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(1)Article. Brain networks involved in Generalized Periodic Discharges (GPD) in post-anoxic-ischemic encephalopathy DE STEFANO, Pia, et al.. Abstract Aim: Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤2.5 Hz GPD using EEG source localization and connectivity analysis. Methods: We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers. Results: Source analysis suggested that the GPD are generated in the cortex of limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in thalamus and hippocampus for the large majority (80%) of patients, together with important activation also in amygdala (70%).. Reference DE STEFANO, Pia, et al. Brain networks involved in Generalized Periodic Discharges (GPD) in post-anoxic-ischemic encephalopathy. Resuscitation, 2020. PMID : 32795598 DOI : 10.1016/j.resuscitation.2020.07.030. Available at: http://archive-ouverte.unige.ch/unige:139736 Disclaimer: layout of this document may differ from the published version..

(2) Journal Pre-proof Brain networks involved in Generalized Periodic Discharges (GPD) in post-anoxic-ischemic encephalopathy Pia De Stefano, Margherita Carboni, Deborah Pugin, Margitta Seeck, Serge Vulliémoz. PII:. S0300-9572(20)30307-5. DOI:. https://doi.org/10.1016/j.resuscitation.2020.07.030. Reference:. RESUS 8643. To appear in:. Resuscitation. Received Date:. 9 April 2020. Revised Date:. 16 July 2020. Accepted Date:. 28 July 2020. Please cite this article as: De Stefano P, Carboni M, Pugin D, Seeck M, Vulliémoz S, Brain networks involved in Generalized Periodic Discharges (GPD) in post-anoxic-ischemic encephalopathy, Resuscitation (2020), doi: https://doi.org/10.1016/j.resuscitation.2020.07.030. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier..

(3) Type of article: Original Paper Word count: 2892/3000 Abstract: 192/250 Number of Figures: 4 Number of Tables: 2 Number of References: 40/40. ro of. Supplementary data: 1 Table and 4 Figures. Title: Brain networks involved in Generalized Periodic Discharges (GPD) in post-anoxicischemic encephalopathy. -p. Authors: Pia De Stefano*, Margherita Carboni*, Deborah Pugin, Margitta Seeck, Serge Vulliémoz. re. Affiliations:. lP. 1. Pia De Stefano (Corresponding Author) *. EEG & Epilepsy Unit, Division of Neurology, Department of Clinical Neurosciences,. na. Geneva University Hospitals. 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland. ur. ORCID: https://orcid.org/0000-0002-7979-0994. Jo. 2. Margherita Carboni *. EEG & Epilepsy Unit, Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland And Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University 1.

(4) of Geneva 9, Chemin des Mines, 1202, Geneva, Switzerland ORCID: https://orcid.org/0000-0003-0426-8242 3. Deborah Pugin Neuro-intensive care Unit, Intensive care Department, University Hospital and Faculty of Medicine of Geneva. 4. Margitta Seeck. ro of. 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland. EEG & Epilepsy Unit, Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals. re. ORCID: https://orcid.org/0000-0002-6702-0167. -p. 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland. lP. 5. Serge Vulliémoz. EEG & Epilepsy Unit, Division of Neurology, Department of Clinical Neurosciences,. na. Geneva University Hospitals. 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland. ur. ORCID: https://orcid.org/0000-0002-1877-8625 * Authors contributed equally. Jo. Corresponding Authors: Pia De Stefano. EEG & Epilepsy Unit, Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals, 4, Rue Gabrielle Perret-Gentil, 1205 Geneva, Switzerland Phone: 0041762446528 Mail: Pia.destefano@hcuge.ch 2.

(5) Abstract (word count: 192) Aim: Generalized periodic discharge (GPD) is an EEG pattern of poor neurological outcome, frequently observed in comatose patients after cardiac arrest. The aim of our study was to identify the neuronal network generating ≤ 2.5 Hz GPD using EEG source localization and connectivity analysis. Methods: We analyzed 40 comatose adult patients with anoxic-ischemic encephalopathy, who had 19 channel-EEG recording. We computed electric source analysis based on distributed. ro of. inverse solution (LAURA) and we estimated cortical activity in 82 atlas-based cortical brain regions. We applied directed connectivity analysis (Partial Directed Coherence) on these sources to estimate the main drivers.. -p. Results: Source analysis suggested that the GPD are generated in the cortex of limbic system in the majority of patients (87.5%). Connectivity analysis revealed main drivers located in. lP. activation also in amygdala (70%).. re. thalamus and hippocampus for the large majority (80%) of patients, together with important. Conclusions: We hypothesize that the anoxic-ischemic dysfunction, leading to hyperactivity of the thalamo-cortical (limbic presumably) circuit, can result in an oscillatory thalamic. na. activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to the case of generalized rhythmic spike-wave discharge. Jo. ur. in convulsive or non-convulsive status epilepticus.. Keywords. Generalized Periodic Discharges; GPD; non-convulsive status epilepticus; anoxic-ischemic encephalopathy; cardiac arrest.. Abbreviations:. 3.

(6) CA= cardiac arrest GPD= generalized periodic discharge NCSE= non convulsive status epilepticus ESI= Electrical Source Imaging iPDC= Information Partial Directed Coherence LSMAC= Locally Spherical Model with Anatomical Constraints LAURA=Local AUtoRegressive Average. ro of. ROI= Region of interest ROIs= Regions of interest. -p. Introduction. The vast majority of patients resuscitated from cardiac arrest (CA) present in coma or with an. re. altered level of consciousness caused by the widespread nature of brain injury 1, showing pathological patterns at electroencephalogram (EEG).. lP. Certain EEG patterns – namely generalized periodic discharges (GPD), post-anoxic nonconvulsive status epilepticus (NCSE), alpha coma and burst suppression or generalized. na. suppression – are associated with a poor prognosis in comatose patients 2. More recently, EEG patterns have been defined as Highly malignant, Malignant or Benign EEGs. If Highly. ur. malignant EEGs predict a poor outcome and Benign EEGs a good outcome, the Malignant. Jo. patterns are yet of unclear significance 3,4 . GPD are defined as any bilateral, bisynchronous and symmetric waveform with no more than 3 phases (i.e. crosses the baseline no more than twice) or any waveform lasting 0.5 seconds or less, regardless of number of phases that recurs with relatively uniform morphology and duration with a quantifiable inter-discharge interval between consecutive waveforms and recurrence of the waveform at nearly regular intervals5.. 4.

(7) Historically, GPD were referred to as Generalized Periodic Epileptiform Discharges, but since the epileptiform activity was not a consistent feature of these discharges, the terminology of GPD has been corrected, suppressing “epileptiform” 5. Nevertheless, for GPD the distinction between non-epileptic GPD and NCSE is still subject of debate on some recordings. Recent criteria support a diagnosis of NCSE in the presence of GPD with frequency ≥2.5 Hz or, in case of slower frequencies, either an electro-clinical improvement after intravenous antiepileptic drugs (within 10 minutes after antiepileptic drugs administration), or subtle. ro of. clinical ictal phenomena or spatio-temporal evolution 6. GPD are seen in the setting of many different types of encephalopathies and have been. reported frequently in patients with anoxic-ischemic encephalopathy, 7 within 12 to 24 hours. -p. after the onset of the anoxic injury 8. Post-mortem histology showed brain damage involving cerebral cortex, cerebellum and hippocampus, but not the thalamus, as is the case for burst-. re. suppression9.. Hypotheses of an ictal-interictal continuum in case of GPD in post-anoxic-ischemic patients. lP. and their mechanism of generation have emerged in the last years10–12. A disruption of the balance between excitatory and inhibitory inputs in the generation of. na. GPD11,12 has been proposed based on a simulation model, similar to what happens in case of epileptic seizure. Such disruption can be irreversible for those patients showing low network. ur. complexity (i.e. background discontinuity, lower discharge frequency)10.. Jo. The aim of our study was to identify the neuronal network generating GPD using EEG source localization and connectivity in the context of post-anoxic-ischemic encephalopathy.. Methods The study has been approved by the ethical committee of the institution in which the work was performed (University Hospitals of Geneva). Number: CCER_Etude 2019-02108.. 5.

(8) Study design and subjects We retrospectively selected 70 EEGs of 53 post-CA comatose adult patients (≥18 years of age) admitted to the ICU of the University Hospitals of Geneva between 2007 and 2019. The analysis was done following the American Clinical Neurophysiology Society’s Standardized Critical Care Terminology 5. We selected those EEGs showing continuous (in terms of pattern prevalence) static (no evolving) GPD patterns5 (Fig. 1).. ro of. Other inclusion criteria were: a) the first EEG performed after cardiac arrest for each patient, b) non-reactive background 5, c) the absence of anaesthetic drugs, d) EEGs free from artefacts for > 2 minutes, e) GPD with frequency ≤ 2.5 Hz with duration according to ICU-EEG. -p. Nomenclature5, f) EEGs recorded with at least 19 electrodes.. Within the 70 EEGs selected, we excluded EEGs that did not match our inclusion criteria and. ------------------------------------. ur. na. FIGURE 1 AROUND HERE. lP. re. we finally included 40 EEGs of 40 different patients.. Jo. -----------------------------------FIGURE 2 AROUND HERE. EEG acquisition and pre-processing. All EEG recordings (19 scalp electrodes + ECG, Deltamed, Natus System, sampling rate = 1000 Hz) were acquired at the University Hospital. 6.

(9) of Geneva. A board-certified EEG expert (PDS) first visually identified and marked 1-minute periods with clear GPD activity (Fig. 2A). The EEG was then filtered in the interval from 1 Hz to 40 Hz with a 4th-order Butterworth filter avoiding phase-distortion and down-sampled to 250 Hz. EEG epochs that contained any artefacts were discarded by visual inspection.. Analysis Methods:. ro of. Analysis were computed in Matlab; preprocessing was computed with a lab-customized pipeline and filtfilt was used in order to avoid phase distortion13.. We estimated the power spectral density for each scalp electrode in a period of 1 minute. -p. (Supplementary S.1).. For further analysis, the EEG signal was split into epochs containing one single discharge, i.e.. re. from the onset to the last intersection with the baseline. Due to the heterogeneity of GPD. lP. patterns across patients, epochs were of different duration across patients ([min: 85ms max: 824ms], mean±std = 296ms ± 113ms, fs=256) (Fig. 2B). We used an atlas based head model parcellation of the brain into 82 regions of interest (ROIs). na. (Figure 2C) and applied linear distributed inverse solution, as well as functional connectivity estimation between cortical sources as described in our previous work13 (Supplementary S.2,. ur. S.3). These steps allowed us to estimate the cortical activity of each region of interest (ROI). Jo. and further calculate their time varying relation by means of Partial Directed Coherence (PDC), based on Granger Causality (Fig. 2D). In order to obtain the power in each frequency band, we computed Welch Power Spectrum in Matlab for the entire 1 minute, with a window length of 2 seconds (Supplementary Data S1). We identified the brain regions with maximum activity (maximum power of the source waveforms). We computed estimated source imaging (ESI) as the main activation across the. 7.

(10) entire epoch: this was due to the shape of the discharges (waveforms with no more than 3 phases or any waveform lasting 0.5 seconds or less), the heterogeneity among patients, and the absence in the literature of the description of any relevant time point (Figure 2E). Functional connectivity allows the estimation of outflow from each region for the broad band signals as well as in a specific frequency band. We included the theta band (4 Hz to 8 Hz), based on information of the spectral power analysis. The summed outflow reflects the importance of information transfer from a ROI to the rest of the network: ROIs with high. ro of. summed outflow strongly drive activity of other ROIs (Fig. 2E) (Supplementary S.3). For each patient the main drivers were defined as the regions with highest summed outflow above. -p. the 95° percentile.. Results. re. EEG: The periodic grapho-elements had 3 phases in 29 patients, 1 phase in 2 patients and 2 phases in 9 patients, with a medium voltage (50-199 microV) in 27 patients and low voltage. lP. (20-49 microV) in 13 patients. In 3 cases there was superimposed fast activity (GPD+F) 5. The period-frequency ranged from < 0.5/sec to 2/sec. The background was non-reactive in all. na. patients, and the background voltage between GPD was suppressed (< 10 microV) in 7. ur. patients, low (<20 microV) in 21 and normal in 12 patients 5 (Supplementary Table S.1).. Jo. Clinical outcome: EEG was performed at a median of 2 days (range 1-17) after CA and the median duration of survival was 4 days (range 1-166). 37 of 40 patients died early in hospital after withdrawal of life-sustaining measures. One patient died of a respiratory tract infection (RTI) 166 days after CA and two patients were still alive with GOS 4 (moderate disability at Glasgow Outcome Score) at discharge in 2009, but then lost to follow-up.. 8.

(11) Imaging: 25 of 40 patients underwent an imaging evaluation. In 12 patients structural MRI was performed and showed bilateral cortical and subcortical hypoxic lesions in 9 and was normal in 3 patients. In another 13 patients a CT scan was performed that did not show any abnormality. In the remaining 15 patients no imaging evaluation was performed. No isolated focal lesion, such as ischemic stroke, hemorrhage or structural tumor was found in any of the 25 patients examined by imaging. Correlation between MRI and EEG findings could not be. ro of. performed due to the low proportion of patients undergoing MRI.. -----------------------------------TABLE 1 AROUND HERE. -p. ------------------------------------. re. TABLE 2 AROUND HERE. Maximum source activity during GPD (ESI):. lP. The source analysis revealed that the maximum activation involved brain regions that are parts of the limbic circuit in the majority of patients. In particular 35/40 (87.5%) of our. na. patients showed maximum activation in thalamus (3 patients), amygdala (6 patients), hippocampus (8 patients), medial-orbitofrontal (16 patients) and cingular cortex regions (2).. ur. The other 5 patients showed maximum activation in temporal pole (2 patients), lateral. Jo. temporal (2 patients) and in precuneus regions (2 patients) (Supplementary Fig. S.2 and Fig. S.3).. Connectivity (summed outflow): In broad band, we found main drivers in the thalamus in 32 patients (80%), as well as hippocampus (80%), amygdala in 28 patients (70%), orbitofrontal in 16 patients (40%), insula. 9.

(12) in 6 (15%), fusiform in 5 patients (12.5%), lateral-temporal in 4 (10%), basal ganglia in 2 (5%) and superior frontal and precentral regions in 1 patient, respectively (2.5%) (Fig. 3 and Fig.4). These findings were in line with the main drivers in the theta frequency (Supplementary Fig. S.4).. ------------------------------------. ro of. FIGURE 3 AROUND HERE. -p. ------------------------------------. lP. re. FIGURE 4 AROUND HERE. Discussion. na. The aim of our study was to investigate the neurophysiological mechanisms of the generation of GPD in post-CA comatose patients, in order to better understand the cerebral origin of this. ur. pathological EEG pattern and its relation to poor outcome. We were interested in post-CA. Jo. GPD pattern both because it is one of the most widely known patterns of poor outcome and because for ≤ 2.5 Hz GPD the previous “epileptiform” term still has controversial clinical significance.. Our data suggest that the discharges of GPD are generated in specific cortical brain regions of the limbic system in the majority of patients (87.5%). Moreover, connectivity analysis showed that the main drivers (highest summed outflow) of the networks involved in the generation of. 10.

(13) GPD pattern were identified as the thalamus and hippocampus for the large majority (80%) of patients, with important outflow also from the amygdala (70%).. Neurobiological implications The central role of certain brain regions in the generation of EEG patterns in coma is known: in particular, studies on animals and humans have shown that the thalamus, basal ganglia, brainstem and especially the fronto-parietal cortex, are all involved in the generation of burst. ro of. suppression, one of the best studied EEG pattern associated with severe encephalopathies. In particular, a study on babies 14 investigated more in detail the regions responsible for burstssuppression EEG patterns in specific neonatal encephalopathic syndromes, and found that. -p. burst phases were associated with coherent sources in the thalamus and brainstem as well as bilateral sources in cortical regions, mainly frontal and parietal, whereas suppression phases. re. were associated with coherent sources in cortical regions only 15.. lP. The reason why specific brain regions appear to be most commonly affected by hypoperfusion is either because they lie in watershed vascular areas or because the neurons in those locations have a higher metabolic rate and metabolic demand, making them less. na. forgiving of periods of relative ischemia 16 . The CA1 pyramidal neurons of the hippocampus are commonly damaged with prolonged ischemia. Other commonly affected neurons include. ur. cerebellar Purkinje cells, thalamic reticular neurons, medium-sized striatal neurons, and. Jo. pyramidal neurons in layers 3, 5, and 6 of the neocortex 17. The least vulnerable part is the brainstem, which could not be analysed in our EEG study. The degree of injury to the brain arousal system (previously ascending reticular activating system) such as subcortical projections, thalamus, and midbrain seems key in determining prognosis18. This gradient is confirmed by MRI that shows, as the commonest pattern, the presence of change in both cortical and deep grey matter territory with involvement of the neocortex,. 11.

(14) basal ganglia, hippocampus, thalamus and cerebellum, varying with the severity of the initial insult and the timing of the imaging 19. Our results show that not all structures contribute equally to GPD pattern, but mainly the hippocampus and thalamus bilaterally. These areas with restricted diffusion most likely reflect rather the consequence of hypoxia/ischemia, but a component of high metabolic demand by high-voltage periodic discharges is possible in some regions20.. ro of. Our findings are in line with thalamic involvement in altered consciousness, notably during sleep and epileptic activity. During slow-wave sleep (stage 2-3), the neocortex is isolated. from external sensory inputs and shows coordinated population activity with large-amplitude,. -p. slow oscillations of local field potentials (LFPs) 21. These oscillations are structured in 2 phases: the downstate 22 (hyperpolarisation of neocortex neurons) and the upstate. re. (depolarisation of neocortex neurons). The upstate corresponds to the hyperpolarisation of. lP. thalamic neurons, an intrinsic rhythmic hyperpolarisation that does not allow the stimuli to pass by the so-called thalamic gate. In sleep, strong stimuli can pass the gate and trigger arousal, in coma this mechanism can be impaired to various degrees. Moreover, thalamic. na. neurons play a central role in the generation and maintenance of generalized rhythmic spikewave discharges associated with alterations of consciousness, 23 suggesting that these. ur. thalamo-cortical circuits are key in the modulation of the cortical networks underlying. Jo. consciousness.. A simulation model of impaired excitatory glutamatergic input to inhibitory cortical interneurons resulted in pathological neuronal synchronization reproducing GPD in postanoxia 12, suggesting that the network mechanisms underlying the generation of GPD are similar to those involved in the generation of certain types of seizure activity and NCSE. Even if their computational model of cerebral dynamics could not study the effect of the thalamo-. 12.

(15) cortical loop on synchronization of GPD, our concordant results support the crucial role of this circuit. A cerebral microdialysis study seems to confirm this hypothesis showing how periodic discharges have similar profile of metabolic crisis compared with epileptic seizure 24, as much as MRI studies show restricted diffusion on cortex and thalamus25. As described in post-mortem histopathology studies9, medial-temporal regions, in particular the hippocampi, are known to be most vulnerable to ischemia and consequent cyto-excitatory. ro of. mechanisms could be at the origin of the pathological graphoelements seen in GPD. Midline frontal regions are involved in the spread and generalization of epileptic discharges of focal origin and a significant activation of these regions, together with thalamus, has also been. -p. shown in the generation of generalized epileptic discharges 26, together with a diffuse. reduction of cortical activity 23. We can postulate that GPD arise from similar thalamo-. re. cortical circuits that are disinhibited by anoxic-ischemic lesions affecting the thalamus, the. lP. cortex or both 12, resulting in a pathological neuronal synchronization, similar to what is seen in epileptic discharges. The anoxic-ischemic dysfunction associated with hyperactivity of the thalamo-cortical (limbic presumably) circuit can therefore take the form of an oscillatory. na. thalamic activity capable of inducing periodic cortical (limbic, mostly medial-temporal and orbitofrontal) discharges, similarly to what happens in convulsive or NCSE.. ur. This could contribute to the absence of reactivity to stimuli in these comatose patients, as well. Jo. as to reduced awareness and reactivity in case of generalized rhythmic spike-wave discharges. It is unclear whether the expression of GPD is facilitated by the impairment of consciousness caused by diffuse cortical and subcortical lesions; it “only” reflects diffuse injury of thalamocortical circuitry; it indicates a residual activity of affected hippocampus; or it has an unrecognised potential worsening effect on the arousal/awareness system or Papez (limbic) Circuit by aggravating metabolic needs and dysfunction with “extreme” neuronal activity.. 13.

(16) Clinical implications A better understanding of the neurophysiological mechanisms at the origin of pathological EEG patterns, such as ≤ 2.5 Hz GPD, not properly considered NCSE, is of utmost importance to understand the state of (un)consciousness of patients and the pathophysiological reasons for a poor outcome. The debate about the (ictal) diagnostic significance and the management of low frequencies GPD is not resolved yet; nevertheless the literature shows cases of GPD 1-2. ro of. Hz having responded to antiepileptic drugs (response to commands) after several days of sedation and therapy 27, as well as “Malignant EEG”, including GPD, but without suppressed background, not invariably associated with poor outcome3,4.. -p. Even if therapeutic approach with antiepileptic drugs for GPD is controversial, it is widely adopted for GPD ≥ 2.5 Hz since they are considered to represent NCSE 28,29. Treatment. re. benefit is currently addressed in a randomized trial 29. Low and higher frequencies GPD are. lP. likely not binary (seizure versus encephalopathy) but rather on a spectrum with a similar neurophysiological mechanism in thalamo-cortical loop for low frequency GPD and for. na. NCSE. Randomized controlled studies comparing low with high frequencies of GPD would be of utmost importance to establish the potential benefit of antiepileptic treatment on outcome in this condition. Indeed, electrographic seizure not properly treated may lead to. ur. secondary neuronal damage, worsening the outcome. Similarly, the response to antiepileptic. Jo. drugs in patients with different voltage background and (dis)continuity, would be interesting given their association with outcome3,10. The standardization of the ICU-EEG terminology has enhanced the recognition, understanding and communication of the EEG findings within the scientific and clinical community. Different procedures (antiepileptic drug administration and intensity, withdrawal. 14.

(17) of life sustaining treatment) can influence outcomes. Therefore, randomized controlled studies leading to standardized therapeutic protocols within the clinical community are needed. This is particularly relevant in this population of comatose patients, for whom withdrawal of care may induce a bias of poor outcome 18 which can strongly vary across centres, and is influenced by ethical and cultural perspectives.. Methodological considerations. ro of. One limitation of our study is the low spatial sampling of scalp electrodes, which can limit the accuracy of source localization between neighboring structures. Nevertheless, previous studies 30,31 showed that in case of high signal noise ratio (SNR), such as in GPD, the. -p. reliability of low density ESI as well as connectivity is not inferior than high-density EEG. In focal epilepsy, identified regions with highest source activity and connectivity were inside the. re. presumed epileptic zone or the resected area 30,31, the same was found during ictal recordings with low density EEG 32. Low-density EEG 33 has been tested to be reliable also with different. lP. inverse solution methods 34, obtaining similar localization of other conventional neuroimaging methods (structural MRI, PET, SPECT and MEG)35. Other studies with simultaneous scalp-. na. intra-cranial EEG have shown that spikes seen on intracranial contacts were properly localized with different inverse solution methods even for some sources remote from the scalp , in the same way one recent study has shown that scalp EEG can detect and correctly. ur. 36,37. Jo. localize signals recorded with intracranial electrodes placed in the centro-medial thalamus, and in the nucleus accumbens 38. Some studies found that ESI applied to widespread spike and wave discharges and K-complex tends to favour localization in deep sources due to the constraints applied to source localization algorithms 39. Further investigations are needed with regard to source localizations of generalized activity such as GPD. One possible approach could be. 15.

(18) simultaneous EEG-fMRI to complement the localization of the regions involved in GPD. During generalised spike-wave discharges of generalized epilepsies, EEG-fMRI studies have consistently shown a thalamic activation associated with widespread neocortical deactivation. This spatial pattern associated with generalized EEG discharges lends support to our findings of “deep” active sources of the high amplitude, bilateral diffuse GPD 23,40 . The brain damage after a major anoxic-ischemic event has no a priori lateralization and is mostly bilateral and symmetric. Therefore, we did not consider lateralization in our analysis. ro of. and bi-hemispheric activation found was only a consequence of the group analysis.. Author’s contribution:. -p. PDS, MC, SV: conception and design of the study. PDS, SV, MS: interpretation of data. lP. PDS, MC: drafting the article. re. PDS: acquisition of data. SV, DP, MS: revising for important intellectual content MS, SV: final approval of the version to be submitted. na. Funding. Author PDS and MS were supported by Swiss National Science Foundation (SNSF) [163398. ur. and Sinergia 180365].. Jo. Author MC and SV were supported by the Swiss National Science Foundation (SNSF) [under grants CRSII5_170873 and 169198]. Author DP did not receive any funding for this work.. Ethics. 16.

(19) The study has been approved by the ethical committee of the institution in which the work was performed (University Hospitals of Geneva). Number: CCER_Etude 2019-02108.. Research data Due to data protection reasons, data cannot be made publicly available. However, anonymized grouped data will be made available upon reasonable request to qualified investigators.. ro of. Conflict of interest PDS, MC and DP report no competing interests.. SV and MS report that they are shareholders of Epilog NV (Ghent, Belgium). MS received. -p. speaker's fees from Philips and Desitin.. re. Acknowledgements. lP. The Cartool software (http://sites.google.com/site/fbmlab/cartool) has been programmed by Denis Brunet from the Functional Brain Mapping Laboratory in Geneva and is supported by the Center for Biomedical Imaging (CIBM) of Geneva and Lausanne, Switzerland.. na. We thank Dr N. Kane and Dr M. J.A.M. van Putten for critically reading the manuscript and. Jo. ur. suggesting substantial improvements.. 17.

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(23) a randomized controlled trial. Trials. 2014; 15(1):1–8. 30.. Coito A, Biethahn S, Tepperberg J, et al. Interictal epileptogenic zone localization in patients with focal epilepsy using electric source imaging and directed functional connectivity from low-density EEG. Epilepsia Open. 2019; 4(2):281–92.. 31.. van Mierlo P, Strobbe G, Keereman V, et al. Automated long-term EEG analysis to localize the epileptogenic zone. Epilepsia Open. 2017; 2(3):322–33.. 32.. Staljanssens W, Strobbe G, Van Holen R, et al. EEG source connectivity to localize the. ro of. seizure onset zone in patients with drug resistant epilepsy. NeuroImage Clin. 2017; 16(May):689–98. 33.. Russo A, Jayakar P, Lallas M, et al. The diagnostic utility of 3D. -p. electroencephalography source imaging in pediatric epilepsy surgery. Epilepsia. 2016; 57(1):24–31.. Sharma P, Scherg M, Pinborg LH, et al. Ictal and interictal electric source imaging in. re. 34.. 35.. lP. pre-surgical evaluation: a prospective study. Eur J Neurol. 2018; 25(9):1154–60. Sharma P, Seeck M, Beniczky S. Accuracy of Interictal and Ictal Electric and Magnetic Source Imaging: A Systematic Review and Meta-Analysis. Front Neurol. 2019;. 36.. na. 10(December):1–12.. Ramantani G, Dümpelmann M, Koessler L, et al. Simultaneous subdural and scalp. Tao JX, Ray A, Hawes-Ebersole S, et al. Intracranial EEG substrates of scalp EEG. Jo. 37.. ur. EEG correlates of frontal lobe epileptic sources. Epilepsia. 2014; 55(2):278–88.. interictal spikes. Epilepsia. 2005; 46(5):669–76.. 38.. Seeber M, Cantonas LM, Hoevels M, et al. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat Commun. 2019; 10(1):1–7.. 39.. Wennberg R, Cheyne D. On noninvasive source imaging of the human K-complex. Clin Neurophysiol. 2013; 124(5):941–55.. 21.

(24) 40.. Hamandi K, Salek-Haddadi A, Laufs H, et al. EEG-fMRI of idiopathic and secondarily. Jo. ur. na. lP. re. -p. ro of. generalized epilepsies. Neuroimage. 2006; 31(4):1700–10.. 22.

(25) -p. ro of. Legends to figures. Figure 1. Example of post-anoxic-ischemic 2 Hz GPD (10 sec. 19-channels EEG in bipolar. Jo. ur. na. lP. re. montage). Distance between vertical bars: 1 second.. 23.

(26) ro of -p re lP na. Jo. ur. Figure 2. Summary of the analysis strategy.. 24.

(27) ro of -p. Figure 3: Connectivity main driver activation. re. Matrix of outflow degree during discharge epochs: main drivers (>95°) in yellow for each patient, as described in the text. The predominance of outflow from thalamus, hippocampus. lP. and amygdala (narrow) and to a lesser degree medial-orbitofrontal cortex, can be clearly. Jo. ur. na. seen.. 25.

(28) Figure 4: Localization of the regions in the (Montreal Neurological Institute) MNI template brain. Only main drivers active in > 50% of patients are represented. Violet spheres represent thalamus and hippocampus, main driver areas in 80% of patients; blue spheres represent amygdala, main driver in 70% of our sample. In red to green color-bar the ESI activation.. Jo. ur. na. lP. re. -p. ro of. GPD pattern on background.. 26.

(29) Table 1. Characteristics, clinical outcome and neurological evaluation of patients. N.patients= number of patients; Female = number of females in our sample; Age= median of years; N. of patients died= number of patients who died; Days alive post-CA= median of the number of days of life for each patient after cardiac arrest; Days interval CA-EEG= median of the number of days between cardiac arrest and EEG recording; MRI performed= number of patients undergoing a brain MRI exam; CT performed= number of patients undergoing a. ro of. brain CT-scan; SSEP (N20) performed= number of patients undergoing a somatosensory evoked potentials evaluation. Total 40. Female. 7 69.5 (24-83). N. of patients died. re. Age (years). -p. N.patients. Median. 38. 4 (1-166). Days interval CA-EEG. lP. Days alive post-CA. 2 (1-17). 12. CT performed. 13. na. MRI performed. 13. Jo. ur. SSEP (N20) performed. 27.

(30) Table 2. MRI findings of 12 patients undergoing MRI examination. X corresponds to the presence of restricted diffusion at DWI (Diffusion weighted imaging) on cortex, basal ganglia, thalamus, cerebellum and hippocampus. In all the patients ischemichypoxic lesions were bilateral. Patient 1-3-12 did not show any lesion at MRI.. x. x. x x. x x. Thalamus. Cerebellum. x. x. x x. x. x. x x x. x x x x. re. x x x. -p. x x x x x x. Hippocampus. Jo. ur. na. lP. 1 2 3 4 5 6 7 8 9 10 11 12. Basal ganglia. ro of. MRI patient Cortex. 28.

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