Michelle Liou

MR Image Segmentation Using a Power Transformation Approach

This study proposes a segmentation method for brain MR images using a distribution transformation approach. The method extends traditional Gaussian mixtures expectation-maximization segmentation to a power transformed version of mixed intensity distributions, which includes Gaussian mixtures as a special case. As MR intensities tend to exhibit non-Gaussianity due to partial volume effects, the proposed method is designed to fit non-Gaussian tissue intensity distributions. One advantage of the method is that it is intuitively appealing and computationally simple. To avoid performance degradation caused by intensity inhomogeneity, different methods for correcting bias fields were applied prior to image segmentation, and their correction effects on the segmentation results were examined in the empirical study. The partitions of brain tissues (i.e., gray and white matter) resulting from the method were validated and evaluated against manual segmentation results based on 38 real T1-weighted image volumes from the Internet brain segmentation repository, and 18 simulated image volumes from BrainWeb. The Jaccard and Dice similarity indexes were computed to evaluate the performance of the proposed approach relative to the expert segmentations. Empirical results suggested that the proposed segmentation method yielded higher similarity measures for both gray matter and white matter as compared with those based on the traditional segmentation using the Gaussian mixtures approach.

EEG-correlates of trait anxiety in the stop-signal paradigm

The relationship between trait anxiety and event-related EEG oscillatory reactions in the stop-signal paradigm was studied in 15 non-clinical subjects with average age of 26 years (13 men). In the paradigm, subjects responded to target stimuli by pressing one of the two choice buttons. In 30 out of 130 trials, target presentation was followed by a stop-signal, indicating that subjects had to refrain from a prepared motor response. The subjects level of anxiety was assessed using the State Trait Anxiety Inventory. Wide-band desynchronization (8-25 Hz) was found before button-press. It was sustained after the subjects pressed the button at 7-14 Hz frequency range. Also, synchronization at 15-25 Hz band occurred in 400-1400 ms after the button-press. Synchronization at lower frequencies (1-7 Hz) was also found during 0-700 ms after the stop-signal onset. Also, desynchronization at 8-20 Hz was found in 300-800 ms after stop-signal onset. The group with higher anxiety showed desynchronization at 10-13 Hz in 0-800 ms after the button-press, whereas the group with lower anxiety showed synchronization at the same frequency range. In 0-600 ms after stop-signal onset, desynchronization at 8-13 Hz was observed in the group with higher anxiety, whereas the group with lower anxiety demonstrated synchronization or weak desynchronization. Our findings support the Eysenck et al. [M.W. Eysenck, N. Derakshan, R. Santos, M.G. Calvo, Anxiety and cognitive performance: attentional control theory, Emotion 7(2) (2007) 336-356] theory that subjects with higher anxiety have more attentional control over reaction and increased use of processing resources as compared with lower anxiety subjects.

EEG correlates of spontaneous self-referential thoughts: a cross-cultural study.

The default mode network (DMN) has been mostly investigated using positron emission tomography and functional magnetic resonance imaging (fMRI) and has received mixed support in electroencephalographic (EEG) studies. In this study, after sLORETA transformation of EEG data, we applied group spatial independent component analysis which is routinely used in fMRI research. In three large and diverse samples coming from two different cultures (Russian and Taiwanese), spontaneous EEG data and retrospective questionnaire measures of subjects state, thoughts, and feelings during the EEG registration were collected. Regression analyses showed that appearance of spontaneous self-referential thoughts was best predicted by enhanced alpha activity within the DMN. Diminished theta and delta activity in the superior frontal gyrus and enhanced beta activity in the postcentral gyrus added to the prediction. The enhanced alpha activity prevailed in the posterior DMN hub in Russian, but in the anterior DMN hub in Taiwanese participants. Possible cross-cultural differences in personality and attitudes underlying this difference are discussed.

Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality

Event-related potentials (ERPs) induced by visual perception and cognitive tasks have been extensively studied in neuropsychological experiments. ERP activities time-locked to stimulus presentation and task performance are often observed separately at individual scalp channels based on averaged time series across epochs and experimental subjects. An analysis using averaged EEG dynamics could discount information regarding interdependency between ongoing EEG and salient ERP features. Advanced tools such as independent component analysis (ICA) have been developed for decomposing collections of single-trial EEG records into separate features. Those features (or independent components) can then be mapped onto the cortical surface using source localization algorithms to visualize brain activation maps and to study between-subject consistency. In this study, we propose a statistical framework for estimating the time course of spatiotemporally independent EEG components simultaneously with their cortical distributions. Within this framework, we implemented Bayesian spatiotemporal analysis for imaging the sources of EEG features on the cortical surface. The framework allows researchers to include prior knowledge regarding spatial locations as well as spatiotemporal independence of different EEG sources. The use of the Electromagnetic Spatiotemporal ICA (EMSICA) method is illustrated by mapping event-related EEG dynamics induced by events in a visual two-back continuous performance task. The proposed method successfully identified several interesting components with plausible corresponding cortical activation topographies, including processes contributing to the late positive complex (LPC) located in central parietal, frontal midline, and anterior cingulate cortex, to atypical mu rhythms associated with the precentral gyrus, and to the central posterior alpha activity in the precuneus.

A method for generating reproducible evidence in fMRI studies.

Insights into cognitive neuroscience from neuroimaging techniques are now required to go beyond the localisation of well-known cognitive functions. Fundamental to this is the notion of reproducibility of experimental outcomes. This paper addresses the central issue that functional magnetic resonance imaging (fMRI) experiments will produce more desirable information if researchers begin to search for reproducible evidence rather than only p value significance. The study proposes a methodology for investigating reproducible evidence without conducting separate fMRI experiments. The reproducible evidence is gathered from the separate runs within the study. The associated empirical Bayes and ROC extensions of the linear model provide parameter estimates to determine reproducibility. Empirical applications of the methodology suggest that reproducible evidence is robust to small sample sizes and sensitive to both the magnitude and persistency of brain activation. It is demonstrated that research findings in fMRI studies would be more compelling with supporting reproducible evidence in addition to standard hypothesis testing evidence.

Estimating Comparable Scores Using Surrogate Variables

The possibility of using surrogate variables (e.g., school grades, other test scores, examinee background information) as replacements for common items predicting sample-selection bias between groups was investigated. The problem was specified as an incomplete data problem of comparability studies and was addressed using nonequivalent groups. A general model for estimating complete data (fitted) distributions through covariates is proposed (including common-item scores and surrogate variables as special cases). Model parameters are estimated using the EM algorithm. Standard errors of comparable scores are derived under the proposed model. Data from an empirical example examined the use of surrogate variables for establishing score comparability.

Estimation of Trait Level in Computerized Adaptive Testing

In computerized adaptive testing (CAT), an examinee’s trait level (Θ) must be estimated with reasonable accuracy based on a small number of item responses. A successful implementation of CAT depends on (1) the accuracy of statistical methods used for estimating and (2) the efficiency of the item-selection criterion. Methods of estimating suitable for CAT are reviewed, and the differences between Fisher and Kullback-Leibler information criteria for selecting items are discussed. The accuracy of different CAT algorithms was examined in an empirical study. The results showed that correcting estimates for bias was necessary at earlier stages of CAT, but most CAT algorithms performed equally well for tests of 10 or more items.

More on the Computation of Higher-Order Derivatives of the Elementary Symmetric Functions in the Rasch Model

A recursive equation for computing higher-order derivatives of the elementary symmetric functions in the Rasch model is proposed. The formula is conceptually simple and relatively more efficient than the sum algorithm (Gustafsson, 1980). A simulation study indicated that the proposed formula has a small loss in accuracy, compared to the sum algorithm, for computing higher-order derivatives when tests contained 60 items or less. Index terms: difference algorithm, elementary symmetric functions, Formanns equation, Jansens equation, Rasch model, sum algorithm.

Standard Errors of the Kernel Equating Methods Under the Common-Item Design

Simplified equations are derived to compute the standard error of the frequency estimation method for studies indicate that the simplified equations work equating score distributions that are continuized using a uniform or Gaussian kernel function (Holland, King, & Thayer, 1989; Holland & Thayer, 1987). The simplified equations can be used to equate both observed- and smoothed-score distributions (Rosenbaum & Thayer, 1987). Results from two empirical reasonably well for moderate-size samples (e.g., 1,000 examinees).

Effects of Microvascular Permeability Changes on Contrast-Enhanced T1 and Pharmacokinetic MR Imagings After Ischemia

Background and Purpose— Brain enhancement on contrast-enhanced T1-weighted imaging (CET1-WI) after ischemic stroke is generally accepted as an indicator of the blood–brain barrier disruption. However, this phenomenon usually starts to become visible at the subacute phase. The purpose of this study was to evaluate the time-course profiles of Ktrans, cerebral blood volume (vp), and CET1-WI with early detection of blood–brain barrier changes on Ktrans maps and their role for prediction of subsequent hemorrhagic transformation in acute middle cerebral arterial infarct. Methods— Twenty-six patients with acute middle cerebral arterial stroke and early spontaneous reperfusion, whose MR images were obtained at predetermined stroke stages, were included. T2*-based MR perfusion-weighted images were acquired using the first-pass pharmacokinetic model to derive Ktrans and vp. Parenchymal enhancement observed on maps of Ktrans, vp, and CET1-WI at each stage was compared. Association among these measurements and hemorrhagic transformation was analyzed. Results— Ktrans map showed significantly higher parenchymal enhancement in ischemic parenchyma as compared with that of vp map and CET1-WI at early stroke stages (P<0.05). The increased Ktrans at acute stage was not associated with parenchymal enhancement in CET1-WI at the same stage. Parenchymal enhancement in CET1-WI started to occur at the late subacute stage and tended to be luxury reperfusion–dependent. Patients with hemorrhagic transformation showed higher mean Ktrans values as compared with patients without hemorrhagic transformation (P=0.02). Conclusions— Postischemic brain enhancement on routine CET1-WI seems to be closely related to the luxury reperfusion at the late subacute stage and is not dependent on microvascular permeability changes at the acute stage.