Richard H.C. Lazeron

Functional connectivity of dissociation in patients with psychogenic non-epileptic seizures.

Introduction Psychogenic non-epileptic seizures (PNES) resemble epileptic seizures, but lack epileptiform brain activity. Instead, the cause is assumed to be psychogenic. An abnormal coping strategy may be exhibited by PNES patients, as indicated by their increased tendency to dissociate. Investigation of resting-state networks may reveal altered routes of information and emotion processing in PNES patients. The authors therefore investigated whether PNES patients differ from healthy controls in their resting-state functional connectivity characteristics and whether these connections are associated with the tendency to dissociate. Methods 11 PNES patients without psychiatric comorbidity and 12 healthy controls underwent task-related paradigms (picture-encoding and Stroop paradigms) and resting-state functional MRI (rsfMRI). Global cognitive performance was tested using the Ravens Matrices test and participants completed questionnaires for evaluating dissociation. Functional connectivity analysis on rsfMRI was based on seed regions extracted from task-related fMRI activation maps. Results The patients displayed a significantly lower cognitive performance and significantly higher dissociation scores. No significant differences were found between the picture-encoding and Stroop colour-naming activation maps between controls and patients with PNES. However, functional connectivity maps from the rsfMRI were statistically different. For PNES patients, stronger connectivity values between areas involved in emotion (insula), executive control (inferior frontal gyrus and parietal cortex) and movement (precentral sulcus) were observed, which were significantly associated with dissociation scores. Conclusion The abnormal, strong functional connectivity in PNES patients provides a neurophysiological correlate for the underlying psychoform and somatoform dissociation mechanism where emotion can influence executive control, resulting in altered motor function (eg, seizure-like episodes).

Resting-state networks and dissociation in psychogenic non-epileptic seizures

OBJECTIVE Psychogenic non-epileptic seizures (PNES) are epilepsy-like episodes which have an emotional rather than organic origin. Although PNES have often been related to the process of dissociation, the psychopathology is still poorly understood. To elucidate underlying mechanisms, the current study applied independent component analysis (ICA) on resting-state fMRI to investigate alterations within four relevant networks, associated with executive, fronto-parietal, sensorimotor, and default mode activation, and within a visual network to examine specificity of between-group differences. METHODS Twenty-one patients with PNES without psychiatric or neurologic comorbidities and twenty-seven healthy controls underwent resting-state functional MR imaging at 3.0T (Philips Achieva). Additional neuropsychological testing included Ravens Matrices test and dissociation questionnaires. ICA with dual regression was used to identify resting-state networks in all participants, and spatial maps of the networks of interest were compared between patients and healthy controls. RESULTS Patients displayed higher dissociation scores, lower cognitive performance and increased contribution of the orbitofrontal, insular and subcallosal cortex in the fronto-parietal network; the cingulate and insular cortex in the executive control network; the cingulate gyrus, superior parietal lobe, pre- and postcentral gyri and supplemental motor cortex in the sensorimotor network; and the precuneus and (para-) cingulate gyri in the default-mode network. The connectivity strengths within these regions of interest significantly correlated with dissociation scores. No between-group differences were found within the visual network, which was examined to determine specificity of between-group differences. CONCLUSIONS PNES patients displayed abnormalities in several resting-state networks that provide neuronal correlates for an underlying dissociation mechanism.

Neurophysiological correlates of dissociative symptoms

Objective Dissociation is a mental process with psychological and somatoform manifestations, which is closely related to hypnotic suggestibility and essentially shows the ability to obtain distance from reality. An increased tendency to dissociate is a frequently reported characteristic of patients with functional neurological symptoms and syndromes (FNSS), which account for a substantial part of all neurological admissions. This review aims to investigate what heart rate variability (HRV), EEG and neuroimaging data (MRI) reveal about the nature of dissociation and related conditions. Methods Studies reporting HRV, EEG and neuroimaging data related to hypnosis, dissociation and FNSS were identified by searching the electronic databases Pubmed and ScienceDirect. Results The majority of the identified studies concerned the physiological characteristics of hypnosis; relatively few investigations on dissociation related FNSS were identified. General findings were increased parasympathetic functioning during hypnosis (as measured by HRV), and lower HRV in patients with FNSS. The large variety of EEG and functional MRI investigations with diverse results challenges definite conclusions, but evidence suggests that subcortical as well as (pre)frontal regions serve emotion regulation in dissociative conditions. Functional connectivity analyses suggest the presence of altered brain networks in patients with FNSS, in which limbic areas have an increased influence on motor preparatory regions. Conclusions HRV, EEG and (functional) MRI are sensitive methods to detect physiological changes related to dissociation and dissociative disorders such as FNSS, and can possibly provide more information about their aetiology. The use of such measures could eventually provide biomarkers for earlier identification of patients at risk and appropriate treatment of dissociative conditions.

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.

Glutamate concentrations vary with antiepileptic drug use and mental slowing

OBJECTIVE Although antiepileptic drugs (AEDs) are effective in suppressing epileptic seizures, they also induce (cognitive) side effects, with mental slowing as a general effect. This study aimed to assess whether concentrations of MR detectable neurotransmitters, glutamate and GABA, are associated with mental slowing in patients with epilepsy taking AEDs. METHODS Cross-sectional data were collected from patients with localization-related epilepsy using a variety of AEDs from three risk categories, i.e., AEDs with low, intermediate, and high risks of developing cognitive problems. Patients underwent 3T MR spectroscopy, including a PRESS (n=55) and MEGA-PRESS (n=43) sequence, to estimate occipital glutamate and GABA concentrations, respectively. The association was calculated between neurotransmitter concentrations and central information processing speed, which was measured using the Computerized Visual Searching Task (CVST) and compared between the different risk categories. RESULTS Combining all groups, patients with lower processing speeds had lower glutamate concentrations. Patients in the high-risk category had a lower glutamate concentration and lower processing speed compared with patients taking low-risk AEDs. Patients taking intermediate-risk AEDs also had a lower glutamate concentration compared with patients taking low-risk AEDs, but processing speed did not differ significantly between those groups. No associations were found between the GABA concentration and risk category or processing speed. CONCLUSIONS For the first time, a relation is shown between glutamate concentration and both mental slowing and AED use. It is suggested that the reduced excitatory action, reflected by lowered glutamate concentrations, may have contributed to the slowing of information processing in patients using AEDs with higher risks of cognitive side effects.

Multimodal seizure detection : A review

A review is given on the combined use of multiple modalities in non electroencephalography (EEG)‐based detection of motor seizures in children and adults. A literature search of papers was done on multimodal seizure detection with extraction of data on type of modalities, study design and algorithm, sensitivity, false detection rate, and seizure types. Evidence of superiority was sought for using multiple instead of single modalities. Seven papers were found from 2010 to 2017, mostly using contact sensors such as accelerometers (n = 5), electromyography (n = 2), heart rate (n = 2), electrodermal activity (n = 1), and oximetry (n = 1). Remote sensors included video, radar, movement, and sound. All studies but one were in‐hospital, with video‐EEG as a gold standard. Algorithms were based on physiology and supervised machine learning, but did not always include a separate test dataset. Sensitivity ranged from 4% to 100% and false detection rate from 0.25 to 20 per 8 hours. Tonic–clonic seizure detection performed best. False detections tended to be restricted to a minority (16%‐30%) of patients. Use of multiple sensors increased sensitivity; false detections decreased in one study, but increased in another.

Chronic antiepileptic drug use and functional network efficiency: A functional magnetic resonance imaging study

AIM To increase our insight in the neuronal mechanisms underlying cognitive side-effects of antiepileptic drug (AED) treatment. METHODS The relation between functional magnetic resonance-acquired brain network measures, AED use, and cognitive function was investigated. Three groups of patients with epilepsy with a different risk profile for developing cognitive side effects were included: A “low risk” category (lamotrigine or levetiracetam, n = 16), an “intermediate risk” category (carbamazepine, oxcarbazepine, phenytoin, or valproate, n = 34) and a “high risk” category (topiramate, n = 5). Brain connectivity was assessed using resting state functional magnetic resonance imaging and graph theoretical network analysis. The Computerized Visual Searching Task was used to measure central information processing speed, a common cognitive side effect of AED treatment. RESULTS Central information processing speed was lower in patients taking AEDs from the intermediate and high risk categories, compared with patients from the low risk category. The effect of risk category on global efficiency was significant (P < 0.05, ANCOVA), with a significantly higher global efficiency for patient from the low category compared with the high risk category (P < 0.05, post-hoc test). Risk category had no significant effect on the clustering coefficient (ANCOVA, P > 0.2). Also no significant associations between information processing speed and global efficiency or the clustering coefficient (linear regression analysis, P > 0.15) were observed. CONCLUSION Only the four patients taking topiramate show aberrant network measures, suggesting that alterations in functional brain network organization may be only subtle and measureable in patients with more severe cognitive side effects.

Psychogenic nonepileptic seizures in adults with epilepsy and intellectual disability: a neglected area

PURPOSE To describe the main characteristics of psychogenic nonepileptic seizures (PNES) in adults with epilepsy and intellectual disability (ID), and to analyse the differences regarding psychosocial functioning, epilepsy severity and ID between patients with PNES and a control group without PNES. METHODS Medical records of adults with ID and epilepsy living at an epilepsy care facility (N = 240) were screened for PNES and evaluated by a neurologist. A control group consisting of patients with epilepsy and ID, without PNES, was matched according to age, sex and level of ID. Characteristics of PNES and epilepsy were provided by the subjects nursing staff or retrieved from patient charts, psychosocial data were collected by standardised questionnaires and level of ID was individually assessed using psychometric instruments. RESULTS The point prevalence of PNES was 7.1%. The patients with PNES (n = 15) were most often female and had a mild or moderate level of ID. Compared to controls, they showed more depressive symptoms, experienced more negative life events and had more often an ID discrepancy (ID profile with one domain particularly more impaired than another). Stress-related triggers were recognised in a large majority by the nursing staff. CONCLUSION PNES appears to be a relatively rare diagnostic entity among inpatients with both epilepsy and ID. However, the complexity of diagnosing PNES in this population, and the similarities in stress-related triggers for PNES in patients with and without ID, suggest that PNES may be underdiagnosed in the ID population. Diagnostic challenges of PNES and, as subcategory, reinforced behavioural patterns are discussed.