially dynamic, with a possible near-term balancing of transgression but ultimately a long-term continuation of inland movement. Regardless of the spatio-temporal timing of this transgression, a salinity gradient supportive of ecologically functional Everglades mangrove estuaries will be required to maintain the integrity of the South Florida ecosystem.

Vegetation:environment relationships and water management in Shark Slough, Everglades National Park

The hydrologic regime of Shark Slough, the most extensive long hydroperiod marsh in Everglades National Park, is largely controlled by the location, volume, and timing of water delivered to it through several control structures from Water Conservation Areas north of the Park. Where natural or anthropogenic barriers to water flow are present, water management practices in this highly regulated system may result in an uneven distribution of water in the marsh, which may impact regional vegetation patterns. In this paper, we use data from 569 sampling locations along five cross-Slough transects to examine regional vegetation distribution, and to test and describe the association of marsh vegetation with several hydrologic and edaphic parameters. Analysis of vegetation:environment relationships yielded estimates of both mean and variance in soil depth, as well as annual hydroperiod, mean water depth, and 30-day maximum water depth within each cover type during the 1990’s. We found that rank abundances of the three major marsh cover types (Tall Sawgrass, Sparse Sawgrass, and Spikerush Marsh) were identical in all portions of Shark Slough, but regional trends in the relative abundance of individual communities were present. Analysis also indicated clear and consistent differences in the hydrologic regime of three marsh cover types, with hydroperiod and water depths increasing in the order Tall Sawgrass , Sparse Sawgrass , Spikerush Marsh. In contrast, soil depth decreased in the same order. Locally, these differences were quite subtle; within a management unit of Shark Slough, mean annual values for the two water depth parameters varied less than 15 cm among types, and hydroperiods varied by 65 days or less. More significantly, regional variation in hydrology equaled or exceeded the variation attributable to cover type within a small area. For instance, estimated hydroperiods for Tall Sawgrass in Northern Shark Slough were longer than for Spikerush Marsh in any of the other regions. Although some of this regional variation may reflect a natural gradient within the Slough, a large proportion is the result of compartmentalization due to current water management practices within the marsh.We conclude that hydroperiod or water depth are the most important influences on vegetation within management units, and attribute larger scale differences in vegetation pattern to the interactions among soil development, hydrology and fire regime in this pivotal portion of Everglades.

Correspondence of historic salinity fluctuations in Florida Bay, USA, to atmospheric variability and anthropogenic changes

Florida Bay is a highly dynamic estuary that exhibits wide natural fluctuations in salinity due to changes in the balance of precipitation, evaporation and freshwater runoff from the mainland. Rapid and large-scale modification of freshwater flow and construction of transportation conduits throughout the Florida Keys during the late nineteenth and twentieth centuries reshaped water circulation and salinity patterns across the ecosystem. In order to determine long-term patterns in salinity variation across the Florida Bay estuary, we used a diatom-based salinity transfer function to infer salinity within 3.27 ppt root mean square error of prediction from diatom assemblages from four ~130 year old sediment records. Sites were distributed along a gradient of exposure to anthropogenic shifts in the watershed and salinity. Precipitation was found to be the primary driver influencing salinity fluctuations over the entire record, but watershed modifications on the mainland and in the Florida Keys during the late-1800s and 1900s were the most likely cause of significant shifts in baseline salinity. The timing of these shifts in the salinity baseline varies across the Bay: that of the northeastern coring location coincides with the construction of the Florida Overseas Railway (AD 1906–1916), while that of the east-central coring location coincides with the drainage of Lake Okeechobee (AD 1881–1894). Subsequent decreases occurring after the 1960s (east-central region) and early 1980s (southwestern region) correspond to increases in freshwater delivered through water control structures in the 1950s–1970s and again in the 1980s. Concomitant increases in salinity in the northeastern and south-central regions of the Bay in the mid-1960s correspond to an extensive drought period and the occurrence of three major hurricanes, while the drop in the early 1970s could not be related to any natural event. This paper provides information about major factors influencing salinity conditions in Florida Bay in the past and quantitative estimates of the pre- and post-South Florida watershed modification salinity levels in different regions of the Bay. This information should be useful for environmental managers in setting restoration goals for the marine ecosystems in South Florida, especially for Florida Bay.

Two-bit pattern analysis for quantitative information flow

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^

An investigation of the relationships among self-care behaviors, health beliefs, and metabolic control in the non-insulin-dependent diabetic adult

Self-care and health beliefs have been found to be important concepts in the management of chronic diseases such as diabetes mellitus. Poor metabolic control has been associated with a higher incidence of complications in diabetic patients. This study sought to explore any relationships among perceptions of self-care behaviors, health beliefs and metabolic control. The sample consisted of 52 outpatients with non-insulin-dependent diabetes from a large teaching medical center. Interviews were done to obtain the patients' perceptions of their self-care behaviors, and their health beliefs concerning diabetes. Results of glycosylated hemoglobin and/or serum glucose levels were obtained from the medical records. Data were analyzed using Cochran-Mantel-Haenzel statistics, and Pearson's r. Results indicated no significant relationships among perceptions of self-care behaviors, health beliefs and metabolic control. Ethnicity, education and gender were found to be significantly associated with self-care behaviors and health beliefs.

Resolving patterns of population genetic and phylogeographic structure to inform control and eradication initiatives for brown rats Rattus norvegicus on South Georgia

Funded by UK Government's Overseas Territories Environmental Programme (OTEP)

A Force-Balanced Control Volume Finite Element Method for Multi-Phase Porous Media Flow Modelling

Peer reviewed