Sophia Rabe-Hesketh

Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain

The authors describe almost entirely automated procedures for estimation of global, voxel, and cluster-level statistics to test the null hypothesis of zero neuroanatomical difference between two groups of structural magnetic resonance imaging (MRI) data. Theoretical distributions under the null hypothesis are available for (1) global tissue class volumes; (2) standardized linear model [analysis of variance (ANOVA and ANCOVA)] coefficients estimated at each voxel; and (3) an area of spatially connected clusters generated by applying an arbitrary threshold to a two-dimensional (2-D) map of normal statistics at voxel level. The authors describe novel methods for economically ascertaining probability distributions under the null hypothesis, with fewer assumptions, by permutation of the observed data. Nominal Type I error control by permutation testing is generally excellent; whereas theoretical distributions may be over conservative. Permutation has the additional advantage that it can be used to test any statistic of interest, such as the sum of suprathreshold voxel statistics in a cluster (or cluster mass), regardless of its theoretical tractability under the null hypothesis. These issues are illustrated by application to MRI data acquired from 18 adolescents with hyperkinetic disorder and 16 control subjects matched for age and gender.

Generalized multilevel structural equation modeling

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent variables. The response model generalizes GLMMs to incorporate factor structures in addition to random intercepts and coefficients. As in GLMMs, the data can have an arbitrary number of levels and can be highly unbalanced with different numbers of lower-level units in the higher-level units and missing data. A wide range of response processes can be modeled including ordered and unordered categorical responses, counts, and responses of mixed types. The structural model is similar to the structural part of a SEM except that it may include latent and observed variables varying at different levels. For example, unit-level latent variables (factors or random coefficients) can be regressed on cluster-level latent variables. Special cases of this framework are explored and data from the British Social Attitudes Survey are used for illustration. Maximum likelihood estimation and empirical Bayes latent score prediction within the GLLAMM framework can be performed using adaptive quadrature in gllamm, a freely available program running in Stata.

Meta-analysis of the P300 and P50 waveforms in schizophrenia

OBJECTIVE To determine whether patients with schizophrenia have abnormalities in the P300 and P50 waves and to quantify the magnitude of any differences from controls. METHOD We conducted a systematic search for articles published between January 1994 and August 2003 that reported P50 or P300 measures in schizophrenic patients and controls. Metaregression analyses were performed using a random effects model. The pooled standardised effect size (PSES) was calculated as the difference between the means of the two groups divided by the common standard deviation. RESULTS We identified 46 studies suitable for analysis of P300 measures, including 1443 patients and 1251 controls. There were 20 P50 studies including 421 patients and 401 controls. The PSES for the P300 amplitude was 0.85 (95% CI: 0.65 to 1.05; p<0.001), and for the P300 latency was -0.57 (95% CI: -0.75 to -0.38; p<0.001). The PSES of the P50 ratio was -1.56 (95% CI: -2.05 to -1.06; p<0.001). There were no significant differences between patients and controls in P50 latency. Across-study variations in filters, task difficulty, antipsychotic medication and duration of illness did not influence the PSES significantly. CONCLUSIONS This meta-analysis confirms the existence of ERP deficits in schizophrenia. The magnitude of these deficits is similar to the most robust findings reported in neuroimaging and neuropsychology in schizophrenia.

Methods for Diagnosis and Treatment of Stimulus-Correlated Motion in Generic Brain Activation Studies Using fMRI

Movement‐related effects in realigned fMRI timeseries can be corrected by regression on linear functions of estimated positional displacements of an individual subjects head during image acquisition. However, this entails biased (under)estimation of the experimental effect whenever subject motion is not independent of the experimental input function. Methods for diagnosing such stimulus‐correlated motion (SCM) are illustrated by application to fMRI data acquired from 5 schizophrenics and 5 normal controls during periodic performance of a verbal fluency task. The schizophrenic group data were more severely affected by SCM than the control group data. Analysis of covariance (ANCOVA) was used, with a voxelwise measure of SCM as a covariate, to estimate between‐group differences in power of periodic signal change while controlling for variability in SCM across groups. Failure to control for SCM in this way substantially exaggerated the number of voxels, apparently demonstrating a between‐group difference in task response. Hum. Brain Mapping 7:38–48, 1999.

Recognizing one's own face

We report two studies of facial self-perception using individually tailored, standardized facial photographs of a group of volunteers and their partners. A computerized morphing procedure was used to merge each target face with an unknown control face. In the first set of experiments, a discrimination task revealed a delayed response time for the more extensively morphed self-face stimuli. In a second set of experiments, functional magnetic resonance imaging (fMRI) was used to measure brain activation while subjects viewed morphed versions of either their own or their partners face, alternating in blocks with presentation of an unknown face. When subjects viewed themselves (minus activation for viewing an unknown face), increased blood oxygenation was detected in right limbic (hippocampal formation, insula, anterior cingulate), left prefrontal cortex and superior temporal cortex. In the partner (versus unknown) experiment, only the right insula was activated. We suggest that a neural network involving the right hemisphere in conjunction with left-sided associative and executive regions underlies the process of visual self-recognition. Together, this combination produces the unique experience of self-awareness.

Meta-analysis of magnetic resonance imaging brain morphometry studies in bipolar disorder

BACKGROUND Several studies assessing volumetric measurements of regional brain structure in bipolar disorder have been published in recent years, but their results have been inconsistent. Our aim was to complete a meta-analysis of regional morphometry in bipolar disorder as assessed using magnetic resonance imaging (MRI). METHODS We conducted a systematic literature search of MRI studies of bipolar disorder and identified studies which reported volume measurements in a selected number of regions. Twenty-six studies comprising volumetric measurements on up to 404 independent patients with bipolar disorder were included. A meta-analysis was carried out comparing the volumes of regions in bipolar disorder to comparison subjects using a random effects model. RESULTS Patients with bipolar disorder had enlargement of the right lateral ventricle, but no other regional volumetric deviations which reached significance. Strong heterogeneity existed for several regions, including the third ventricle, left subgenual prefrontal cortex, bilateral amygdala and thalamus. CONCLUSIONS Regional volume of most structures we studied is preserved in bipolar disorder as a whole, which was significantly associated only with right-sided ventricular enlargement. However the extensive heterogeneity detected indicates the need for further studies to establish if consistent regional brain volume deviation exists in bipolar disorder or in specific clinical subsets of the illness.

Multilevel logistic regression for polytomous data and rankings

We propose a unifying framework for multilevel modeling of polytomous data and rankings, accommodating dependence induced by factor and/or random coefficient structures at different levels. The framework subsumes a wide range of models proposed in disparate methodological literatures. Partial and tied rankings, alternative specific explanatory variables and alternative sets varying across units are handled. The problem of identification is addressed. We develop an estimation and prediction methodology for the model framework which is implemented in the generally available gllamm software. The methodology is applied to party choice and rankings from the 1987–1992 panel of the British Election Study. Three levels are considered: elections, voters and constituencies.

Does dysplasia cause anatomical dysconnectivity in schizophrenia

Evidence is reviewed that dysplastic brain development in the second half of pregnancy predisposes to schizophrenia. We suggest that an important corollary of aberrant development at this stage of ontogenesis is abnormal afferentation of the cortical plate, and that this may be macroscopically measurable in terms of abnormal correlational structure in adult brain imaging data. This prediction is tested by analysis of multiple cortical volume measures on magnetic resonance imaging data acquired from 35 male right-handed schizophrenics and 35 matched controls. There are no significant differences between groups in global, intra-hemispheric or inter-hemispheric correlational structure; but schizophrenics are shown to have significantly reduced dependencies between frontal and temporal lobe volumes, and frontal and hippocampal volumes, in the left hemisphere. We conclude that anatomical dysconnectivity (between frontal and temporal cortex) in schizophrenia may be caused by dysplasia.

A comparative study of iatrogenesis, medication abuse, and psychiatric morbidity in chronic pain patients with and without medically explained symptoms.

&NA; We report a case control study comparing patients attending a pain clinic whose symptoms were not considered medically explained (cases) with those whose symptoms were considered medically explained (controls). Principal comparisons were psychiatric morbidity, medication use, and iatrogenic factors assessed by interview, and questionnaire measures of anxiety, depression, functional impairment, coping strategies and pain beliefs. Medically unexplained symptoms were associated with the presence of psychiatric morbidity (odds ratio=3.4, 95% C.I.: 1.4,8.2), and of possible iatrogenic factors. There were no significant differences with regards to medication abuse/dependence.

Lifetime course of eating disorders: design and validity testing of a new strategy to define the eating disorders phenotype

BACKGROUND Aetiological studies of eating disorders would benefit from a solution to the problem of instability of eating disorder symptoms. We present an approach to defining an eating disorders phenotype based on the retrospective assessment of lifetime eating disorders symptoms to define a lifetime pattern of illness. We further validate this approach by testing the most common lifetime categories for differences in the prevalence of specific childhood personality traits. METHOD Ninety-seven females participated in this study, 35 with a current diagnosis of restricting anorexia nervosa, 32 with binge/purging subtype of anorexia nervosa and 30 with bulimia nervosa. Subjects were interviewed by a newly developed EATATE Lifetime Diagnostic Interview for a retrospective assessment of the lifetime course of eating disorders symptoms and childhood traits reflecting obsessive-compulsive personality. RESULTS The data illustrate the extensive instability of the eating disorders diagnosis. Four most common lifetime diagnostic categories were identified that significantly differ in the prevalence of childhood traits. Perfectionism and rigidity were more common in groups with a longer duration of underweight status, longer episodes of severe food restriction, excessive exercising, and shorter duration of binge eating. CONCLUSIONS The assessment of lifetime symptoms may produce a more accurate definition of the eating disorders phenotype. Obsessive-compulsive traits in childhood may moderate the course producing longer periods of underweight status. These findings may have important implications for nosology, treatment and future aetiological studies of eating disorders.