DECREASE OF COMPLEXITY IN EEG AS A SYMPTOM OF DEPRESSION

被引：67

作者：

NANDRINO, JL

PEZARD, L

MARTINERIE, J

ELMASSIOUI, F

RENAULT, B

JOUVENT, R

ALLILAIRE, JF

WIDLOCHER, D

机构：

[1] UNIV PARIS 06,LENA,UNITE PSYCHOPHYSIOL COGNIT,CNRS,URA 654,F-75651 PARIS 13,FRANCE

[2] HOP LA PITIE SALPETRIERE,UNITE PSYCHOBIOL TEMPERAMENTS RISQUE,CNRS,EP 53,F-75651 PARIS 13,FRANCE

[3] HOP LA PITIE SALPETRIERE,SERV PSYCHIAT ADULTES,F-75651 PARIS 13,FRANCE

来源：

NEUROREPORT | 1994年 / 5卷 / 04期

关键词：

DYNAMIC COMPLEXITY; DEPRESSION; ELECTROENCEPHALOGRAM; NONLINEAR FORECASTING; DYNAMIC SYSTEMS;

D O I：

10.1097/00001756-199401120-00042

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

NONLINEAR dynamic analysis provides new methods for the processing of the electroencephalogram (EEG). We demonstrate here that the EEG dynamics of major depressive subjects is more predictable, that is less complex, than that of control subjects. Moreover, the consequence of treatment upon the EEG dynamics seems to be dependent on the appearance of the illness. Although the specificity of this dynamic signature for different stages of depression is to be confirmed, the assumption of a strong link between a healthy system and a high level of complexity in dynamics is further supported.

引用

页码：528 / 530

页数：3

共 23 条

[1] SINGULAR-VALUE DECOMPOSITION AND THE GRASSBERGER-PROCACCIA ALGORITHM [J].