John Henderson, PhD - US grants

The longterm objectives of this proposal are: 1) to define the regulating mechanisms of hepatic and systemic hemodynamics in liver disease, and determine in which patients pharmacologic manipulation is beneficial to hepatic function: and 2) to initiate study of the hemodynamics of the denervated, transplanted liver. The first objective will be achieved in two phases. Firs, a prospective randomized trial will be conducted in patients with alcoholic cirrhosis after distal splenorenal shunt. This will test the hypothesis that reduction of the systemic hyperdynamic response with propranolol will lower intrahepatic resistance sufficient to allow maintenance of portal flow and hepatic function, with improved survival. In parallel to this study, propranolol, verapamil, ketanserin and the nitrates, drugs which lower intrahepatic resistance, will be evaluated in stable patients with cirrhosis. This phase will test the hypothesis that reduction of intrahepatic resistance will improve portal perfusion and hepatic function. Methodologic studies focus on measurement of portal flow and peripheral vascular resistance. These will use Doppler/ultrasound, magnetic resonance imaging, and angiodynography. Differentiation of peripheral (limb) vascular resistance from total systemic vascular resistance will help elucidate mechanisms of pharmacologic manipulation. The transplanted liver is denervated, and hence the neural control of blood flow is lost. Liver blood flow and portal venous flow will be measured in transplant patients to test the hypothesis that blood flow is increased, and this is primarily through increased hepatic arterial flow. Studies will be conducted in a pig model of liver denervation to define the altered hepatic and systemic hemodynamics, and the response to hypovolemic shock. Cirrhosis has a high morbidity/mortality with variceal bleeding and liver failure. Improved regulation of the abnormal hemodynamics, which are the common denominator to this morbidity, should significantly enhance patient care. The increased application of liver transplant mandates the need for careful study of the pathophysiology of the hemodynamic alterations after transplant and their longterm impact on graft function. These two objectives have common ground in the regulating mechanisms o liver blood flow in health and disease.

9319272 Ferreira ABSTRACT The purpose of this project is to explore the architecture of the language processing system by examining how prosody is created and used. More specifically, the goals are to: (1) elaborate a model of prosodic production proposed recently by Ferreira (1993), which in turn will shed light on more global models of production; (2) use this model to develop and test hypothesis about how prosodic information might be used and integrated with syntactic and semantic information during auditory language comprehension; and (3) develop an online task for examining auditory language comprehension, an auditory analogue of the moving window task. In addition, by combining research in production and comprehension, this project will shed light on the important question of how the language production and comprehension systems are related. The proposed studies are divided into two sections, one on production and one on comprehension. The production experiments employ a paradigm in which participants view a picture or answer a question and generate a sentence in response to the stimulus. These studies designed to explore the prosody of spoken sentences employ a paradigm in which speakers read a sentence, memorize it, and produce it upon receipt of a cue. These experiments will examine the syntactic and phonological factors influencing the durational and pitch properties of spoken sentences. The comprehension experiments will use a technique Ferreira has recently developed called the Auditory Moving Window, which measures processing load across a sentence. (To allow comparison of sentence processing in the auditory and visual domains, the comprehension studies will also be conducted using eye movement monitoring and the visual moving window paradigms.) The listeners will hear sentences containing prosodic cues normally produced by speakers for those sentences, either with or without biasing lexical and contextual information. The goal of these studies is to examine how t hese sources of information interact during auditory language processing.

Vision is a dynamic process involving continuous changes to the proximal stimulus. Objects move, disappear behind occluding surfaces and then reappear, and are displaced across the retina due to eye, head, and body movements. The purpose of the proposed research is to investigate the nature of the maintenance and combination of information over time and space during dynamic visual object identification. The main focus is to test the hypothesis that the maintenance and combination of object information is a product of two processes, the construction and reviewing of temporary episodic representations (object tokens), and the activation of prestored long-term representations (object types). A secondary focus is to determine whether the maintenance and combination of object information over time and space operates similarly across saccadic eye movements and within a single eye fixation. In order to investigate these issues, three paradigms will be employed. The transsaccadic preview paradigm will provide data concerning the maintenance and combination of object information across saccades. The simulated-saccade preview paradigm will provide data concerning the degree to which the results from the transsaccadic paradigm are contingent on the execution of an eye movement. The within-fixation preview paradigm will provide data concerning the issue of information maintenance and combination in central vision during a single eye fixation. Together, the proposed studies will provide data with which to constrain models of dynamic visual object identification.

The proposed project will investigate the role of enterprise expertise in how organizations develop and leverage one particular organizational capability, namely: fast-cycle response. The investigation will be undertaken in collaboration with six organizational partners--IBM, ITT Hartford, Ameritech, Swiss Bank Corporation, U.S. Army, and New England Medical--and will consist of both intensive case studies and extensive survey research. The research is distinguished by four attributes. One: A conceptualization of enterprise expertise as a multi-level construct as opposed to a single level of analysis--individual, group, organization, or network. Two: An examination of the specific role of information technology in supporting enterprise expertise as well as organizational capability, thus contributing to the emerging body of research on the impact of information technology on organization strategy and design. Three: A focus on how enterprise expertise can affect a previously under-emphasized aspect of quality, namely fast-cycle response capability, which is particularly critical given the seeming tension between quality and speed of organizational response. Four: Using organizational processes as the sampling unit for survey research, thus developing specific methodological suggestions on how to use process as the focus of analysis in organizational research.

9873531
Henderson
Mobile organisms make accurate behavioral decisions with extraordinary speed and flexibility in real-world environments despite incomplete knowledge about the state of the world and the effects of their actions. This ability must be shared by artificial agents such as mobile robots if they are to operate flexibly in similar environments. The main goal of the research is to undertake a detailed interdisciplinary study of sequential decision making across animals and robots, with a focus on real time learning and control of information gathering and navigational behaviors.

The project will take a comparative approach, combining psychophysical and cognitive research techniques from the study of human eye movement control, behavioral research techniques from the study of insect navigation, and computational methods from the study of mobile robots. All of these systems provide experimentally tractable test-beds for studying real-time decision making in partially observable environments.

The research is guided by a class of sequential decision making models called Markov decision processes (MDP). These models are attractive because they provide a formal framework for computing optimal behavior in uncertain environments. However, these models do not fully capture the complexity of decision making in organisms. We will explore extensions of the MDP framework using insights gained from the study of behavior in organisms and algorithms in artificial agents. This synergy will lead both to a better theoretical understanding of sequential decision making in biological organisms, and to the development of efficient algorithms for artificial agents.

A major outcome of the project will be to show how the design of artificial creatures (robots) can be guided by, and serve as a guide for, the study of sequential behavior in animals. Understanding the challenges that robot designers face, and the formal framework that they have developed to tackle these challenges, leads to novel questions about organisms behavior. Similarly, insights gained from organisms will help suggest ways for improving algorithms for building intelligent artificial agents.
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This project will critically examine the potential for accreditation of programs in computer information science/systems/technology, including programs that cover essentially this material, but may have chosen to use a somewhat different title. This will include developing a set of criteria which could be used for accrediting such programs, the procedures for such accreditation, and surveying schools and employers to get their feedback as to both the value of such accreditation and any adjustments they would desire in the criteria and procedures that are developed.

Under the direction of Dr. John Henderson, MS Christina Luke will collect data for her doctoral dissertation. Her goal is to understand the processes which led to the rise and maintenance of complex prehistoric societies in Middle America and she shall focus on Late Classic period peoples in the Ulua Valley of Honduras and adjacent Belize. Although the Mayans and Aztec are the best known civilizations in this general region, this same level of complexity was achieved by multiple other groups. Ulua Valley societies were unique in their production of highly standardized elaborately carved marble vessels and artisans mastered techniques of crafting this relatively soft rock. Produced for only several hundred years at the height of the civilization, these vessels appear in exclusively elite contexts and MS Luke hypothesizes that they served to reinforce ties between rulers in adjacent areas. By understanding how and where they were produced, MS Luke believes it will be possible to reconstruct interactions between sites within this exchange network. Examination of degree of standardization will also shed light on the degree of centralized control over their production and the extent to which full time craft specialists were present. MS Luke will conduct a stylistic study of excavated specimens housed in many museums. She will also collect marble samples from multiple geological outcrops in the Ulua Valley and determine their trace element and isotopic signatures. These together with petrographic analysis will, hopefully, permit her to match finished product to geological source. Preliminary results indicate that within source chemical and petrographic variation is small enough and between source variation significantly large to allow success.

This research is important for several reasons. It will provide the first chemical characterization of Middle American marble and provide a data base of great potential value. It will shed new light on the development of civilization in Middle America and the role which the production and distribution of elite items played in its creation and maintenance. It will also assist in training a promising young scientist.

(9908680)

Ferreira
0083570

The grant provides funds to allow the investigators to obtain significant instrumentation for cognitive / behavioral research. The requested-funds wo6/ld be used to purchase a free-viewing, mobile eye movement monitoring system, along with a computer workstation and a monitor for displaying some stimuli (in other cases, stimuli will be real, three-dimensional objects and scenes). The mobile eyetracker allows the viewer to examine real-world scenes or visual displays of scenes while making normal, natural head and body movements. Indeed, the system allows researchers to obtain precise information about where a person is looking as he or she moves through or manipulates objects in a natural environment. The instrumentation would be used for a variety of studies in cognitive and behavioral sciences. These include: (1) Research to examine how comprehenders quickly obtain interpretations for spoken sentences. No other existing methodology allows researchers to measure moment-by-moment processing for aurally presented sentences. (2) Research to study how real-world scenes are represented, and how representations of objects and scenes are generated dynamically over time in the context of meaningful actions. (3) Investigations of how humans are able to navigate novel and familiar environments, focusing particularly on eye movement patterns (e.g., what objects are used as guideposts and landmarks). (4) Studies of human-computer interaction, including the representation of objects and navigation through "virtual reality" environments. The free-viewing eyetracker would complement the Principal Investigators' existing laboratory facilities and greatly enhance the ability to train undergraduate and graduate students in sophisticated methodologies for studying complex behavior in intelligent systems.

This IGERT project examines the problem of sequential decision-making as a unifying framework for the study of several central topics in cognitive science: selective attention, navigation, language processing, and the coordination of action in multiple-agent groups. The overarching question our students are trained to investigate is the following: how is it possible for an agent to decide what actions to take to achieve long-term goals? We recognize that decision-making in complex environments is a sequential process, involving a series of episodes in which an agent, based on information available through its senses and stored in memory, selects the action appropriate for its goals. The problem is made difficult by perceptual uncertainty arising from sensory limitations and environmental complexity, by the challenge of sorting through the large space of actions available, and by inherent delays in feedback about the long-term consequences of actions. A wide variety of fundamental cognitive tasks can be cast as sequential decision-making problems. Understanding how such problems may be solved will be a critical component of a general theory of intelligent behavior in organisms, and will be essential for the design of truly intelligent machines. To study these problems, we adopt a comparative approach, combining insights from a range of model systems, including humans, non-human animals, robots, and intelligent software agents. This multidisciplinary framework will enable students to integrate ideas and methods from different fields that have been concerned with the study of sequential decision-making (psychology, behavioral biology, linguistics, and computer science), but that have so far remained largely separate. The training program is designed to create a new generation of scientists trained in this innovative, multidisciplinary approach. Graduate training will be focused on fundamental disciplinary education, a common set of courses focused on the sequential decision-making framework, and a strong emphasis on mentored, interdisciplinary research activities that span each student's entire graduate program.

IGERT is an NSF-wide program intended to meet the challenges of educating Ph.D. scientists and engineers with the multidisciplinary backgrounds and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing new, innovative models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In the fourth year of the program, awards are being made to twenty-two institutions for programs that collectively span all areas of science and engineering supported by NSF. The intellectual foci of this specific award reside in the Directorates for Social, Behavioral, and Economic Sciences; Computer and Information Science and Engineering; Engineering; Biological Sciences; and Education and Human Resources.

We experience the visual world subjectively as a full-color panorama of visual detail. This experience naturally leads to the belief that the human visual system generates a complete and truthful internal copy of the outside scene, similar to a detailed color photograph. Consistent with this intuition, past research has demonstrated that human visual memory for scenes can be exceptionally good. At the same time, it is well known that visual detail and rich color are only available where the eyes are directly pointed. To compensate for this constraint, our eyes flit from place to place over a scene in a series of very fast eye movements called saccades. Interspersed among these saccades are brief pauses, called fixations, and it is only during these fixational pauses that visual information is actually acquired from the scene. Therefore, if our visual system does in fact create a complete internal representation of the external world, as experience suggests, then this representation must be stitched together from the individual snapshots taken during each fixation. In contrast to this intuitively appealing view, there is a good deal of recent evidence that the human visual system does not construct such a high-fidelity copy of the world. For example, a remarkable recent discovery is that human viewers are often very insensitive to dramatic changes in the visual world that take place from one moment to the next. This finding suggests that despite experience and intuition, a photographic image of the entire scene is not concurrently available for comparison to the current state of the world. What, then, is the nature of the internal representation that is generated and retained over time by the human visual system?

The main objective of this research is to understand the visual representations that arise as the human viewer examines the world dynamically over extended time. The research will be directed toward discovering the principles that underlie human visual perception, visual cognition, and visual memory. The research will use sophisticated methods that combine fast and powerful graphics manipulation and presentation systems with a highly accurate eyetracking system. Using these instruments, complex scenes will be changed in real time contingent on a specific eye movement within the scene, and the sensitivity of the visual system to such changes will be measured under a variety of conditions. The results of this work will expand our understanding of how the human brain gives rise to perceptual experience and visually guided performance and will help guide the design of new human-computer interfaces. The results will also help guide scientists in building the next generation of artificial vision systems.

This project investigates the choices that US legislative candidates make in their campaigns as strategic members of a collective party organization. The central question motivating the project is: When do congressional candidates run with or away from their party at election time?

In addressing this question, the project aims to fill three major gaps in extant political science research. First, due to the lack of historical advertising data, we know relatively little about the kinds of issues and statements candidates typically raise in their campaigns, especially for elections prior to 2000. Second, we have only a limited understanding of the role that parties play in these elections and of change over time in that role. Finally, the most widely held view of parties in congressional organization is based on the largely untested assumption that the electoral prospects of party candidates are strongly linked to the fates of the parties? reputations in Congress. According to this view, candidates have a restricted ability to develop campaign strategies to deal with good and bad partisan election swings. Yet no systematic analysis is available to appraise this fundamental assumption or to explore the messages actually issued by candidates.

This project will examine the strategic statements communicated directly by candidates in their advertisements over the last forty years. The primary research task will be to code and analyze the content of the over 80,000 radio and television congressional ads housed at the Julian P. Kanter Political Commercial Archive, at the University of Oklahoma. The ads will be examined through a combination of traditional and computer-automated approaches, in order to assess the kinds of issues the candidates raise, the sorts of images and references they make about the parties and party leaders, and the frequency with which they make clear, ambiguous, or inconsistent statements over time and across districts. The research will also evaluate the level of coordination that is exhibited within parties on similar election messages as each party grows more ideologically extreme and unified. The project will also conduct survey experiments aimed at addressing the behavioral foundations of partisan candidate strategies and the ways that those strategies might be linked to the information available to voters.

The project will make several broader contributions. The campaign data collected in the project will be of interest to scholars in multiple areas, including media and communication, social and public policy, economics, and political science. The computer-based coding method developed and used in this project could find additional application in such fields as linguistics and legal scholarship. The datasets and findings from the project will shed light on a range of important aspects of contemporary US politics, and may prove to be a resource for teachers, journalists, and policy-makers.

DESCRIPTION (provided by applicant): Asthma and wheezing illness are important causes of impaired quality of life, health care utilisation, consumption of prescribed drugs and hospital admission in children (Anderson et al., 2007). While some of the environmental causes of elevated childhood asthma morbidity are relatively well established, the role played by domestic pets in the development of asthmatic symptoms remains unclear. We propose here to carry out a detailed analysis of a large scale longitudinal study in which detailed prospective information about cat, dog and other pet exposures have been collected at a number of key time points and combined with objective measures of asthma occurrence and allergic sensitization. We will do this in the context of careful statistical adjustments for potential mediators and confounds. The research study we propose will represent the largest and most comprehensive investigation to date of the associations between household pet ownership and the development of childhood asthma. Over half of UK households own a pet of some type, while in the US, pet ownership is even more common. The potentially beneficial impact of companion animal ownership on the physical, psychological and social well-being of children has been widely discussed in recent years. But decisions concerning how to weigh this against possible negative effects, such as an increased incidence of asthma and wheeze in pet owning children, ultimately depend on reliable empirical data that can only be supplied by large scale birth cohort studies such as the one proposed here. A recent review of the role played by cats and dogs in the development of asthma and allergy concluded that, to date, no definitive conclusions can be drawn concerning their deleterious or protective effects (Chen et al, 2010). We propose to make use of the rich longitudinal data collected as part of the Avon Longitudinal Study of Parents and Children (ALSPAC), a British-based, ongoing, cohort study of more than 14,000 children born in the early 1990s. This will provide us with detailed information concerning the numbers and types of pets kept in participant children's households from gestation through repeated (approx. yearly) sampling points across childhood until age 8 years. It will allow us to investigate any associations between these and a number of objectively measured outcome measures (inc., atopic sensitization to animal and other allergens, and a variety of lung function scores), and parentally reported outcome variables (maternally reported wheeze, doctor diagnosed asthma) whilst also allowing us to control for potential confounds and moderators.

When we view the visual world, our eyes flit from one location to another about three times per second, in movements called saccades. Useful visual information is acquired only during fixations, brief periods of time when gaze rests on an object or scene feature. The cognitive and neural processes that direct saccades and fixations through a scene in real time fall under the term 'gaze control'. This project focuses on unraveling how human gaze control operates during active real-world scene perception.

This project approaches human gaze control by starting with the insight that understanding eye movement timing will provide key insight into the underlying cognitive and neural systems that control gaze. The research combines innovative eye-tracking methods with a working computational model that simulates eye movement control. In this research program, the empirical and computational threads are complementary and synergistic. On the one hand, we can test our understanding of gaze control by determining whether the model can produce eye movements that look like those produced by people. On the other hand, insights from the model can be used as a tool to enhance our theoretical understanding of gaze control, and these insights can be further tested with new experiments.

The results from this project will enhance basic scientific understanding of how humans perceive and understand the visual world. The project also has wide-ranging implications for the creation of new display technologies and machine interfaces that can be controlled by eye movements. And the results are relevant for the design of new artificial vision systems that actively track and focus on relevant information in the environment.

Project Summary  Real-­world scenes contain far more information that we can perceive and comprehend at any given moment. A  key mechanism for making real-­world scene perception tractable is visual attention?the mechanism of  preferentially processing only part of the scene at any given time. What we attend to in a scene determines  what we see, understand, and remember. Attention is guided by both the visual properties of the scene itself  and by our knowledge about similar scenes and the world in general. How knowledge is used to guide  attention through a meaningful scene remains largely unknown. The central idea behind this proposal is to  address this fundamental scientific question by focusing on two critical aspects of scene knowledge:  knowledge about where a given object is likely to appear in a scene, and knowledge about which regions and  objects in a scene are meaningful and informative. The studies aim to determine how spatial and meaning  constraints are used to guide attention in scenes.   This proposed research is innovative in combining high-­resolution eyetracking with novel experimental  paradigms for manipulating and measuring knowledge-­based constraints. First, a new fusion of spatial learning  methods with eyetracking is used to study the influence of spatial knowledge on attentional guidance. Second,  new quantitative scene-­rating and information-­theoretic metrics are used to index meaning in scenes, providing  a new theoretical approach to scene meaning and new empirical tools for investigating meaning. Third, real-­ time scene manipulation based on the viewer?s eye movements is combined with manipulations of spatial and  meaning constraints to investigate how quickly knowledge about a scene becomes available to guide attention.  The project is significant in challenging current models to explain the role of knowledge in guiding attention in  scenes. The experiments are designed to advance the field regardless of the outcome, and will provide rich  and theoretically constraining results that may have a transformative effect on current theory. In addition, the  proposed research has important translational implications because deficits in attention and perception are  suffered by many psychiatric and neurological populations. By understanding how knowledge influences the  guidance of attention in real scenes, the proposed studies can ultimately lead to the development of targeted  rehabilitation strategies for the real world that better capitalize on both disrupted and spared functions. 

Project Summary Efficient cognitive processing relies on the brain?s ability to engage in prediction and to use forward modeling to anticipate cognitive events, including during language processing. The central goal of this proposal is to test two competing hypotheses concerning how age influences prediction during auditory and visual language processing. Current evidence is contradictory and sparse, reflecting the need for systematic investigation. The project has three Specific Aims: Aim1: Determine whether older adults predict words in manipulated sentence contexts less or more than younger adults do by examining prediction during reading, using both electrophysiology (EEG) and eyetracking methods. Aim2: Determine whether, during spoken language processing, older adults predict words in manipulated sentence contexts less or more than younger adults do, using EEG and Visual World eyetracking methods. Spoken language processing merits targeted investigation because evidence suggests older adults have specific problems with auditory input. Moreover, in the young adult literature on prediction in language processing, relatively few studies have focused on spoken language, so little is known about whether prediction differs in the two modalities. Aim3: Determine whether older adults predict upcoming words in connected passages less or more than younger adults do, using fixation-related fMRI and EEG methods in reading, with prediction assessed by continuous measures of lexical surprisal and entropy. Surprisal and entropy measures permit the investigation of more naturally varying levels of predictability, more natural distributions of predictable and less predictable information, and allow the investigation of how natural texts (i.e., stimuli not specifically created for an experiment) are comprehended. Innovations: The project is innovative in (1) the use of converging eyetracking, EEG, and fMRI methods to systematically evaluate the extent of prediction during older adults' language comprehension, emphasizing replication across techniques and modalities; (2) the use of continuously varying surprisal/entropy in connected text to index age differences in prediction; (3) the use of a novel technique developed by PI Henderson, Fixation-Related fMRI, to relate neural activation to word-by-word surprisal and entropy during natural reading. Significance: The experiments will yield high temporal resolution information about prediction in older adults during online reading and spoken comprehension, together with detailed information about the neural bases of prediction operations. The findings have important implications for theories of normal cognitive aging. Translational significance: A psychometrically valid assessment of everyday language skills will be used to evaluate the relationship between prediction skills and a measure that has been shown to predict impairments associated with Alzheimer?s disease. Overall, prediction in language processing is potentially a model system for enhancing our scientific understanding of how cognitive and neural decline associated with aging trades off against greater knowledge and experience.

Real-world scenes comprise a blooming, buzzing confusion of information. Yet at any given moment, we can only perceive and understand a small portion of that information. What we see and understand is quite literally determined by where we look. But what determines where we look? This project seeks to answer this important question. The project investigates the idea that the meaning of a scene plays the key role in guiding our eyes. If our hypothesis is correct, then we should find that meaning predicts where people look. Such a result will advance scientific knowledge of how our brains and minds work. The results will also be useful to applied areas of computer science and engineering, contributing to increased US economic competitiveness. High-tech applications include virtual and augmented reality, artificial vision and gaze-based input systems, baggage screening, medical image assessment, satellite image analysis, and other computer-based vision systems. The project will also contribute to training of culture- and gender-diverse students and researchers in these high-tech and scientific fields, advancing the development of a diverse, globally competitive workforce.

Attentional guidance during scene viewing draws on both the visual properties of the scene and its semantic content. Although the role of visual properties (e.g., physical salience) on attentional guidance has been extensively studied, far less is known about how the semantic content of a scene guides attention. Recent work in my lab indicates that the influence of physical saliency is reduced or even eliminated when semantic content is available to guide attention. These findings have opened up important new questions about how and when meaning guides attention in scenes. The central idea behind the current work is to address these questions with a set of targeted experiments. The proposed experiments will integrate new methods for representing the meaning of local objects and scene regions with high-resolution eyetracking to measure the influence of knowledge on attentional guidance in real-world scenes. The research includes experiments motivated by four goals: (1) To compare the roles of contextualized versus context-free local scene meaning in attentional guidance. (2) To evaluate the causal relationship between local scene meaning and attentional guidance. (3) To test the generality of guidance by scene meaning across tasks and viewing time. (4) To compare the roles of physical versus semantic features in scenes using search target templates. The research will establish the foundation for a new theoretical approach to the representation of scene meaning and attentional guidance in scenes. The ultimate objective is to develop a theory of attentional guidance in scenes based on guidance by meaning.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.