Resting electroencephalogram asymmetry and posttraumatic stress disorder

Network analysis of frontal lobe alpha asymmetry confirms the neurophysiological basis of four subtypes of depressive behavior

Introduction

Although depression is widespread carries a major disease burden, current treatments remain non-universally effective, arguably due to the heterogeneity of depression, and leading to the consideration of depressive "subtypes" or "depressive behavior subtypes." One such model of depressive behavior (DB) subtypes was investigated for its associations with frontal lobe asymmetry (FLA), using a different data analytic procedure than in previous research in this field.

Methods

100 community volunteers (54 males, 46 females) aged between 18 yr. and 75 years (M = 32.53 yr., SD = 14.13 yr) completed the Zung Self-rating Depression Scale (SDS) and underwent 15 min of eyes closed EEG resting data collection across 10 frontal lobe sites. DB subtypes were defined on the basis of previous research using the SDS, and alpha-wave (8-13 Hz) data produced an index of FLA. Data were examined via network analysis.

Results

Several network analyses were conducted, producing two models of the association between DB subtypes and FLA, confirming unique neurophysiological profiles for each of the four DB subtypes.

Discussion

As well as providing a firm basis for using these DB subtypes in clinical settings, these findings provide a reasonable explanation for the inconsistency in previous FLA-depression research.

EEG frontal lobe asymmetry as a function of sex, depression severity, and depression subtype

To investigate possible contributors to the inconsistent association between frontal lobe asymmetry (FLA) and depression, EEG data were collected across five frontal sites, and examined for their associations with four subtypes of depression (Depressed mood, Anhedonia, Cognitive depression, Somatic depression). One hundred community volunteers (54 males, 46 females) aged at least 18 yr completed standardized scales for depression and anxiety, and gave EEG data under Eyes Open and Eyes Closed conditions. Results indicated that, although there was no significant correlation between the differences in EEG power across each of the five pairs of frontal sites and total depression scores, there were several meaningful correlations (accounting for at least 10% of the variance) between specific EEG site differences data and each of the four depression subtypes. There were also different patterns of association between FLA and the depression subtypes according to sex, and total depression severity. These findings help to explain the apparent inconsistency in previous FLA-depression results, and argue for a more nuanced approach to this hypothesis.

Heart and brain traumatic stress biomarker analysis with and without machine learning: A scoping review

The enigma of post-traumatic stress disorder (PTSD) is embedded in a complex array of physiological responses to stressful situations that result in disruptions in arousal and cognitions that characterise the psychological disorder. Deciphering these physiological patterns is complex, which has seen the use of machine learning (ML) grow in popularity. However, it is unclear to what extent ML has been used with physiological data, specifically, the electroencephalogram (EEG) and electrocardiogram (ECG) to further understand the physiological responses associated with PTSD. To better understand the use of EEG and ECG biomarkers, with and without ML, a scoping review was undertaken. A total of 124 papers based on adult samples were identified comprising 19 ML studies involving EEG and ECG. A further 21 studies using EEG data, and 84 studies employing ECG meeting all other criteria but not employing ML were included for comparison. Identified studies indicate classical ML methodologies currently dominate EEG and ECG biomarkers research, with derived biomarkers holding clinically relevant diagnostic implications for PTSD. Discussion of the emerging trends, algorithms used and their success is provided, along with areas for future research.

Resting-state EEG functional connectivity predicts post-traumatic stress disorder subtypes in veterans

Objective. Post-traumatic stress disorder (PTSD) is highly heterogeneous, and identification of quantifiable biomarkers that could pave the way for targeted treatment remains a challenge. Most previous electroencephalography (EEG) studies on PTSD have been limited to specific handpicked features, and their findings have been highly variable and inconsistent. Therefore, to disentangle the role of promising EEG biomarkers, we developed a machine learning framework to investigate a wide range of commonly used EEG biomarkers in order to identify which features or combinations of features are capable of characterizing PTSD and potential subtypes.Approach. We recorded 5 min of eyes-closed and 5 min of eyes-open resting-state EEG from 202 combat-exposed veterans (53% with probable PTSD and 47% combat-exposed controls). Multiple spectral, temporal, and connectivity features were computed and logistic regression, random forest, and support vector machines with feature selection methods were employed to classify PTSD. To obtain robust results, we performed repeated two-layer cross-validation to test on an entirely unseen test set.Main results. Our classifiers obtained a balanced test accuracy of up to 62.9% for predicting PTSD patients. In addition, we identified two subtypes within PTSD: one where EEG patterns were similar to those of the combat-exposed controls, and another that were characterized by increased global functional connectivity. Our classifier obtained a balanced test accuracy of 79.4% when classifying this PTSD subtype from controls, a clear improvement compared to predicting the whole PTSD group. Interestingly, alpha connectivity in the dorsal and ventral attention network was particularly important for the prediction, and these connections were positively correlated with arousal symptom scores, a central symptom cluster of PTSD.Significance. Taken together, the novel framework presented here demonstrates how unsupervised subtyping can delineate heterogeneity and improve machine learning prediction of PTSD, and may pave the way for better identification of quantifiable biomarkers.

Translational relevance of behavioral, neural, and electroencephalographic profiles in a mouse model of post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a severe, long-term psychological disorder triggered by distressing events. The neural basis and underlying mechanisms of PTSD are not completely understood. Therefore, it is important to determine the pathology of PTSD using reliable animal models that mimic the symptoms of patients. However, the lack of evidence on the clinical relevance of PTSD animal models makes it difficult to interpret preclinical studies from a translational perspective. In this study, we performed a comprehensive screening of the behavioral, neuronal, glial, and electroencephalographic (EEG) profiles in the single prolonged stress and electric foot shock (SPS&S) mouse model. Based on the clinical features of PTSD, we observed fearful and excessive responses to trauma-related environments in the SPS&S mouse model that lasted longer than 14 days. The mice exhibited a defective and strong resistance to the extinction of fear memories caused by auditory cues and also showed enhanced innate fear induced by visual stimuli with concomitant phobias and anxiety. Furthermore, neurons, astrocytes, and microglia in PTSD-related brain regions were activated, supporting abnormal brain activation and neuroimmune changes. EEG assessment also revealed decreased power and impaired coupling strength between cortical regions. These results demonstrated that the SPS&S mouse model recapitulates the behavioral symptoms as well as neural and EEG profiles of PTSD patients, justifying the preclinical use of this mouse model.

Changes in Brain Electrical Activity According to Post-traumatic Stress Symptoms in Survivors of the Sewol Ferry Disaster: A 1-year Longitudinal Study

Objective

The pathology of post-traumatic stress disorder (PTSD) is associated with changes in brain structure and function, especially in the amygdala, medial prefrontal cortex, hippocampus, and insula. Survivors of tragic accidents often experience psychological stress and develop post-traumatic stress symptoms (PTSS), regardless of the diagnosis of PTSD. This study aimed to evaluate electroencephalographic changes according to PTSS in victims of a single traumatic event.

Methods

This study enrolled 60 survivors of the Sewol ferry disaster that occurred in 2014 from Danwon High School and collected electroencephalographic data through 19 channels twice for each person in 2014 and 2015 (mean 451.88 [standard deviation 25.77] days of follow-up). PTSS was assessed using the PTSD Checklist-Civilian Version (PCL-C) and the participants were divided into two groups according to the differences in PCL-C scores between 2014 and 2015. Electroencephalographic data were converted to three-dimensional data to perform low-resolution electrical tomographic analysis.

Results

Significant electroencephalographic changes over time were observed. The group of participants with worsened PCL-C score showed an increased change of delta slow waves in Brodmann areas 13 and 44, with the largest difference in the insula region, compared to those with improved PCL-C scores.

Conclusion

Our findings suggests that the electrophysiological changes in the insula are associated with PTSS changes.

EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities

Background:

A large body of evidence suggested that disruption of neural rhythms and synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes. Cognitive deficits are common features of psychiatric disorders that complicate treatment of the motivational, affective and emotional symptoms.

Objective:

Electrophysiological correlates of cognitive functions will contribute to understanding of neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and developing novel targets for the treatment of cognitive impairments.

Methods:

This review includes a description of brain oscillations in Alzheimer’s disease, bipolar disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders, anxiety disorders, schizophrenia and autism.

Results:

The review clearly shows that the reviewed neuropsychiatric diseases are associated with fundamental changes in both spectral power and coherence of EEG oscillations.

Conclusion:

In this article, we examined the nature of brain oscillations, the association of brain rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric disorders.

Biomarkers of Pathological Dissociation: A Systematic Review

Pathological dissociation is a severe, debilitating and transdiagnostic psychiatric symptom. This review identifies biomarkers of pathological dissociation in a transdiagnostic manner to recommend the most promising research and treatment pathways in support of the precision medicine framework. A total of 205 unique studies that met inclusion criteria were included. Studies were divided into four biomarker categories, namely neuroimaging, psychobiological, psychophysiological and genetic biomarkers. The dorsomedial and dorsolateral prefrontal cortex, bilateral superior frontal regions, (anterior) cingulate, posterior association areas and basal ganglia are identified as neurofunctional biomarkers of pathological dissociation and decreased hippocampal, basal ganglia and thalamic volumes as neurostructural biomarkers. Increased oxytocin and prolactin and decreased tumor necrosis factor alpha (TNF-α) are identified as psychobiological markers. Psychophysiological biomarkers, including blood pressure, heart rate and skin conductance, were inconclusive. For the genetic biomarker category studies related to dissociation were limited and no clear directionality of effect was found to warrant identification of a genetic biomarker. Recommendations for future research pathways and possible clinical applicability are provided.

Nervous and Endocrine System Dysfunction in Posttraumatic Stress Disorder: An Overview and Consideration of Sex as a Biological Variable

Decades of research into the biological mechanisms of posttraumatic stress disorder (PTSD) suggests that chronic activation of the stress response leads to long-lasting changes in the structure and function of the nervous and endocrine systems. While the prevalence of PTSD is twice as high in females as males, little is known about how sex differences in neuroendocrine systems may contribute to PTSD. In response to the paucity of research on sex-related mechanisms, the National Institutes of Health created a policy that asks researchers to consider sex as a biological variable. This review provides an overview of the current understanding of nervous and endocrine dysfunction in PTSD (e.g., neural circuitry, autonomic arousal, hormonal response), highlighting areas where the influence of sex has been characterized and where further research is needed. We also provide recommendations for using the sex-as-a-biological-variable policy to address specific gaps in PTSD neuroscience research.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

The Electrical Aftermath: Brain Signals of Posttraumatic Stress Disorder Filtered Through a Clinical Lens

This review aims to identify patterns of electrical signals identified using electroencephalography (EEG) linked to posttraumatic stress disorder (PTSD) diagnosis and symptom dimensions. We filter EEG findings through a clinical lens, evaluating nuances in findings according to study criteria and participant characteristics. Within the EEG frequency domain, greater right than left parietal asymmetry in alpha band power is the most promising marker of PTSD symptoms and is linked to exaggerated physiological arousal that may impair filtering of environmental distractors. The most consistent findings within the EEG time domain focused on event related potentials (ERPs) include: 1) exaggerated frontocentral responses (contingent negative variation, mismatch negativity, and P3a amplitudes) to task-irrelevant distractors, and 2) attenuated parietal responses (P3b amplitudes) to task-relevant target stimuli. These findings suggest that some individuals with PTSD suffer from attention dysregulation, which could contribute to problems concentrating on daily tasks and goals in lieu of threatening distractors. Future research investigating the utility of alpha asymmetry and frontoparietal ERPs as diagnostic and predictive biomarkers or intervention targets are recommended.

EEG in psychiatric practice: to do or not to do?

Electroencephalography (EEG) is a non-invasive investigation that can aid the diagnosis of psychiatric and neuropsychiatric disorders. A good predictor of an abnormal EEG recording is the presence of an organic factor identified during the clinical assessment. The non-invasiveness and low cost of the procedure and its ability to measure spontaneous brain activity appear to attract clinicians to utilise this investigative tool. However, studies have reported that EEGs arising from psychiatric referrals have the lowest abnormality detection rate. The focus of this article is to improve this by highlighting the current pitfalls and providing recommendations for appropriate utilisation of EEG. We describe specific EEG changes associated with major psychiatric disorders. We conclude by offering pragmatic considerations when referring a patient for EEG, emphasising the fact that the information provided to the neurophysiologist plays a crucial role in interpreting the EEG recording in a diagnostically meaningful way.

The Relationship between Exposure to Missiles and PTSD Symptoms as a Function of Hemispheric Preference in Israelis

Recent research proposes that left hemispheric lateralization (HL) may protect against the effects of life events on mental distress. This study extends these findings by examining the protective role of left HL in the relationship between war threat (missile exposure) and PTSD symptoms. A sample of 186 Israelis, exposed to missile attacks, completed brief scales of self-reported missile exposure, a subjective and a neuropsychological HL measure, and of PTSD symptoms. The sample was split into right HL and left HL individuals on both HL measures. Self-reported missile exposure was positively associated with PTSD symptoms in right HL, but not in left HL individuals on both HL measures. These results replicate, extend our previous results and suggest that left HL may even protect against the effects of severe life threatening events. Results are discussed in relation to neuropsychological and neurophysiological differences between the hemispheres.

The effects of gender and depression severity on the association between alpha asymmetry and depression across four brain regions

Data describing the association between EEG asymmetry and depression status have been equivocal. Effects from brain regions involved, depression severity, and the generalisability of findings across genders, have been inconsistently examined and/or verified. This study investigated these issues within a community sample to potentially expand the asymmetry hypothesis to non-severe depression participants. The singular effects of brain region and electrode site, gender, and depression severity, plus the interaction between gender and depression severity across brain regions were investigated in a study of alpha asymmetry among 46 males and 54 females (M age=32.5 yr, SD=14.13 yr) using the Self-rating Depression Scale (Zung, 1973). There was no significant difference across genders or age for depression severity. Dichotomous classification of depressed state produced similar but slightly different results from analysis of the whole range of depression status, although the frontal region was the only area where depression was consistently significantly associated with EEG asymmetry, and then only for females. However, the direction of those differences for females was opposite of that predicted by the EEG asymmetry-depression hypothesis. Several methodological issues that may have contributed to these findings are discussed, with suggestions made for future research that focusses upon individual depression symptom profiles rather than dichotomous or total depression scores in order to assist in developing a clinically-relevant model of EEG asymmetry in depressed persons.

Alpha oscillations and their impairment in affective and post-traumatic stress disorders

Affective and anxiety disorders are debilitating conditions characterized by impairments in cognitive and social functioning. Elucidating their neural underpinnings may assist in improving diagnosis and developing targeted interventions. Neural oscillations are fundamental for brain functioning. Specifically, oscillations in the alpha frequency range (alpha rhythms) are prevalent in the awake, conscious brain and play an important role in supporting perceptual, cognitive, and social processes. We review studies utilizing various alpha power measurements to assess abnormalities in brain functioning in affective and anxiety disorders as well as obsessive compulsive and post-traumatic stress disorders. Despite some inconsistencies, studies demonstrate associations between aberrant alpha patterns and these disorders both in response to specific cognitive and emotional tasks and during a resting state. We conclude by discussing methodological considerations and future directions, and underscore the need for much further research on the role of alpha functionality in social contexts. As social dysfunction accompanies most psychiatric conditions, research on alpha's involvement in social processes may provide a unique window into the neural mechanisms underlying these disorders.

EEG correlates of the severity of posttraumatic stress symptoms: A systematic review of the dimensional PTSD literature

BACKGROUND

Considering the Research Domain Criteria (RDoC) framework, it is crucial to investigate posttraumatic stress disorder (PTSD) as a spectrum that ranges from normal to pathological. This dimensional approach is especially important to aid early PTSD detection and to guide better treatment options. In recent years, electroencephalography (EEG) has been used to investigate PTSD; however, reviews regarding EEG data related to PTSD are lacking, especially considering the dimensional approach. This systematic review examined the literature regarding EEG alterations in trauma-exposed people with posttraumatic stress symptoms (PTSS) to identify putative EEG biomarkers of PTSS severity.

METHOD

A systematic review of EEG studies of trauma-exposed participants with PTSS that reported dimensional analyses (e.g., correlations or regressions) between PTSS and EEG measures was performed.

RESULTS

The literature search yielded 1178 references, of which 34 studies were eligible for inclusion. Despite variability among the reviewed studies, the PTSS severity was often associated with P2, P3-family event-related potentials (ERPs) and alpha rhythms.

LIMITATIONS

The search was limited to articles published in English; no information about non-published studies or studies reported in other languages was obtained. Another limitation was the heterogeneity of studies, which made meta-analysis challenging.

CONCLUSIONS

EEG provides promising candidates to act as biomarkers, although further studies are required to confirm the findings. Thus, EEG, in addition to being cheaper and easier to implement than other central techniques, has the potential to reveal biomarkers of PTSS severity.

The role of frontal EEG asymmetry in post-traumatic stress disorder

Frontal alpha asymmetry, a biomarker derived from electroencephalography (EEG) recordings, has often been associated with psychological adjustment, with more left-sided frontal activity predicting approach motivation and lower levels of depression and anxiety. This suggests high relevance to post-traumatic stress disorder (PTSD), a disorder comprising anxiety and dysphoria symptoms. We review this relationship and show that frontal asymmetry can be plausibly linked to neuropsychological abnormalities seen in PTSD. However, surprisingly few studies (k = 8) have directly addressed frontal asymmetry in PTSD, mostly reporting that trait frontal asymmetry has little (if any) predictive value. Meanwhile, preliminary evidence suggest that state-dependent asymmetry during trauma-relevant stimulation distinguishes PTSD patients from resilient individuals. Thus, exploring links between provocation-induced EEG asymmetry and PTSD appears particularly promising. Additionally, we recommend more fine-grained analyses into PTSD symptom clusters in relation to frontal asymmetry. Finally, we highlight hypotheses that may guide future research and help to fully apprehend the practical and theoretical relevance of this biological marker.

Peak high-frequency HRV and peak alpha frequency higher in PTSD

Posttraumatic stress disorder (PTSD) is difficult to treat and current PTSD treatments are not effective for all people. Despite limited evidence for its efficacy, some clinicians have implemented biofeedback for PTSD treatment. As a first step in constructing an effective biofeedback treatment program, we assessed respiration, electroencephalography (EEG) and heart rate variability (HRV) as potential biofeedback parameters for a future clinical trial. This cross-sectional study included 86 veterans; 59 with and 27 without PTSD. Data were collected on EEG measures, HRV, and respiration rate during an attentive resting state. Measures were analyzed to assess sensitivity to PTSD status and the relationship to PTSD symptoms. Peak alpha frequency was higher in the PTSD group (F(1,84) = 6.14, p = 0.01). Peak high-frequency HRV was lower in the PTSD group (F(2,78) = 26.5, p < 0.00005) when adjusting for respiration rate. All other EEG and HRV measures and respiration were not different between groups. Peak high-frequency HRV and peak alpha frequency are sensitive to PTSD status and may be potential biofeedback parameters for future PTSD clinical trials.

Childhood abuse and EEG source localization in crack cocaine dependence

Fourteen subjects with histories of sexual and/or physical abuse in childhood and 13 matched control subjects were selected from a consecutive series of clients in residential treatment for crack cocaine dependence. Standardized low-resolution electromagnetic brain tomography (sLORETA) was used to estimate the source generators of the EEG in a cortical mask with voxel z-scores referenced to normative data at frequency intervals of 039 Hz, with nonparametric permutation to correct by randomization for the number of comparisons and the intercorrelations and variance of distribution of voxel values. Subjects with histories of abuse in childhood had significantly greater EEG power than controls in the theta frequency range (3.51-7.41 Hz), with greatest differences in the 3.90-Hz band distributed mainly in the parahippocampal, fusiform, lingual, posterior cingulate, and insular gyri. The groups did not differ significantly with regard to delta (1.56-3.12 Hz), alpha (7.81-12.48 Hz), beta (12.87-19.89 Hz), and gamma (20.28-35.10 Hz) frequency power. In excess, theta EEG power, a bandwidth of transactions among hippocampus and amygdala and paralimbic and visual association cortex, may be a correlate of childhood exposure to abuse.

The quantitative electroencephalogram and the low-resolution electrical tomographic analysis in posttraumatic stress disorder

The electroencephalogram (EEG) is the recording of the brain electrical activity as measured on the scalp. Using mathematical algorithms, the 3-dimensional (3D) distribution of the electrical potential inside the brain can be calculated. One of the methods to calculate it is the low-resolution electrical tomographic analysis (LORETA). In this research, we seek to find the brain structures that differentiate patients with posttraumatic stress disorder (PTSD) from controls. Ten right-handed consenting adult male patients were recruited from a PTSD clinic. All patients fulfilled Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision [DSM-IV-TR]) criteria for chronic PTSD (duration >2 years.) and were on drug treatment regimens that had been stable for at least 2 months (involving only serotonin reuptake inhibitors [SSRIs] and benzodiazepines).The control group consisted of 10 healthy hospital staff members. All study participants underwent 19 channel EEG measurements according to current standards of practice. All artifact-free EEG strips were examined for spectral as well as LORETA analysis focusing on the theta (4-7 Hz) band which is suggested to reflect the activity of the limbic system. The theta band showed a statistically significant difference (P < .05) between the 2 groups in the right temporal lobe and in both the right and left frontal lobes. Our findings support existing research data obtained via other imaging technologies, which demonstrated structural alterations in the right temporal and frontal areas in PTSD. These results indicate that combining quantitative EEG (QEEG) and the LORETA method, among other methods, may improve the neuroanatomical resolution of EEG data analysis.

Lateralized abnormalities in auditory M50 sensory gating and cortical thickness of the superior temporal gyrus in post-traumatic stress disorder: preliminary results

Auditory sensory gating deficits have been reported in subjects with post-traumatic stress disorder (PTSD), but the hemispheric and neuronal origins of this deficit are not well understood. The objectives of this study were to: (1) investigate auditory sensory gating of the 50-ms response (M50) in patients diagnosed with PTSD by utilizing magnetoencephalography (MEG); (2) explore the relationship between M50 sensory gating and cortical thickness of the superior temporal gyrus (STG) measured with structural magnetic resonance imaging (MRI); and (3) examine the association between PTSD symptomatology and bilateral sensory gating. Seven participants with combat-related PTSD and eleven controls underwent the paired-click sensory gating paradigm. MEG localized M50 neuronal generators to the STG in both groups. The PTSD group displayed impaired M50 gating in the right hemisphere. Thinner right STG cortical thickness was associated with worse right sensory gating in the PTSD group. The right S1 M50 source strength and gating ratio were correlated with PTSD symptomatology. These findings suggest that the structural integrity of right hemisphere STG cortices play an important role in auditory sensory gating deficits in PTSD.

Pure-tone auditory thresholds are decreased in depressed people with post-traumatic stress disorder

BACKGROUND

Depression has been related to sensory modulation and notably to auditory modifications such as alterations in auditory event-related potentials, abnormal patterns of auditory habituation, increased activation of primary and secondary auditory cortex, and higher bilateral auditory thresholds. However, few experiments have considered the exploration of the auditory system in depression. The aim of the experiment is to further explore auditory thresholds across a higher number of frequencies than has previously been undertaken in depressed subjects, to determine whether thresholds are modified as compared to controls, and if so, at which frequencies.

METHODS

25 pure-tones covering a large range of frequencies from 125Hz to 8kHz were used to measure both air and bone conduction (AC and BC respectively) hearing thresholds. 13 patients with depression and post-traumatic disorder matched for age, sex and education level with 13 healthy subjects, were tested.

RESULTS

Hearing thresholds were found to be significantly poorer in depressed participants than in controls for frequencies from 2.75Hz to 8kHz in BC, and for 0.5, 0.75, 0.875 and 2.0-8.0kHz pure-tone frequencies in AC.

LIMITATIONS

Given that the depressed patients also had comorbid post-traumatic disorder, it should be verified whether their modified pure-tone audiometry is only related to depression.

CONCLUSIONS

The AC and BC pure-tone auditory threshold measurement may provide new and different insights into the aetiology and evolution of depression.

Dysfunctions of cortical excitability in drug-naïve posttraumatic stress disorder patients

BACKGROUND

The investigation of a wide set of transcranial magnetic stimulation (TMS)-related variables in both hemispheres might help to identify a pattern of cortical excitability changes in posttraumatic stress disorder (PTSD) patients, reflecting gamma-amino-butiric acid (GABA)/glutamate balance and dysfunction, and to determine whether some of these variables are related to clinical features.

METHODS

In 20 drug-naive PTSD patients without comorbidity and 16 matched healthy control subjects we tested bilaterally with standard TMS procedures: resting motor threshold (RMT) to single-pulse TMS (reflecting ion channel function), paired-pulse short-latency intracortical inhibition (SICI; mainly reflecting GABA(A) function) and intracortical facilitation (ICF; mainly reflecting glutamatergic function), single-pulse cortical silent period (CSP; mainly reflecting GABA(B)-ergic function), and paired-pulse short-latency afferent inhibition (SAI; reflecting cholinergic mechanisms and their presynaptic GABA(A)-mediated modulation).

RESULTS

The PTSD patients showed widespread impairment of GABA(A)-ergic SICI, which was reversed toward facilitation in both hemispheres in one-half of the patients, marked increase of glutamatergic ICF in the right hemisphere, and right-sided impairment of SAI. Illness duration and avoidance symptoms but not anxiety correlated with right-lateralized dysfunctions of cortical excitability.

CONCLUSIONS

Although the neurobiological complexity of each TMS variable makes current results theoretical, the pattern of cortical excitability accompanying PTSD symptoms suggests a bilateral decrease of the GABA(A)-ergic function. This prevails in the right hemisphere, in association with a relative prevalence of the glutamatergic tone, a new finding that current neuroimaging investigations cannot provide due to the lack of reliable glutamate tracers. Results might help to disclose new pathophysiological aspects of PTSD symptoms, providing a rationale for future neuromodulatory strategies of treatment.

Genetic and environmental influences on frontal EEG asymmetry and alpha power in 9-10-year-old twins

Modest genetic influences on frontal EEG asymmetry have been found in adults, but little is known about its genetic origins in children. Resting frontal asymmetry and alpha power were examined in 951 9-10-year-old twins. Results showed that in both males and females: (1) a modest but significant amount of variance in frontal asymmetry was accounted for by genetic factors (11-28%) with the remainder accounted for by non-shared environmental influences, and (2) alpha power were highly heritable, with 71-85% of the variance accounted for by genetic factors. Results suggest that the genetic architecture of frontal asymmetry and alpha power in late childhood are similar to that in adulthood and that the high non-shared environmental influences on frontal asymmetry may reflect environmentally influenced individual differences in the maturation of frontal cortex as well as state-dependent influences on specific measurements.

Evidence-based medicine evaluation of electrophysiological studies of the anxiety disorders

We provide a systematic, evidence-based medicine (EBM) review of the field of electrophysiology in the anxiety disorders. Presently, electrophysiological studies of anxiety focus primarily on etiological aspects of brain dysfunction. The review highlights many functional similarities across studies, but also identifies patterns that clearly differentiate disorder classifications. Such measures offer clinical utility as reliable and objective indicators of brain dysfunction in individuals and indicate potential as biomarkers for the improvement of diagnostic specificity and for informing treatment decisions and prognostic assessments. Common to most of the anxiety disorders is basal instability in cortical arousal, as reflected in measures of quantitative electroencephalography (qEEG). Resting electroencephalographic (EEG) measures tend to correlate with symptom sub-patterns and be exacerbated by condition-specific stimulation. Also common to most of the anxiety disorders are condition-specific difficulties with sensory gating and the allocation and deployment of attention. These are clearly evident from evoked potential (EP) and event-related potential (ERP) electrical measures of information processing in obsessive compulsive disorder (OCD), post-traumatic stress disorder (PTSD), panic disorder (PD), generalized anxiety disorder (GAD) and the phobias. Other'ERP measures clearly differentiate the disorders. However, there is considerable variation across studies, with inclusion and exclusion criteria, medication status and control group selection not standardized within condition or across studies. Study numbers generally preclude analysis for confound removal or for the derivation of diagnostic biomarker patterns at this time. The current trend towards development of databases of brain and cognitive function is likely to obviate these difficulties. In particular, electrophysiological measures of function are likely to play a significant role in the development and subsequent adaptations of DSM-V and assist critically in securing improvements in nosological and treatment specificity.