Figure 1.

Probing the basis of a psychiatric disorder at multiple levels. Schematic of how psychological, genetic, neurobiological and epidemiological observations can be used to automatically learn the difference between healthy individuals and affected patients. For each type of measurement (e.g., attention test scores), a learning algorithm is trained on part of the data and subsequently evaluated on remaining test data from independent individuals to obtain prediction performance estimates (50% accuracy corresponds to random guessing). The statistical uncertainty of the prediction accuracies is shown by 95% confidence intervals obtained from bootstrap resampling of data points with replacement.