Heart rate variability measures as biomarkers in patients with psychogenic nonepileptic seizures: potential and limitations

Hypertension and other vascular risk factors in patients with functional seizures

OBJECTIVE

Recent literature has suggested that functional seizures are associated with an elevated risk for vascular disease and mortality. We investigated the prevalence of risk factors for vascular disease in patients who were admitted to the epilepsy monitoring unit.

METHODS

Patients who were admitted to the epilepsy monitoring unit and received a definitive diagnosis of either functional seizures or epilepsy were identified. Data collected included demographic, clinical characteristics, medication list, comorbidities, and scheduled blood pressure measurements that occurred every 12 h during the admission. The mean blood pressures were calculated and if they were above the American College of Cardiology and the American Heart Association guideline cutoff of 130/80 mm Hg or the patient had a documented history of hypertension the patient was counted as having the condition. A multiple logistic regression model was developed to evaluate the independent association of the patient's diagnosis (i.e., epilepsy or functional seizures) and vascular risk factors that controlled for the number of blood pressure measurements, age, sex, and if the patient was taking antihypertensive medications.

RESULTS

270 patients were included in this study of which 147 patients had epilepsy and 123 had functional seizures. Among those with functional seizures, 57.72 % had either a history of hypertension or a mean blood pressure above 130/80 compared to 38.78 % of those with epilepsy (p = 0.0022). In addition, 30.89 % of functional seizures patients had hyperlipidemia and 63.41 % were obese. The logistic regression model indicated that functional seizures were independently associated with high blood pressure (OR: 2.47, 95 % CI 1.10-5.69), hyperlipidemia (OR: 3.38, 95 % CI 1.35-8.86), and obesity (OR: 4.25, 95 % CI 2.22-8.36) compared to those with epilepsy. There was no significant difference in the prevalence of diabetes (OR: 0.81, 95 % CI 0.24-2.77) or current tobacco use (OR: 1.04, 95 % CI 0.48-2.25) between the groups.

SIGNIFICANCE

Patients with functional seizures had an elevated prevalence of several vascular risk factors. These findings may partially account for complications associated with functional seizures and have implications related to their pathophysiology.

Emotional Dysregulation and Temperament-Character Traits in Adolescents With Functional Neurological Symptom Disorder (Conversion Disorder)

ABSTRACT

The purpose of this study was to evaluate emotion dysregulation and temperament-character traits in adolescents with functional neurological symptom disorder (FNSD). Forty adolescents with FNSD and 40 healthy adolescents were evaluated by a semiconstructed diagnosis interview, Temperament and Character Inventory (TCI), Difficulties in Emotion Regulation Scale (DERS), Regulation of Emotions Questionnaire (REQ), and Children's Somatization Inventory-24 (CSI-24). The external and internal dysfunctional emotion regulation scores of REQ, all subscales of DERS, except the awareness subscale, and CSI-24 scores were significantly higher in FNSD patients compared with healthy controls. There were significant differences between the groups in terms of harm avoidance and reward dependence subscale scores of TCI. Multiple logistic regression analysis showed that the external dysfunctional emotion regulation strategy, somatization, and reward dependence are significant predictors of FNSD. Our results provide evidence that adolescents with FNSD experience emotional dysregulation and that the differential value of some temperament-character traits in the diagnosis of FNSD.

Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures

OBJECTIVE

20-40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS.

METHODS

The prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18-65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri‑ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS.

RESULTS

The study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83-0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99).

SIGNIFICANCE

HR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.

A systems biology approach for discovering the cellular and molecular aspects of psychogenic non-epileptic seizure

Objectives

Psychogenic non-epileptic seizure (PNES) is the most common non-epileptic disorder in patients referring to epilepsy centers. Contrary to common beliefs about the disease's harmlessness, the death rate of PNES patients is similar to drug-resistant epilepsy. Meanwhile, the molecular pathomechanism of PNES is unknown with very limited related research. Thus, the aim of this in silico study was to find different proteins and hormones associated with PNES via a systems biology approach.

Methods

Different bioinformatics databases and literature review were used to find proteins associated with PNES. The protein-hormone interaction network of PNES was constructed to discover its most influential compartments. The pathways associated with PNES pathomechanism were found by enrichment analysis of the identified proteins. Besides, the relationship between PNES-related molecules and psychiatric diseases was discovered, and the brain regions that could express altered levels of blood proteins were discovered.

Results

Eight genes and three hormones were found associated with PNES through the review process. Proopiomelanocortin (POMC), neuropeptide Y (NPY), cortisol, norepinephrine, and brain-derived neurotrophic factor (BDNF) were identified to have a high impact on the disease pathogenesis network. Moreover, activation of Janus kinase-signaling transducer and activator of transcription (JAK-STAT) and JAK, as well as signaling of growth hormone receptor, phosphatidylinositol 3-kinase /protein kinase B (PI3K/AKT), and neurotrophin were found associated with PNES molecular mechanism. Several psychiatric diseases such as depression, schizophrenia, and alcohol-related disorders were shown to be associated with PNES predominantly through signaling molecules.

Significance

This study was the first to gather the biochemicals associated with PNES. Multiple components and pathways and several psychiatric diseases associated with PNES, and some brain regions that could be altered during PNES were suggested, which should be confirmed in further studies. Altogether, these findings could be used in future molecular research on PNES patients.

Forecasting psychogenic non-epileptic seizure likelihood from ambulatory EEG and ECG

Objective.Critical slowing features (variance and autocorrelation) of long-term continuous electroencephalography (EEG) and electrocardiography (ECG) data have previously been used to forecast epileptic seizure onset. This study tested the feasibility of forecasting non-epileptic seizures using the same methods. In doing so, we examined if long-term cycles of brain and cardiac activity are present in clinical physiological recordings of psychogenic non-epileptic seizures (PNES).Approach.Retrospectively accessed ambulatory EEG and ECG data from 15 patients with non-epileptic seizures and no background of epilepsy were used for developing the forecasting system. The median period of recordings was 161 h, with a median of 7 non-epileptic seizures per patient. The phases of different cycles (5 min, 1 h, 6 h, 12 h, 24 h) of EEG and RR interval (RRI) critical slowing features were investigated. Forecasters were generated using combinations of the variance and autocorrelation of both EEG and the RRI of the ECG at each of the aforementioned cycle lengths. Optimal forecasters were selected as those with the highest area under the receiver-operator curve (AUC).Main results.It was found that PNES events occurred in the rising phases of EEG feature cycles of 12 and 24 h in duration at a rate significantly above chance. We demonstrated that the proposed forecasters achieved performance significantly better than chance in 8/15 of patients, and the mean AUC of the best forecaster across patients was 0.79.Significance.To our knowledge, this is the first study to retrospectively forecast non-epileptic seizures using both EEG and ECG data. The significance of EEG in the forecasting models suggests that cyclic EEG features of non-epileptic seizures exist. This study opens the potential of seizure forecasting beyond epilepsy, into other disorders of episodic loss of consciousness or dissociation.

Entropy Measures of Electroencephalograms towards the Diagnosis of Psychogenic Non-Epileptic Seizures

Psychogenic non-epileptic seizures (PNES) may resemble epileptic seizures but are not caused by epileptic activity. However, the analysis of electroencephalogram (EEG) signals with entropy algorithms could help identify patterns that differentiate PNES and epilepsy. Furthermore, the use of machine learning could reduce the current diagnosis costs by automating classification. The current study extracted the approximate sample, spectral, singular value decomposition, and Renyi entropies from interictal EEGs and electrocardiograms (ECG)s of 48 PNES and 29 epilepsy subjects in the broad, delta, theta, alpha, beta, and gamma frequency bands. Each feature-band pair was classified by a support vector machine (SVM), k-nearest neighbour (kNN), random forest (RF), and gradient boosting machine (GBM). In most cases, the broad band returned higher accuracy, gamma returned the lowest, and combining the six bands together improved classifier performance. The Renyi entropy was the best feature and returned high accuracy in every band. The highest balanced accuracy, 95.03%, was obtained by the kNN with Renyi entropy and combining all bands except broad. This analysis showed that entropy measures can differentiate between interictal PNES and epilepsy with high accuracy, and improved performances indicate that combining bands is an effective improvement for diagnosing PNES from EEGs and ECGs.

Quality of life for patients with psychogenic nonepilepsy seizures in comparison with age- and gender-matched patients with epilepsy - Cross-sectional study

AIMS

Patients with psychogenic nonepileptic seizures (PNES), and age- and gender-matched patients with epilepsy (PWE) who utilized an out-patient service were compared regarding quality of life (QoL) and self-reported symptoms of depression. Additionally, the impact of miscellaneous clinical variables including symptoms of depression on QoL in patients with PNES and PWE in real-world settings was assessed.

SUBJECTS AND METHODS

Adult patients who had a diagnosis of definite or documented PNES based on LaFrance's criteria (PNES group, n = 62), or of epilepsy based on results of clinical and EEG procedures (Epilepsy group, n = 61) were enrolled. To assess QoL and evaluate depression, the Quality of Life in Epilepsy Inventory-10 (QOLIE-10) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), respectively, were administered.

RESULTS

Comparisons between the groups revealed a shorter duration of illness and fewer number of attacks in patients with PNES as compared to the Epilepsy group (p < 0.0001; p = 0.0003, respectively). There was no significant difference between the groups revealed by the QOLIE-10 (p = 0.141), while the patients with PNES tended to have higher NDDI-E scores (p = 0.068). Multiple regression analysis of QOLIE-10 results in the PNES group revealed that NDDI-E score was the sole significant contributor (β = -0.425 p = 0.001). In contrast, NDDI-E score as well as attack frequency had a significant impact on QOLIE-10 results in the Epilepsy group (β = -0.283 p = 0.026; β = -0.272 p = 0.031, respectively).

CONCLUSION

In PWE and patients with PNES who utilized an out-patient service, QoL did not differ significantly between those groups. For treating PNES, psychosocial factors may be a more appropriate indicator of therapeutic goal than attack frequency.

Shame in patients with psychogenic nonepileptic seizure: A narrative review

Psychogenic Nonepileptic Seizures (PNES) have been linked to dysregulated emotions and arousal. However, the question which emotions may be most relevant has received much less attention. In this multidisciplinary narrative review, we argue that the self-conscious emotion of shame is likely to be of particular importance for PNES. We summarize current concepts of the development of shame processing and its relationship with other emotional states. We demonstrate the potential of acute shame to cause a sudden disruption of normal cognitive function and trigger powerful behavioral, cognitive, physiological and secondary emotional responses which closely resemble key components of PNES. These responses may lead to the development of shame avoidance strategies which can become disabling in themselves. We discuss how excessive shame proneness and shame dysregulation are linked to several psychopathologies often associated with PNES (including depression and PTSD) and how they may predispose to, precipitate and perpetuate PNES disorders, not least by interacting with stigma. We consider current knowledge of the neurobiological underpinnings of shame and PNES. We explore how shame could be the link between PNES and a heterogeneous range of possible etiological factors, and how it may link historical aversive experiences with individual PNES events occurring much later and without apparent external trigger. We argue that, in view of the potential direct links between shame and PNES, the well-documented associations of shame with common comorbidities of this seizure disorder and the well-characterized relationship between chronic shame and stigma, there is a compelling case to pay greater attention to shame in relation to PNES. Its role in the treatment of patients with PNES is discussed in a separate, linked review incorporating case vignettes to highlight the complex interactions of different but interlinked shame-related issues in individual patients.

Autonomic, Endocrine, and Inflammation Profiles in Functional Neurological Disorder: A Systematic Review and Meta-Analysis

OBJECTIVE

Functional neurological disorder (FND) is a core neuropsychiatric condition. To date, promising yet inconsistently identified neural circuit profiles have been observed in patients with FND, suggesting that gaps remain in our systems-level neurobiological understanding. As such, other important physiological variables, including autonomic, endocrine, and inflammation findings, need to be contextualized for a more complete mechanistic picture.

METHODS

The investigators conducted a systematic review and meta-analysis of available case-control and cohort studies of FND. PubMed, PsycINFO, and Embase databases were searched for studies from January 1, 1900, to September 1, 2020, that investigated autonomic, endocrine, and inflammation markers in patients with FND. Sixty-six of 2,056 screened records were included in the review, representing 1,699 patients; data from 20 articles were used in the meta-analysis.

RESULTS

Findings revealed that children and adolescents with FND, compared with healthy control subjects (HCs), have increased resting heart rate (HR); there is also a tendency toward reduced resting HR variability in patients with FND across the lifespan compared with HCs. In adults, peri-ictal HR differentiated patients with functional seizures from those with epileptic seizures. Other autonomic and endocrine profiles for patients with FND were heterogeneous, with several studies highlighting the importance of individual differences.

CONCLUSIONS

Inflammation research in FND remains in its early stages. Moving forward, there is a need for the use of larger sample sizes to consider the complex interplay between functional neurological symptoms and behavioral, psychological, autonomic, endocrine, inflammation, neuroimaging, and epigenetic/genetic data. More research is also needed to determine whether FND is mechanistically (and etiologically) similar or distinct across phenotypes.

Heart rate variability in patients with refractory epilepsy: The influence of generalized convulsive seizures

OBJECTIVE

Patients with epilepsy, mainly drug-resistant, have reduced heart rate variability (HRV), linked to an increased risk of sudden death in various other diseases. In this context, it could play a role in SUDEP. Generalized convulsive seizures (GCS) are one of the most consensual risk factors for SUDEP. Our objective was to assess the influence of GCS in HRV parameters in patients with drug-resistant epilepsy.

METHODS

We prospectively evaluated 121 patients with refractory epilepsy admitted to our Epilepsy Monitoring Unit. All patients underwent a 48-hour Holter recording. Only patients with GCS were included (n = 23), and we selected the first as the index seizure. We evaluated HRV (AVNN, SDNN, RMSSD, pNN50, LF, HF, and LF/HF) in 5-min epochs (diurnal and nocturnal baselines; preictal - 5 min before the seizure; ictal; postictal - 5 min after the seizure; and late postictal - >5 h after the seizure). These data were also compared with normative values from a healthy population (controlling for age and gender).

RESULTS

We included 23 patients, with a median age of 36 (min-max, 16-55) years and 65% were female. Thirty percent had cardiovascular risk factors, but no previously known cardiac disease. HRV parameters AVNN, RMSSD, pNN50, and HF were significantly lower in the diurnal than in the nocturnal baseline, whereas the opposite occurred with LF/HF and HR. Diurnal baseline parameters were inferior to the normative population values (which includes only diurnal values). We found significant differences in HRV parameters between the analyzed periods, especially during the postictal period. All parameters but LF/HF suffered a reduction in that period. LF/HF increased in that period but did not reach statistical significance. Visually, there was a tendency for a global reduction in our patients' HRV parameters, namely AVNN, RMSSD, and pNN50, in each period, comparing with those from a normative healthy population. No significant differences were found in HRV between diurnal and nocturnal seizures, between temporal lobe and extra-temporal-lobe seizures, between seizures with and without postictal generalized EEG suppression, or between seizures of patients with and without cardiovascular risk factors.

SIGNIFICANCE/CONCLUSION

Our work reinforces the evidence of autonomic cardiac dysfunction in patients with refractory epilepsy, at baseline and mainly in the postictal phase of a GCS. Those changes may have a role in some SUDEP cases. By identifying patients with worse autonomic cardiac function, HRV could fill the gap of a lacking SUDEP risk biomarker.

Evidence-Based Practice for the Clinical Assessment of Psychogenic Nonepileptic Seizures: A Report From the American Neuropsychiatric Association Committee on Research

The American Neuropsychiatric Association's Committee on Research assigned the task of defining the most helpful clinical factors and tests in establishing the diagnosis of psychogenic nonepileptic seizures (PNES) during a neuropsychiatric assessment. A systematic review of the literature was conducted using three search engines and specified search terms for PNES and the predetermined clinical factors and diagnostic tests, followed by a selection process with specific criteria. Data extraction results from selected articles are presented for clinical factors (semiology, psychiatric comorbidities, medical comorbidities, psychological traits) and diagnostic tests (EEG, psychometric and neuropsychological measures, prolactin level, clinical neuroimaging, autonomic testing). Semiology with video EEG (vEEG) remains the most valuable tool to determine the diagnosis of PNES. With the exception of semiology, very few studies revealed the predictive value of a clinical factor for PNES, and such findings were isolated and not replicated in most cases. Induction techniques, especially when coupled with vEEG, can lead to a captured event, which then confirms the diagnosis. In the absence of a captured event, postevent prolactin level and personality assessment can support the diagnosis but need to be carefully contextualized with other clinical factors. A comprehensive clinical assessment in patients with suspected PNES can identify several clinical factors and may include a number of tests that can support the diagnosis of PNES. This is especially relevant when the gold standard of a captured event with typical semiology on vEEG cannot be obtained.

Myths and truths about pediatric psychogenic nonepileptic seizures

Psychogenic nonepileptic seizures (PNES) is a neuropsychiatric condition that causes a transient alteration of consciousness and loss of self-control. PNES, which occur in vulnerable individuals who often have experienced trauma and are precipitated by overwhelming circumstances, are a body's expression of a distressed mind, a cry for help. PNES are misunderstood, mistreated, under-recognized, and underdiagnosed. The mindbody dichotomy, an artificial divide between physical and mental health and brain disorders into neurology and psychiatry, contributes to undue delays in the diagnosis and treatment of PNES. One of the major barriers in the effective diagnosis and treatment of PNES is the dissonance caused by different illness perceptions between patients and providers. While patients are bewildered by their experiences of disabling attacks beyond their control or comprehension, providers consider PNES trivial because they are not epileptic seizures and are caused by psychological stress. The belief that patients with PNES are feigning or controlling their symptoms leads to negative attitudes of healthcare providers, which in turn lead to a failure to provide the support and respect that patients with PNES so desperately need and deserve. A biopsychosocial perspective and better understanding of the neurobiology of PNES may help bridge this great divide between brain and behavior and improve our interaction with patients, thereby improving prognosis. Knowledge of dysregulated stress hormones, autonomic nervous system dysfunction, and altered brain connectivity in PNES will better prepare providers to communicate with patients how intangible emotional stressors could cause tangible involuntary movements and altered awareness.

Interoception and stress in patients with Functional Neurological Symptom Disorder

INTRODUCTION

Research suggests that patients with Functional Neurological Symptom Disorder (pwFND) struggle to identify their own emotions and associated physiological cues (interoceptive sensitivity, IS). However, it is not known how this deficit interacts with stress. This study aimed to assess IS in pwFND at baseline and following stress induction, and relate the findings to self-reported emotion processing difficulties.

METHODS

Twenty-six pwFND and 27 healthy controls performed the Heart Beat Detection Task pre- and post-stress induction with the Cold Pressor Test. Participants also completed questionnaires assessing anxiety (GAD-7) and depressive symptomology (PHQ-9), as well as emotion processing (EPS-25).

RESULTS

Patients reported deficits in emotion processing (p < . 001) and had lower IS (p = .032) than healthy controls. IS improved following stress induction across both groups (p = .003) but patients' IS was lower than that of healthy controls' pre-and post-stress induction. Exploratory analyses revealed that patients reporting sensory symptoms had lower IS at baseline than patients who did not.

CONCLUSION

Our findings suggest that pwFND are relatively impaired in the identification of their emotions at baseline and following stress induction. This may be related to the experience of functional sensory symptoms and has implications for the psychological treatment of emotion dysregulation in this population.

Clinical differentiation of psychogenic non-epileptic seizure: a practical diagnostic approach

Background

Psychogenic non-epileptic seizure (PNES) has long been the counterpart of epileptic seizure (ES). Despite ample of evidence differentiating the two, PNES mistakenly diagnosed as ES was still common, resulting in unnecessary exposure to long-term antiepileptic medications and reduced patient’s and caregiver’s quality of life, not to mention the burgeoning financial costs.

Objectives

In this review, we aimed to elucidate various differences between PNES and epileptic seizure with respect to baseline characteristics, seizure semiology, EEG pattern, and other key hallmark features.

Methods

An unstructured search was carried out in PubMed, MEDLINE, and EMBASE using keywords pertinent to PNES and ES differentiation. Relevant information was subsequently summarized herein.

Results

PNES differs significantly with ES in terms of baseline characteristics, prodromal symptoms, seizure semiology, presence of pseudosleep, and other hallmark features (for instance provoking seizure with suggestion). The combined approach, if applied appropriately, can yield high diagnostic yield.

Conclusions

PNES can be clearly differentiated from ES via careful adherence to a set of valid clinical cues. The summarized clinical hallmarks is highly useful to prevent unnecessary ES diagnosis and treatment with AEDs.

Complexity Measures of Heart-Rate Variability in Amyotrophic Lateral Sclerosis with Alternative Pulmonary Capacities

OBJECTIVE

the complexity of heart-rate variability (HRV) in amyotrophic lateral sclerosis (ALS) patients with different pulmonary capacities was evaluated.

METHODS

We set these according to their pulmonary capacity, and specifically forced vital capacity (FVC). We split the groups according to FVC (FVC > 50% (n = 29) and FVC < 50% (n = 28)). In ALS, the presence of an FVC below 50% is indicative of noninvasive ventilation with two pressure levels and with the absence of other respiratory symptoms. As the number of subjects per group was different, we applied the unbalanced one-way analysis of variance (uANOVA1) test after three tests of normality, and effect size by Cohen's d to assess parameter significance.

RESULTS

with regard to chaotic global analysis, CFP4 (p < 0.001; d = 0.91), CFP5 (p = 0.0022; d = 0.85), and CFP6 (p = 0.0009; d = 0.92) were enlarged. All entropies significantly increased. Shannon (p = 0.0005; d = 0.98), Renyi (p = 0.0002; d = 1.02), Tsallis (p = 0.0004; d = 0.99), approximate (p = 0.0005; d = 0.97), and sample (p < 0.0001; d = 1.22). Detrended fluctuation analysis (DFA) (p = 0.0358) and Higuchi fractal dimension (HFD) (p = 0.15) were statistically inconsequential between the two groups.

CONCLUSIONS

HRV complexity in ALS subjects with different pulmonary capacities increased via chaotic global analysis, especially CFP5 and 3 out of 5 entropies.

Psychogenic non-epileptic seizures in children - psychophysiology & dissociative characteristics

The purpose of this study was to determine psychophysiology and dissociative characteristics of psychogenic non-epileptic seizures (PNES) in a clinical pediatric setting. A retrospective chart review was conducted over a 5-year period that included children meeting criteria for probable, clinically established or documented PNES. Of these, 33 patients (81%) underwent psychophysiology assessment as part of standardized care and were selected for study inclusion. Ages ranged from 10 to 17 years inclusive (70% female). The majority of patients were found to have some form of autonomic decompensation at baseline (82%) and lack of autonomic recovery from a cognitive stressor (58%). Inhibition of electrodermal skin response to laboratory stressor was associated with significantly longer duration of PNES illness (t=2.65, p=.013), while elevated heart rate (above 90^th percentile) was associated with significantly higher frequency of PNES events in the month preceding diagnosis (t=3.1, p=.004). High levels of dissociation and hyperventilation symptoms were self-reported by adolescent patients (n=19) with a moderate degree of positive association (r=0.35, p=.038). The majority of patients (n= 25, 89%) were taught to correct respiratory CO₂ levels during a single biofeedback training session. Conclusions: Child PNES populations appear to be characterized by chronic autonomic hyperarousal reflecting severity of their symptoms, which can feasibly be targeted for behavioral treatment.

Catastrophising and repetitive negative thinking tendencies in patients with psychogenic non-epileptic seizures or epilepsy

PURPOSE

Previous research suggests that catastrophisation and perseverative, or repetitive negative thinking (RNT) could play an important role in the aetiology of Psychogenic Nonepileptic Seizures (PNES). This study was designed to explore whether these cognitive tendencies are more prevalent in patients with PNES than those with epilepsy and to examine the relationship between these cognitions, depression, anxiety, seizure frequency and diagnosis.

METHODS

26 patients with PNES (PWPNES) and 29 with epilepsy (PWE) self-reported RNT (Perseverative Thinking Questionnaire), catastrophisation tendencies (modified Safety Behaviors and Catastrophizing Scale), symptoms of anxiety (Generalised Anxiety Disorder Assessment 7) and depression (Primary Health Questionnaire 9) as well as seizure frequency.

RESULTS

RNT and catastrophic thinking were highly correlated with each other and more prevalent in PWPNES than PWE. Positive correlations were also found between all other self-report measures and seizure frequency. The PNES diagnosis predicted RNT (perseverative thinking) independently of catastrophic thinking, anxiety, depression and seizure frequency.

CONCLUSION

PWPNES exhibit greater negative perseverative and catastrophising cognitive tendencies than PWE. PNES as a diagnosis independently predicted RNT. Hence, RNT and catastrophisation should be considered as possible specific targets for psychological interventions in patients with PNES.

What Does Neuroscience Tell Us About the Conversion Model of Functional Neurological Disorders?

A dualistic mind-body understanding of functional neurological disorders (FNDs), also known as conversion disorders, has led to the view that the cause of the symptom should be either psychological (psychogenic) or physical (neurogenic-"organic"). One of the most influential psychological approaches is the Freudian model of conversion, which suggests that FNDs arise from a defense process in which emotional stress is converted into physical symptoms. This conversion theory has been challenged in recent years, accompanied by a shift in emphasis toward neuropathophysiological models of FND and away from historical psychological concepts. In this review, the authors consider the contemporary relevance of the conversion model from the neuroscientific perspective to reconcile the role of both psychological and biological factors in FND. A narrative review of recent neuroscientific findings pertaining to the conversion model of FND, encompassing neuroimaging, cognitive psychology, biological markers, and epigenetic studies, was performed. Research on the role of psychological stressors is discussed. Neurobiological mechanisms of repression of traumatic memories and their translation into physical symptoms are then explored. Finally, the role of physical symptoms as a potential protective defense mechanism against social stressors is considered. The authors argue that the conversion concept is consistent with recent neuroscientific research findings, and the model allows psychological and neurobiological concepts to be reconciled within a single account of FND that begins to resolve the dualistic mind-body dichotomy.

Skin conductance response and emotional response in women with psychogenic non-epileptic seizures

PURPOSE

Recent etiopathogenic models place emotional dysregulation at the core of psychogenic nonepileptic seizure (PNES). Our purpose was to assess physiological, cognitive, and behavioral emotional responses of PNES patients.

METHODS

This study compared three types of emotional responses to visual emotional stimuli between 34 female PNES group and 34 matched healthy controls: physiological response measured by skin conductance response (SCR) (rate, amplitude and latency) and heart rate deceleration; cognitive response measured by valence and arousal elicited by the images; and behavioural response measured by latency of ratings. The groups were characterized on psychiatric comorbidities, traumatic history, alexithymia, and dissociation.

RESULTS

Compared to controls, PNES group displayed lower SCR for all images (p = 0.038), shorter amplitude of heart rate deceleration (p = 0.024) and faster arousal rating for all images (p = 0.019), but no difference on cognitive rating of images. Within-groups analyses showed only in PNES subjects increased rate (+19.35%, p = 0.046) SCR for negative stimuli with strong arousal compared to negative with low arousal. PNES physiological response (SCR and heart rate deceleration) was negatively correlated to dissociation tendency (r=-0.48, p = 0.0083) and alexithymia (r=-0.44, p = 0.012)). For cognitive response, no correlation was found.

CONCLUSION

These results are in favour of a lower physiological emotional response but with an over-reactivity at behavioral level contrasting with similar cognitive assessment. For strong aversive stimuli, PNES might present a trend to overreact at physiological and behavioural levels. Our results suggest that dissociation and difficulty in describing feelings are associated with an altered physiological response in PNES women only.

Heart Rate Variability Parameters During Psychogenic Non-epileptic Seizures: Comparison Between Patients With Pure PNES and Comorbid Epilepsy

Introduction: Psychogenic non-epileptic seizures (PNES) may resemble epileptic seizures. There are few data about ictal ANS activity alterations induced by PNES in patients with pure PNES (pPNES) compared to PNES with comorbid epilepsy (PNES/ES). We aimed to compare heart rate variability (HRV) parameters and hence autonomic regulation in PNES in epileptic and non-epileptic patients.

Methods: We obtained HRV data from video-electroencephalography recordings in 22 patients presenting PNES (11 pPNES and 11 PNES/ES) in awake, and supine states. We calculated HRV parameters in both time and frequency domains including low frequency (LF) power, high frequency power (HF), LF/HF ratio, square root of the mean of the sum of the squares of differences between adjacent R wave intervals (RMSSD) and the standard deviation of all consecutive R wave intervals (SDNN). We also evaluated approximate entropy (ApEn), cardiosympathetic index (CSI), and cardiovagal index (CVI). Four conditions were considered: basal condition (BAS), before PNES (PRE), during PNES (ICT) and after PNES (POST).

Results: HRV analysis showed significantly higher ICT LF and LF/HF ratio vs. each condition. We also found higher POST HF vs. PRE and BAS, lower RRI in ICT vs. each condition and PRE vs. BAS. POST RMSSD was significantly higher compared to all other states. ICT CSI was significantly higher compared to all other states, whereas CSI was significantly lower in POST vs. PRE and PRE CVI lower than ICT and higher in POST vs. BAS and PRE. Also, ICT ApEn was lower than in all other states. Higher LF in pPNES vs. PNES/ES was also evident when compared across groups.

Significance: A few studies examined HRV alterations in PNES, reporting high sympathetic tone (although less evident than in epileptic seizures). Our data suggest a sympathetic overdrive before and during PNES followed by a post-PNES increase in vagal tone. A sympathovagal imbalance was more evident in pPNES as compared to PNES/ES.

Complexity of Cardiac Autonomic Modulation in Diabetes Mellitus: A New Technique to Perceive Autonomic Dysfunction

Backgound and aims. In this study we analyzed heart rate variability (HRV) via chaotic global techniques so as to discriminate diabetics from control subjects. Matherial and method. Chaotic global analysis of the RR-intervals from the electrocardiogram and preprocessing adjustments were undertaken. The effect of varying two parameters to adjust the Multi-Taper Method (MTM) power spectrum were evaluated. Then, cubic spline interpolations from 1Hz to 13Hz were applied whilst the spectral parameters were fixed. Precisely 1000 RR-intervals of data were recorded. Results. CFP1 and CFP3 are the only significant combinations of chaotic globals when the default standard conditions are enforced. MTM spectral adjustments and cubic spline interpolation are trivial at effecting the outcome between the two datasets. The most influencial constraint on the outcome is data length. Conclusion. Chaotic global analysis was offered as a reliable, low-cost and robust technique to detect autonomic dysfunction in subjects with diabetes mellitus.

Identifying signal-dependent information about the preictal state: A comparison across ECoG, EEG and EKG using deep learning

Background

The inability to reliably assess seizure risk is a major burden for epilepsy patients and prevents developing better treatments. Recent advances have paved the way for increasingly accurate seizure preictal state detection algorithms, primarily using electrocorticography (ECoG). To develop seizure forecasting for broad clinical and ambulatory use, however, less complex and invasive modalities are needed. Algorithms using scalp electroencephalography (EEG) and electrocardiography (EKG) have also achieved better than chance performance. But it remains unknown how much preictal information is in ECoG versus modalities amenable to everyday use – such as EKG and single channel EEG - and how to optimally extract that preictal information for seizure prediction.

Methods

We apply deep learning - a powerful method to extract information from complex data - on a large epilepsy data set containing multi-day, simultaneous recordings of EKG, ECoG, and EEG, using a variety of feature sets. We use the relative performance of our algorithms to compare the preictal information contained in each modality.

Results

We find that single-channel EKG contains a comparable amount of preictal information as scalp EEG with up to 21 channels and that preictal information is best extracted not with standard heart rate measures, but from the power spectral density. We report that preictal information is not preferentially contained in EEG or ECoG channels within the seizure onset zone.

Conclusion

Collectively, these insights may help to devise future prospective, minimally invasive long-term epilepsy monitoring trials with single-channel EKG as a particularly promising modality.

Stress and functional neurological disorders: mechanistic insights

At the interface between mind and body, psychiatry and neurology, functional neurological disorder (FND) remains poorly understood. Formerly dominant stress-related aetiological models have been increasingly challenged, in part due to cases without any history of past or recent trauma. In this perspective article, we review current evidence for such models, and how research into the role of traumatic stress in other disorders and the neurobiology of the stress response can inform our mechanistic understanding of FND. First, we discuss the association between stress and the onset or exacerbation of a variety of physical and mental health problems. Second, we review the role of hypothalamic-pituitary-adrenal axis dysfunction in the neurobiology of ill-health, alongside evidence for similar mechanisms in FND. Third, we advocate a stress-diathesis model, in which biological susceptibility interacts with early life adversity, where FND can be precipitated by traumatic events later in life and maintained by psychological responses. We hypothesise that greater biological susceptibility to FND is associated with less severe remote and recent stress, and that FND precipitated by more severe stress is associated with lower biological vulnerability. This would explain clinical experience of variable exposure to historical and recent traumatic stress among people with FND and requires empirical investigation. A testable, evidence-based stress-diathesis model can inform nuanced understanding of how biological and psychological factors interact at the individual level, with potential to inform personalised treatment pathways. Much-needed research to establish the aetiology of FND will enhance clinical care and communication, facilitate effective treatment and inform prevention strategies.

Emotional processing in functional neurological disorder: a review, biopsychosocial model and research agenda

Functional neurological disorder (FND) is a common and highly disabling disorder, but its aetiology remains enigmatic. Conceptually, there has been reduced emphasis on the role of psychosocial stressors in recent years, with a corresponding increase in neurobiological explanations. However, a wealth of evidence supports the role of psychosocial adversities (eg, stressful life events, interpersonal difficulties) as important risk factors for FND. Therefore, there is a need to integrate psychosocial (environmental) and neurobiological factors (eg, sensorimotor and cognitive functions) in contemporary models of FND. Altered emotional processing may represent a key link between psychosocial risk factors and core features of FND. Here, we summarise and critically appraise experimental studies of emotional processing in FND using behavioural, psychophysiological and/or neuroimaging measures in conjunction with affective processing tasks. We propose that enhanced preconscious (implicit) processing of emotionally salient stimuli, associated with elevated limbic reactivity (eg, amygdala), may contribute to the initiation of basic affective/defensive responses via hypothalamic and brainstem pathways (eg, periaqueductal grey). In parallel, affect-related brain areas may simultaneously exert a disruptive influence on neurocircuits involved in voluntary motor control, awareness and emotional regulation (eg, sensorimotor, salience, central executive networks). Limbic-paralimbic disturbances in patients with FND may represent one of several neurobiological adaptations linked to early, severe and/or prolonged psychosocial adversity. This perspective integrates neurobiological and psychosocial factors in FND and proposes a research agenda, highlighting the need for replication of existing findings, multimodal sampling across emotional response domains and further examination of emotional influences on sensorimotor and cognitive functions in FND populations.

Preictal autonomic dynamics in psychogenic nonepileptic seizures

OBJECTIVES

Psychogenic nonepileptic seizures (PNES) resemble seizures but are psychological in origin. The etiology of PNES remains poorly understood, yet several theories argue for the importance of autonomic dysregulation in its pathophysiology. We therefore conducted a retrospective study to investigate autonomic dynamics leading up to a seizure to inform their mechanistic relevance.

METHODS

One hundred one patients with PNES and 45 patients with epileptic seizure (ES) were analyzed for preictal heart rate (HR) and respiratory rate (RR) at baseline and at minute intervals from 5 min to onset.

RESULTS

Patients with PNES showed rising HR (p < 0.001, repeated-measures analysis of variance (ANOVA)) and rising RR (p = 0.012, repeated-measures ANOVA) from baseline to the onset of their seizures. Patients with ES did not exhibit significant preictal HR or RR increase. Patients with PNES had nonsignificantly higher preictal HR and RR than patients with ES.

SIGNIFICANCE

Patients with PNES exhibit increasing autonomic arousal prior to seizure events unlike patients with epilepsy. This may reflect increasing levels of preictal anxiety, and future studies could study patients' subjective experiences of the preictal period, and more definitive measures of ventilation to see if this supported a model of PNES as "panic without panic".

A unifying conceptual framework of factors associated to cardiac vagal control

Cardiac vagal control (CVC) reflects the activity of the vagus nerve regulating cardiac functioning. CVC can be inferred via heart rate variability measurement, and it has been positively associated to a broad range of cognitive, emotional, social, and health outcomes. It could then be considered as an indicator for effective self-regulation, and given this role, one should understand the factors increasing and decreasing CVC. The aim of this paper is to review the broad range of factors influencing CVC, and to provide a unifying conceptual framework to integrate comprehensively those factors. The structure of the unifying conceptual framework is based on the theory of ecological rationality, while its functional aspects are based on the neurovisceral integration model. The structure of this framework distinguishes two broad areas of associations: person and environment, as this reflects adequately the role played by CVC regarding adaptation. The added value of this framework lies at different levels: theoretically, it allows integrating findings from a variety of scientific disciplines and refining the predictions of the neurovisceral integration model; methodologically, it helps identifying factors that increase and decrease CVC; and lastly at the applied level, it can play an important role for society regarding health policies and for the individual to empower one's flourishing.

Heart rate variability measurement in epilepsy: How can we move from research to clinical practice?

Our objective was to critically evaluate the literature surrounding heart rate variability (HRV) in people with epilepsy and to make recommendations as to how future research could be directed to facilitate and accelerate integration into clinical practice. We reviewed relevant HRV publications including those involving human subjects with seizures. HRV has been studied in patients with epilepsy for more than 30 years and, overall, patients with epilepsy display altered interictal HRV, suggesting a shift in autonomic balance toward sympathetic dominance. This derangement appears more severe in those with temporal lobe epilepsy and drug-resistant epilepsy. Normal diurnal variation in HRV is also disturbed in at least some people with epilepsy, but this aspect has received less study. Some therapeutic interventions, including vagus nerve stimulation and antiepileptic medications, may partially normalize altered HRV, but studies in this area are sometimes contradictory. During seizures, the changes in HRV may be complex, but the general trend is toward a further increase in sympathetic overactivity. Research in HRV in people with epilepsy has been limited by inconsistent experimental protocols and studies that are often underpowered. HRV measurement has the potential to aid clinical epilepsy management in several possible ways. HRV may be useful in predicting which patients are likely to benefit from surgical interventions such as vagus nerve stimulation and focal cerebral resection. As well, HRV could eventually have utility as a biomarker of risk for sudden unexpected death in epilepsy (SUDEP). However, at present, the inconsistent measurement protocols used in research are hindering translation into clinical practice. A minimum protocol for HRV evaluation, to be used in all studies involving epilepsy patients, is necessary to eventually allow HRV to become a useful tool for clinicians. We propose a straightforward protocol, involving 5-minute measurements of root mean square of successive differences in wakefulness and light sleep.

Patient-specific seizure prediction based on heart rate variability and recurrence quantification analysis

Epilepsy is often associated with modifications in autonomic nervous system, which usually precede the onset of seizures of several minutes. Thus, there is a great interest in identifying these modifications enough time in advance to prevent a dangerous effect and to intervene. In addition, these changes can be a risk factor for epileptic patients and can increase the possibility of death. Notably autonomic changes associated to seizures are highly depended of seizure type, localization and lateralization. The aim of this study was to develop a patient-specific approach to predict seizures using electrocardiogram (ECG) features. Specifically, from the RR series, both time and frequency variables and features obtained by the recurrence quantification analysis were used. The algorithm was applied in a dataset of 15 patients with 38 different types of seizures. A feature selection step, was used to identify those features that were more significant in discriminating preictal and interictal phases. A preictal interval of 15 minutes was selected. A support vector machine (SVM) classifier was then built to classify preictal and interictal phases. First, a classifier was set up to classify preictal and interictal segments of each patient and an average sensibility of 89.06% was obtained, with a number of false positive per hour (FP/h) of 0.41. Then, in those patients who had at least 3 seizures, a double-cross-validation approach was used to predict unseen seizures on the basis of a training on previous ones. The results were quite variable according to seizure type, achieving the best performance in patients with more stereotypical seizure. The results of the proposed approach show that it is feasible to predict seizure in advance, considering patient-specific, and possible seizure specific, characteristics.

Psychogenic non-epileptic seizures: aetiology, diagnosis and management

Psychogenic non-epileptic seizures (PNES) have a significant impact on most patients in terms of distress, disability, loss of income and iatrogenic harm. Three-quarters of patients with PNES are initially misdiagnosed and treated for epilepsy. Misdiagnosis exposes patients to multiple iatrogenic harms and prevents them from accessing psychological treatment. In most cases, the patient's history (and witness accounts) should alert clinicians to the likely diagnosis of PNES. Since this diagnosis may be resisted by patients and may involve ‘un-diagnosing’ epilepsy, video-electroencephalogram recording of typical seizures is often helpful. The underlying causes of PNES are diverse: a model combining predisposing, precipitating and perpetuating factors is a useful way of conceptualising their aetiology. The initial step of treatment should be to limit iatrogenic harm. There is some evidence for the effectiveness of psychotherapy.

Biological and perceived stress in motor functional neurological disorders

BACKGROUND

Current models explaining motor functional neurological disorders (FND) integrate both the neurobiological mechanisms underlying symptoms production and the role of psychosocial stressors. Imaging studies have suggested abnormal motor control linked to impaired emotional and stress regulation. However, little is known on the biological stress regulation in FND. Our aim was to study the biological and perceived response to stress in patients with motor FND.

METHODS

Sixteen patients with motor FND (DSM-5 criteria) and fifteen healthy controls underwent the Trier Social Stress Test. Hypothalamo-pituitary-adrenal axis (HPA) response was evaluated with salivary cortisol and autonomous sympathetic response with salivary alpha-amylase. Area under the curve was computed to reflect background levels (AUCg) and change over time (AUCi). Life adversities and perceived subjective stress on a visual analog scale (VAS) were correlated with biological responses.

RESULTS

FND patients had significantly higher background levels (AUCg) of both stress markers (cortisol and amylase) than controls. The biological response (AUCi) to stress did not differ between groups for both markers but the subjective response showed an interaction effect with patients reporting higher levels of stress than controls. After stress, controls showed a strong correlation between subjective and objective sympathetic values (amylase) but not patients. The number and subjective impact of adverse life events correlated with cortisol AUCg in patients only.

CONCLUSION

This study confirms a baseline HPA-axis and sympathetic hyperarousal state in motor FND related to life adversities. During a social stress, dissociation between perceived stress and biological markers was observed in patients only, reflecting a dysregulation of interoception capacity, which might represent an endophenotype of this disorder.

Early Seizure Detection Based on Cardiac Autonomic Regulation Dynamics

Epilepsy is a neurological disorder that causes changes in the autonomic nervous system. Heart rate variability (HRV) reflects the regulation of cardiac activity and autonomic nervous system tone. The early detection of epileptic seizures could foster the use of new treatment approaches. This study presents a new methodology for the prediction of epileptic seizures using HRV signals. Eigendecomposition of HRV parameter covariance matrices was used to create an input for a support vector machine (SVM)-based classifier. We analyzed clinical data from 12 patients (9 female; 3 male; age 34.5 ± 7.5 years), involving 34 seizures and a total of 55.2 h of interictal electrocardiogram (ECG) recordings. Data from 123.6 h of ECG recordings from healthy subjects were used to test false positive rate per hour (FP/h) in a completely independent data set. Our methodological approach allowed the detection of impending seizures from 5 min to just before the onset of a clinical/electrical seizure with a sensitivity of 94.1%. The FP rate was 0.49 h⁻¹ in the recordings from patients with epilepsy and 0.19 h⁻¹ in the recordings from healthy subjects. Our results suggest that it is feasible to use the dynamics of HRV parameters for the early detection and, potentially, the prediction of epileptic seizures.

Diurnal patterns and relationships between physiological and self-reported stress in patients with epilepsy and psychogenic non-epileptic seizures

PURPOSE

Patients with epilepsy and those with psychogenic non-epileptic seizures (PNES) experience high levels of stress and stress is one of the most frequently self-identified seizure precipitants. Although stress is a multifaceted phenomenon, few studies have systematically examined its different components in patients with seizures. The aim of this study was therefore to describe diurnal patterns of psychological and physiological measures of stress in patients with epilepsy and patients with PNES, and explore their relationships to each other in order to improve our understanding of the mechanisms underlying stress and seizure occurrence in these patients.

METHOD

A range of stress markers including self-reported stress, salivary cortisol, and heart rate variability (HRV) were explored in adult patients with refractory epilepsy (N=22) and those with PNES (N=23) undergoing three- to five-day video-telemetry.

RESULTS

A diurnal pattern was observed in the physiological measures, characterized by higher levels of physiological arousal in the mornings and lower levels at night in both patients with epilepsy and PNES. The physiological measures (cortisol and HRV) were associated with each other in patients with epilepsy; no close relationship was found with self-reported stress in either of the two patient groups.

CONCLUSION

The findings contribute to and expand on previous studies of the patterns of stress in patients with seizures. The results also indicate a discrepancy between patients' physiological responses and their subjective stress perceptions, suggesting that simple self-reports cannot be used as a proxy of physiological arousal in patients with seizures and stress. Stress in these patient groups should be studied using a combination of complementary measures.

Cortical arousal in children and adolescents with functional neurological symptoms during the auditory oddball task

OBJECTIVE

Stress, pain, injury, and psychological trauma all induce arousal-mediated changes in brain network organization. The associated, high level of arousal may disrupt motor-sensory processing and result in aberrant patterns of motor function, including functional neurological symptoms. We used the auditory oddball paradigm to assess cortical arousal in children and adolescents with functional neurological symptom disorder.

METHOD

Electroencephalogram (EEG) data was collected in fifty-seven children and adolescents (41 girls; 16 boys, aged 8.5-18 years) with acute functional neurological symptoms and age- sex- matched controls during a conventional auditory oddball task. The high-resolution fragmentary decomposition technique was used to analyse the amplitude of event-related potentials (ERPs) to target tones at midline sites (Fz, Cz, and Pz).

RESULTS

Compared to age- and sex-matched controls, and across all three midline sites, children and adolescents with functional neurological symptoms showed increased amplitude of all ERP components (P50, N100, P200, N200, and P300) (t-value range 2.28-8.20; p value-range 0.023 to < 0.001) to the emotionally-neutral auditory stimulus.

CONCLUSIONS

Our findings add to a growing literature indicating that a baseline state of high arousal may be a precondition for generating functional neurological symptoms, a finding that helps explain why a range of psychological and physiological stressors can trigger functional neurological symptoms in some patients. Interventions that target cortical arousal may be central to the treatment of paediatric patients with functional neurological symptom disorder.

Explicit Facial Emotion Processing in Patients With Dissociative Seizures

OBJECTIVE

There have, as yet, been few experimental studies of explicit facial affect recognition in patients with dissociative seizures (DS). The aim of the study was to examine explicit recognition and physiological responses to facial expressions in this group, relative to healthy controls.

METHODS

Forty patients with DS and 43 controls completed a computerized test of facial affect recognition, including five basic expressions (happiness, anger, disgust, fear, neutral). Recognition accuracy, emotional intensity judgements, and skin conductance levels and responses were dependent measures. Analyses controlled for a range of potentially confounding variables, including anxiety, depression, and medication effects.

RESULTS

The DS group was less accurate at identifying facial expressions than controls (p = .005, ηp = 0.10). No group difference emerged for intensity judgements (p = .72, ηp = 0.002). Mean skin conductance levels were higher in the DS group relative to controls (p = .046, ηp = 0.053). However, a subgroup of DS patients showed attenuated skin conductance responses to the facial stimuli, compared with controls (p = .015, ηp = 0.18). These differences could not be accounted for by possible confounding variables. Recognition accuracy for neutral faces correlated negatively with trauma scores (r = -0.486, p = .002) and abandonment concerns (r = -0.493, p = .002) in the DS group.

CONCLUSIONS

Patients with DS showed reduced recognition accuracy for facial affect, despite accurately perceiving its intensity. Elevated autonomic arousal may characterize patients with DS in general, alongside reduced phasic autonomic responses to facial expressions in some patients with the disorder.

Impaired resting vagal tone in patients with functional movement disorders

INTRODUCTION

The autonomic nervous system plays an integral role in the maintenance of homeostasis during times of stress. The functioning of the autonomic nervous system in patients with functional movement disorders (FMD) is of particular interest given the hypothesis that converted psychological stress plays a critical role in FMD disease pathogenesis. We sought to investigate autonomic nervous system activity in FMD patients by examining heart rate variability (HRV), a quantitative marker of autonomic function.

METHODS

35 clinically definite FMD patients and 38 age- and sex-matched healthy controls were hospitalized overnight for continuous electrocardiogram recording. Standard time and frequency domain measures of HRV were calculated in the awake and asleep stages. All participants underwent a thorough neuropsychological battery, including the Hamilton Anxiety and Depression scales and the Beck Depression Inventory.

RESULTS

Compared to controls, patients with FMD exhibited decreased root mean square of successive differences between adjacent NN intervals (RMSSD) (p = 0.02), a marker of parasympathetic activity, as well as increased mean heart rate (p = 0.03). These measures did not correlate with the depression and anxiety scores included in our assessment as potential covariates.

CONCLUSION

In this exploratory study, patients with FMD showed evidence of impaired resting state vagal tone, as demonstrated by reduced RMSSD. This decreased vagal tone may reflect increased stress vulnerability in patients with FMD.

Psychological and psychiatric aspects of psychogenic non-epileptic seizures (PNES): A systematic review

Psychogenic non-epileptic seizures (PNES) are common in neurological settings and often associated with considerable distress and disability. The psychological mechanisms underlying PNES are poorly understood and there is a lack of well-established, evidence-based treatments. This paper advances our understanding of PNES by providing a comprehensive systematic review of the evidence pertaining to the main theoretical models of this phenomenon. Methodological quality appraisal and effect size calculation were conducted on one hundred forty empirical studies on the following aspects of PNES: life adversity, dissociation, anxiety, suggestibility, attentional dysfunction, family/relationship problems, insecure attachment, defence mechanisms, somatization/conversion, coping, emotion regulation, alexithymia, emotional processing, symptom modelling, learning and expectancy. Although most of the studies were only of low to moderate quality, some findings are sufficiently consistent to warrant tentative conclusions: (i) physical symptom reporting is elevated in patients with PNES; (ii) trait dissociation and exposure to traumatic events are common but not inevitable correlates of PNES; (iii) there is a mismatch between subjective reports of anxiety and physical arousal during PNES; and (iv) inconsistent findings in this area are likely to be attributable to the heterogeneity of patients with PNES. Empirical, theoretical and clinical implications are discussed.

Autonomic nervous system functioning associated with psychogenic nonepileptic seizures: Analysis of heart rate variability

OBJECTIVE

Psychogenic nonepileptic seizures (PNESs) resemble epileptic seizures but originate from psychogenic rather than organic causes. Patients with PNESs are often unable or unwilling to reflect on underlying emotions. To gain more insight into the internal states of patients during PNES episodes, this study explored the time course of heart rate variability (HRV) measures, which provide information about autonomic nervous system functioning and arousal.

METHODS

Heart rate variability measures were extracted from double-lead electrocardiography data collected during 1-7days of video-electroencephalography monitoring of 20 patients with PNESs, in whom a total number of 118 PNESs was recorded. Heart rate (HR) and HRV measures in time and frequency domains (standard deviation of average beat-to-beat intervals (SDANN), root mean square of successive differences (RMSSD), high-frequency (HF) power, low-frequency (LF) power, and very low-frequency (VLF) power) were averaged over consecutive five-minute intervals. Additionally, quantitative analyses of Poincaré plot parameters (SD1, SD2, and SD1/SD2 ratio) were performed.

RESULTS

In the five-minute interval before PNES, HR significantly (p<0.05) increased (d=2.5), whereas SDANN (d=-0.03) and VLF power (d=-0.05) significantly decreased. During PNES, significant increases in HF power (d=0.0006), SD1 (d=0.031), and SD2 (d=0.016) were observed. In the five-minute interval immediately following PNES, SDANN (d=0.046) and VLF power (d=0.073) significantly increased, and HR (d=-5.1) and SD1/SD2 ratio (d=-0.14) decreased, compared to the interval preceding PNES.

CONCLUSION

The results suggest that PNES episodes are preceded by increased sympathetic functioning, which is followed by an increase in parasympathetic functioning during and after PNES. Future research needs to identify the exact nature of the increased arousal that precedes PNES.

Excitatory and inhibitory conversive experiences: neurobiological features involving positive and negative conversion symptoms

Previous reviews have focused on neurobiological and physiological mechanisms underlying conversion disorder, but they do not usually distinguish between negative and positive conversion symptoms. Some authors have proposed that different phenomena should underlie both situations and that diverse emotion regulation strategies (under- vs. overregulation of affect) should be related to different internal experiences (excitatory experiences with hyperarousal manifestations vs. inhibitory experiences coexisting with hypoarousal states, respectively). After a careful review of the literature, we conclude that there is not a unique theory comprising all findings. Nevertheless, we have also collected some replicated findings that should be salient. Patients manifesting positive conversion symptoms tended to present with limbic hyperfunction, not sufficiently counteracted by prefrontal control. This leads to underregulation of affect mechanisms, increased emotional reactivity and autonomic hyperarousal. The opposite pattern (with a prefrontal overfunction working as a cognitive brake over the limbic system) has been described during negative conversion manifestations. We also highlight the influence of fronto-limbic circuits over cortico-striato-thalamo-cortical circuits’ regulation, whose horizontal and vertical synchronization has been at the spotlight of the genesis of conversion and dissociative disorders.

Biomarkers in the diagnosis and study of psychogenic nonepileptic seizures: A systematic review

OBJECTIVE

Video electroencephalography (vEEG) is the gold-standard method for diagnosing psychogenic nonepileptic seizures (PNES), but such assessment is expensive, unavailable in many centers, requires prolonged hospitalization, and many times is unable to capture an actual seizure episode. This paper systematically reviews other non-vEEG candidate biomarkers that may facilitate both diagnosis and study of PNES as differentiated from epileptic seizures (ES).

METHODS

PubMed database was searched to identify articles between 1980 and 2015 (inclusion: adult PNES population with or without controls, English language; exclusion: review articles, meta-analyses, single case reports).

RESULTS

A total of 49 studies were examined, including neuroimaging, autonomic nervous system, prolactin, other (non-prolactin) hormonal, enzyme, and miscellaneous marker studies. Functional MRI studies have shown PNES is hyperlinked with dissociation and emotional dysregulation centers in the brain, although conflicting findings are seen across studies and none used psychiatric comparators. Heart rate variability suggests increased vagal tone in PNES when compared to ES. Prolactin is elevated in ES but not PNES, although shows low diagnostic sensitivity. Postictal cortisol and creatine kinase are nonspecific. Other miscellaneous biomarkers (neuron specific enolase, brain derived neurotropic factor, ghrelin, leptin, leukocytosis) showed no conclusive evidence of utility. Many studies are limited by lack of psychiatric comparators, size, and other methodological issues.

CONCLUSION

No single biomarker successfully differentiates PNES from ES; in fact, PNES is only diagnosed via the negation of ES. Clinical assessment and rigorous investigation of psychosocial variables specific to PNES remain critical, and subtyping of PNES is warranted. Future investigational and clinical imperatives are discussed.

Progressive development of cardiomyopathy following altered autonomic activity in status epilepticus

Seizures are associated with altered autonomic activity, which has been implicated in the development of cardiac dysfunction and structural damage. This study aimed to investigate the involvement of the autonomic nervous system in seizure-induced cardiomyopathy. Male Sprague-Dawley rats (320–350 g) were implanted with EEG/ECG electrodes to allow simultaneous telemetric recordings during seizures induced by intrahippocampal (2 nmol, 1 μl/min) kainic acid and monitored for 7 days. Seizure activity occurred in conjunction with increased heart rate (20%), blood pressure (25%), and QTc prolongation (15%). This increased sympathetic activity was confirmed by the presence of raised plasma noradrenaline levels at 3 h post-seizure induction. By 48 h post-seizure induction, sympathovagal balance was shifted in favor of sympathetic dominance, as indicated by both heart rate variability (LF/HF ratio of 3.5 ± 1.0) and pharmacological autonomic blockade. Functional cardiac deficits were evident at 7 and 28 days, as demonstrated by echocardiography showing a decreased ejection fraction (14% compared with control, P < 0.05) and dilated cardiomyopathy present at 28 days following seizure induction. Histological changes, including cardiomyocyte vacuolization, cardiac fibrosis, and inflammatory cell infiltration, were evident within 48 h of seizure induction and remained present for up to 28 days. These structural changes most probably contributed to an increased susceptibility to aconitine-induced arrhythmias. This study confirms that prolonged seizure activity results in acute and chronic alterations in cardiovascular control, leading to a deterioration in cardiac structure and function. This study further supports the need for modulation of sympathetic activity as a promising therapeutic approach in seizure-induced cardiomyopathy.

New insights into psychogenic nonepileptic seizures 2011-2014

PURPOSE

There has been a rapid increase in the rate of publications about psychogenic nonepileptic seizures (PNES). This review summarises insights from the 50 most important original articles about PNES published since 2011 and describes the advances made in the understanding of PNES over the last 3 years.

METHOD

We carried out a systematic literature search of all English language publications about PNES published between October 2011 and October 2014 on Scopus, Ovid Medline and Web of Knowledge, and inspected all abstracts. Having excluded all review articles, case reports, conference abstracts, articles exploring PNES in children, and articles not actually focussing on PNES, we considered 150 papers for inclusion in this review. We assessed the quality of the identified studies and used expert judgement to identify the 50 most important publications from the review period and composed a narrative review based on these original papers.

RESULTS

Almost one half of the studies initially identified only provided Class 4 evidence. Recent work has provided more support for a biopsychosocial account of PNES. It has illustrated the heterogeneity of PNES, identifying varying and distinct psychological profiles of individuals with this disorder. These findings suggest that intervention needs to be flexible or adaptive if it is appropriately to target the different mechanisms which may give rise to PNES. Several educational and psychotherapeutic interventions for PNES have been described, but sufficiently powered randomised controlled trials are yet to be undertaken. Recent research using social, economic and quality of life indicators has provided further evidence of the societal and individual burden of PNES.

CONCLUSION

The research into PNES published over the last 3 years has deepened our understanding of the condition as a biopsychosocial disorder which is neither a "physical" nor a "psychological" condition. A number of small studies have demonstrated the potential of educational and psychotherapeutic treatments, but rigorous and sufficiently large trials still need to be conducted to determine the effectiveness of these interventions.

Autonomic changes in psychogenic nonepileptic seizures: toward a potential diagnostic biomarker?

Disturbances of the autonomic nervous system (ANS) are common in neuropsychiatric disorders. Disease specific alterations of both sympathetic and parasympathetic activity can be assessed by heart rate variability (HRV), whereas electrodermal activity (EDA) can assess sympathetic activity. In posttraumatic stress disorder (PTSD), parasympathetic HRV parameters are typically decreased and EDA is increased, whereas in major depressive disorder (MDD) and dissociation, both parasympathetic and sympathetic markers are decreased. ANS abnormalities have also been identified in psychogenic nonepileptic seizures (PNES) by using HRV, indicating lower parasympathetic activity at baseline. In addition to reviewing the current literature on ANS abnormalities in PTSD, MDD, and disorders with prominent dissociation, including borderline personality disorder (BPD), this article also presents data from a pilot study on EDA in patients with PNES. Eleven patients with PNES, during an admission to our epilepsy monitoring unit (EMU), were compared with 9 with generalized tonic-clonic seizures (GTCS). The area under the EDA curve, the number of EDA responses lasting longer than 2 seconds, and the number of EDA surges during sleep (sympathetic sleep storms) were calculated on ictal and interictal days by an automated algorithm. EDA changes in PNES patients did not follow a systematic pattern of sympathetic hyperarousal (like EDA after GTCS) but were more variable. How specific PNES semiologies, and/or underlying neuropsychiatric disorders, may influence ictal and interictal EDA patterns, and lead to a novel diagnostic biomarker remains to be evaluated in future larger studies.