1
|
Hays MA, Daraie AH, Smith RJ, Sarma SV, Crone NE, Kang JY. Network excitability of stimulation-induced spectral responses helps localize the seizure onset zone. Clin Neurophysiol 2024; 166:43-55. [PMID: 39096821 PMCID: PMC11401764 DOI: 10.1016/j.clinph.2024.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 03/11/2024] [Accepted: 07/19/2024] [Indexed: 08/05/2024]
Abstract
OBJECTIVE While evoked potentials elicited by single pulse electrical stimulation (SPES) may assist seizure onset zone (SOZ) localization during intracranial EEG (iEEG) monitoring, induced high frequency activity has also shown promising utility. We aimed to predict SOZ sites using induced cortico-cortical spectral responses (CCSRs) as an index of excitability within epileptogenic networks. METHODS SPES was conducted in 27 epilepsy patients undergoing iEEG monitoring and CCSRs were quantified by significant early (10-200 ms) increases in power from 10 to 250 Hz. Using response power as CCSR network connection strengths, graph centrality measures (metrics quantifying each site's influence within the network) were used to predict whether sites were within the SOZ. RESULTS Across patients with successful surgical outcomes, greater CCSR centrality predicted SOZ sites and SOZ sites targeted for surgical treatment with median AUCs of 0.85 and 0.91, respectively. We found that the alignment between predicted and targeted SOZ sites predicted surgical outcome with an AUC of 0.79. CONCLUSIONS These findings indicate that network analysis of CCSRs can be used to identify increased excitability of SOZ sites and discriminate important surgical targets within the SOZ. SIGNIFICANCE CCSRs may supplement traditional passive iEEG monitoring in seizure localization, potentially reducing the need for recording numerous seizures.
Collapse
Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Amir H Daraie
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA; Department of Neuroengineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|
2
|
Frauscher B, Bartolomei F, Baud MO, Smith RJ, Worrell G, Lundstrom BN. Stimulation to probe, excite, and inhibit the epileptic brain. Epilepsia 2023; 64 Suppl 3:S49-S61. [PMID: 37194746 PMCID: PMC10654261 DOI: 10.1111/epi.17640] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/18/2023]
Abstract
Direct cortical stimulation has been applied in epilepsy for nearly a century and has experienced a renaissance, given unprecedented opportunities to probe, excite, and inhibit the human brain. Evidence suggests stimulation can increase diagnostic and therapeutic utility in patients with drug-resistant epilepsies. However, choosing appropriate stimulation parameters is not a trivial issue, and is further complicated by epilepsy being characterized by complex brain state dynamics. In this article derived from discussions at the ICTALS 2022 Conference (International Conference on Technology and Analysis for Seizures), we succinctly review the literature on cortical stimulation applied acutely and chronically to the epileptic brain for localization, monitoring, and therapeutic purposes. In particular, we discuss how stimulation is used to probe brain excitability, discuss evidence on the usefulness of stimulation to trigger and stop seizures, review therapeutic applications of stimulation, and finally discuss how stimulation parameters are impacted by brain dynamics. Although research has advanced considerably over the past decade, there are still significant hurdles to optimizing use of this technique. For example, it remains unclear to what extent short timescale diagnostic biomarkers can predict long-term outcomes and to what extent these biomarkers add information to already existing biomarkers from passive electroencephalographic recordings. Further questions include the extent to which closed loop stimulation offers advantages over open loop stimulation, what the optimal closed loop timescales may be, and whether biomarker-informed stimulation can lead to seizure freedom. The ultimate goal of bioelectronic medicine remains not just to stop seizures but rather to cure epilepsy and its comorbidities.
Collapse
Affiliation(s)
- Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Fabrice Bartolomei
- Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, France. AP-HM, Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
| | - Maxime O. Baud
- Sleep-Wake-Epilepsy Center, NeuroTec and Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Bern
| | - Rachel J. Smith
- University of Alabama at Birmingham, Electrical and Computer Engineering Department, Birmingham, Alabama, US. University of Alabama at Birmingham, Neuroengineering Program, Birmingham, Alabama, US
| | - Greg Worrell
- Department of Neurology, Mayo Clinic, Rochester, US
| | | |
Collapse
|
3
|
Gunnarsdottir KM, Li A, Smith RJ, Kang JY, Korzeniewska A, Crone NE, Rouse AG, Cheng JJ, Kinsman MJ, Landazuri P, Uysal U, Ulloa CM, Cameron N, Cajigas I, Jagid J, Kanner A, Elarjani T, Bicchi MM, Inati S, Zaghloul KA, Boerwinkle VL, Wyckoff S, Barot N, Gonzalez-Martinez J, Sarma SV. Source-sink connectivity: a novel interictal EEG marker for seizure localization. Brain 2022; 145:3901-3915. [PMID: 36412516 PMCID: PMC10200292 DOI: 10.1093/brain/awac300] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 07/05/2022] [Accepted: 08/01/2022] [Indexed: 07/26/2023] Open
Abstract
Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.
Collapse
Affiliation(s)
| | - Adam Li
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Joon-Yi Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Adam G Rouse
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Jennifer J Cheng
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Michael J Kinsman
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Patrick Landazuri
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Utku Uysal
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Carol M Ulloa
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Nathaniel Cameron
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Iahn Cajigas
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Jonathan Jagid
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Andres Kanner
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Turki Elarjani
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Manuel Melo Bicchi
- Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sara Inati
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kareem A Zaghloul
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Varina L Boerwinkle
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Sarah Wyckoff
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ 85016, USA
| | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| |
Collapse
|
4
|
Papadelis C, Perry MS. Localizing the Epileptogenic Zone with Novel Biomarkers. Semin Pediatr Neurol 2021; 39:100919. [PMID: 34620466 PMCID: PMC8501232 DOI: 10.1016/j.spen.2021.100919] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 01/01/2023]
Abstract
Several noninvasive methods, such as high-density EEG or magnetoencephalography, are currently used to delineate the epileptogenic zone (EZ) during the presurgical evaluation of patients with drug resistant epilepsy (DRE). Yet, none of these methods can reliably identify the EZ by their own. In most cases a multimodal approach is needed. Challenging cases often require the implantation of intracranial electrodes, either through stereo-taxic EEG or electro-corticography. Recently, a growing body of literature introduces novel biomarkers of epilepsy that can be used for analyzing both invasive as well as noninvasive electrophysiological data. Some of these biomarkers are able to delineate the EZ with high precision, augment the presurgical evaluation, and predict the surgical outcome of patients with DRE undergoing surgery. However, the use of these epilepsy biomarkers in clinical practice is limited. Here, we summarize and discuss the latest technological advances in the presurgical neurophysiological evaluation of children with DRE with emphasis on electric and magnetic source imaging, high frequency oscillations, and functional connectivity.
Collapse
Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX; Department of Bioengineering, University of Texas at Arlington, Arlington, TX; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.
| | - M Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
| |
Collapse
|
5
|
Sun K, Wang H, Bai Y, Zhou W, Wang L. MRIES: A Matlab Toolbox for Mapping the Responses to Intracranial Electrical Stimulation. Front Neurosci 2021; 15:652841. [PMID: 34194294 PMCID: PMC8236813 DOI: 10.3389/fnins.2021.652841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 04/26/2021] [Indexed: 11/26/2022] Open
Abstract
Propose Directed cortical responses to intracranial electrical stimulation are a good standard for mapping inter-regional direct connectivity. Cortico-cortical evoked potential (CCEP), elicited by single pulse electrical stimulation (SPES), has been widely used to map the normal and abnormal brain effective network. However, automated processing of CCEP datasets and visualization of connectivity results remain challenging for researchers and clinicians. In this study, we develop a Matlab toolbox named MRIES (Mapping the Responses to Intracranial Electrical Stimulation) to automatically process CCEP data and visualize the connectivity results. Method The MRIES integrates the processing pipeline of the CCEP datasets and various methods for connectivity calculation based on low- and high-frequency signals with stimulation artifacts removed. The connectivity matrices are saved in different folders for visualization. Different visualization patterns (connectivity matrix, circle map, surface map, and volume map) are also integrated to the graphical user interface (GUI), which makes it easy to intuitively display and compare different connectivity measurements. Furthermore, one sample CCEP data set collected from eight epilepsy patients is used to validate the MRIES toolbox. Result We show the GUI and visualization functions of MRIES using one example CCEP data that has been described in a complete tutorial. We applied this toolbox to the sample CCEP data set to investigate the direct connectivity between the medial temporal lobe and the insular cortex. We find bidirectional connectivity between MTL and insular that are consistent with the findings of previous studies. Conclusion MRIES has a friendly GUI and integrates the full processing pipeline of CCEP data and various visualization methods. The MRIES toolbox, tutorial, and example data can be freely downloaded. As an open-source package, MRIES is expected to improve the reproducibility of CCEP findings and facilitate clinical translation.
Collapse
Affiliation(s)
- Kaijia Sun
- School of Systems Science, Beijing Normal University, Beijing, China.,CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Haixiang Wang
- Epilepsy Center, Tsinghua University Yuquan Hospital, Beijing, China
| | - Yunxian Bai
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China
| | - Wenjing Zhou
- Epilepsy Center, Tsinghua University Yuquan Hospital, Beijing, China
| | - Liang Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
6
|
Kamali G, Smith RJ, Hays M, Coogan C, Crone NE, Kang JY, Sarma SV. Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials. Front Neurol 2020; 11:579961. [PMID: 33362689 PMCID: PMC7758451 DOI: 10.3389/fneur.2020.579961] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 10/12/2020] [Indexed: 11/26/2022] Open
Abstract
Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent “peak gain” of the system as measured by the H∞ norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest “floor gain” (gain at which the dipped H∞ 3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes.
Collapse
Affiliation(s)
- Golnoosh Kamali
- Neuromedical Control Systems Laboratory, Department of Electrical and Computer Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Rachel June Smith
- Neuromedical Control Systems Laboratory, Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Mark Hays
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Christopher Coogan
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Nathan E Crone
- Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Joon Y Kang
- Department of Neurology-Epilepsy, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Sridevi V Sarma
- Neuromedical Control Systems Laboratory, Department of Electrical and Computer Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.,Neuromedical Control Systems Laboratory, Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| |
Collapse
|
7
|
Tóth E, Bokodi V, Somogyvári Z, Maglóczky Z, Wittner L, Ulbert I, Erőss L, Fabó D. Laminar distribution of electrically evoked hippocampal short latency ripple activity highlights the importance of the subiculum in vivo in human epilepsy, an intraoperative study. Epilepsy Res 2020; 169:106509. [PMID: 33310654 DOI: 10.1016/j.eplepsyres.2020.106509] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/04/2020] [Accepted: 11/21/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE The goal of this study was to define the pathology and anesthesia dependency of single pulse electrical stimulation (SPES) dependent high-frequency oscillations (HFOs, ripples, fast ripples) in the hippocampal formation. METHODS Laminar profile of electrically evoked short latency (<100 ms) high-frequency oscillations (80-500 Hz) was examined in the hippocampus of therapy-resistant epileptic patients (6 female, 2 male) in vivo, under general anesthesia. RESULTS Parahippocampal SPES evoked HFOs in all recorded hippocampal subregions (Cornu Ammonis 2-3, dentate gyrus, and subiculum) were not uniform, rather the combination of ripples, fast ripples, sharp transients, and multiple unit activities. Mild and severe hippocampal sclerosis (HS) differed in the probability to evoke fast ripples: it decreased with the severity of sclerosis in CA2-3 but increased in the subiculum. Modulation in the ripple spectrum was observed only in the subiculum with increased fast HFO rate and frequency in severe HS. Inhalational anesthetics (isoflurane) suppressed the chance to evoke HFOs compared to propofol. CONCLUSION The presence of early HFOs in the dentate gyrus and early fast HFOs (>250 Hz) in the other subregions indicate the pathological nature of these evoked oscillations. Subiculum was found to be active producing HFOs in parallel with the cell loss in the hippocampus proper, which emphasize the role of this region in the generation of epileptic activity.
Collapse
Affiliation(s)
- Emília Tóth
- Epilepsy Centrum, Dept of Neurology, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary; Department of Neurology, The University of Texas Health Science Center at Houston, Houston, Texas, 77030, USA (present affiliation)
| | - Virág Bokodi
- Epilepsy Centrum, Dept of Neurology, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary; Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, 1083, Hungary
| | - Zoltán Somogyvári
- Department of Computational Sciences, Wigner Research Centre, Eötvös Loránd Research Network, Budapest, 1121, Hungary
| | - Zsófia Maglóczky
- Department of Cellular and Network Neurobiology, Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, 1083, Hungary; Human Brain Research Laboratory, Institute of Experimental Medicine, Eötvös Loránd Research Network, Budapest, 1083, Hungary
| | - Lucia Wittner
- Epilepsy Centrum, Dept of Neurology, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary; Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, 1083, Hungary; Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Eötvös Loránd Research Network, Budapest, 1117, Hungary
| | - István Ulbert
- Epilepsy Centrum, Dept of Neurology, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary; Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, 1083, Hungary; Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Eötvös Loránd Research Network, Budapest, 1117, Hungary
| | - Loránd Erőss
- Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, 1083, Hungary; Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary
| | - Dániel Fabó
- Epilepsy Centrum, Dept of Neurology, National Institute of Clinical Neurosciences, Budapest, 1145, Hungary.
| |
Collapse
|
8
|
Usami K, Korzeniewska A, Matsumoto R, Kobayashi K, Hitomi T, Matsuhashi M, Kunieda T, Mikuni N, Kikuchi T, Yoshida K, Miyamoto S, Takahashi R, Ikeda A, Crone NE. The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation. Sleep 2019; 42:zsz050. [PMID: 30794319 PMCID: PMC6559171 DOI: 10.1093/sleep/zsz050] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 02/01/2019] [Indexed: 12/12/2022] Open
Abstract
Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.
Collapse
Affiliation(s)
- Kiyohide Usami
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Takefumi Hitomi
- Department of Clinical Laboratory Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
- Department of Respiratory Care and Sleep Control Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Masao Matsuhashi
- Research and Educational Unit of Leaders for Integrated Medical System, Kyoto University Graduate School of medicine, Sakyo-ku, Kyoto, Japan
- Human Brain Research Center, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
- Department of Neurosurgery, Ehime University Graduate School of Medicine, Shizukawa Toon city, Ehime, Japan
| | - Nobuhiro Mikuni
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
- Department of Neurosurgery, Sapporo Medical University, Chuo-ku, Sapporo, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto, Japan
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| |
Collapse
|
9
|
Thomschewski A, Hincapié AS, Frauscher B. Localization of the Epileptogenic Zone Using High Frequency Oscillations. Front Neurol 2019; 10:94. [PMID: 30804887 PMCID: PMC6378911 DOI: 10.3389/fneur.2019.00094] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/23/2019] [Indexed: 01/22/2023] Open
Abstract
For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40-50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.
Collapse
Affiliation(s)
- Aljoscha Thomschewski
- Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria
- Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
| | - Ana-Sofía Hincapié
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| |
Collapse
|
10
|
Khadjevand F, Cimbalnik J, Worrell GA. Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2017. [PMID: 29532041 DOI: 10.1016/j.cobme.2017.09.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
High-frequency oscillations (HFOs: 100 - 600 Hz) have been widely proposed as biomarkers of epileptic brain tissue. In addition, HFOs over a broader range of frequencies spanning 30 - 2000 Hz are potential biomarkers of both physiological and pathological brain processes. The majority of the results from humans with focal epilepsy have focused on HFOs recorded directly from the brain with intracranial EEG (iEEG) in the high gamma (65 - 100 Hz), ripple (100 - 250 Hz), and fast ripple (250 - 600 Hz) frequency ranges. These results are supplemented by reports of HFOs recorded with iEEG in the low gamma (30 - 65Hz) and very high frequency (500 - 2000 Hz) ranges. Visual detection of HFOs is laborious and limited by poor inter-rater agreement; and the need for accurate, reproducible automated HFOs detection is well recognized. In particular, the clinical translation of HFOs as a biomarker of the epileptogenic brain has been limited by the ability to reliably detect and accurately classify HFOs as physiological or pathological. Despite these challenges, there has been significant progress in the field, which is the subject of this review. Furthermore, we provide data and corresponding analytic code in an effort to promote reproducible research and accelerate clinical translation.
Collapse
Affiliation(s)
- Fatemeh Khadjevand
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA
| | - Jan Cimbalnik
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA.,International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic
| | - Gregory A Worrell
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA.,Department of Biomedical Engineering and Physiology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA
| |
Collapse
|
11
|
Single pulse electrical stimulation and high-frequency oscillations, a complicated marriage. Clin Neurophysiol 2017; 128:1026-1027. [PMID: 28341565 DOI: 10.1016/j.clinph.2017.02.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 02/22/2017] [Indexed: 11/23/2022]
|
12
|
Asano E. High-frequency oscillations are under your control. Don't chase all of them. Clin Neurophysiol 2017; 128:841-842. [PMID: 28283356 DOI: 10.1016/j.clinph.2017.02.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 02/10/2017] [Indexed: 10/20/2022]
Affiliation(s)
- Eishi Asano
- Departments of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University, Detroit Medical Center, Detroit, MI 48201, USA.
| |
Collapse
|