Visual fixation and smooth pursuit eye movement abnormalities in patients with schizophrenia and their relatives.
ABSTRACT Increasing evidence suggests that smooth pursuit eye movement (SPEM) dysfunction may serve as an endophenotype or genetic marker of schizophrenia. The authors tested SPEM and visual fixation (VF) in 31 patients with schizophrenia, 33 of their first-degree relatives, and 24 patients with major depressive disorder. A high rate of abnormal VF was found in schizophrenic patients and their first-degree relatives, but not in affective disorder patients with or without psychotic features. Rate of VF abnormality distinguished schizophrenic patients from acutely depressed mood disorder patients; SPEM did not. VF and SPEM performance correlated only moderately, suggesting that the pathophysiologies of these two eye movement abnormalities may be partially independent. Implications for identifying a schizophrenia endophenotype are discussed.
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ABSTRACT: We have investigated which eye-movement tests alone and combined can best discriminate schizophrenia cases from control subjects and their predictive validity. A training set of 88 schizophrenia cases and 88 controls had a range of eye movements recorded; the predictive validity of the tests was then examined on eye-movement data from 34 9-month retest cases and controls, and from 36 novel schizophrenia cases and 52 control subjects. Eye movements were recorded during smooth pursuit, fixation stability, and free-viewing tasks. Group differences on performance measures were examined by univariate and multivariate analyses. Model fitting was used to compare regression, boosted tree, and probabilistic neural network approaches. As a group, schizophrenia cases differed from control subjects on almost all eye-movement tests, including horizontal and Lissajous pursuit, visual scanpath, and fixation stability; fixation dispersal during free viewing was the best single discriminator. Effects were stable over time, and independent of sex, medication, or cigarette smoking. A boosted tree model achieved perfect separation of the 88 training cases from 88 control subjects; its predictive validity on retest assessments and novel cases and control subjects was 87.8%. However, when we examined the whole data set of 298 assessments, a cross-validated probabilistic neural network model was superior and could discriminate all cases from controls with near perfect accuracy at 98.3%. Simple viewing patterns can detect eye-movement abnormalities that can discriminate schizophrenia cases from control subjects with exceptional accuracy.Biological psychiatry 05/2012; 72(9):716-24. DOI:10.1016/j.biopsych.2012.04.019 · 8.93 Impact Factor
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ABSTRACT: Several definitions, measurements, and implicit meanings of 'fixation stability' have been used in clinical vision research, leading to some confusion. One definition concerns eye movements observed within fixations (i.e., within periods separated by saccades) when observing a point target: drift, microsaccades and physiological tremor all lead to some degree of within-fixation instability. A second definition relates to eye position during multiple fixations (and saccades) when patients fixate a point target. Increased between-fixation variability, combined with within-fixation instability, is known to be associated with poorer visual function in people with retinal disease such as age-related macular degeneration. In this review article, methods of eye stability measurement and quantification are summarised. Two common measures are described in detail: the bivariate contour ellipse area (BCEA) and the within-isolines area. The first measure assumes normality of the underlying positions distribution whereas the second does not. Each of these measures can be applied to two fundamentally different kinds of eye position data collected during a period of target observation. In the first case, mean positions of eye fixations are used to obtain an estimate of between-fixation variability. In the second case, often used in clinical vision research, eye position samples recorded by the eyetracker are used to obtain an estimate that confounds within- and between-fixation variability.We show that these two methods can produce significantly different values of eye stability, especially when reported as BCEA values. Statistical techniques for describing eye stability when the distribution of eye positions is multimodal and not normally distributed are also reviewed.Seeing and perceiving 02/2012; 25:449-469. DOI:10.1163/187847611X620955 · 1.14 Impact Factor