EEG-arousal regulation as predictor of treatment response in patients suffering from obsessive compulsive disorder

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.

Psychotherapies and digital interventions for OCD in adults: What do we know, what do we need still to explore?

BACKGROUND

Despite significant advances in the understanding and treatment of obsessive compulsive disorder (OCD), current treatment options are limited in terms of efficacy for symptom remission. Thus, assessing the potential role of iterative or alternate psychotherapies is important. Also, the potential role of digital technologies to enhance the accessibility of these therapies, should not be underestimated. We also need to embrace the idea of a more personalized treatment choice, being cognisant of clinical, genetic and neuroimaging predictors of treatment response.

PROCEDURES

Non-systematic review of current literature on emerging psychological and digital therapies for OCD, as well as of potential biomarkers of treatment response.

FINDINGS

A number of 'third wave' therapies (e.g., Acceptance and Commitment Therapy, Mindfulness-Based Cognitive Therapy) have an emerging and encouraging evidence base in OCD. Other approaches entail employment of elements of other psychotherapies such as Dialectical Behaviour Therapy; or trauma-focussed therapies such as Eye Movement Desensitisation and Reprocessing, and Imagery Rescripting and Narrative Therapy. Further strategies include Danger Ideation Reduction Therapy and Habit Reversal. For these latter approaches, large-scale randomised controlled trials are largely lacking, and the precise role of these therapies in treating people with OCD, remains to be clarified. A concentrated 4-day program (the Bergen program) has shown promising short- and long-term results. Exercise, music, and art therapy have not been adequately tested in people with OCD, but may have an adjunctive role. Digital technologies are being actively investigated for enhancing reach and efficacy of psychological therapies for OCD. Biomarkers, including genetic and neuroimaging, are starting to point to a future with more 'personalised medicine informed' treatment strategizing for OCD.

CONCLUSIONS

There are a number of potential psychological options for the treatment of people with OCD who do not respond adequately to exposure/response prevention or cognitive behaviour therapy. Adjunctive exercise, music, and art therapy might be useful, albeit the evidence base for these is very small. Consideration should be given to different ways of delivering such interventions, including group-based, concentrated, inpatient, or with outreach, where appropriate. Digital technologies are an emerging field with a number of potential applications for aiding the treatment of OCD. Biomarkers for treatment response determination have much potential capacity and deserve further empirical testing.

Heart rate variability in obsessive compulsive disorder in comparison to healthy controls and as predictor of treatment response

OBJECTIVE

Obsessive compulsive disorder (OCD) has a large impact on the quality of life of patients. It often takes years to get the right diagnosis and to receive treatment. Therefore, biomarkers that could inform the diagnostic process and provide information on response or non-response for first line treatment approaches are urgently needed. The aim of this study was to analyze whether (1) heart rate (HR) and heart rate variability (HRV) markers of the autonomous nervous system could distinguish between healthy controls (HC) and patients suffering from OCD and (2) HRV parameters additionally yield useful information to separate therapy-responders from non-responders.

METHODS

A fifteen-minute resting state ECG (electrocardiogram) was recorded from 51 unmedicated OCD patients before treatment and 28 HC. The function of the autonomic nervous system was assessed by using parameters of the HRV. Clinical Global Impression (CGI) scores served as baseline and outcome parameters following three to six months of therapy (cognitive behavioral therapy n = 18, selective-serotonin-reuptake-inhibitor n = 11 or combination n = 22). Differences between patients and HC and responders and non-responders were identified using analysis of covariance (ANCOVAs). Predictive values were calculated following binary regression modelling and receiver operating characteristics (ROC).

RESULTS

OCD patients revealed a significantly higher HR in comparison to HC. Although patients were thus characterized by increased sympathetic and decreased parasympathetic tone, treatment responders exhibited a larger High Frequency Power as a marker for increased parasympathetic activity at baseline. ROC-curves for OCD vs HC and R vs NR showed clinically relevant areas under curve (83%, 88% respectively).

CONCLUSIONS

These results are in line with findings of increased sympathetic and decreased parasympathetic activity in OCD in comparison to healthy subjects. The findings further provide clinically useful information on treatment response in OCD.

SIGNIFICANCE

Results may facilitate the clinical use of electrophysiological markers in OCD.

The Role of Neurophysiological Biomarkers in Obsessive-Compulsive Disorder

BACKGROUND

Obsessive-compulsive disorder is a highly debilitating psychiatric disorder with a high rate of treatment resistance. Biomarkers for obsessive-compulsive disorder may assist clinicians by predicting response to treatments and prognosis.

OBJECTIVE

To review the literature with regards to two of the more easily ascertainable and relatively inexpensive physiological biomarkers, i.e. heart rate variability and electroencephalography.

METHODS

Narrative review of the literature.

RESULTS

Decreased heart rate variability has been associated with increased symptom severity of obsessive-compulsive disorder. Findings from electroencephalography have also predicted response to pharmacotherapy and it is likely that biomarkers for OCD will have their greatest utility in predicting response to different pharmacological agents. However, the number of studies is small and results are inconsistent.

CONCLUSIONS

More research is required to determine whether heart rate variability and electrophysiological studies have a clinical role as biomarkers for obsessive-compulsive disorder.

Electroencephalographic Correlates and Predictors of Treatment Outcome in OCD: A Brief Narrative Review

Electroencephalography (EEG) measures the brain's electrical activity with high temporal resolution. In comparison to neuroimaging modalities such as MRI or PET, EEG is relatively cheap, non-invasive, portable, and simple to administer, making it an attractive tool for clinical deployment. Despite this, studies utilizing EEG to investigate obsessive-compulsive disorder (OCD) are relatively sparse. This contrasts with a robust literature using other brain imaging methodologies. The present review examines studies that have used EEG to examine predictors and correlates of response in OCD and draws tentative conclusions that may guide much needed future work. Key findings include a limited literature base; few studies have attempted to predict clinical change from EEG signals, and they are confounded by the effects of both pharmacotherapy and psychotherapy. The most robust literature, consisting of several studies, has examined event-related potentials, including the P300, which several studies have reported to be abnormal at baseline in OCD and to normalize with treatment; but even here the literature is quite heterogeneous, and more work is needed. With more robust research, we suggest that the relatively low cost and convenience of EEG, especially in comparison to fMRI and PET, make it well-suited to the development of feasible personalized treatment algorithms.

Use of EEG for Predicting Treatment Response to Transcranial Magnetic Stimulation in Obsessive Compulsive Disorder

Aim. In this study we assessed the predictive power of quantitative EEG (qEEG) for the treatment response to right frontal transcranial magnetic stimulation (TMS) in obsessive compulsive disorder (OCD) using a machine learning approach. Method. The study included 50 OCD patients (35 responsive to TMS, 15 nonresponsive) who were treated with right frontal low frequency stimulation and identified retrospectively from Uskudar Unversity, NPIstanbul Brain Hospital outpatient clinic. All patients were diagnosed with OCD according to the DSM-IV-TR and DSM-5 criteria. We first extracted pretreatment band powers for patients. To explore the prediction accuracy of pretreatment EEG, we employed machine learning methods using an artificial neural network model. Results. Among 4 EEG bands, theta power successfully discriminated responsive from nonresponsive patients. Responsive patients had more theta powers for all electrodes as compared to nonresponsive patients. Discussion. qEEG could be helpful before deciding about treatment strategy in OCD. The limitations of our study are moderate sample size and limited number of nonresponsive patients and that treatment response was defined by clinicians and not by using a formal symptom measurement scale. Future studies with larger samples and prospective design would show the role of qEEG in predicting TMS response better.

Neurobiological Mechanisms of Metacognitive Therapy - An Experimental Paradigm

INTRODUCTION

The neurobiological mechanisms underlying the clinical effects of psychotherapy are scarcely understood. In particular, the modifying effects of psychotherapy on neuronal activity are largely unknown. We here present data from an innovative experimental paradigm using the example of a patient with treatment resistant obsessive-compulsive disorder (trOCD) who underwent implantation of bilateral electrodes for deep brain stimulation (DBS). The aim of the paradigm was to examine the short term effect of metacognitive therapy (MCT) on neuronal local field potentials (LFP) before and after 5 MCT sessions.

METHODS

DBS electrodes were implanted bilaterally with stereotactic guidance in the bed nucleus of the stria terminalis/ internal capsule (BNST/IC). The period between implantation of the electrodes and the pacemaker was used for the experimental paradigm. DBS electrodes were externalized via extension cables, yielding the opportunity to record LFP directly from the BNST/IC. The experimental paradigm was designed as follows: (a) baseline recording of LFP from the BNST/IC, (b) application of 5 MCT sessions over 3 days, (c) post-MCT recording from the BNST/IC. The Obsessive-Compulsive Disorder- scale (OCD-S) was used to evaluate OCD symptoms.

RESULTS

OCD symptoms decreased after MCT. These reductions were accompanied by a decrease of the relative power of theta band activity, while alpha, beta, and gamma band activity was significantly increased after MCT. Further, analysis of BNST/IC LFP and frontal cortex EEG coherence showed that MCT decreased theta frequency band synchronization.

DISCUSSION

Implantation of DBS electrodes for treating psychiatric disorders offers the opportunity to gather data from neuronal circuits, and to compare effects of therapeutic interventions. Here, we demonstrate direct effects of MCT on neuronal oscillatory behavior, which may give possible cues for the neurobiological changes associated with psychotherapy.

Electrophysiology of obsessive compulsive disorder: A systematic review of the electroencephalographic literature

Obsessive-compulsive disorder (OCD) is a chronic disease that causes significant decline in the quality of life of those affected. Due to our limited understanding of the underlying pathophysiology of OCD, successful treatment remains elusive. Although many have studied the pathophysiology of OCD through electroencephalography (EEG), limited attempts have been made to synthesize and interpret their findings. To bridge this gap, we conducted a comprehensive literature review using Medline/PubMed and considered the 65 most relevant studies published before June 2018. The findings are categorised into quantitative EEG, sleep related EEG and event related potentials (ERPs). Increased frontal asymmetry, frontal slowing and an enhancement in the ERP known as error related negativity (ERN) were consistent findings in OCD. However, sleep EEG and other ERP (P3 and N2) findings were inconsistent. Additionally, we analysed the usefulness of ERN as a potential candidate endophenotype. We hypothesize that dysfunctional frontal circuitry and overactive performance monitoring are the major underlying impairments in OCD. Additionally, we conceptualized that defective fronto-striato-thalamic circuitry causing poor cerebral functional connectivity gives rise to the OCD behavioural manifestations. Finally, we have discussed transcranial magnetic stimulation and EEG (TMS-EEG) applications in future research to further our knowledge of the underlying pathophysiology of OCD.

Deep brain stimulation in the treatment of obsessive-compulsive disorder: current perspectives

Deep brain stimulation (DBS) is a neuro-psychosurgical technique widely accepted in movement disorders, such as Parkinson's disease. Since 1999, DBS has been explored for severe, chronic and treatment-refractory psychiatric diseases. Our review focuses on DBS in obsessive-compulsive disorder (OCD), considered as a last treatment resort by most of learned societies in psychiatry. Two main stimulation areas have been studied: the striatal region and the subthalamic nucleus. But, most of the trials are open-labeled, and the rare controlled ones have failed to highlight the most efficient target. The recent perspectives are otherwise encouraging. Indeed, clinicians are currently considering other promising targets. A case series of 2 patients reported a decrease in OCD symptoms after DBS in the medial forebrain bundle and an open-label study is exploring bilateral habenula stimulation. New response criteria are also investigating such as quality of life, or subjective and lived-experience. Moreover, first papers about cost-effectiveness which is an important criterion in decision making, have been published. The effectiveness of tractography-assisted DBS or micro-assisted DBS is studying with the aim to improve targeting precision. In addition, a trial involving rechargeable pacemakers is undergoing because this mechanism could be efficient and have a positive impact on cost-effectiveness. A recent trial has discussed the possibility of using combined cognitive behavioral therapy (CBT) and DBS as an augmentation strategy. Finally, based on RDoc Research, the latest hypotheses about the understanding of cortico-striato-thalamo-cortical circuits could offer new directions including clinical predictors and biomarkers to perform adaptive closed-loop systems in the next future.