EEG studies of sleep in the diagnosis of depression

Psychiatric diagnoses have traditionally been made on the basis of clinical criteria, including current phenomenology and historical information. This traditional procedure presents several problems, including standardization of data gathering and interpretation. Biological criteria have been shown to be useful aids to diagnosis, but the same problems of standardization must be overcome. We present here the derivation of discriminant functions (DFs) using sleep EEG data to separate depressed from normal subjects. More important, we have cross-validated these DFs in a separate group of patients, using them to separate endogenous (ED) from nonendogenous depressed (ND) patients. ADF using the sleep variables REM latency and REM density can make this discrimination with sensitivity = 0.61 and specificity = 0.93. We also present our preliminary findings in support of the earlier conclusion that the sleep of unipolar ED patients is more disturbed than that of bipolar ED patients.