Is anorexia nervosa a neuropsychological disease?

Evidence for central nervous system, and more particularly cortical, etiology of anorexia nervosa is reviewed. Topics covered are neuropsychiatric comorbidity, inheritance patterns, the neurobiology of body-image disturbance and of the eating function, perinatal and alcoholic insult to the brain, neurochemical and neuroelectric disturbance, anatomic and metabolic brain imaging, and neuropsychological impairment. It is concluded that there is indeed an important neuropsychological etiological dimension to anorexia nervosa. The profile most frequently associated with anorexia nervosa is right posterior hypometabolism, followed by right anterior hypermetabolism, both associated with right-sided abnormal electroencephalogram spiking. It is also proposed that bulimia consists of a positive neurological subtype and that restricting anorexia represents a negative neurological subtype. Priorities for further research into anorexia nervosa are specified to include twin adoption studies, brain electrical topography studies, postmortem histological studies, and experimentally inspired neuropsychological studies.     

Subjective contours 1900–1990: Research trends and bibliography

Abibliography on subjective contours and a brief summary of trends in research-on-thin problem are presented. The bibliography covers the years 1900–1990 and contains 445 entries, each briefly annotated with a code that indicates the general content and theoretical orientation of the item.     

Visual perception of surface curvature: psychophysics of curvature detection induced by motion parallax

The continuous approach to optic-flow processing shows that the curvature of a moving surface is related to a second spatial derivative of the velocity field, the spin variation (Droulez & Cornilleau-Pérès, 1989). With this approach as a theoretical framework, visual sensitivity to the curvature of a cylinder in motion was measured using a task of discrimination between cylindrical and planar patches. The results confirm the predictions suggested by the theory: (1) Sensitivity to curvature was always greater when the cylinder axis and the frontal translation were parallel than when they were orthogonal. The ratio of curvature detection thresholds in the two cases was between 1.3 and 2.5; the value predicted from the spin variation theory is about 2. (2) Sensitivity to curvature increased strongly with the velocity of the motion but was only weakly affected by its amplitude and the duration of viewing for the range of values used in our experiments.     

Using item-specific instructional information in achievement modeling

The problem of detecting instructional sensitivity (item basis) in test items is considered. An illustration is given which shows that for tests with many biased items, traditional item bias detection schemes give a very poor assessment of bias. A new method is proposed instead. This method extends item response theory (IRT) by including item-specific auxiliary measurement information related to opportunity-to-learn. Item-specific variation in measurement relations across students with varying opportunity-to-learn is allowed for.This paper was presented at the 1987 AERA meeting in Washington, DC. This research was supported by grant OERI-G-86-003 from the Office of Educational Research and Improvement, Department of Education. The author thanks Michael Hollis and Chih-fen Kao for valuable research assistance, and appreciates valuable comments made by an anonymous reviewer.     

Statistical analysis of fuzzy-set data from neuronal networks

In this study, we describe the process of transforming neuron polarization values that meet the assumptions of ratio data into ordinal data. This is a crisp-to-fuzzy set transformation. A computerized simulation of the application of this process is discussed and nonparametric methods of analyzing fuzzy-set data are presented.     

Factor structure in groups selected on observed scores

A new method is proposed for estimating factor means and factor covariances in a group of individuals selected on their observed scores. The selection variable is, for example, the total score on an admissions test. Given a factor model for the test items based on the group of test takers, we may be interested in the factor structure for those in the top quartile. The differences in factor means and covariances between this selected group and the full group gives useful information both on successful test performance and on test validity. The new method draws on the classic Pearson-Lawley selection formulas. It avoids the fallacy of factor analysis on the selected group, which would lead to incorrect estimates. The new method is applied to a simple factor structure model for the GMAT test. Although the majority of the GMAT items test verbal skills, it is found that a quantitative factor shows the greatest change in moving from average to top quartile test takers.     

Information Consistency and Perceptual Set: Overcoming the Mental Retardation “Schema”1

Two factors that were thought to promote or inhibit schema-based or stereotypic responding in impression formation were examined in two experiments. Subjects were asked to provide evaluations of artwork supposedly painted by either mentally retarded or nonretarded children. Based on previous research, it was assumed that subjects would expect relatively poor quality artwork from retarded children, which would he consistent with a negative schema that they maintain for this group. It was also predicted that this negative schema would result in cursory examinations and unfavorable evaluations of the retarded artists' artwork, but only when the evaluative conditions were conducive to schematic responding. Specifically, the schema effect was predicted to occur when the artwork was of poor quality and subjects were instructed to provide an overall evaluation of the painting rather than an assessment of its specific characteristics. No derogation was expected when these factors were not present. Results supported these hypotheses. Additional analyses indicated that subjects were conducting a cursory search of the target stimuli when conditions favored schema-based responding.     

On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.     

Three-dimensional perspective drawing of two-dimensional functions with microcomputers

In this paper, we present a BASIC program for Apple II series computers that allows the user to obtain perspective drawings of two-dimensional functions of known analytical expression. Also, we outline a procedure for obtaining perspective representations of two-dimensional arrays of data using the same program. The program should run on any computer with graphics mode with only slight modifications in the graphics commands.