Virtual reality testing of multi-modal integration in schizophrenic patients.

Our goal is to develop a new family of automatic tools for the diagnosis of schizophrenia, using Virtual Reality Technology (VRT). VRT is specifically suitable for this purpose, because it allows for multi-modal stimulation in a complex setup, and the simultaneous measurement of multiple parameters. In this work we studied sensory integration within working memory, in a navigation task through a VR maze. Along the way subjects pass through multiple rooms that include three doors each, only one of which can be used to legally exit the room. Specifically, each door is characterized by three features (color, shape and sound), and only one combination of features -- as determined by a transient opening rule -- is legal. The opening rule changes over time. Subjects must learn the rule and use it for successful navigation throughout the maze. 39 schizophrenic patients and 21 healthy controls participated in this study. Upon completion, each subject was assigned a performance profile, including various error scores, response time, navigation ability and strategy. We developed a classification procedure based on the subjects' performance profile, which correctly predicted 85% of the schizophrenic patients (and all the controls). We observed that a number of parameters showed significant correlation with standard diagnosis scores (PANSS), suggesting the potential use of our measurements for future diagnosis of schizophrenia. On the other hand, our patients did not show unusual repetition of response despite stimulus cessation (called perseveration in classical studies of schizophrenia), which is usually considered a robust marker of the disease. Interestingly, this deficit only appeared in our study when subjects did not receive proper explanation of the task.