Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations

Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mech- anisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cogni- tion will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.

An intercontinental comparison of chironomid palaeotemperature inference models: Europe vs North America

Chironomid-temperature inference models based on North American, European and combined surface sediment training sets were compared to assess the overall reliability of their predictions. Between 67 and 76 of the major chironomid taxa in each data set showed a unimodal response to July temperature, whereas between 5 and 22 of the common taxa showed a sigmoidal response. July temperature optima were highly correlated among the training sets, but the correlations for other taxon parameters such as tolerances and weighted averaging partial least squares (WA-PLS) and partial least squares (PLS) regression coefficients were much weaker. PLS, weighted averaging, WA-PLS, and the Modern Analogue Technique, all provided useful and reliable temperature inferences. Although jack-knifed error statistics suggested that two-component WA-PLS models had the highest predictive power, intercontinental tests suggested that other inference models performed better. The various models were able to provide good July temperature inferences, even where neither good nor close modern analogues for the fossil chironomid assemblages existed. When the models were applied to fossil Lateglacial assemblages from North America and Europe, the inferred rates and magnitude of July temperature changes varied among models. All models, however, revealed similar patterns of Lateglacial temperature change. Depending on the model used, the inferred Younger Dryas July temperature decrease ranged between 2.5 and 6°C.

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

Variance of familial dietary intake

Although many family-based genetic studies have collected dietary data, very few have used the dietary information in published findings. No single solution has been presented or discussed in the literature to deal with the problem of using factor analyses for the analyses of dietary data from several related individuals from a given household. The standard statistical approach of factor analysis cannot be applied to the VIVA LA FAMILIA Study diet data to ascertain dietary patterns since this population consists of three children from each family, thus the dietary patterns of the related children may be correlated and non-independent. Addressing this problem in this project will enable us to describe the dietary patterns in Hispanic families and to explore the relationships between dietary patterns and childhood obesity. ^ In the VIVA LA FAMILIA Study, an overweight child was first identified and then his/her siblings and parents were brought in for data collection which included 24 hour recalls and food frequency questionnaire (FFQ). Dietary intake data were collected using FFQ and 24 hour recalls on 1030 Hispanic children from 319 families. ^ The design of the VIVA LA FAMILIA Study has important and unique statistical considerations since its participants are related to each other, the majority form distinct nuclear families. Thus, the standard approach of factor analysis cannot be applied to these diet data to ascertain dietary patterns. In this project we propose to investigate whether the determinants of the correlation matrix of each family unit will allow us to adjust the original correlation matrix of the dietary intake data prior to ascertaining dietary intake patterns. If these methods are appropriate, then in the future the dietary patterns among related individuals could be assessed by standard orthogonal principal component factor analysis.^

COSTS AND EFFECTS OF ARKANSAS' LONG-TERM CARE DEMONSTRATION PROJECT (MEDICAID, CHANELLING, COMMUNITY ASSESSMENT)

The purpose of this study was to assess the impact of the Arkansas Long-Term Care Demonstration Project upon Arkansas' Medicaid expenditures and upon the clients it serves. A Retrospective Medicaid expenditure study component used analyses of variance techniques to test for the Project's effects upon aggregated expenditures for 28 demonstration and control counties representing 25 percent of the State's population over four years, 1979-1982.^ A second approach to the study question utilized a 1982 prospective sample of 458 demonstration and control clients from the same 28 counties. The disability level or need for care of each patient was established a priori. The extent to which an individual's variation in Medicaid utilization and costs was explained by patient need, presence or absence of the channeling project's placement decision or some other patient characteristic was examined by multiple regression analysis. Long-term and acute care Medicaid, Medicare, third party, self-pay and the grand total of all Medicaid claims were analyzed for project effects and explanatory relationships.^ The main project effect was to increase personal care costs without reducing nursing home or acute care costs (Prospective Study). Expansion of clients appeared to occur in personal care (Prospective Study) and minimum care nursing home (Retrospective Study) for the project areas. Cost-shifting between Medicaid and Medicare in the project areas and two different patterns of utilization in the North and South projects tended to offset each other such that no differences in total costs between the project areas and demonstration areas occurred. The project was significant ((beta) = .22, p < .001) only for personal care costs. The explanatory power of this personal care regression model (R('2) = .36) was comparable to other reported health services utilization models. Other variables (Medicare buy-in, level of disability, Social Security Supplemental Income (SSI), net monthly income, North/South areas and age) explained more variation in the other twelve cost regression models. ^

An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Age models of ODP Sites 117-722 and 117-728

Pliocene and Pleistocene sediments of the Oman margin and Owen Ridge are characterized by continuous alternation of light and dark layers of nannofossil ooze and marly nannofossil ooze and cyclic variation of wet-bulk density. Origin of the wet-bulk density and color cycles was examined at Ocean Drilling Program Site 722 on the Owen Ridge and Site 728 on the Oman margin using 3.4-m.y.-long GRAPE (gamma ray attenuation) wet-bulk density records and records of sediment color represented as changes in gray level on black-and-white core photographs. At Sites 722 and 728 sediments display a weak correlation of decreasing wet-bulk density with increasing darkness of sediment color. Wet-bulk density is inversely related to organic carbon concentration and displays little relation to calcium carbonate concentration, which varies inversely with the abundance of terrigenous sediment components. Sediment color darkens with increasing terrigenous sediment abundance (decreasing carbonate content) and with increasing organic carbon concentration. Upper Pleistocene sediments at Site 722 display a regular pattern of dark colored intervals coinciding with glacial periods, whereas at Site 728 the pattern of color variation is more irregular. There is not a consistent relationship between the dark intervals and their relative wet-bulk density in the upper Pleistocene sections at Sites 722 and 728, suggesting that dominance of organic matter or terrigenous sediment as primary coloring agents varies. Spectra of wet-bulk density and optical density time series display concentration of variance at orbital periodicities of 100, 41, 23, and 19 k.y. A strong 41-k.y. periodicity characterizes wet-bulk density and optical density variation at both sites throughout most of the past 3.4 m.y. Cyclicity at the 41-k.y. periodicity is characterized by a lack of coherence between wet-bulk density and optical density suggesting that the bulk density and color cycles reflect the mixed influence of varying abundance of terrigenous sediments and organic matter. The 23-k.y. periodicity in wet-bulk density and sediment color cycles is generally characterized by significant coherence between wet-bulk density and optical density, which reflects an inverse relationship between these parameters. Varying organic matter abundance, associated with changes in productivity or preservation, is inferred to more strongly influence changes in wet-bulk density and sediment color at this periodicity.

Age models for ODP Leg 172 sites

Ten ODP sites drilled in a depth transect (2164-4775 m water depth) during Leg 172 recovered high-deposition rate (>20 cm/kyr) sedimentary sections from sediment drifts in the western North Atlantic. For each site an age model covering the past 0.8-0.9 Ma has been developed. The time scales have a resolution of 10-20 kyr and are derived by tuning variations of estimated carbonate content to the orbital parameters precession and obliquity. Based on the similarity in the signature of proxy records and the spectral character of the time series, the sites are divided into two groups: precession cycles are better developed in carbonate records from a group of shallow sites (2164-2975 m water depth, Sites 1055-1058) while the deeper sites (2995-4775 m water depth, Sites 1060-1063) are characterized by higher spectral density in the obliquity band. The resulting time scales show excellent coherence with other dated carbonate and isotope records from low latitudes. Besides the typical Milankovitch cyclicity significant variance of the resulting carbonate time series is concentrated at millennial-scale changes with periods of about 12, 6, 4, 2.5, and 1.5 kyr. Comparisons of carbonate records from the Blake Bahama Outer Ridge and the Bermuda Rise reveal a remarkable similarity in the time and frequency domain indicating a basin-wide uniform sedimentation pattern during the last 0.9 Ma.

Area-averaged mean seasonal cycles of chlorophyll-a concentration, sea surface temperature, alongshore wind stress, westward wind speed and dust component of the aerosol optical depth at 550 nm

Nutrient supply in the area off Northwest Africa is mainly regulated by two processes, coastal upwelling and deposition of Saharan dust. In the present study, both processes were analyzed and evaluated by different methods, including cross-correlation, multiple correlation, and event statistics, using remotely sensed proxies of the period from 2000 to 2008 to investigate their influence on the marine environment. The remotely sensed chlorophyll-a concentration was used as a proxy for the phytoplankton biomass stimulated by nutrient supply into the euphotic zone from deeper water layers and from the atmosphere. Satellite-derived alongshore wind stress and sea-surface temperature were applied as proxies for the strength and reflection of coastal upwelling processes. The westward wind and the dust component of the aerosol optical depth describe the transport direction of atmospheric dust and the atmospheric dust column load. Alongshore wind stress and induced upwelling processes were most significantly responsible for the surface chlorophyll-a variability, accounting for about 24% of the total variance, mainly in the winter and spring due to the strong north-easterly trade winds. The remotely sensed proxies allowed determination of time lags between biological response and its forcing processes. A delay of up to 16 days in the surface chlorophyll-a concentration due to the alongshore wind stress was determined in the northern winter and spring. Although input of atmospheric iron by dust storms can stimulate new phytoplankton production in the study area, only 5% of the surface chlorophyll-a variability could be ascribed to the dust component in the aerosol optical depth. All strong desert storms were identified by an event statistics in the time period from 2000 to 2008. The 57 strong storms were studied in relation to their biological response. Six events were clearly detected in which an increase of chlorophyll-a was caused by Saharan dust input and not by coastal upwelling processes. Time lags of <8 days, 8 days, and 16 days were determined. An increase in surface chlorophyll-a concentration of up to 2.4 mg m**3 after dust storms in which the dust component of the aerosol optical depth was up to 0.9 was observed.

Age models and sea-surface paleotemperature reconstruction of sediment cores from the eastern equatorial Atlantic

Based on the faunal record of planktonic foraminifers in three long gravity sediment cores from the eastern equatorial Atlantic, the sea-surface temperature history ove the last 750,000 years was studied at a resolution of 3,000 to 10,000 years. Detailed oxygen-isotope and paleomagnetic stratigraphy helped to identify the following major faunal events: Globorotaloides hexagonus and Globorotalia tumida flexuosa became extinct in the eastern tropical Atlantic at the isotope stage 4/5 boundary, now dated at 68,000 years B.P. The persistent occurrence of the pink variety of Globigerinoides ruber started during the late stage 12 at 410,000 years B.P. CARTUNE-age. This datum may provide an easily detectible faunal stratigraphic marker for the mid-Brunhes Chron. The updated scheme of the Ericson zones helped the recognition of a hiatus at the northwestern slope of the Sierra Leone Basin covering oxygen-isotope stages 10 to 12. Classifying the planktonic foraminifer counts into six faunal assemblages, according to the factor analysis derived model of Pflaumann (1985), the tropical and the tropical-upwelling communities account for 57 % at Site 16415, and 86 % at Site 13519, respectively of the variance of the faunal record. A largely continuous paleotemperature record for both winter and summer seasons was obtained from the top of the Sierra Leone Rise with the winter temperatures ranging between 20 and 25 °C, and the summer ones between 24 and 30 °C. The record of cores from greater water depths is frequently interrupted by samples with no-analogue faunal communities and/or poor preservation. Based on the seasonality signal, during cold periods the termal equator shifted to a geographically mnore asymmetrical northern position. Dissolution altering the faunal communities becomes stronger with greater water depth, the estimated mean minimum loss of specimens increases from 70 % to 80 % between 2,860 and 3,850 water depth although some species will be more susceptible than others. Enhanced dissolution occured during stage 4 but also during cold phases in the warm stage 7 and 9. Correlations between the Foraminiferal Dissolution Index and the estimated sea-surface temperatures are significant. Foraminiferal flux rates, negatively correlated to the flux rates of organic carbon and of diatoms, may be a result of enhanced dissolution during cold stages, destroying still more of the faunal signal than indicated by the calculated minimum loss. The fluctuations of the oxygen-isotope curves and the hibernal sea-surfave temperatures are fairly coherent. During warm oxygen-isotope stages the temperature maxima lag often by 5 to 15 ka behind the respective sotope minima. During cold stages, sea-surface temperature changes are partly out of phase and contain additional fluctuations.

Photosynthetic parameters, chlorophyll concentration, and diffuse attenuation coefficients in the Rhode River, Maryland (USA), 1990-2009

Parameters in the photosynthesis-irradiance (P-E) relationship of phytoplankton were measured at weekly to bi-weekly intervals for 20 yr at 6 stations on the Rhode River, Maryland (USA). Variability in the light-saturated photosynthetic rate, PBmax, was partitioned into interannual, seasonal, and spatial components. The seasonal component of the variance was greatest, followed by interannual and then spatial. Physiological models of PBmax based on balanced growth or photoacclimation predicted the overall mean and most of the range, but not individual observations, and failed to capture important features of the seasonal and interannual variability. PBmax correlated most strongly with temperature and the concentration of dissolved inorganic carbon (IC), with lesser correlations with chlorophyll a, diffuse attenuation coefficient, and a principal component of the species composition. In statistical models, temperature and IC correlated best with the seasonal pattern, but temperature peaked in late July, out of phase with PBmax, which peaked in September, coincident with the maximum in monthly averaged IC concentration. In contrast with the seasonal pattern, temperature did not contribute to interannual variation, which instead was governed by IC and the additional lesser correlates. Spatial variation was relatively weak and uncorrelated with ancillary measurements. The results demonstrate that both the overall distribution of PBmax and its relationship with environmental correlates may vary from year to year. Coefficients in empirical statistical models became stable after including 7 to 10 yr of data. The main correlates of PBmax are amenable to automated monitoring, so that future estimates of primary production might be made without labor-intensive incubations.

Component NRM Directions for two sediment cores from the Arctic Ocean

Inclination patterns of natural remanent magnetization (NRM) in Quaternary sediment cores from the Arctic Ocean have been widely used for stratigraphic correlation and the construction of age models, however, shallow and negative NRM inclinations in sediments deposited during the Brunhes Chron in the Arctic Ocean appear to have a partly diagenetic origin. Rock magnetic and mineralogical studies demonstrate the presence of titanomagnetite and titanomaghemite. Thermal demagnetization of the NRM indicates that shallow and negative inclination components are largely "unblocked" below ~300 °C, consistent with a titanomaghemite remanence carrier. Following earlier studies on the Mendeleev-Alpha Ridge, shallow and negative NRM inclination intervals in cores from the Lomonosov Ridge and Yermak Plateau are attributed to partial self-reversed chemical remanent magnetization (CRM) carried by titanomaghemite formed during seafloor oxidation of host (detrital) titanomagnetite grains. Distortion of paleomagnetic records due to seafloor maghemitization appears to be especially important in the perennially ice covered western (Mendeleev-Alpha Ridge) and central Arctic Ocean (Lomonosov Ridge) and, to a lesser extent, near the ice edge (Yermak Plateau). On the Yermak Plateau, magnetic grain size parameters mimic the global benthic oxygen isotope record back to at least marine isotope stage 6, implying that magnetic grain size is sensitive to glacial-interglacial changes in bottom-current velocity and/or detrital provenance.