Chaos in schizophrenia associations, reality or metaphor?

被引:10
作者
Bob, Petr [1 ,2 ,3 ]
Susta, Marek [1 ,2 ,3 ]
Chladek, Jan [4 ]
Glaslova, Katerina [3 ]
Palus, Milan [1 ,2 ,5 ]
机构
[1] Charles Univ Prague, Dept Psychiat, Fac Med 1, Ke Karlovu 11, Prague 12800, Czech Republic
[2] Charles Univ Prague, UHSL, Fac Med 1, Prague 12800, Czech Republic
[3] Ctr Neuropsychiat Res Traumat Stress, Prague, Czech Republic
[4] Acad Sci Czech Republic, Inst Sci Instruments, CS-61264 Brno, Czech Republic
[5] Acad Sci Czech Republic, Inst Comp Sci, Prague, Czech Republic
关键词
Chaos; Schizophrenia; Associations; Electrodermal activity; Lyapunov exponent; ELECTRODERMAL ACTIVITY; THOUGHT-DISORDER; BRAIN; MODEL; NEUROSCIENCE; DYSFUNCTION; RESPONSES; DYNAMICS; REPRESENTATION; OSCILLATIONS;
D O I
10.1016/j.ijpsycho.2008.12.013
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
There is evidence that schizophrenic associations display "chaotic", random-like behavior and decreased predictability. The evidence suggests a hypothesis that the "chaotic" mental disorganization could be explained within the concept of nonlinear dynamics and complexity in the brain that may cause chaotic neural organization. Testing of the hypothesis in the present study was performed using nonlinear analysis of bilateral electrodermal activity (EDA) during resting state and an association test in 56 schizophrenic patients and 44 healthy participants. EDA is a suitable measure of brain and autonomic activity reflecting neurobiological changes in schizophrenia that may indicate changes in nonlinear neural dynamics related to associative process. The results show that quantitative indices of chaotic dynamics (the largest Lyapunov exponents) calculated from EDA signals recorded during rest and the association test are significantly higher in schizophrenia patients than in the control group and increase during the test in comparison to the resting state. The difference was confirmed by statistical methods and using surrogate data testing that rejected an explanation within the linear statistical framework. The results provide supportive evidence that pseudorandomness of schizophrenic associations and less predictability could be linked to increased complexity of nonlinear neural dynamics, although certain limitations in data interpretation must be taken into account. (c) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:179 / 185
页数:7
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