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Purpose: The average delay from first seizure to diagnosis of psychogenic non-epileptic seizures (PNES) is over 7 years. The reason for this delay is not well understood. We hypothesized that a perceived decrease in seizure frequency after starting an anti-seizure medication (ASM) may contribute to longer delays, but the frequency of such a response has not been well established.Methods: Time from onset to diagnosis, medication history and associated seizure frequency was acquired from the medical records of 297 consecutive patients with PNES diagnosed using video-electroencephalographic monitoring. Exponential regression was used to model the effect of medication trials and response on diagnostic delay.Results: Mean diagnostic delay was 8.4 years (min 1 day, max 52 years). The robust average diagnostic delay was 2.8 years (95% CI: 2.2-3.5 years) based on an exponential model as 10 to the mean of log10 delay. Each ASM trial increased the robust average delay exponentially by at least one third of a year (Wald t=3.6, p=0.004). Response to ASM trials did not significantly change diagnostic delay (Wald t=-0.9, p=0.38).Conclusion: Although a response to ASMs was observed commonly in these patients with PNES, the presence of a response was not associated with longer time until definitive diagnosis. Instead, the number of ASMs tried was associated with a longer delay until diagnosis, suggesting that ASM trials were continued despite lack of response. These data support the guideline that patients with seizures should be referred to epilepsy care centers after failure of two medication trials. [ABSTRACT FROM AUTHOR]

Hypersynchronous (HYP) and low voltage fast (LVF) activity are two separate ictal depth EEG onsets patterns often recorded in presurgical patients with MTLE. Evidence suggests the mechanisms generating HYP and LVF onset seizures are distinct, including differential involvement of hippocampal and extra-hippocampal sites. Yet the extent of extra-hippocampal structural alterations, which could support these two common seizures, is not known. In the current study, preoperative MRI from 24 patients with HYP or LVF onset seizures were analyzed to determine changes in cortical thickness and relate structural changes to spatiotemporal properties of the ictal EEG. Overall, onset and initial ipsilateral spread of HYP onset seizures involved mesial temporal structures, whereas LVF onset seizures involved mesial and lateral temporal as well as orbitofrontal cortex. MRI analysis found reduced cortical thickness correlated with longer duration of epilepsy. However, in patients with HYP onsets, the most affected areas were on the medial surface of each hemisphere, including parahippocampal regions and cingulate gyrus, whereas in patients with LVF onsets, the lateral surface of the anterior temporal lobe and orbitofrontal cortex showed the greatest effect. Most patients with HYP onset seizures were seizure-free after resective surgery, while a higher proportion of patients with LVF onset seizures had only worthwhile improvement. Our findings confirm the view that recurrent seizures cause progressive changes in cortical thickness, and provide information concerning the structural basis of two different epileptogenic networks responsible for MTLE. One, identified by HYP ictal onsets, chiefly involves hippocampus and is associated with excellent outcome after standardized anteromedial temporal resection, while the other also involves lateral temporal and orbitofrontal cortex and a seizure-free surgical outcome occurs less after this procedure. These results suggest that a more extensive tailored resection may be required for patients with the second type of MTLE. [ABSTRACT FROM AUTHOR]

In the majority of neuropsychiatric conditions, marked gender-based differences have been found in the epidemiology, clinical manifestations, and therapy of disease. One possible reason is that sex differences in cerebral morphology, structural and functional connections, render men and women differentially vulnerable to various disease processes. The present review addresses this issue with respect to the functional and structural correlates to some forms of epilepsy. [ABSTRACT FROM AUTHOR]

Alterations in both structural connectivity (SC) and functional connectivity (FC) have been reported in temporal lobe epilepsy (TLE). However, the relationship between FC and SC remains less understood. This study used functional connectivity MRI and diffusion tensor imaging to examine coupling of FC and SC within the limbic network of TLE, as well as its relation to epilepsy duration, regional changes, and disease laterality in 14 patients with left TLE, 10 with right TLE, and 11 healthy controls. Structural and functional networks were separately constructed and the correlation estimated between structural and functional connectivity. This measure of SC–FC coupling was compared between left/right TLE and controls, and correlated with epilepsy duration. Elastic net regression was used to investigate regional structural and functional changes associated with SC–FC coupling. SC–FC coupling was decreased in left TLE compared to controls, and accompanied by reductions in FC for left and right TLE and in SC for left TLE. When examined in relation to disease duration, an increase in SC–FC coupling with longer epilepsy duration was observed, associated predominantly with structural loss of the fusiform and frontal inferior orbital gyrus in left TLE and functional hub redistribution in right TLE. These results suggest that decoupling between structural and functional networks in TLE is modulated by several factors, including epilepsy duration and regional changes in the fusiform, frontal inferior orbital gyrus, posterior cingulate, and hippocampus. SC–FC coupling may provide a more sensitive biomarker of disease burden in TLE than biomarkers based on single imaging modalities. [ABSTRACT FROM AUTHOR]

Summary Purpose To investigate lateralized differences in limbic system functional connectivity between left and right temporal lobe epilepsy (TLE) using graph theory. Methods Interictal resting state fMRI was performed in 14 left TLE patients, 11 right TLE patients, and 12 controls. Graph theory analysis of 10 bilateral limbic regions of interest was conducted. Changes in edgewise functional connectivity, network topology, and regional topology were quantified, and then left and right TLE were compared. Results Limbic edgewise functional connectivity was predominantly reduced in both left and right TLE. More regional connections were reduced in right TLE, most prominently involving reduced interhemispheric connectivity between the bilateral insula and bilateral hippocampi. A smaller number of limbic connections were increased in TLE, more so in left than in right TLE. Topologically, the most pronounced change was a reduction in average network betweenness centrality and concurrent increase in left hippocampal betweenness centrality in right TLE. In contrast, left TLE exhibited a weak trend toward increased right hippocampal betweenness centrality, with no change in average network betweenness centrality. Conclusion Limbic functional connectivity is predominantly reduced in both left and right TLE, with more pronounced reductions in right TLE. In contrast, left TLE exhibits both edgewise and topological changes that suggest a tendency toward reorganization. Network changes in TLE and lateralized differences thereof may have important diagnostic and prognostic implications. [ABSTRACT FROM AUTHOR]

Objective Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic. Methods Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews. Results The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70–79%) and prospective specificity of 71% (95% CI: 64–82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20 years, age of onset after 31 years for men, and age of onset after 40 years for women had no additional effect on the likelihood of PNES. Discussion Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men. [ABSTRACT FROM AUTHOR]

Objective To develop and validate a detector that identifies ripple (80–200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). Methods iEEG recordings from 16 patients were first band-pass filtered (80–600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. Results The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). Conclusions Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Significance Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers. [ABSTRACT FROM AUTHOR]

Objective To develop a reliable software method using a topographic analysis of time-frequency plots to distinguish ripple (80–200 Hz) oscillations that are often associated with EEG sharp waves or spikes (RonS) from sinusoid-like waveforms that appear as ripples but correspond with digital filtering of sharp transients contained in the wide bandwidth EEG. Methods A custom algorithm distinguished true from false ripples in one second intracranial EEG (iEEG) recordings using wavelet convolution, identifying contours of isopower, and categorizing these contours into sets of open or closed loop groups. The spectral and temporal features of candidate groups were used to classify the ripple, and determine its duration, frequency, and power. Verification of detector accuracy was performed on the basis of simulations, and visual inspection of the original and band-pass filtered signals. Results The detector could distinguish simulated true from false ripple on spikes (RonS). Among 2934 visually verified trials of iEEG recordings and spectrograms exhibiting RonS the accuracy of the detector was 88.5% with a sensitivity of 81.8% and a specificity of 95.2%. The precision was 94.5% and the negative predictive value was 84.0% (N = 12). Among, 1,370 trials of iEEG recording exhibiting RonS that were reviewed blindly without spectrograms the accuracy of the detector was 68.0%, with kappa equal to 0.01 ± 0.03. The detector successfully distinguished ripple from high spectral frequency ‘fast ripple’ oscillations (200–600 Hz), and characterize ripple duration and spectral frequency and power. The detector was confounded by brief bursts of gamma (30–80 Hz) activity in 7.31 ± 6.09% of trials, and in 30.2 ± 14.4% of the true RonS detections ripple duration was underestimated. Conclusions Characterizing the topographic features of a time-frequency plot generated by wavelet convolution is useful for distinguishing true oscillations from false oscillations generated by filter ringing. Significance Categorizing ripple oscillations and characterizing their properties can improve the clinical utility of the biomarker. [ABSTRACT FROM AUTHOR]

Objective Early and accurate diagnosis of patients with psychogenic nonepileptic seizures (PNES) leads to appropriate treatment and improves long-term seizure prognosis. However, this is complicated by the need to record seizures to make a definitive diagnosis. Suspicion for PNES can be raised through knowledge that patients with PNES have increased somatic sensitivity and report more positive complaints on review-of-systems questionnaires (RoSQs) than patients with epileptic seizures. If the responses on the RoSQ can differentiate PNES from other seizure types, then these forms could be an early screening tool. Methods Our dataset included all patients admitted from January 2006 to June 2016 for video-electroencephalography at UCLA. RoSQs prior to May 2015 were acquired through retrospective chart review (n = 405), whereas RoSQs from subsequent patients were acquired prospectively (n = 190). Controlling for sex and number of comorbidities, we used binomial regression to compare the total number of symptoms and the frequency of specific symptoms between five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of RoSQs to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and the number of medical comorbidities. Results On average, patients with PNES or mixed PNES and ES reported more than twice as many symptoms than patients with isolated ES or PSLE (p < 0.001). The prospective accuracy to differentiate PNES from ES was not significantly higher than naïve assumption that all patients had ES (76% vs 70%, p > 0.1). Discussion This analysis of RoSQs confirms that patients with PNES with and without comorbid ES report more symptoms on a population level than patients with epilepsy or PSLE. While these differences help describe the population of patients with PNES, the consistency of RoSQ responses was neither accurate nor specific enough to be used solely as an early screening tool for PNES. Our results suggest that the RoSQ may help differentiate PNES from ES only when, based on other information, the pre-test probability of PNES is at least 50%. [ABSTRACT FROM AUTHOR]

Epilepsy is both a disease of the brain and the mind. Here, we present the first of two papers with extended summaries of selected presentations of the Third International Congress on Epilepsy, Brain and Mind (April 3–5, 2014; Brno, Czech Republic). Epilepsy in history and the arts and its relationships with religion were discussed, as were overviews of epilepsy and relevant aspects of social cognition, handedness, accelerated forgetting and autobiographical amnesia, and large-scale brain networks. [ABSTRACT FROM AUTHOR]

Temporal lobe epilepsy (TLE) is often associated with progressive changes to seizures, memory, and mood during its clinical course. However, the cerebral changes related to this progression are not well understood. Because the changes may be related to changes in brain networks, we used functional connectivity MRI (fcMRI) to determine whether brain network parameters relate to the duration of TLE. Graph theory-based analysis of the sites of reported regions of TLE abnormality was performed on resting-state fMRI data in 48 subjects: 24 controls, 13 patients with left TLE, and 11 patients with right TLE. Various network parameters were analyzed including betweenness centrality (BC), clustering coefficient (CC), path length (PL), small-world index (SWI), global efficiency (GE), connectivity strength (CS), and connectivity diversity (CD). These were compared for patients with TLE as a group, compared to controls, and for patients with left and right TLE separately. The association of changes in network parameters with epilepsy duration was also evaluated. We found that CC, CS, and CD decreased in subjects with TLE compared to control subjects. Analyzed according to epilepsy duration, patients with TLE showed a progressive reduction in CD. In conclusion, we found that several network parameters decreased in patients with TLE compared to controls, which suggested reduced connectivity in TLE. Reduction in CD associated with epilepsy duration suggests a homogenization of connections over time in TLE, indicating a reduction of the normal repertoire of stronger and weaker connections to other brain regions. [ABSTRACT FROM AUTHOR]