Electroencephalogram abnormalities in panic disorder patients: a study of symptom characteristics and pathology

Abnormal Electroencephalogram Findings and Its Correlation With Clinical Features From Pediatric Patients in Psychiatric Clinic

Objective: We aimed to evaluate the occurrence of electroencephalogram (EEG) abnormalities in pediatric patients attending an outpatient psychiatry clinic at a tertiary center. We examined the rates of abnormalities and specific findings based on demographics, specific diagnoses, and clinical severity. Methods: This study included pediatric patients who underwent EEG at the outpatient psychiatry clinic. Patient demographics, psychiatric diagnosis, intellectual disability, intelligent quotient (IQ) score, family history of psychiatric disorders, and Clinical Global Impression-Severity (CGI-S) score were obtained through retrospective electronic health record analysis. The rate of EEG abnormalities was calculated, and specific abnormal findings were reviewed. Relationships between the rate of EEG abnormalities and diagnosis, severity, IQ, and age at EEG examination were analyzed. Results: Of 319 patients who underwent EEG, 21.3% (68 patients) of patients exhibited abnormalities, including background abnormalities (14.7%, 47 patients), interictal epileptiform discharges (IEDs) (10.3%, 33 patients), and a slow posterior dominant rhythm (3.8%, 10 patients). The frontal region was the most commonly affected area. Neurodevelopmental disorders (NDDs) had the most frequent abnormalities (29.8%), followed by anxiety (16.7%), sleep (14.3%), mood (11.7%), psychotic (5%), and conduct disorders (0%). Disease severity did not correlate with the rate of EEG abnormalities. Adjusted for age, sex, severity, and family history, patients with EEG abnormalities exhibited lower IQ scores. Conclusion: EEG abnormalities were common in pediatric patients with psychiatric disorders, with background abnormalities detected as frequently as IEDs. Disease severity was not associated with EEG abnormality, while IQ scores showed a negative correlation.

The Computer Simulation for Triggering Anxiety in Panic Disorder Patients Modulates the EEG Alpha Power during an Oddball Task

Aim: The present study investigated the differences between the Panic Disorder (PD) patients groups’ and healthy controls for the EEG alpha dynamics under the frontal cortex and reaction time during the oddball task. Material and Methods: The reaction time during the oddball paradigm concomitant to EEG alpha power was tested in nine PD patients and ten healthy controls before and after a computer simulation presentation. Results: The findings revealed a decrease in EEG alpha power in PD patients concerning the control group (p ≤ 0.0125). However, both groups demonstrated an increased cortical oscillation after the computer simulation, except for the Fp1 electrode during M3 moment in the experimental group. The experimental group has a fast reaction time compared to healthy individuals during the oddball task (p = 0.002). Conclusions: We propose that the decrease in EEG alpha power in the PD patients may indicate an increase in processing related to an anxiogenic stimulus and interference of the anxiety state that compromises the inhibitory control. The reaction time task reveals cognitive symptoms in the experimental group, which may be related to the faster reactivity and high impulsivity to stimuli.

Isolated epileptiform activity in children and adolescents: prevalence, relevance, and implications for treatment

In the field of psychiatry diagnoses are primarily based on the report of symptoms from either the patient, parents, or both, and a psychiatrist's observations. A psychiatric diagnosis is currently the most widely used basis for medication selection and the brain is seldom investigated directly as a source of those symptoms. This study addresses the request from the National Institute of Mental Health (NIMH) Research Domain Criteria Project (RDoC) for scientific research into neurological abnormalities that can be linked to psychiatric symptoms for the purpose of predicting medication response. One such neurological abnormality that has been the focus of many studies over the last three decades is isolated epileptiform discharges (IEDs) in children and adolescents without seizures. We conducted a systematic review of the literature to determine prevalence rates of IEDs within diagnostic categories. We then compared the prevalence of IEDs in the selected literature to our IRB-approved data archive. Our study found a consistent high prevalence of IEDs specifically for ADHD (majority > 25%) and ASD (majority > 59%), and consistent low prevalence rates were found for Depression (3%). If children and adolescents have failed multiple medication attempts, and more than one-third of them have IEDs, then an EEG would be justified within the RDoC paradigm.

Panic attack prediction using wearable devices and machine learning: Development and cohort study (Preprint)

Background

A panic attack (PA) is an intense form of anxiety accompanied by multiple somatic presentations, leading to frequent emergency department visits and impairing the quality of life. A prediction model for PAs could help clinicians and patients monitor, control, and carry out early intervention for recurrent PAs, enabling more personalized treatment for panic disorder (PD).

Objective

This study aims to provide a 7-day PA prediction model and determine the relationship between a future PA and various features, including physiological factors, anxiety and depressive factors, and the air quality index (AQI).

Methods

We enrolled 59 participants with PD (Diagnostic and Statistical Manual of Mental Disorders, 5th edition, and the Mini International Neuropsychiatric Interview). Participants used smartwatches (Garmin Vívosmart 4) and mobile apps to collect their sleep, heart rate (HR), activity level, anxiety, and depression scores (Beck Depression Inventory [BDI], Beck Anxiety Inventory [BAI], State-Trait Anxiety Inventory state anxiety [STAI-S], State-Trait Anxiety Inventory trait anxiety [STAI-T], and Panic Disorder Severity Scale Self-Report) in their real life for a duration of 1 year. We also included AQIs from open data. To analyze these data, our team used 6 machine learning methods: random forests, decision trees, linear discriminant analysis, adaptive boosting, extreme gradient boosting, and regularized greedy forests.

Results

For 7-day PA predictions, the random forest produced the best prediction rate. Overall, the accuracy of the test set was 67.4%-81.3% for different machine learning algorithms. The most critical variables in the model were questionnaire and physiological features, such as the BAI, BDI, STAI, MINI, average HR, resting HR, and deep sleep duration.

Conclusions

It is possible to predict PAs using a combination of data from questionnaires and physiological and environmental data.

Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review

Depersonalisation/derealisation disorder (DPD) refers to frequent and persistent detachment from bodily self and disengagement from the outside world. As a dissociative disorder, DPD affects 1-2 % of the population, but takes 7-12 years on average to be accurately diagnosed. In this systematic review, we comprehensively describe research targeting the neural correlates of core DPD symptoms, covering publications between 1992 and 2020 that have used electrophysiological techniques. The aim was to investigate the diagnostic potential of these relatively inexpensive and convenient neuroimaging tools. We review the EEG power spectrum, components of the event-related potential (ERP), as well as vestibular and heartbeat evoked potentials as likely electrophysiological biomarkers to study DPD symptoms. We argue that acute anxiety- or trauma-related impairments in the integration of interoceptive and exteroceptive signals play a key role in the formation of DPD symptoms, and that future research needs analysis methods that can take this integration into account. We suggest tools for prospective studies of electrophysiological DPD biomarkers, which are urgently needed to fully develop their diagnostic potential.

Transient Cognitive Impairment in Epilepsy

Impairments of the dialog between excitation and inhibition (E/I) is commonly associated to neuropsychiatric disorders like autism, bipolar disorders and epilepsy. Moderate levels of hyperexcitability can lead to mild alterations of the EEG and are often associated with cognitive deficits even in the absence of overt seizures. Indeed, various testing paradigms have shown degraded performances in presence of acute or chronic non-ictal epileptiform activity. Evidences from both animal models and the clinics suggest that anomalous activity can cause cognitive deficits by transiently disrupting cortical processing, independently from the underlying etiology of the disease. Here, we will review our understanding of the influence of an abnormal EEG activity on brain computation in the context of the available clinical data and in genetic or pharmacological animal models.

White matter network alterations in patients with depersonalization/derealization disorder

BACKGROUND

Depersonalization/derealization disorder (DPD) is a chronic and distressing condition characterized by detachment from oneself and/or the external world. Neuroimaging studies have associated DPD with structural and functional alterations in a variety of distinct brain regions. Such local neuronal changes might be mediated by altered interregional white matter connections. However, to our knowledge, no research on network characteristics in this patient population exists to date.

METHODS

We explored the structural connectome in 23 individuals with DPD and 23 matched, healthy controls by applying graph theory to diffusion tensor imaging data. Mean interregional fractional anisotropy (FA) was used to define the network weights. Group differences were assessed using network-based statistics and a link-based controlling procedure.

RESULTS

Our main finding refers to lower FA values within left temporal and right temporoparietal regions in individuals with DPD than in healthy controls when using a link-based controlling procedure. These links were also associated with dissociative symptom severity and could not be explained by anxiety or depression scores. Using network-based statistics, no significant results emerged. However, we found a trend for 1 subnetwork that may support the model of frontolimbic dysbalance suggested to underlie DPD symptomatology.

LIMITATIONS

To ensure ecological validity, patients with certain comorbidities or psychotropic medication were included in the study. Confirmatory replications are necessary to corroborate the results of this explorative investigation.

CONCLUSION

In patients with DPD, the structural connectivity between brain regions crucial for multimodal integration and emotion regulation may be altered. Aberrations in fibre tract communication seem to be not solely a secondary effect of local grey matter volume loss, but may present a primary pathophysiology in patients with DPD.

Are there advances in pharmacotherapy for panic disorder? A systematic review of the past five years

INTRODUCTION

Several effective medications are available for treating panic disorder (PD). However, outcomes are unsatisfactory in a number of patients, suggesting the usefulness of expanding the array of antipanic drugs and improving the quality of response to current recommended treatments.

AREAS COVERED

The authors have performed an updated systematic review of pharmacological studies (phase III onwards) to examine whether advances have been made in the last five years. Only four studies were included. D-cycloserine no longer seemed promising as a cognitive-behavioral therapy (CBT) enhancer. Some preliminary findings concerning the optimization of recommended medications deserved consideration, including: the possibility that SSRIs are more effective than CBT alone in treating panic attacks, combined therapy is preferable when agoraphobia is present, and clonazepam is more potent than paroxetine in decreasing panic relapse.

EXPERT OPINION

Given the lack of novel treatments, expanding a personalized approach to the existing medications seems to be the most feasible strategy to improve pharmacotherapy outcomes regarding PD. Recent technological progress, including wearable devices collecting real-time data, 'big data' platforms, and application of machine learning techniques might help make outcome prediction more reliable. Further research on previously promising novel treatments is also recommended.

[Perspectives for the Electroencephalogram in Psychiatry]

Perspectives for the Electroencephalogram in Psychiatry Abstract. The electroencephalogram (EEG) is a non-invasive and cost-effective method to monitor spontaneous neuronal activity over time. Pathologies in EEG recordings indicate with high sensitivity but low specificity abnormal functional brain states. The main psychiatric indications for EEG recordings include atypical clinical symptoms of a neuropsychiatric syndrome or atypical reactions to medication as well as a baseline diagnostic before starting treatment with specific drugs or stimulation modalities. In recent research the EEG continues to be a valuable tool not only in diagnostics but also for the prediction of treatment success. The following paper focuses on basic electrophysiological understanding of EEG recordings, the diagnostic value of EEG recordings in different clinical entities, and new research attempts in diagnostic and treatment prediction.

White matter network alterations in patients with depersonalization/derealization disorder

BACKGROUND

Depersonalization/derealization disorder (DPD) is a chronic and distressing condition characterized by detachment from oneself and/or the external world. Neuroimaging studies have associated DPD with structural and functional alterations in a variety of distinct brain regions. Such local neuronal changes might be mediated by altered interregional white matter connections. However, to our knowledge, no research on network characteristics in this patient population exists to date.

METHODS

We explored the structural connectome in 23 individuals with DPD and 23 matched, healthy controls by applying graph theory to diffusion tensor imaging data. Mean interregional fractional anisotropy (FA) was used to define the network weights. Group differences were assessed using network-based statistics and a link-based controlling procedure.

RESULTS

Our main finding refers to lower FA values within left temporal and right temporoparietal regions in individuals with DPD than in healthy controls when using a link-based controlling procedure. These links were also associated with dissociative symptom severity and could not be explained by anxiety or depression scores. Using network-based statistics, no significant results emerged. However, we found a trend for 1 subnetwork that may support the model of frontolimbic dysbalance suggested to underlie DPD symptomatology.

LIMITATIONS

To ensure ecological validity, patients with certain comorbidities or psychotropic medication were included in the study. Confirmatory replications are necessary to corroborate the results of this explorative investigation.

CONCLUSION

In patients with DPD, the structural connectivity between brain regions crucial for multimodal integration and emotion regulation may be altered. Aberrations in fibre tract communication seem to be not solely a secondary effect of local grey matter volume loss, but may present a primary pathophysiology in patients with DPD.

Clinical features of outpatients with somatization symptoms treated at a Japanese psychosomatic medicine clinic

Background

Somatization is produced due to the summation of psychological factors, irrespective of the presence or absence of physical factors. A group of diseases with severe pain and other disorders exhibit so-called Medically Unexplained Symptoms (MUS), and the characteristics of patients with MUS are largely unexplained. In this paper, the characteristics of a series of new patients with somatization treated in a Japanese university hospital are discussed.

Method

The subjects were 871 patients who newly visited the Department of Psychosomatic Medicine, Toho University Omori Medical Center between January and December of 2015. Under the assumption that the definition of somatization is same as that of MUS, the correlation between somatization and the age, sex, academic background, chief complaints, reasons for visiting the medical center, diagnosis, symptoms, presence or absence of a referral form, continued treatment after the first visit, and marital status of these patients at the time of their respective examinations were evaluated.

Results

Of the patients studied, 68% suffered from somatization. Among them, 11% met the definition of Functional Somatic Symptoms (FSS) and 74% had somatization associated with mood disorder or anxiety disorder. Digestive symptoms were reported by 33%, headaches by 24%, and unusual sensations by 21%. Whereas no correlation was found between somatization symptoms and the patients’ academic background, marital history, or medical history after the first visit, a positive correlation (p < 0.05) was found between somatization and patients who had been referred by their doctor.

Conclusion

Many of the studied patients who suffered from somatization, regardless of age and sex, were referred to us by doctors from other hospitals. It was concluded that many patients difficult to diagnose or deal with are referred the Department of Psychosomatic Medicine of Japanese university hospitals, thus these hospitals must assume great responsibility for preventing mistaken diagnoses by conducting effective psychological treatment and thorough medical examinations.

A structural MRI study of cortical thickness in depersonalisation disorder

Depersonalisation disorder (DPD) is characterised by a sense of unreality about the self and the world. Research suggests altered autonomic responsivity and dysfunction in prefrontal and temporal lobe areas in this condition. We report the first structural magnetic resonance imaging study of 20 patients with DPD and 21 controls using the FreeSurfer analysis tool employing both region-of-interest and vertex-based methods. DPD patients showed significantly lower cortical thickness in the right middle temporal region according to both methods of analysis. The vertex-based method revealed additional differences in bilateral temporal lobes, inferior frontal regions, the right posterior cingulate, and increased thickness in the right gyrus rectus and left precuneus. Clinical severity scores were negatively correlated with cortical thickness in middle and right inferior frontal regions. In sum, grey matter changes in the frontal, temporal, and parietal lobes are associated with DPD. Further research is required to specify the functional significance of the findings and whether they are vulnerability or disease markers.

The diagnostic value of clinical EEG in detecting abnormal synchronicity in panic disorder

Electroencephalographic (EEG) findings repeatedly reported abnormal synchronous or even epileptiform discharges in panic disorder. Although less frequently occurring in patients with panic disorder, these deviant EEG features during panic attacks were also observed in intracranial EEG. For this purpose, our article reviews the consideration of abnormal synchronous neuronal activity in different neurocircuits, particularly limbic, as a suggested condition of panic attacks. Therapeutic approaches of anticonvulsants have shown reductions of symptoms and frequency of attacks in numerous patients suffering from panic disorder, supporting the presumption of underlying abnormal synchronous neuronal activity. Thus, scalp EEG recordings are still recommended for discovering indications of abnormal synchronous neuronal activity in panic patients.