Schizophrenia (SCZ), bipolar disorder (BP), and depression (DEP) are systematically associated with a severe impairment of the overall abilities of patients, which precludes them from functioning adequately in daily life. A large body of literature emphasises the importance of identifying specific markers for these pathologies to prevent or anticipate the emergence of new psychopathological symptoms. As a result, one of the current research challenges is to develop new, faster, and more reliable tools. Eye movements are physiological signs involving brain areas that control cognitive processes. These same processes could be altered in psychiatric disorders, and these alterations could produce many eye movement abnormalities. The literature highlights some eye movement abnormalities specific to each targeted pathology. However, to our knowledge, no study has compared eye movement abnormalities in a virtual environment projected in a head-mounted display (HMD). The investigators hypothesised that an eye tracker connected to an HMD could identify specific eye movement abnormalities of SCZ, BP, and DEP. Recording eye movements specific to these pathologies in pseudo-ecological situations could lead to better identification methods.
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Record dwell time (millisecond) and saccadic parameters (millisecond and degree) using an eye-tracker connected to a virtual reality HMD. Then, compare each measure to identify schizophrenia, bipolar, depression and control group differences.
Timeframe: 90 minutes