Steven M. Boker - US grants

DESCRIPTION (Adapted from the Applicant's Abstract): Falling is a common problem among elderly adults. Each year about half the residents of nursing homes experience a fall, and of those individuals about 15% are seriously injured. While there are many factors that may be associated with falling, deterioration of the postural control system is a serious risk factor for falling. This proposal is designed to provide evidence with regard to the following five questions: 1) whether linear models are sufficient to capture the behavior of the postural control system, 2) whether the assumption of static equilibrium is supported by the behavior of the postural control system, 3) whether center of pressure (COP) and head movement can be used interchangeably, 4) whether there exist resonant frequencies in the postural control system, and 5) whether prospective adjustment in visually guided postural control is related to resonant frequencies in the system. Each of these questions is likely to exhibit age-related differences that may be diagnostic of reduced postural control in aging and the attendant increased risk of falling in older adults. There are seven specific aims that are addressed by this research project: 1) constrain the choice of models for postural control, 2) test whether kinematic and COP measurements can be used interchangeably, 3) provide evidence against either the static or dynamic equilibrium hypotheses, 4) test for age-related differences in the first 3 aims, 5) generate a young-adult baseline set of observations and develop and test models of postural control in these data, 6) test for both parametric and structural age-related differences in these models, and 7) prepare and archive the data for data-sharing and longitudinal follow-up.

DESCRIPTION (provided by applicant): Empirical research in gerontology, psychology, education, and neuroscience is increasingly dependent on the use of statistical tools to design experiments, verify measurement instruments, test hypotheses, and interpret models. As these tools become more advanced, training in the appropriate use of quantitative methodology becomes both more important and more specialized. The present proposal addresses this problem by increasing the number of opportunities for exposure to advanced quantitative methods available to researchers in the social sciences. An annual conference and workshop will be held at the University of Notre Dame in which top scholars in quantitative methodology will present a series of talks focused around either a central unifying methodological theme or targeted for a particular audience of substantive research in the behavioral sciences. The present proposal covers the second year in this series: Dynamical Systems Data Analysis. The sessions will present practical techniques for the analysis of experimental data from a dynamical systems perspective with the purpose that attendees may immediately use their acquired knowledge to improve the quality of their sponsored research and improve the experimental designs within proposals for sponsored research.

[unreadable] DESCRIPTION (provided by applicant): Summary Statistical modeling plays a central role in a wide range of scientific investigations. Studies of complex traits and disorders such as addictive behaviors, psychopathology, cardiovascular disease, obesity, and cancer are now faced with a set of statistical challenges that require improved software. The challenges include: i) the difficulty of measuring behavioral traits; ii) the availability of technologies - such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning, and iii) increased sophistication in the statistical models used to analyze the data. The current project proposes to rewrite the popular Mx statistical package in order to address these challenges. Both the user specification of models and the algorithms used to ?t them will be significantly improved. The software will be i) split into modules that interoperate with the R statistical package, ii) released as open source so as to provide a stable path for future maintenance and development and iii) integrated with the VDL parallel work software. Grid/parallel computing and data management using VDL will provide significant speedup for processing large (up to multi-terabyte) data sets, through the use of analytical work that provide detailed provenance tracking and annotation of derived results. Revised algorithms for model and optimization will increase both the scope of the software and its performance. Both the code and its use will be documented and disseminated at national and international workshops. Studies of complex traits and disorders such as addictive behaviors, psychopathology, cardiovascular disease, obesity, and cancer are now faced with a set of statistical challenges that require improved software. The challenges include: i) the difficulty of measuring behavioral traits; ii) the availability of technologies - such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning; and iii) increased sophistication in the statistical models used to analyze the data. The current project proposes to develop software that uses massively parallel computing grids, "cyberinfrastructure", in order to address these challenges. [unreadable] [unreadable] [unreadable]

As we talk with others, facial expressions, head movements and nonverbal speech characteristics serve as crucial cues to our emotional tone. For this process to be effective, the cues to expressed affect must change constantly and are difficult to study. The lack of tools for measuring and modeling the multiple cues used to interpret live facial expressions has limited the scientific study of the regulation of facial expression in conversation. This proposal consists of experiments designed to manipulate the specific cues thought to determine perceivers' understanding of communicators' emotional states during live conversations. The primary goals of this project are twofold. The first goal is to develop and refine tools (e.g., computer software programs) that will allow scientists to better understand the specific facial and movement cues that allow people to express and understand communicated affect during live conversation. The second goal is to refine the software that allows such tests of affective communication, so that it serves as a new tool for a host of behavioral scientists who wish to study and manipulate the nature of live interactions. For example, this software will allow experimenters to manipulate the perceived gender of two people who are having a live getting-acquainted conversation -- so that a man who is actually talking to another man sees a realistic, convincing facial avatar of a woman (who perfectly mimics the facial and head movements of the actual male interaction partner). This software developed and refined in this proposal will thus allow social and cognitive psychologists to manipulate, for example, the social categories of people's interaction partners in ways not imagined a decade ago.

The impact of this project is exceptionally wide ranging. One area of application is measuring and modeling facial dynamics -- that is, using this technology to further study live facial expression. The current project will provide open source software that can be distributed free for research purposes. Research labs who wish to use the software will also be provided with free supporting materials (e.g., plans, equipment lists) to facilitate the dissemination of the technology resulting from the current project. A second area of application is the study of intercultural communication. This new technology will allow sophisticated studies of social interactions and communication in small group, high stress settings in which emotional regulation is critical (e.g., intercultural interactions by police or military personnel) or in negotiation settings (e.g., diplomatic relations). Further the technology could be used to allow live video interactions between people that maintain the tone and content of communications while still maintaining speaker confidentiality. A third area of application is educational technology. A problem with virtual learning environments is the difficulty of detecting students' nonverbal cues -- cues that a live classroom teacher often uses to assess student understanding or confusion. The work may lead to automatic recognition of these cues from video capture. This information could then be used to improve the virtual learning environment or refine the specific teaching materials that are broadcast to students.