title: Simple viewing tests can detect eye movement abnormalities that distinguish schizophrenia cases from controls with exceptional accuracy.
abstract: BACKGROUND
  We have investigated which eye-movement tests alone and combined can best discriminate schizophrenia cases from control subjects and their predictive validity.
  
  
  METHODS
  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.
  
  
  RESULTS
  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%.
  
  
  CONCLUSIONS
  Simple viewing patterns can detect eye-movement abnormalities that can discriminate schizophrenia cases from control subjects with exceptional accuracy.
authors.affiliation: School of Psychology, King's College, University of Aberdeen, Aberdeen, United Kingdom. philip.benson@abdn.ac.uk
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Benson
authors.forename: Sara A
authors.initials: SA
authors.lastname: Beedie
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Shephard
authors.forename: Ina
authors.initials: I
authors.lastname: Giegling
authors.forename: Dan
authors.initials: D
authors.lastname: Rujescu
authors.forename: David
authors.initials: D
authors.lastname: St Clair
mesh_terms: D000328:Adult; D016022:Case-Control Studies; D005133:Eye Movements / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009483:Neuropsychological Tests / Q000706:statistics & numerical data; D015835:Ocular Motility Disorders / Q000150:complications / Q000503:physiopathology*; D011237:Predictive Value of Tests; D012559:Schizophrenia / Q000150:complications / Q000175:diagnosis / Q000503:physiopathology*; D012907:Smoking / Q000503:physiopathology; D013997:Time Factors