Comparing EEG Nonlinearity in Deficit and Nondeficit Schizophrenia Patients: Preliminary Data
Recommended Citation
Cerquera A, Gjini K, Bowyer SM, and Boutros N. Comparing EEG nonlinearity in deficit and nondeficit schizophrenia patients: Preliminary data. Clin EEG Neurosci 2017: 48(6):376-382.
Document Type
Article
Publication Date
11-1-2017
Publication Title
Clinical EEG and neuroscience : official journal of the EEG and Clinical Neuroscience Society (ENCS)
Abstract
Electroencephalogram (EEG) contains valuable information obtained noninvasively that can be used for assessment of brain's processing capacity of patients with psychiatric disorders. The purpose of the present work was to evaluate possible differences in EEG complexity between deficit (DS) and nondeficit (NDS) subtypes of schizophrenia as a reflection of the cognitive processing capacities in these groups. A particular nonlinear metric known as Lempel-Ziv complexity (LZC) was used as a computational tool in order to determine the randomness in EEG alpha band time series from 3 groups (deficit schizophrenia [n = 9], nondeficit schizophrenia [n = 10], and healthy controls [n = 10]) according to time series randomness. There was a significant difference in frontal EEG complexity between the DS and NDS subgroups ( p = .013), with DS group showing less complexity. A significant positive correlation was found between LZC values and Positive and Negative Syndrome Scale (PANSS) general psychopathology scores (ie, larger frontal EEG complexity correlated with more severe psychopathology), explained partially by the emotional component subscore of the PANSS. These findings suggest that cognitive processing occurring in the frontal networks in DS is less complex compared to NDS patients as reflected by EEG complexity measures. The data also suggest that there may be a relationship between the degree of emotionality and the complexity of the frontal EEG signal.
Medical Subject Headings
Adult; Brain; Electroencephalography; Emotions; Female; Humans; Male; Middle Aged; Nerve Net; Schizophrenia; Transcranial Magnetic Stimulation
PubMed ID
28618836
Volume
48
Issue
6
First Page
376
Last Page
382