Kempenhaeghe

Heeze, Netherlands

Kempenhaeghe

Heeze, Netherlands
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de Munck J.C.,VU University Amsterdam | van Houdt P.J.,VU University Amsterdam | Goncalves S.I.,University of Coimbra | van Wegen E.,VU University Amsterdam | Ossenblok P.P.W.,Kempenhaeghe
NeuroImage | Year: 2013

Co-registered EEG and functional MRI (EEG/fMRI) is a potential clinical tool for planning invasive EEG in patients with epilepsy. In addition, the analysis of EEG/fMRI data provides a fundamental insight into the precise physiological meaning of both fMRI and EEG data. Routine application of EEG/fMRI for localization of epileptic sources is hampered by large artefacts in the EEG, caused by switching of scanner gradients and heartbeat effects. Residuals of the ballistocardiogram (BCG) artefacts are similarly shaped as epileptic spikes, and may therefore cause false identification of spikes. In this study, new ideas and methods are presented to remove gradient artefacts and to reduce BCG artefacts of different shapes that mutually overlap in time.Gradient artefacts can be removed efficiently by subtracting an average artefact template when the EEG sampling frequency and EEG low-pass filtering are sufficient in relation to MR gradient switching (Gonçalves et al., 2007). When this is not the case, the gradient artefacts repeat themselves at time intervals that depend on the remainder between the fMRI repetition time and the closest multiple of the EEG acquisition time. These repetitions are deterministic, but difficult to predict due to the limited precision by which these timings are known. Therefore, we propose to estimate gradient artefact repetitions using a clustering algorithm, combined with selective averaging. Clustering of the gradient artefacts yields cleaner EEG for data recorded during scanning of a 3. T scanner when using a sampling frequency of 2048. Hz. It even gives clean EEG when the EEG is sampled with only 256. Hz.Current BCG artefacts-reduction algorithms based on average template subtraction have the intrinsic limitation that they fail to deal properly with artefacts that overlap in time. To eliminate this constraint, the precise timings of artefact overlaps were modelled and represented in a sparse matrix. Next, the artefacts were disentangled with a least squares procedure. The relevance of this approach is illustrated by determining the BCG artefacts in a data set consisting of 29 healthy subjects recorded in a 1.5. T scanner and 15 patients with epilepsy recorded in a 3. T scanner. Analysis of the relationship between artefact amplitude, duration and heartbeat interval shows that in 22% (1.5. T data) to 30% (3. T data) of the cases BCG artefacts show an overlap. The BCG artefacts of the EEG/fMRI data recorded on the 1.5. T scanner show a small negative correlation between HBI and BCG amplitude.In conclusion, the proposed methodology provides a substantial improvement of the quality of the EEG signal without excessive computer power or additional hardware than standard EEG-compatible equipment. © 2012 Elsevier Inc.


van Houdt P.J.,Kempenhaeghe | van Houdt P.J.,VU University Amsterdam | Ossenblok P.P.W.,Kempenhaeghe | Colon A.J.,Kempenhaeghe | And 2 more authors.
NeuroImage | Year: 2012

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings.For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients.The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery. © 2012 Elsevier Inc..


van Houdt P.J.,Kempenhaeghe | van Houdt P.J.,VU University Amsterdam | de Munck J.C.,VU University Amsterdam | Leijten F.S.S.,University Utrecht | And 4 more authors.
NeuroImage | Year: 2013

EEG-correlated functional MRI (EEG-fMRI) visualizes brain regions associated with interictal epileptiform discharges (IEDs). This technique images the epileptiform network, including multifocal, superficial and deeply situated cortical areas. To understand the role of EEG-fMRI in presurgical evaluation, its results should be validated relative to a gold standard. For that purpose, EEG-fMRI data were acquired for a heterogeneous group of surgical candidates (n = 16) who were later implanted with subdural grids and strips (ECoG). The EEG-fMRI correlation patterns were systematically compared with brain areas involved in IEDs ECoG, using a semi-automatic analysis method, as well as to the seizure onset zone, resected area, and degree of seizure freedom. In each patient at least one of the EEG-fMRI areas was concordant with an interictally active ECoG area, always including the early onset area of IEDs in the ECoG data. This confirms that EEG-fMRI reflects a pattern of onset and propagation of epileptic activity. At group level, 76% of the BOLD regions that were covered with subdural grids, were concordant with interictally active ECoG electrodes. Due to limited spatial sampling, 51% of the BOLD regions were not covered with electrodes and could, therefore, not be validated. From an ECoG perspective it appeared that 29% of the interictally active ECoG regions were missed by EEG-fMRI and that 68% of the brain regions were correctly identified as inactive with EEG-fMRI. Furthermore, EEG-fMRI areas included the complete seizure onset zone in 83% and resected area in 93% of the data sets. No clear distinction was found between patients with a good or poor surgical outcome: in both patient groups, EEG-fMRI correlation patterns were found that were either focal or widespread. In conclusion, by comparison of EEG-fMRI with interictal invasive EEG over a relatively large patient population we were able to show that the EEG-fMRI correlation patterns are spatially accurate at the level of neurosurgical units (i.e. anatomical brain regions) and reflect the underlying network of IEDs. Therefore, we expect that EEG-fMRI can play an important role for the determination of the implantation strategy. © 2013 Elsevier Inc.


Ryvlin P.,University Claude Bernard Lyon 1 | Gilliam F.G.,Pennsylvania State University | Nguyen D.K.,University of Notre Dame | Colicchio G.,Catholic University of the Sacred Heart | And 12 more authors.
Epilepsia | Year: 2014

Objective To evaluate whether vagus nerve stimulation (VNS) as adjunct to best medical practice (VNS + BMP) is superior to BMP alone in improving long-term health-related quality of life (HRQoL). Methods PuLsE (Open Prospective Randomized Long-term Effectiveness) was a prospective, randomized, parallel-group, open-label, and long-term effectiveness study (conducted at 28 sites in Europe and Canada). Adults with pharmacoresistant focal seizures (n = 112) received VNS + BMP or BMP (1:1 ratio). Medications and VNS parameters could be adjusted as clinically indicated for optimal seizure control while minimizing adverse effects. Primary endpoint was mean change from baseline HRQoL (using Quality of Life in Epilepsy Inventory-89 total score; QOLIE-89). Secondary endpoints included changes in seizure frequency, responder rate (≥50% decrease in seizure frequency), Centre for Epidemiologic Studies Depression scale (CES-D), Neurological Disorders Depression Inventory-Epilepsy scale (NDDI-E), Clinical Global Impression-Improvement scale (CGI-I), Adverse Event Profile (AEP), and antiepileptic drug (AED) load. The study was prematurely terminated due to recruitment difficulties prior to completing the planned enrollment of n = 362. Results for n = 96 who had baseline and at least one follow-up QOLIE-89 assessment (from months 3-12) were included in this analysis. Mixed model repeated measures (MMRM) analysis of variance was performed on change from baseline for the primary and secondary endpoints. Results Significant between-group differences in favor of VNS + BMP were observed regarding improvement in HRQoL, seizure frequency, and CGI-I score (respective p-values < 0.05, 0.03, and 0.01). More patients in the VNS + BMP group (43%) reported adverse events (AEs) versus BMP group (21%) (p = 0.01), a difference reflecting primarily mostly transient AEs related to VNS implantation or stimulation. No significant difference between treatment groups was observed for changes in CES-D, NDDI-E, AEP, and AED load. Significance VNS therapy as a treatment adjunct to BMP in patients with pharmacoresistant focal seizures was associated with a significant improvement in HRQoL compared with BMP alone. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here. © 2014 The Authors Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.


Van Houdt P.J.,Epilepsy Center Kempenhaeghe | Van Houdt P.J.,VU University Amsterdam | Ossenblok P.P.W.,Kempenhaeghe | Boon P.A.J.M.,Epilepsy Center Kempenhaeghe | And 4 more authors.
Human Brain Mapping | Year: 2010

EEG correlated functional MRI (EEG-fMRI) allows the delineation of the areas corresponding to spontaneous brain activity, such as epileptiform spikes or alpha rhythm. A major problem of fMRI analysis in general is that spurious correlations may occur because fMRI signals are not only correlated with the phenomena of interest, but also with physiological processes, like cardiac and respiratory functions. The aim of this study was to reduce the number of falsely detected activated areas by taking the variation in physiological functioning into account in the general linear model (GLM). We used the photoplethysmogram (PPG), since this signal is based on a linear combination of oxy- and deoxyhemoglobin in the arterial blood, which is also the basis of fMRI. We derived a regressor from the variation in pulse height (VIPH) of PPG and added this regressor to the GLM. When this regressor was used as predictor it appeared that VIPH explained a large part of the variance of fMRI signals acquired from five epilepsy patients and thirteen healthy volunteers. As a confounder VIPH reduced the number of activated voxels by 30% for the healthy volunteers, when studying the generators of the alpha rhythm. Although for the patients the number of activated voxels either decreased or increased, the identification of the epileptogenic zone was substantially enhanced in one out of five patients, whereas for the other patients the effects were smaller. In conclusion, applying VIPH as a confounder diminishes physiological noise and allows a more reliable interpretation of fMRI results. © 2009 Wiley-Liss, Inc.


Boets B.,Catholic University of Leuven | Boets B.,Massachusetts Institute of Technology | Verhoeven J.,Kempenhaeghe | Verhoeven J.,Catholic University of Leuven | And 2 more authors.
Journal of Autism and Developmental Disorders | Year: 2015

We investigated low-level auditory spectral and temporal processing in adolescents with autism spectrum disorder (ASD) and early language delay compared to matched typically developing controls. Auditory measures were designed to target right versus left auditory cortex processing (i.e. frequency discrimination and slow amplitude modulation (AM) detection versus gap-in-noise detection and faster AM detection), and to pinpoint the task and stimulus characteristics underlying putative superior spectral processing in ASD. We observed impaired frequency discrimination in the ASD group and suggestive evidence of poorer temporal resolution as indexed by gap-in-noise detection thresholds. These findings question the evidence of enhanced spectral sensitivity in ASD and do not support the hypothesis of superior right and inferior left hemispheric auditory processing in ASD. © 2014, Springer Science+Business Media New York.


PubMed | Kempenhaeghe, Stichting Epilepsie Instellingen Nederland and TU Eindhoven
Type: | Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology | Year: 2017

Diagnostic value and efficacy of re-interpretation of previous EEGs in 100 patients admitted to a tertiary epilepsy center with EEG results conflicting with the clinical diagnosis after the first visit.EEGs were reclassified. A matched control group was included to assess the efficiency of the re-interpretation process. Efficacy was assessed by questionnaires and costs as number of technician hours needed.In 85 patients the previous EEG conclusion was known. In 43 the conclusion was altered. In 23 the epileptic activity changed from positive to negative (17) or the reverse (6). In 15 the focus changed (7 originally classified as generalized epileptic activity). In 5 the syndrome changed. 57% of the re-interpretation group needed no extra EEG afterwards. 96% of the re-interpretations were considered useful by requesting and 72% by not involved neurologists. The average time per EEG technologist per patient was 8,81h in controls and 5,40 in the re-interpretation group.In 43 from the 85 patients (51%) re-interpretation of controversial EEGs led to a different opinion. The re-interpretations were useful and less time consuming, compared to new EEGs in controls.Re-interpretation of controversial EEGs is useful and cost effective.


Van Liempt S.,Research Center Military Mental Healthcare | Van Liempt S.,Rudolf Magnus Institute of Neuroscience | Vermetten E.,Research Center Military Mental Healthcare | Lentjes E.,University Utrecht | And 2 more authors.
Psychoneuroendocrinology | Year: 2011

Background: Healthy sleep facilitates the consolidation of newly acquired memories. Although patients with posttraumatic stress disorder (PTSD) often complain of sleep disturbances and memory deficits, the interrelatedness of these symptoms is not well understood. Sleep may be disturbed in PTSD by increased awakenings during sleep, which has been associated with decreased growth hormone (GH) secretion. We conducted a controlled study in which we assessed sleep fragmentation, nocturnal secretion of GH, and memory consolidation in patients with PTSD. Methods: While sleep EEG was being monitored, 13 veterans with PTSD, 15 trauma controls (TC) and 15 healthy controls (HC) slept with an iv catheter, through which blood was collected every 20. min from 23:00. h to 08:00. h. Declarative memory encoding was assessed with the 15 word task before sleep, and consolidation was assessed the next morning by a free recall. Results: Sleep was more fragmented in patients with PTSD, with more awakenings in the first half of the night (p<0.05). Plasma levels of GH during the night were significantly decreased in PTSD compared with HC (p<0.05). Furthermore, GH secretion and awakenings were independent predictors for delayed recall, which was lower in PTSD compared to HC (p<0.05). Conclusions: These data show that PTSD is associated with increased awakenings during sleep and decreased nocturnal GH secretion. Furthermore, decreased GH secretion may be related to sleep fragmentation and both variables may exert a negative effect on sleep dependent memory consolidation. © 2011 Elsevier Ltd.


EEG-correlated functional MRI (EEG-fMRI) visualizes brain regions associated with interictal epileptiform discharges (IEDs). This technique images the epileptiform network, including multifocal, superficial and deeply situated cortical areas. To understand the role of EEG-fMRI in presurgical evaluation, its results should be validated relative to a gold standard. For that purpose, EEG-fMRI data were acquired for a heterogeneous group of surgical candidates (n=16) who were later implanted with subdural grids and strips (ECoG). The EEG-fMRI correlation patterns were systematically compared with brain areas involved in IEDs ECoG, using a semi-automatic analysis method, as well as to the seizure onset zone, resected area, and degree of seizure freedom. In each patient at least one of the EEG-fMRI areas was concordant with an interictally active ECoG area, always including the early onset area of IEDs in the ECoG data. This confirms that EEG-fMRI reflects a pattern of onset and propagation of epileptic activity. At group level, 76% of the BOLD regions that were covered with subdural grids, were concordant with interictally active ECoG electrodes. Due to limited spatial sampling, 51% of the BOLD regions were not covered with electrodes and could, therefore, not be validated. From an ECoG perspective it appeared that 29% of the interictally active ECoG regions were missed by EEG-fMRI and that 68% of the brain regions were correctly identified as inactive with EEG-fMRI. Furthermore, EEG-fMRI areas included the complete seizure onset zone in 83% and resected area in 93% of the data sets. No clear distinction was found between patients with a good or poor surgical outcome: in both patient groups, EEG-fMRI correlation patterns were found that were either focal or widespread. In conclusion, by comparison of EEG-fMRI with interictal invasive EEG over a relatively large patient population we were able to show that the EEG-fMRI correlation patterns are spatially accurate at the level of neurosurgical units (i.e. anatomical brain regions) and reflect the underlying network of IEDs. Therefore, we expect that EEG-fMRI can play an important role for the determination of the implantation strategy. Copyright © 2013 Elsevier Inc. All rights reserved.


van der Kruijs S.J.M.,Kempenhaeghe | Bodde N.M.G.,Kempenhaeghe | Aldenkamp A.P.,Kempenhaeghe
Acta Neurologica Belgica | Year: 2011

Misdiagnosis of patients with psychogenic non-epileptic seizures (PNES) as having epilepsy is a clinical relevant problem. Considerable problems for the patients, such as unnecessary anticonvulsant medication use and delay of suitable therapy, as well as a considerable economic burden are involved. Furthermore, after the diagnosis of PNES is confirmed, there is a lack of scientific evidence about the most efficient treatment for PNES. Evaluation of contributing factors is necessary. These factors should be implemented in explanatory models for the occurrence of PNES, which should be employed in diagnosis and treatment. Recent evidence suggests a role of deficiencies in neuronal information processing in multiple mental conditions. Although the focus in PNES research over the last two decades primarily has been on differential diagnosis and psychological and environmental factors, abnormalities in psychophysiological characteristics might also be involved in PNES. This review focuses on neurobiological substrates of PNES and dissociation, a trait which is often associated with PNES, to explore whether deviant information processing is involved in the aetiology of PNES. All studies examining the relationship between psychophysiological parameters and PNES have an exploratory character. However, the results suggest that neurophysiological characteristics, such as brain activity as visualized by functional MRI, cardiovascular measurements and neuroendocrine functioning, may be abnormal in patients with PNES. Future investigations should therefore elucidate the exact role of neurophysiological abnormalities in the aetiology of PNES.

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