POST-TRAUMATIC STRESS DISORDER (PTSD) is a psychiatric disorder that may develop after an extremely traumatic psychological event such as combat experience, car accidents or sexual abuse. The major PTSD symptoms include loss of memory, recurrent intrusive thoughts or images, excessively high levels of anxiety, depression, and nightmares. Thus, PTSD patients re-experience the life-threatening events through repeated memories, dreams, flashbacks and/or exposure to a similar situation. It is reported that approximately 3.5% of adults aged ≥18 years – approximately 7.7 million people in the USA – suffer from PTSD.1
Many studies have now shown the seriousness of PTSD and demonstrated physiological etiologies in the cerebra of those suffering from PTSD. For example, there have been extensive studies showing volumetric and metabolic alterations in the brains of PTSD patients, particularly in the hippocampus and the anterior cingulate gyrus.2–9 These studies reported a decrease in hippocampal volume.2–4,10 Also, studies on metabolic rates have reported decreased N-acetylaspartate/creatine (NAA/Cr) ratio and increased choline/creatine (Cho/Cr) ratio in the bilateral hippocampus, as well as reductions in the NAA/Cr ratio in the anterior cingulate gyrus.8,9
A few spatiotemporal dynamic studies on PTSD have been performed. EEG analysis of PTSD patients recently indicated diverse features: increased theta activity over the central regions, increased beta activity over the frontal, central and left occipital regions,11 decreased alpha power in overall regions,12 and increased gamma activity in the frontal region.13 Functional connectivity studies using coherence measures on PTSD are even less common. Metzger et al. found increased right-sided parietal activation in association with PTSD arousal symptoms.14 Enhanced right anterior and posterior activation has also been reported in PTSD patients.15
Although abnormalities of functional connectivity have been found in patients with PTSD, the connection regions and properties are not consistent across the experiments and analyses. In addition, most of the studies on functional connectivity are based on volumetric and metabolic imaging of PTSD patients, but few studies have been done using electroencephalograms (EEG). Recently, our group showed that the dimensional complexity of the EEG in PTSD patients was lower than that of normal individuals, indicating that PTSD patients have globally reduced complexity in their EEG waveforms.16 This suggests that PTSD patients might exhibit abnormal functional integrations, because the dimensional complexity of the EEG reflects the functional integration between different cortical regions.
Therefore, the primary aim of the present study was to investigate abnormalities in functional connectivity of cortical networks in PTSD based on the EEG. The specific aims of the present study were (i) to assess if there is any abnormality in functional connectivity among different cortical regions in PTSD patients compared with normal subjects; (ii) to estimate the non-linearity in functional connectivity in PTSD; and (iii) to measure the direction of information transmission between different cortical regions in PTSD in a resting state condition using non-linear interdependence (NI).
Several non-linear multivariate measures for EEG have been proposed and used to quantify non-linear information transmission among cortical regions such as mutual information, phase synchronization, and NI. While cross-correlation measures linear dependence between two time series, these non-linear measures also estimate both linear and non-linear dependence between two time series. The non-linear measures have been applied to the EEG in patients with neuropsychiatric disorders. They have shown abnormalities in non-linear information transmission among cortical regions, which cannot be detected by linear measures such as cross-correlation. Mutual information has been applied, as a non-linear information transmission measure, to EEG in Alzheimer's disease and has demonstrated reduced information transmission among interhemispheric regions.17 Mutual information has also been applied to the EEG in schizophrenia18 and in sleep deprivation.19 Synchronization likelihood, another non-linear measure, was also applied to EEG in mild cognition impairment (MCI) and Alzheimer's disease,20–24 epileptic seizures25,26 and schizophrenia.27 They showed abnormal information flow patterns in these disorders.
Particularly, NI is a significant measure of the degree of both linear and non-linear information transmission between two time series. In addition, NI is capable of providing information as to the direction of information flow between two regions that generate time series.28 NI has been used to investigate the relationships between EEG signals recorded from epileptogenic areas, and has identified the proper spatiotemporal organization of the seizures of medial temporal lobe origin.29 A dysregulation in the organization of dynamic interactions across supra-regional brain systems was found in schizophrenia, including larger concurrent clusters of NI across the scalp, and stronger disturbance in left intrahemispheric coupling.30