Focke, Niels K.

[["dc.bibliographiccitation.firstpage","170"],["dc.bibliographiccitation.journal","Epilepsia"],["dc.bibliographiccitation.lastpage","171"],["dc.bibliographiccitation.volume","52"],["dc.contributor.author","Focke, Niels K."],["dc.contributor.author","Helms, G."],["dc.contributor.author","Nitsche, M. A."],["dc.contributor.author","Paulus, Walter J."],["dc.date.accessioned","2018-11-07T08:53:26Z"],["dc.date.available","2018-11-07T08:53:26Z"],["dc.date.issued","2011"],["dc.identifier.isi","000294217200549"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/22409"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Malden"],["dc.relation.conference","29th International Epilepsy Congress"],["dc.relation.eventlocation","Rome, ITALY"],["dc.relation.issn","0013-9580"],["dc.title","IMAGE BIAS CORRECTION PROFOUNDLY INFLUENCES VOXEL-BASED MORPHOMETRY IN MESIAL TEMPORAL LOBE EPILEPSY"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1905"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","Human Brain Mapping"],["dc.bibliographiccitation.lastpage","1915"],["dc.bibliographiccitation.volume","32"],["dc.contributor.author","Focke, Niels K."],["dc.contributor.author","Helms, Gunther"],["dc.contributor.author","Scheewe, Sebstian"],["dc.contributor.author","Pantel, Pia M."],["dc.contributor.author","Bachmann, Cornelius G."],["dc.contributor.author","Dechent, Peter"],["dc.contributor.author","Ebentheuer, Jens"],["dc.contributor.author","Mohr, Alexander"],["dc.contributor.author","Paulus, Walter J."],["dc.contributor.author","Trenkwalder, Claudia"],["dc.date.accessioned","2018-11-07T08:50:18Z"],["dc.date.available","2018-11-07T08:50:18Z"],["dc.date.issued","2011"],["dc.description.abstract","Voxel-based morphometry (VBM) shows a differentiated pattern in patients with atypical Parkinson syndrome but so far has had little impact in individual cases. It is desirable to translate VBM findings into clinical practice and individual classification. To this end, we examined whether a support vector machine (SVM) can provide useful accuracies for the differential diagnosis. We acquired a volumetric 3D T1-weighted MRI of 21 patients with idiopathic Parkinson syndrome (IPS), 11 multiple systems atrophy (MSA-P) and 10 progressive supranuclear palsy (PSP), and 22 healthy controls. Images were segmented, normalized, and compared at group level with SPM8 in a classical VBM design. Next, a SVM analysis was performed on an individual basis with leave-one-out cross-validation. VBM showed a strong white matter loss in the mesencephalon of patients with PSP, a putaminal grey matter loss in MSA, and a cerebellar grey matter loss in patients with PSP compared with IPS. The SVM allowed for an individual classification in PSP versus IPS with up to 96.8% accuracy with 90% sensitivity and 100% specificity. In MSA versus IPS, an accuracy of 71.9% was achieved; sensitivity, however, was low with 36.4%. Patients with IPS could not be differentiated from controls. In summary, a voxel-based SVM analysis allows for a reliable classification of individual cases in PSP that can be directly clinically useful. For patients with MSA and IPS, further developments like quantitative MRI are needed. Hum Brain Mapp 32:1905-1915, 2011. (C) 2011 Wiley Periodicals, Inc."],["dc.identifier.doi","10.1002/hbm.21161"],["dc.identifier.isi","000296850700012"],["dc.identifier.pmid","21246668"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/21663"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1065-9471"],["dc.title","Individual Voxel-Based Subtype Prediction can Differentiate Progressive Supranuclear Palsy from Idiopathic Parkinson Syndrome and Healthy Controls"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","246"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Epilepsy Research"],["dc.bibliographiccitation.lastpage","254"],["dc.bibliographiccitation.volume","95"],["dc.contributor.author","Bonelli, Silvia B."],["dc.contributor.author","Powell, Rob"],["dc.contributor.author","Thompson, Pamela J."],["dc.contributor.author","Yogarajah, Mahinda"],["dc.contributor.author","Focke, Niels K."],["dc.contributor.author","Stretton, Jason"],["dc.contributor.author","Vollmar, Christian"],["dc.contributor.author","Symms, Mark R."],["dc.contributor.author","Price, Cathy J."],["dc.contributor.author","Duncan, John S."],["dc.contributor.author","Koepp, Matthias J."],["dc.date.accessioned","2018-11-07T08:53:33Z"],["dc.date.available","2018-11-07T08:53:33Z"],["dc.date.issued","2011"],["dc.description.abstract","Purpose: In patients with left temporal lobe epilepsy (TLE) due to hippocampal sclerosis (HS) decreased naming ability is common, suggesting a critical role for the medial left temporal lobe in this task. We investigated the integrity of language networks with functional MRI (fMRI) in controls and TLE patients. Experimental design: We performed an fMRI verbal fluency paradigm in 22 controls and 66 patients with unilateral mesial TLE (37 left HS, 29 right HS). Verbal fluency and naming ability were investigated as part of the standard presurgical neuropsychological assessment. Naming ability was assessed using a visual confrontation naming test. Results: Left TLE patients had significantly tower naming scores than controls and those with right TLE. Right TLE patients performed less well than controls, but better than those with left TLE. Left TLE had significantly lower scores for verbal fluency than controls. In controls and right TLE, left hippocampal activation during the verbal fluency task was significantly correlated with naming, characterised by higher scores in subjects with greater hippocampal fMRI activation. In left TLE no correlation with naming scores was seen in the left hippocampus, but there was a significant correlation in the left middle and inferior frontal gyri, not observed in controls and right TLE. In left and right TLE, out of scanner verbal fluency scores significantly correlated with fMRI activation for verbal fluency in the left middle and inferior frontal gyri. Conclusion: Good confrontation naming ability depends on the integrity of the hippocampus and the connecting fronto-temporal networks. Functional MRI activation in the left hippocampus during verbal fluency is associated with naming function in healthy controls and patients with right TLE. In left TLE, there was evidence of involvement of the left frontal lobe when naming was more proficient, most likely reflecting a compensatory response due to the ongoing epileptic activity and/or underlying pathology. (C) 2011 Elsevier B.V. All rights reserved."],["dc.identifier.doi","10.1016/j.eplepsyres.2011.04.007"],["dc.identifier.isi","000293727600009"],["dc.identifier.pmid","21592730"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11299"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/22438"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Elsevier Science Bv"],["dc.relation.issn","0920-1211"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0"],["dc.title","Hippocampal activation correlates with visual confrontation naming: fMRI findings in controls and patients with temporal lobe epilepsy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1653"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Epilepsia"],["dc.bibliographiccitation.lastpage","1664"],["dc.bibliographiccitation.volume","58"],["dc.contributor.author","Martin, Pascal"],["dc.contributor.author","Winston, Gavin P."],["dc.contributor.author","Bartlett, Philippa"],["dc.contributor.author","de Tisi, Jane"],["dc.contributor.author","Duncan, John S."],["dc.contributor.author","Focke, Niels K."],["dc.date.accessioned","2019-12-16T15:44:53Z"],["dc.date.accessioned","2021-10-27T13:21:57Z"],["dc.date.available","2019-12-16T15:44:53Z"],["dc.date.available","2021-10-27T13:21:57Z"],["dc.date.issued","2017"],["dc.description.abstract","OBJECTIVE: Although the general utility of voxel-based processing of structural magnetic resonance imaging (MRI) data for detecting occult lesions in focal epilepsy is established, many differences exist among studies, and it is unclear which processing method is preferable. The aim of this study was to compare the ability of commonly used methods to detect epileptogenic lesions in magnetic resonance MRI-positive and MRI-negative patients, and to estimate their diagnostic yield. METHODS: We identified 144 presurgical focal epilepsy patients, 15 of whom had a histopathologically proven and MRI-visible focal cortical dysplasia; 129 patients were MRI negative with a clinical hypothesis of seizure origin, 27 of whom had resections. We applied four types of voxel-based morphometry (VBM), three based on T1 images (gray matter volume, gray matter concentration, junction map [JM]) and one based on normalized fluid-attenuated inversion recovery (nFSI). Specificity was derived from analysis of 50 healthy controls. RESULTS: The four maps had different sensitivity and specificity profiles. All maps showed detection rates for focal cortical dysplasia patients (MRI positive and negative) of >30% at a strict threshold of p < 0.05 (family-wise error) and >60% with a liberal threshold of p < 0.0001 (uncorrected), except for gray matter volume (14% and 27% detection rate). All maps except nFSI showed poor specificity, with high rates of false-positive findings in controls. In the MRI-negative patients, absolute detection rates were lower. A concordant nFSI finding had a significant positive odds ratio of 7.33 for a favorable postsurgical outcome in the MRI-negative group. Spatial colocalization of JM and nFSI was rare, yet showed good specificity throughout the thresholds. SIGNIFICANCE: All VBM variants had specific diagnostic properties that need to be considered for an adequate interpretation of the results. Overall, structural postprocessing can be a useful tool in presurgical diagnostics, but the low specificity of some maps has to be taken into consideration."],["dc.identifier.doi","10.1111/epi.13851"],["dc.identifier.isbn","28745400"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16969"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/92057"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.issn","0013-9580"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Voxel-based magnetic resonance image postprocessing in epilepsy"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1226"],["dc.bibliographiccitation.issue","14"],["dc.bibliographiccitation.journal","Neurology"],["dc.bibliographiccitation.lastpage","1234"],["dc.bibliographiccitation.volume","81"],["dc.contributor.author","Mollenhauer, B."],["dc.contributor.author","Trautmann, E."],["dc.contributor.author","Sixel-Doring, F."],["dc.contributor.author","Wicke, T."],["dc.contributor.author","Ebentheuer, J."],["dc.contributor.author","Schaumburg, M."],["dc.contributor.author","Lang, E."],["dc.contributor.author","Focke, N. K."],["dc.contributor.author","Kumar, K. R."],["dc.contributor.author","Trenkwalder, C."],["dc.contributor.authorgroup","On behalf of the DeNoPa Study Group"],["dc.date.accessioned","2021-06-01T10:48:12Z"],["dc.date.available","2021-06-01T10:48:12Z"],["dc.date.issued","2013"],["dc.description.abstract","Objective: To determine nonmotor signs (NMS) and evaluate the utility of several diagnostic tools in patients with de novo Parkinson disease (PD). Methods: This is a large single-center study of the DeNoPa cohort, including frequency-matched healthy controls. This study covers motor signs, NMS, and a combination of diagnostic tests including olfactory testing, transcranial sonography of substantia nigra (TCS), and polysomnography (PSG). We report the frequency and characteristics of NMS and the outcomes of nonmotor tests at the time of diagnosis. Results: Cross-sectional analyses of baseline investigations identified significant differences in the NMS Questionnaire (NMSQuest) and the Scopa-AUT Gastrointestinal score in 159 drug-naive PD patients vs 110 controls. In addition, patients with PD showed reduced olfactory function, hyperechogenicity on TCS, and higher frequency of REM sleep behavior disorder (RBD). In exploring predictive markers, we found that the combination of several investigations, i.e., the NMSQuest, Scopa-AUT Gastrointestinal score, and Smell Identification Test reached an area under the receiver operating characteristic curve (AUC) of 0.913 (95% confidence interval [CI] 0.878-0.948). With the addition of serum cholesterol and mean heart rate values, the AUC value reached 0.919 (95% CI 886-0.953); when TCS and PSG were added, the AUC increased to 0.963 (95% CI 0.943-0.982). Conclusions: We show feasibility and utility of standardized data acquisition in a large, single-center cohort of patients with de novo PD and matched healthy controls. The baseline results from our prospective investigations reached a value of >0.9 sensitivity and specificity for biological markers when we added routine laboratory investigations and quantified nonmotor features including sleep."],["dc.identifier.doi","10.1212/WNL.0b013e3182a6cbd5"],["dc.identifier.isi","000330768200012"],["dc.identifier.pmid","23997153"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/85857"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Lippincott Williams & Wilkins"],["dc.relation.eissn","1526-632X"],["dc.relation.issn","0028-3878"],["dc.title","Nonmotor and diagnostic findings in subjects with de novo Parkinson disease of the DeNoPa cohort"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0135247"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Bonilha, Leonardo"],["dc.contributor.author","Gleichgerrcht, Ezequiel"],["dc.contributor.author","Fridriksson, Julius"],["dc.contributor.author","Rorden, Chris"],["dc.contributor.author","Breedlove, Jesse L."],["dc.contributor.author","Nesland, Travis"],["dc.contributor.author","Paulus, Walter J."],["dc.contributor.author","Helms, Gunther"],["dc.contributor.author","Focke, Niels K."],["dc.date.accessioned","2018-11-07T09:51:49Z"],["dc.date.available","2018-11-07T09:51:49Z"],["dc.date.issued","2015"],["dc.description.abstract","Rationale Disruptions of brain anatomical connectivity are believed to play a central role in several neurological and psychiatric illnesses. The structural brain connectome is typically derived from diffusion tensor imaging (DTI), which may be influenced by methodological factors related to signal processing, MRI scanners and biophysical properties of neuroanatomical regions. In this study, we evaluated how these variables affect the reproducibility of the structural connectome. Methods Twenty healthy adults underwent 3 MRI scanning sessions (twice in the same MRI scanner and a third time in a different scanner unit) within a short period of time. The scanning sessions included similar T1 weighted and DTI sequences. Deterministic or probabilistic tractography was performed to assess link weight based on the number of fibers connecting gray matter regions of interest (ROI). Link weight and graph theory network measures were calculated and reproducibility was assessed through intra-class correlation coefficients, assuming each scanning session as a rater. Results Connectome reproducibility was higher with data from the same scanner. The probabilistic approach yielded larger reproducibility, while the individual variation in the number of tracked fibers from deterministic tractography was negatively associated with reproducibility. Links connecting larger and anatomically closer ROIs demonstrated higher reproducibility. In general, graph theory measures demonstrated high reproducibility across scanning sessions. Discussion Anatomical factors and tractography approaches can influence the reproducibility of the structural connectome and should be factored in the interpretation of future studies. Our results demonstrate that connectomemapping is a largely reproducible technique, particularly as it relates to the geometry of network architecture measured by graph theory methods."],["dc.identifier.doi","10.1371/journal.pone.0135247"],["dc.identifier.isi","000360613800024"],["dc.identifier.pmid","26332788"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12082"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35991"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Reproducibility of the Structural Brain Connectome Derived from Diffusion Tensor Imaging"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0190480"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","PlOS ONE"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Sahib, Ashish Kaul"],["dc.contributor.author","Erb, Michael"],["dc.contributor.author","Marquetand, Justus"],["dc.contributor.author","Martin, Pascal"],["dc.contributor.author","Elshahabi, Adham"],["dc.contributor.author","Klamer, Silke"],["dc.contributor.author","Vulliemoz, Serge"],["dc.contributor.author","Scheffler, Klaus"],["dc.contributor.author","Ethofer, Thomas"],["dc.contributor.author","Focke, Niels K"],["dc.date.accessioned","2019-07-09T11:45:07Z"],["dc.date.available","2019-07-09T11:45:07Z"],["dc.date.issued","2018"],["dc.description.abstract","The human brain is known to contain several functional networks that interact dynamically. Therefore, it is desirable to analyze the temporal features of these networks by dynamic functional connectivity (dFC). A sliding window approach was used in an event-related fMRI (visual stimulation using checkerboards) to assess the impact of repetition time (TR) and window size on the temporal features of BOLD dFC. In addition, we also examined the spatial distribution of dFC and tested the feasibility of this approach for the analysis of interictal epileptiforme discharges. 15 healthy controls (visual stimulation paradigm) and three patients with epilepsy (EEG-fMRI) were measured with EPI-fMRI. We calculated the functional connectivity degree (FCD) by determining the total number of connections of a given voxel above a predefined threshold based on Pearson correlation. FCD could capture hemodynamic changes relative to stimulus onset in controls. A significant effect of TR and window size was observed on FCD estimates. At a conventional TR of 2.6 s, FCD values were marginal compared to FCD values using sub-seconds TRs achievable with multiband (MB) fMRI. Concerning window sizes, a specific maximum of FCD values (inverted u-shape behavior) was found for each TR, indicating a limit to the possible gain in FCD for increasing window size. In patients, a dynamic FCD change was found relative to the onset of epileptiform EEG patterns, which was compatible with their clinical semiology. Our findings indicate that dynamic FCD transients are better detectable with sub-second TR than conventional TR. This approach was capable of capturing neuronal connectivity across various regions of the brain, indicating a potential to study the temporal characteristics of interictal epileptiform discharges and seizures in epilepsy patients or other brain diseases with brief events."],["dc.identifier.doi","10.1371/journal.pone.0190480"],["dc.identifier.pmid","29357371"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15034"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59160"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.subject.mesh","Adult"],["dc.subject.mesh","Brain"],["dc.subject.mesh","Brain Mapping"],["dc.subject.mesh","Case-Control Studies"],["dc.subject.mesh","Electroencephalography"],["dc.subject.mesh","Epilepsy"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Magnetic Resonance Imaging"],["dc.subject.mesh","Middle Aged"],["dc.subject.mesh","Young Adult"],["dc.title","Evaluating the impact of fast-fMRI on dynamic functional connectivity in an event-based paradigm"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Epilepsia"],["dc.bibliographiccitation.volume","50"],["dc.contributor.author","Focke, Niels K."],["dc.contributor.author","Klinker, Florian"],["dc.contributor.author","Nitsche, M."],["dc.contributor.author","Dechent, Peter"],["dc.contributor.author","Paulus, Walter J."],["dc.contributor.author","Helms, G."],["dc.date.accessioned","2018-11-07T08:34:23Z"],["dc.date.available","2018-11-07T08:34:23Z"],["dc.date.issued","2009"],["dc.format.extent","58"],["dc.identifier.isi","000264881600193"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/17800"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell Publishing, Inc"],["dc.publisher.place","Malden"],["dc.relation.conference","8th European Congress on Epileptology"],["dc.relation.eventlocation","Berlin, GERMANY"],["dc.relation.issn","0013-9580"],["dc.title","FEASIBILITY OF A NOVEL, QUANTITATIVE MAGNETIZATION TRANSFER MAPPING TECHNIQUE IN FOCAL EPILEPSY"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","128"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Zeitschrift für Epileptologie"],["dc.bibliographiccitation.lastpage","133"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Martin, Pascal"],["dc.contributor.author","Schmidt, Kathie"],["dc.contributor.author","Reimold, Matthias"],["dc.contributor.author","Bender, Benjamin"],["dc.contributor.author","Focke, Niels K."],["dc.date.accessioned","2020-12-10T14:11:15Z"],["dc.date.available","2020-12-10T14:11:15Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1007/s10309-018-0172-3"],["dc.identifier.eissn","1610-0646"],["dc.identifier.issn","1617-6782"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71018"],["dc.language.iso","de"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Multimodale Bildgebung"],["dc.title.alternative","Multimodal imaging. How do we solve the puzzle?"],["dc.title.subtitle","Wie fügen wir das Puzzle zusammen?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","533"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Epileptic disorders"],["dc.bibliographiccitation.lastpage","536"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Beniczky, Sándor"],["dc.contributor.author","Husain, Aatif"],["dc.contributor.author","Ikeda, Akio"],["dc.contributor.author","Alabri, Haifa"],["dc.contributor.author","Cross, J. Helen"],["dc.contributor.author","Wilmshurst, Jo"],["dc.contributor.author","Seeck, Margitta"],["dc.contributor.author","Focke, Niels"],["dc.contributor.author","Braga, Patricia"],["dc.contributor.author","Wiebe, Samuel"],["dc.contributor.author","Trinka, Eugen"],["dc.date.accessioned","2021-09-01T06:38:22Z"],["dc.date.available","2021-09-01T06:38:22Z"],["dc.date.issued","2021"],["dc.identifier.doi","10.1684/epd.2021.1292"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/88917"],["dc.notes.intern","DOI-Import GROB-455"],["dc.relation.eissn","1950-6945"],["dc.relation.issn","1294-9361"],["dc.title","Importance of access to epilepsy monitoring units during the COVID-19 pandemic: consensus statement of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]