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Cho E, Kwon J, Lee G, Shin J, Lee H, Lee SH, Chung CK, Yoon J, Ho WK. Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy. Nat Commun 2024; 15:6683. [PMID: 39107293 PMCID: PMC11303528 DOI: 10.1038/s41467-024-51065-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 07/26/2024] [Indexed: 08/10/2024] Open
Abstract
Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs.
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Affiliation(s)
- Eunhye Cho
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Jii Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Gyuwon Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Jiwoo Shin
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Hyunsu Lee
- Department of Physiology, Pusan National University School of Medicine, Busan, Korea
| | - Suk-Ho Lee
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea
| | - Chun Kee Chung
- Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea.
- Neuroscience Research Institute, Seoul National University Medical Research Center, Seoul, Korea.
| | - Jaeyoung Yoon
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea.
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Won-Kyung Ho
- Cell Physiology Laboratory, Department of Physiology, Seoul National University College of Medicine, Seoul, Korea.
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea.
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Wendling F, Koksal-Ersoz E, Al-Harrach M, Yochum M, Merlet I, Ruffini G, Bartolomei F, Benquet P. Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy. Clin Neurophysiol 2024; 161:198-210. [PMID: 38520800 DOI: 10.1016/j.clinph.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 03/06/2024] [Accepted: 03/11/2024] [Indexed: 03/25/2024]
Abstract
OBJECTIVE The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. METHODS We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. RESULTS For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. CONCLUSIONS The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SIGNIFICANCE These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.
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Affiliation(s)
| | | | | | | | | | | | - Fabrice Bartolomei
- APHM, Timone Hospital, Epileptology and Cerebral Rhythmology Department, Marseille, France; Univ Aix Marseille, INSERM, INS, Inst Neurosci Syst, Marseille, France
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3
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Goldenberg AM, Schmidt S, Mitelman R, Levy DR, Prigge M, Katz Y, Yizhar O, Beck H, Lampl I. Localized chemogenetic silencing of inhibitory neurons: a novel mouse model of focal cortical epileptic activity. Cereb Cortex 2023; 33:2838-2856. [PMID: 35788286 DOI: 10.1093/cercor/bhac245] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/17/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Focal cortical epilepsies are frequently refractory to available anticonvulsant drug therapies. One key factor contributing to this state is the limited availability of animal models that allow to reliably study focal cortical seizures and how they recruit surrounding brain areas in vivo. In this study, we selectively expressed the inhibitory chemogenetic receptor, hM4D, in GABAergic neurons in focal cortical areas using viral gene transfer. GABAergic silencing using Clozapine-N-Oxide (CNO) demonstrated reliable induction of local epileptiform events in the electroencephalogram signal of awake freely moving mice. Anesthetized mice experiments showed consistent induction of focal epileptiform-events in both the barrel cortex (BC) and the medial prefrontal cortex (mPFC), accompanied by high-frequency oscillations, a known characteristic of human seizures. Epileptiform-events showed propagation indication with favored propagation pathways: from the BC on 1 hemisphere to its counterpart and from the BC to the mPFC, but not vice-versa. Lastly, sensory whisker-pad stimulation evoked BC epileptiform events post-CNO, highlighting the potential use of this model in studying sensory-evoked seizures. Combined, our results show that targeted chemogenetic inhibition of GABAergic neurons using hM4D can serve as a novel, versatile, and reliable model of focal cortical epileptic activity suitable for systematically studying cortical ictogenesis in different cortical areas.
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Affiliation(s)
- Adi Miriam Goldenberg
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Sarah Schmidt
- Institute for Experimental Epileptology and Cognition Research, Life and Brain Center, University of Bonn, Bonn 53105, Germany
| | - Rea Mitelman
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Dana Rubi Levy
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Matthias Prigge
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Yonatan Katz
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Ofer Yizhar
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Heinz Beck
- Institute for Experimental Epileptology and Cognition Research, Life and Brain Center, University of Bonn, Bonn 53105, Germany
| | - Ilan Lampl
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
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4
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Lai N, Li Z, Xu C, Wang Y, Chen Z. Diverse nature of interictal oscillations: EEG-based biomarkers in epilepsy. Neurobiol Dis 2023; 177:105999. [PMID: 36638892 DOI: 10.1016/j.nbd.2023.105999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/07/2023] [Accepted: 01/09/2023] [Indexed: 01/11/2023] Open
Abstract
Interictal electroencephalogram (EEG) patterns, including high-frequency oscillations (HFOs), interictal spikes (ISs), and slow wave activities (SWAs), are defined as specific oscillations between seizure events. These interictal oscillations reflect specific dynamic changes in network excitability and play various roles in epilepsy. In this review, we briefly describe the electrographic characteristics of HFOs, ISs, and SWAs in the interictal state, and discuss the underlying cellular and network mechanisms. We also summarize representative evidence from experimental and clinical epilepsy to address their critical roles in ictogenesis and epileptogenesis, indicating their potential as electrophysiological biomarkers of epilepsy. Importantly, we put forwards some perspectives for further research in the field.
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Affiliation(s)
- Nanxi Lai
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhisheng Li
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Cenglin Xu
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yi Wang
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhong Chen
- Institute of Pharmacology & Toxicology, NHC and CAMS Key Laboratory of Medical Neurobiology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China; Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Science, Zhejiang Chinese Medical University, Hangzhou, China; Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
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Kalogeropoulos K, Kleidonas D, Psarropoulou C. Timing differences between HFOs and interictal epileptiform discharges generated in vitro by different mechanisms in rat hippocampal slices: A novel approach. Epilepsia Open 2022; 7:608-615. [PMID: 35908206 PMCID: PMC9712485 DOI: 10.1002/epi4.12633] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/28/2022] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To investigate the effect of generating mechanism on the relationship between interictal-like epileptiform discharges (IEDs) and the underlying High Frequency Oscillations (HFOs; Ripples, R, and Fast Ripples, FR). METHODS Synchronous spontaneous IEDs were recorded from the CA1 area of hippocampal slices from adult rats, perfused by Mg2+ -free ACSF (n = 41slices/14 animals) or 4-aminopyridine (50 μM, n = 37slices/16 animals); IED filtering revealed Rs and FRs and several metrics were calculated and compared (amplitude, duration, relative onset, time lag, % overlap, peak frequency, peak power, FR/R). RESULTS Longer IEDs and higher 1st Population Spike (PS) amplitude in Mg2+ -free ACSF (vs 4-AP; P < .001, P < .001) correlated with longer duration and higher amplitude Rs (P < .0001, P = .001) and longer duration FRs (P < .001). In both media, Rs and FRs appeared before IED onset with Rs preceding FRs; R- and FR-IED lag (P = .008, P = .01) as well as R-FR lag (P = .04) were significantly longer in Mg2+ -free ACSF vs in 4-AP. R peak frequency and power were higher in Mg2+ -free ACSF, while no such differences were observed in FRs. Inter-model differences were mostly reflected in Rs, not FRs, suggesting that mechanisms unique to R generation are more active in Mg2+ -free ACSF vs in 4-AP. FRs appeared to contribute equally to IEDs irrespective of generating mechanism. SIGNIFICANCE Several of the metrics used, particularly those regarding the timing between HFOs and IEDs, appear to correlate with the synchronizing mechanism and we propose that they may be useful when investigating antiepileptic substance effects on neuronal network activity.
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Affiliation(s)
- Konstantinos Kalogeropoulos
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health SciencesUniversity of IoanninaIoanninaGreece
| | - Dimitrios Kleidonas
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health SciencesUniversity of IoanninaIoanninaGreece,Department of Neuroanatomy, Faculty of MedicineInstitute of Anatomy and Cell Biology, University of FreiburgFreiburgGermany
| | - Caterina Psarropoulou
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health SciencesUniversity of IoanninaIoanninaGreece,Department of Biological Applications & TechnologiesUniversity of IoanninaIoanninaGreece
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Bruder JC, Wagner K, Lachner-Piza D, Klotz KA, Schulze-Bonhage A, Jacobs J. Mesial-Temporal Epileptic Ripples Correlate With Verbal Memory Impairment. Front Neurol 2022; 13:876024. [PMID: 35720106 PMCID: PMC9204013 DOI: 10.3389/fneur.2022.876024] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/05/2022] [Indexed: 12/03/2022] Open
Abstract
Rationale High frequency oscillations (HFO; ripples = 80–200, fast ripples 200–500 Hz) are promising epileptic biomarkers in patients with epilepsy. However, especially in temporal epilepsies differentiation of epileptic and physiological HFO activity still remains a challenge. Physiological sleep-spindle-ripple formations are known to play a role in slow-wave-sleep memory consolidation. This study aimed to find out if higher rates of mesial-temporal spindle-ripples correlate with good memory performance in epilepsy patients and if surgical removal of spindle-ripple-generating brain tissue correlates with a decline in memory performance. In contrast, we hypothesized that higher rates of overall ripples or ripples associated with interictal epileptic spikes correlate with poor memory performance. Methods Patients with epilepsy implanted with electrodes in mesial-temporal structures, neuropsychological memory testing and subsequent epilepsy surgery were included. Ripples and epileptic spikes were automatically detected in intracranial EEG and sleep-spindles in scalp EEG. The coupling of ripples to spindles was automatically analyzed. Mesial-temporal spindle-ripple rates in the speech-dominant-hemisphere (left in all patients) were correlated with verbal memory test results, whereas ripple rates in the non-speech-dominant hemisphere were correlated with non-verbal memory test performance, using Spearman correlation). Results Intracranial EEG and memory test results from 25 patients could be included. All ripple rates were significantly higher in seizure onset zone channels (p < 0.001). Patients with pre-surgical verbal memory impairment had significantly higher overall ripple rates in left mesial-temporal channels than patients with intact verbal memory (Mann–Whitney-U-Test: p = 0.039). Spearman correlations showed highly significant negative correlations of the pre-surgical verbal memory performance with left mesial-temporal spike associated ripples (rs = −0.458; p = 0.007) and overall ripples (rs = −0.475; p = 0.006). All three ripple types in right-sided mesial-temporal channels did not correlate with pre-surgical nonverbal memory. No correlation for the difference between post- and pre-surgical memory and pre-surgical spindle-ripple rates was seen in patients with left-sided temporal or mesial-temporal surgery. Discussion This study fails to establish a clear link between memory performance and spindle ripples. This highly suggests that spindle-ripples are only a small portion of physiological ripples contributing to memory performance. More importantly, this study indicates that spindle-ripples do not necessarily compromise the predictive value of ripples in patients with temporal epilepsy. The majority of ripples were clearly linked to areas with poor memory function.
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Affiliation(s)
- Jonas Christian Bruder
- Clinic of Neuropediatrics and Muscle Disorders, Freiburg University Medical Center, Breisgau, Germany
- *Correspondence: Jonas Christian Bruder
| | - Kathrin Wagner
- Abteilung Epileptologie Epilepsiezentrum, Klinik Für Neurochirurgie, Universitätsklinikum Freiburg, Breisgau, Germany
| | - Daniel Lachner-Piza
- Clinic of Neuropediatrics and Muscle Disorders, Freiburg University Medical Center, Breisgau, Germany
| | - Kerstin Alexandra Klotz
- Clinic of Neuropediatrics and Muscle Disorders, Freiburg University Medical Center, Breisgau, Germany
| | - Andreas Schulze-Bonhage
- Abteilung Epileptologie Epilepsiezentrum, Klinik Für Neurochirurgie, Universitätsklinikum Freiburg, Breisgau, Germany
| | - Julia Jacobs
- Clinic of Neuropediatrics and Muscle Disorders, Freiburg University Medical Center, Breisgau, Germany
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Schumm SN, Gabrieli D, Meaney DF. Plasticity impairment exposes CA3 vulnerability in a hippocampal network model of mild traumatic brain injury. Hippocampus 2022; 32:231-250. [PMID: 34978378 DOI: 10.1002/hipo.23402] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/08/2021] [Accepted: 11/18/2021] [Indexed: 11/10/2022]
Abstract
Proper function of the hippocampus is critical for executing cognitive tasks such as learning and memory. Traumatic brain injury (TBI) and other neurological disorders are commonly associated with cognitive deficits and hippocampal dysfunction. Although there are many existing models of individual subregions of the hippocampus, few models attempt to integrate the primary areas into one system. In this work, we developed a computational model of the hippocampus, including the dentate gyrus, CA3, and CA1. The subregions are represented as an interconnected neuronal network, incorporating well-characterized ex vivo slice electrophysiology into the functional neuron models and well-documented anatomical connections into the network structure. In addition, since plasticity is foundational to the role of the hippocampus in learning and memory as well as necessary for studying adaptation to injury, we implemented spike-timing-dependent plasticity among the synaptic connections. Our model mimics key features of hippocampal activity, including signal frequencies in the theta and gamma bands and phase-amplitude coupling in area CA1. We also studied the effects of spike-timing-dependent plasticity impairment, a potential consequence of TBI, in our model and found that impairment decreases broadband power in CA3 and CA1 and reduces phase coherence between these two subregions, yet phase-amplitude coupling in CA1 remains intact. Altogether, our work demonstrates characteristic hippocampal activity with a scaled network model of spiking neurons and reveals the sensitive balance of plasticity mechanisms in the circuit through one manifestation of mild traumatic injury.
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Affiliation(s)
- Samantha N Schumm
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David Gabrieli
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David F Meaney
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Neurosurgery, Penn Center for Brain Injury and Repair, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Gliske SV. High frequency oscillations and interictal discharges at 50 μm spatial resolution. Clin Neurophysiol 2021; 132:2894-2895. [PMID: 34563456 PMCID: PMC8675397 DOI: 10.1016/j.clinph.2021.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 08/29/2021] [Indexed: 11/19/2022]
Affiliation(s)
- Stephen V Gliske
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE, USA.
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Stovall T, Hunt B, Glynn S, Stacey WC, Gliske SV. Interictal high frequency background activity as a biomarker of epileptogenic tissue. Brain Commun 2021; 3:fcab188. [PMID: 34704026 PMCID: PMC8417455 DOI: 10.1093/braincomms/fcab188] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 06/17/2021] [Accepted: 06/28/2021] [Indexed: 11/16/2022] Open
Abstract
High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency ‘background’ data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the EZ. We analysed intracranial EEG (30–500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63–307 h per subject), excluding all detected HFOs. We assessed association between each feature and the seizure onset zone (SOZ) and resected volume (RV) using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross-validation to avoid in-sample training. Association of the pathology score with the SOZ and RV was quantified using an asymmetry measure. Many features were associated with the SOZ: 23/38 features had odds ratios >1.3 or <0.7 and 17/38 had odds ratios different than zero with high significance (P < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of HFOs, and their channel-wise product were each strongly associated with the SOZ [median asymmetry ≥0.44, good surgery outcome patients; median asymmetry ≥0.40, patients with other outcomes; 95% confidence interval (CI) > 0.27 in both cases]. The pathology score and the channel-wise product also had higher asymmetry with respect to the SOZ than the HFO rate alone (median difference in asymmetry ≥0.18, 95% CI >0.05). These results support that the high frequency background data contains useful information for determining the EZ, distinct and complementary to information from detected HFOs. The concordance between the high frequency activity pathology score and the rate of HFOs appears to be a better biomarker of epileptic tissue than either measure alone.
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Affiliation(s)
- Truman Stovall
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Brian Hunt
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Simon Glynn
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - William C Stacey
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Stephen V Gliske
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.,Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE, USA
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Lisgaras CP, Mikroulis A, Psarropoulou C. Region-specific Effects of Early-life Status Epilepticus on the Adult Hippocampal CA3 - Medial Entorhinal Cortex Circuitry In vitro: Focus on Interictal Spikes and Concurrent High-frequency Oscillations. Neuroscience 2021; 466:235-247. [PMID: 33961962 DOI: 10.1016/j.neuroscience.2021.04.030] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 04/25/2021] [Accepted: 04/26/2021] [Indexed: 11/29/2022]
Abstract
Convulsive status epilepticus (SE) in immature life is often associated with lasting neurobiological changes. We provoked SE by pentylenetetrazole in postnatal day 20 rat pups and examined communication modalities between the temporal hippocampus and medial entorhinal cortex (mEC) in vitro. After a minimum of 40 days post-SE, we prepared combined temporal hippocampal - medial entorhinal cortex (mEC) slices from conditioned (SE) and naïve (N) adult rats and recorded 4-aminopyridine-induced spontaneous epileptiform interictal-like discharges (IED) simultaneously from CA3 and mEC layer V-VI. We analyzed IED frequency and high frequency oscillations (HFOs) in intact slices and after surgical separation of hippocampus from mEC, by two successive incisions (Schaffer collateral cut, Parasubiculum cut). In all slices, IED frequency was higher in CA3 vs mEC (5N, 4SE) and Raster plots indicated no temporal coincidence between them either in intact or in CA1-cut slices (4N, 4SE). IED frequency was significantly higher in SE mEC, but similar in SE and N CA3, independently of connectivity state. Ripples (R) and Fast Ripples (FR) coincided with IEDs and their power differed between SE and N intact slices (22N, 12SE), both in CA3 and mEC. CA3 FR/R ratios were higher in the absence of mEC (14N, 8SE). Moreover, SE (vs N) slices showed significantly higher FR/R ratios independently of the presence of mEC. Taken together, these findings suggest lasting effects of immature SE in network dynamics governing hippocampal-entorhinal communication which may impact adult cognitive, behavioral, and/or seizure threshold sequalae.
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Affiliation(s)
- Christos Panagiotis Lisgaras
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health Sciences, University of Ioannina, 45110 Ioannina, Greece.
| | - Apostolos Mikroulis
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health Sciences, University of Ioannina, 45110 Ioannina, Greece.
| | - Caterina Psarropoulou
- Laboratory of Animal and Human Physiology, Department of Biological Applications and Technology, Faculty of Health Sciences, University of Ioannina, 45110 Ioannina, Greece.
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Chiprés-Tinajero GA, Núñez-Ochoa MA, Medina-Ceja L. Increased immunoreactivity of glutamate receptors, neuronal nuclear protein and glial fibrillary acidic protein in the hippocampus of epileptic rats with fast ripple activity. Exp Brain Res 2021; 239:2015-2024. [PMID: 33909110 DOI: 10.1007/s00221-021-06108-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 04/08/2021] [Indexed: 11/28/2022]
Abstract
Epilepsy is a neurological disorder in which an imbalance between excitatory and inhibitory transmission is observed. Glutamate is the principal excitatory neurotransmitter that acts through ionic and metabotropic receptors; both types of receptors are involved in temporal lobe epilepsy (TLE). High frequency oscillations called fast ripples (FR, 250-600 Hz) have been observed, particularly in the hippocampus, and they are involved in epileptogenesis. The present study analyzed the immunoreactivity of the principal glutamate receptors associated with epilepsy in epileptic animals with FR activity. Male Swiss-Wistar rats (210-250 gr) were injected with pilocarpine (2.4 mg/2 µl) and were video monitored (24/7) until the appearance of spontaneous and recurrent seizures. Then, a deep microelectrode implantation surgery was performed in the DG, CA3 and CA1 regions, and FR activity was observed 1-, 2-, 3-, 7-, and 14-day postsurgery. The animals were sacrificed on day 15, and fluorescence immunohistochemistry was carried out in the hippocampus for the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), N-methyl-D-aspartate (NMDA) and mGlu-R5 glutamate receptors as well as Neuronal Nuclear Protein (NeuN) and Glial Fibrillary Acidic Protein (GFAP). An increase in the immunoreactivity for the three receptors was found. However, the AMPA receptor showed an increase in the three regions analyzed (i.e., DG, CA1 and CA3). The findings showed a decrease of NeuN in the DG and an increase of GFAP. These results suggest an important role of glutamate receptors in the hippocampus of epileptic rats with FR activity.
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Affiliation(s)
- Gustavo A Chiprés-Tinajero
- Laboratory of Neurophysiology, Department of Cellular and Molecular Biology, CUCBA, University of Guadalajara, Camino Ing. R. Padilla Sánchez 2100, Las Agujas, Nextipac, Zapopan, Jalisco, 45110, México
| | - Miguel A Núñez-Ochoa
- Laboratory of Neurophysiology, Department of Cellular and Molecular Biology, CUCBA, University of Guadalajara, Camino Ing. R. Padilla Sánchez 2100, Las Agujas, Nextipac, Zapopan, Jalisco, 45110, México
| | - Laura Medina-Ceja
- Laboratory of Neurophysiology, Department of Cellular and Molecular Biology, CUCBA, University of Guadalajara, Camino Ing. R. Padilla Sánchez 2100, Las Agujas, Nextipac, Zapopan, Jalisco, 45110, México.
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Abstract
Temporal lobe epilepsy (TLE) is the most common type of drug-resistant focal epilepsy. Epilepsy can be conceptualized as a network disorder with the epileptogenic zone a critical node of the network. Temporal lobe networks can be identified on the microscale and macroscale, both during the interictal and ictal periods. This review summarizes the current understanding of TLE networks as studied by neurophysiological and imaging techniques discussing both functional and structural connectivity.
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Donos C, Mîndruţă I, Barborica A. Unsupervised Detection of High-Frequency Oscillations Using Time-Frequency Maps and Computer Vision. Front Neurosci 2020; 14:183. [PMID: 32265622 PMCID: PMC7104802 DOI: 10.3389/fnins.2020.00183] [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: 08/01/2019] [Accepted: 02/19/2020] [Indexed: 12/15/2022] Open
Abstract
High-frequency oscillations >80 Hz (HFOs) have unique features distinguishing them from spikes and artifactual components that can be well-evidenced in the time-frequency representations. We introduce an unsupervised HFO detector that uses computer-vision algorithms to detect HFO landmarks on two-dimensional (2D) time-frequency maps. To validate the detector, we introduce an analytical model of the HFO based on a sinewave having a Gaussian envelope, for which analytical equations in time-frequency space can be derived, allowing us to establish a direct correspondence between common HFO detection criteria in the time domain with the ones in the frequency domain, used by the computer-vision detection algorithm. The detector identifies potential HFO events on the time-frequency representation, which are classified as true HFOs if criteria regarding the HFO's frequency, amplitude, and duration are met. The detector is validated on simulated HFOs according to the analytical model, in the presence of noise, with different signal-to-noise ratios (SNRs) ranging from −9 to 0 dB. The detector's sensitivity was 0.64 at an SNR of −9 dB, 0.98 at −6 dB, and >0.99 at −3 dB and 0 dB, while its positive prediction value was >0.95, regardless of the SNR. Using the same simulation dataset, our detector is benchmarked against four previously published HFO detectors. The F-measure, a combined metric that takes into account both sensitivity and positive prediction value, was used to compare detection algorithms. Our detector surpassed the other detectors at −6, −3, and 0 dB and had the second best F-score at −9 dB SNR after the MNI detector (0.77 vs. 0.83). The ability to detect HFOs in clinical recordings has been tested on a set of 36 intracranial electroencephalogram (EEG) channels in six patients, with 89% of the detections being validated by two independent reviewers. The results demonstrate that the unsupervised detection of HFOs based on their 2D features in time-frequency maps is feasible and has a performance comparable or better than the most used HFO detectors.
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Affiliation(s)
- Cristian Donos
- Physics Department, Bucharest University, Bucharest, Romania
| | - Ioana Mîndruţă
- Department of Neurology, Bucharest University Emergency Hospital, Bucharest, Romania.,Department of Neurology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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14
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Holzbecher A, Kempter R. Interneuronal gap junctions increase synchrony and robustness of hippocampal ripple oscillations. Eur J Neurosci 2019; 48:3446-3465. [PMID: 30414336 DOI: 10.1111/ejn.14267] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 10/12/2018] [Accepted: 10/31/2018] [Indexed: 01/21/2023]
Abstract
Sharp wave-ripples (SWRs) are important for memory consolidation. Their signature in the hippocampal extracellular field potential can be decomposed into a ≈100 ms long sharp wave superimposed by ≈200 Hz ripple oscillations. How ripple oscillations are generated is currently not well understood. A promising model for the genesis of ripple oscillations is based on recurrent interneuronal networks (INT-INT). According to this hypothesis, the INT-INT network in CA1 receives a burst of excitation from CA3 that generates the sharp wave, and recurrent inhibition leads to an ultrafast synchronization of the CA1 network causing the ripple oscillations; fast-spiking parvalbumin-positive basket cells (PV+ BCs) may constitute the ripple-generating interneuronal network. PV+ BCs are also coupled by gap junctions (GJs) but the function of GJs for ripple oscillations has not been quantified. Using simulations of CA1 hippocampal networks of PV+ BCs, we show that GJs promote synchrony beyond a level that could be obtained by only inhibition. GJs also increase the neuronal firing rate of the interneuronal ensemble, while they affect the ripple frequency only mildly. The promoting effect of GJs on ripple oscillations depends on fast GJ transmission ( ≲ 0.5 ms), which requires proximal GJ coupling ( ≲ 100 μm from soma), but is robust to variability in the delay and the amplitude of GJ coupling.
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Affiliation(s)
- André Holzbecher
- Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Richard Kempter
- Department of Biology, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Berlin, Germany
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15
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Liu X, Kuzum D. Hippocampal-Cortical Memory Trace Transfer and Reactivation Through Cell-Specific Stimulus and Spontaneous Background Noise. Front Comput Neurosci 2019; 13:67. [PMID: 31680922 PMCID: PMC6798041 DOI: 10.3389/fncom.2019.00067] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 09/10/2019] [Indexed: 01/07/2023] Open
Abstract
The hippocampus plays important roles in memory formation and retrieval through sharp-wave-ripples. Recent studies have shown that certain neuron populations in the prefrontal cortex (PFC) exhibit coordinated reactivations during awake ripple events. These experimental findings suggest that the awake ripple is an important biomarker, through which the hippocampus interacts with the neocortex to assist memory formation and retrieval. However, the computational mechanisms of this ripple based hippocampal-cortical coordination are still not clear due to the lack of unified models that include both the hippocampal and cortical networks. In this work, using a coupled biophysical model of both CA1 and PFC, we investigate possible mechanisms of hippocampal-cortical memory trace transfer and the conditions that assist reactivation of the transferred memory traces in the PFC. To validate our model, we first show that the local field potentials generated in the hippocampus and PFC exhibit ripple range activities that are consistent with the recent experimental studies. Then we demonstrate that during ripples, sequence replays can successfully transfer the information stored in the hippocampus to the PFC recurrent networks. We investigate possible mechanisms of memory retrieval in PFC networks. Our results suggest that the stored memory traces in the PFC network can be retrieved through two different mechanisms, namely the cell-specific input representing external stimuli and non-specific spontaneous background noise representing spontaneous memory recall events. Importantly, in both cases, the memory reactivation quality is robust to network connection loss. Finally, we find out that the quality of sequence reactivations is enhanced by both increased number of SWRs and an optimal background noise intensity, which tunes the excitability of neurons to a proper level. Our study presents a mechanistic explanation for the memory trace transfer from the hippocampus to neocortex through ripple coupling in awake states and reports two different mechanisms by which the stored memory traces can be successfully retrieved.
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Affiliation(s)
- Xin Liu
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, United States
| | - Duygu Kuzum
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, United States
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16
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Zweiphenning WJEM, Keijzer HM, van Diessen E, van ‘t Klooster MA, van Klink NEC, Leijten FSS, van Rijen PC, van Putten MJAM, Braun KPJ, Zijlmans M. Increased gamma and decreased fast ripple connections of epileptic tissue: A high-frequency directed network approach. Epilepsia 2019; 60:1908-1920. [PMID: 31329277 PMCID: PMC6852371 DOI: 10.1111/epi.16296] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Revised: 07/01/2019] [Accepted: 07/02/2019] [Indexed: 01/11/2023]
Abstract
OBJECTIVE New insights into high-frequency electroencephalographic activity and network analysis provide potential tools to improve delineation of epileptic tissue and increase the chance of postoperative seizure freedom. Based on our observation of high-frequency oscillations "spreading outward" from the epileptic source, we hypothesize that measures of directed connectivity in the high-frequency range distinguish epileptic from healthy brain tissue. METHODS We retrospectively selected refractory epilepsy patients with a malformation of cortical development or tumor World Health Organization grade I/II who underwent epilepsy surgery with intraoperative electrocorticography for tailoring the resection based on spikes. We assessed directed functional connectivity in the theta (4-8 Hz), gamma (30-80 Hz), ripple (80-250 Hz), and fast ripple (FR; 250-500 Hz) bands using the short-time direct directed transfer function, and calculated the total, incoming, and outgoing propagation strength for each electrode. We compared network measures of electrodes covering the resected and nonresected areas separately for patients with good and poor outcome, and of electrodes with and without spikes, ripples, and FRs (group level: paired t test; patient level: Mann-Whitney U test). We selected the measure that could best identify the resected area and channels with epileptic events using the area under the receiver operating characteristic curve, and calculated the positive and negative predictive value, sensitivity, and specificity. RESULTS We found higher total and outstrength in the ripple and gamma bands in resected tissue in patients with good outcome (rippletotal : P = .01; rippleout : P = .04; gammatotal : P = .01; gammaout : P = .01). Channels with events showed lower total and instrength, and higher outstrength in the FR band, and higher total and outstrength in the ripple, gamma, and theta bands (FRtotal : P = .05; FRin : P < .01; FRout : P = .02; gammatotal : P < .01; gammain : P = .01; gammaout : P < .01; thetatotal : P = .01; thetaout : P = .01). The total strength in the gamma band was most distinctive at the channel level (positive predictive value [PPV]good = 74%, PPVpoor = 43%). SIGNIFICANCE Interictally, epileptic tissue is isolated in the FR band and acts as a driver up to the (fast) ripple frequency range. The gamma band total strength seems promising to delineate epileptic tissue intraoperatively.
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Affiliation(s)
- Willemiek J. E. M. Zweiphenning
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Hanneke M. Keijzer
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
- MIRA Institute for Biomedical Technology and Technical MedicineClinical Neurophysiology GroupUniversity of TwenteEnschedethe Netherlands
| | - Eric van Diessen
- Department of Pediatric NeurologyUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Maryse A. van ‘t Klooster
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Nicole E. C. van Klink
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Frans S. S. Leijten
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Peter C. van Rijen
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Michel J. A. M. van Putten
- MIRA Institute for Biomedical Technology and Technical MedicineClinical Neurophysiology GroupUniversity of TwenteEnschedethe Netherlands
| | - Kees P. J. Braun
- Department of Pediatric NeurologyUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
| | - Maeike Zijlmans
- Department of Neurology and NeurosurgeryUniversity Medical Center Utrecht Brain CenterUtrecht UniversityUtrechtthe Netherlands
- Epilepsy Foundation of the NetherlandsHeemstedethe Netherlands
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17
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Ahmed OJ, Sudhakar SK. High-Frequency Activity During Stereotyped Low-Frequency Events Might Help to Identify the Seizure Onset Zone. Epilepsy Curr 2019; 19:1535759719842236. [PMID: 31012323 PMCID: PMC6610385 DOI: 10.1177/1535759719842236] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy. Liu S, Gurses C, Sha Z, Quach MM, Sencer A, Bebek N, et al. Brain. 2018;141(3):713-730. doi:10.1093/brain/awx374. PMID: 29394328 . High-frequency oscillations in local field potentials recorded with intracranial electroencephalogram are putative biomarkers of seizure-onset zones in epileptic brain. However, localized 80- to 500-Hz oscillations can also be recorded from normal and nonepileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones that limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 patients with epilepsy and 5 control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent of the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step toward the translation of these signature events into valid clinical biomarkers.
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18
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Ren S, Gliske SV, Brang D, Stacey WC. Redaction of false high frequency oscillations due to muscle artifact improves specificity to epileptic tissue. Clin Neurophysiol 2019; 130:976-985. [PMID: 31003116 DOI: 10.1016/j.clinph.2019.03.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 03/04/2019] [Accepted: 03/16/2019] [Indexed: 11/17/2022]
Abstract
OBJECTIVE High Frequency Oscillations (HFOs) are a promising biomarker of epilepsy. HFOs are typically acquired on intracranial electrodes, but contamination from muscle artifacts is still problematic in HFO analysis. This paper evaluates the effect of myogenic artifacts on intracranial HFO detection and how to remove them. METHODS Intracranial EEG was recorded in 31 patients. HFOs were detected for the entire recording using an automated algorithm. When available, simultaneous scalp EEG was used to identify periods of muscle artifact. Those markings were used to train an automated scalp EMG detector and an intracranial EMG detector. Specificity to epileptic tissue was evaluated by comparison with seizure onset zone and resected volume in patients with good outcome. RESULTS EMG artifacts are frequent and produce large numbers of false HFOs, especially in the anterior temporal lobe. The scalp and intracranial EMG detectors both had high accuracy. Removing false HFOs improved specificity to epileptic tissue. CONCLUSIONS Evaluation of HFOs requires accounting for the effect of muscle artifact. We present two tools that effectively mitigate the effect of muscle artifact on HFOs. SIGNIFICANCE Removing muscle artifacts improves the specificity of HFOs to epileptic tissue. Future HFO work should account for this effect, especially when using automated algorithms or when scalp electrodes are not present.
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Affiliation(s)
- Sijin Ren
- Department of Neurology, University of Michigan, USA.
| | - Stephen V Gliske
- Department of Neurology, University of Michigan, USA; Department of Biomedical Engineering, Biointerfaces Institute, University of Michigan, USA.
| | - David Brang
- Department of Psychology, University of Michigan, USA.
| | - William C Stacey
- Department of Neurology, University of Michigan, USA; Department of Biomedical Engineering, Biointerfaces Institute, University of Michigan, USA.
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19
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Ewell LA, Fischer KB, Leibold C, Leutgeb S, Leutgeb JK. The impact of pathological high-frequency oscillations on hippocampal network activity in rats with chronic epilepsy. eLife 2019; 8:42148. [PMID: 30794155 PMCID: PMC6386518 DOI: 10.7554/elife.42148] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 02/09/2019] [Indexed: 11/29/2022] Open
Abstract
In epilepsy, brain networks generate pathological high-frequency oscillations (pHFOs) during interictal periods. To understand how pHFOs differ from normal oscillations in overlapping frequency bands and potentially perturb hippocampal processing, we performed high-density single unit and local field potential recordings from hippocampi of behaving rats with and without chronic epilepsy. In epileptic animals, we observed two types of co-occurring fast oscillations, which by comparison to control animals we could classify as ‘ripple-like’ or ‘pHFO’. We compared their spectral characteristics, brain state dependence, and cellular participants. Strikingly, pHFO occurred irrespective of brain state, were associated with interictal spikes, engaged distinct subnetworks of principal neurons compared to ripple-like events, increased the sparsity of network activity, and initiated both general and immediate disruptions in spatial information coding. Taken together, our findings suggest that events that result in pHFOs have an immediate impact on memory processes, corroborating the need for proper classification of pHFOs to facilitate therapeutic interventions that selectively target pathological activity.
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Affiliation(s)
- Laura A Ewell
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Kyle B Fischer
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Neuroscience Graduate Program, University of California, San Diego, La Jolla, United States
| | - Christian Leibold
- Department Biologie II, Ludwig-Maximilians-Universität München, Martinsried, Germany.,Berstein Center for Computational Neuroscience Munich, Martinried, Germany
| | - Stefan Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States.,Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, United States
| | - Jill K Leutgeb
- Neurobiology Section and Center for Neural Circuits and Behavior, Division of Biological Sciences, University of California, San Diego, La Jolla, United States
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20
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Farahmand S, Sobayo T, Mogul DJ. Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients. IEEE Trans Neural Syst Rehabil Eng 2018; 26:2270-2279. [PMID: 30452374 DOI: 10.1109/tnsre.2018.2881606] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Spatiotemporal evolution of synchrony dynamics among neuronal populations plays an important role in decoding complicated brain function in normal cognitive processing as well as during pathological conditions such as epileptic seizures. In this paper, a non-linear analytical methodology is proposed to quantitatively evaluate the phase-synchrony dynamics in epilepsy patients. A set of finite neuronal oscillators was adaptively extracted from a multi-channel electrocorticographic (ECoG) dataset utilizing noise-assisted multivariate empirical mode de-composition (NA-MEMD). Next, the instantaneous phases of the oscillatory functions were extracted using the Hilbert transform in order to be utilized in the mean-phase coherence analysis. The phase-synchrony dynamics were then assessed using eigenvalue decomposition. The extracted neuronal oscillators were grouped with respect to their frequency range into wideband (1-600 Hz), ripple (80-250 Hz), and fast-ripple (250-600 Hz) bands in order to investigate the dynamics of ECoG activity in these frequency ranges as seizures evolve. Drug-refractory patients with frontal and temporal lobe epilepsy demonstrated a reduction in phase-synchrony around seizure onset. However, the network phase-synchrony started to increase toward seizure end and achieved its maximum level at seizure offset for both types of epilepsy. This result suggests that hyper-synchronization of the epileptic network may be an essential self-regulatory mechanism by which the brain terminates seizures.
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21
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Dulla CG, Janigro D, Jiruska P, Raimondo JV, Ikeda A, Lin CCK, Goodkin HP, Galanopoulou AS, Bernard C, de Curtis M. How do we use in vitro models to understand epileptiform and ictal activity? A report of the TASK1-WG4 group of the ILAE/AES Joint Translational Task Force. Epilepsia Open 2018; 3:460-473. [PMID: 30525115 PMCID: PMC6276782 DOI: 10.1002/epi4.12277] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/27/2018] [Indexed: 02/06/2023] Open
Abstract
In vitro brain tissue preparations allow the convenient and affordable study of brain networks and have allowed us to garner molecular, cellular, and electrophysiologic insights into brain function with a detail not achievable in vivo. Preparations from both rodent and human postsurgical tissue have been utilized to generate in vitro electrical activity similar to electrographic activity seen in patients with epilepsy. A great deal of knowledge about how brain networks generate various forms of epileptiform activity has been gained, but due to the multiple in vitro models and manipulations used, there is a need for a standardization across studies. Here, we describe epileptiform patterns generated using in vitro brain preparations, focusing on issues and best practices pertaining to recording, reporting, and interpretation of the electrophysiologic patterns observed. We also discuss criteria for defining in vitro seizure‐like patterns (i.e., ictal) and interictal discharges. Unifying terminologies and definitions are proposed. We suggest a set of best practices for reporting in vitro studies to favor both efficient across‐lab comparisons and translation to in vivo models and human studies.
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Affiliation(s)
- Chris G Dulla
- Department of Neuroscience Tufts University School of Medicine Boston Massachusetts U.S.A
| | - Damir Janigro
- Flocel Inc. and Case Western Reserve University Cleveland Ohio U.S.A
| | - Premysl Jiruska
- Department of Developmental Epileptology Institute of Physiology of the Czech Academy of Sciences Prague Czechia
| | - Joseph V Raimondo
- Division of Cell Biology and Neuroscience Institute Department of Human Biology Faculty of Health Sciences University of Cape Town Cape Town South Africa
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders and Physiology Kyoto University Graduate School of Medicine Kyoto Japan
| | - Chou-Ching K Lin
- Department of Neurology National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan
| | - Howard P Goodkin
- The Departments of Neurology and Pediatrics University of Virginia Charlottesville Virginia U.S.A
| | - Aristea S Galanopoulou
- Laboratory of Developmental Epilepsy Saul R. Korey Department of Neurology Isabelle Rapin Division of Child Neurology Dominick P. Purpura Department of Neuroscience Albert Einstein College of Medicine, and Einstein/Montefiore Epilepsy Center Montefiore Medical Center Bronx New York U.S.A
| | | | - Marco de Curtis
- Epilepsy Unit Fondazione IRCCS Istituto Neurologico Carlo Besta Milano Italy
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22
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High frequency oscillations in epileptic rodents: Are we doing it right? J Neurosci Methods 2018; 299:16-21. [PMID: 29476870 DOI: 10.1016/j.jneumeth.2018.02.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 02/16/2018] [Accepted: 02/20/2018] [Indexed: 11/24/2022]
Abstract
BACKGROUND The detection of high-frequency oscillations (HFOs, ripples: 80-200 Hz, fast ripples: 250-500 Hz) is often based on considering ripples or fast ripples in isolation; overlapping ripples and fast ripples are excluded from further analysis. Here, we studied overlapping HFOs during spontaneous seizures in pilocarpine-treated animals. NEW METHOD Spontaneous seizures (n = 6 animals) presented with either hypersynchronous- (HYP, n = 18) or low-voltage fast-onset (LVF, n = 21) pattern. Ripples and fast ripples overlapping by more than 30% were analysed. RESULTS Overlapping HFOs could show a unimodal power spectrum between 80-500 Hz (n = 188, 58.9%) or a bimodal power spectrum, with peaks in power between 80 and 200 Hz and between 250 and 500 Hz (n = 131, 41.1%,). Overlapping HFOs occurred at higher rates during HYP seizures compared to the pre-ictal period in seizure onset zones (p < 0.001) and regions of secondary spread (p < 0.001). When comparing HYP and LVF seizures, we found that overlapping HFOs occurred at higher rates before LVF seizures (p < 0.05) compared to HYP seizures but, during the ictal period, HYP seizures showed higher rates of overlapping HFOs than LVF seizures (p < 0.001). COMPARISON WITH EXISTING METHODS We have analysed overlapping ripples and fast ripples shortly before and during seizures. CONCLUSIONS Although overlapping ripples and fast ripples represent a minority of HFOs, they may provide additional information on the excitability of neuronal networks that generate seizures in animal models and patients presenting with mesial temporal lobe epilepsy.
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23
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Canakci S, Toy MF, Inci AF, Liu X, Kuzum D. Computational analysis of network activity and spatial reach of sharp wave-ripples. PLoS One 2017; 12:e0184542. [PMID: 28915251 PMCID: PMC5600383 DOI: 10.1371/journal.pone.0184542] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2016] [Accepted: 08/25/2017] [Indexed: 11/19/2022] Open
Abstract
Network oscillations of different frequencies, durations and amplitudes are hypothesized to coordinate information processing and transfer across brain areas. Among these oscillations, hippocampal sharp wave-ripple complexes (SPW-Rs) are one of the most prominent. SPW-Rs occurring in the hippocampus are suggested to play essential roles in memory consolidation as well as information transfer to the neocortex. To-date, most of the knowledge about SPW-Rs comes from experimental studies averaging responses from neuronal populations monitored by conventional microelectrodes. In this work, we investigate spatiotemporal characteristics of SPW-Rs and how microelectrode size and distance influence SPW-R recordings using a biophysical model of hippocampus. We also explore contributions from neuronal spikes and synaptic potentials to SPW-Rs based on two different types of network activity. Our study suggests that neuronal spikes from pyramidal cells contribute significantly to ripples while high amplitude sharp waves mainly arise from synaptic activity. Our simulations on spatial reach of SPW-Rs show that the amplitudes of sharp waves and ripples exhibit a steep decrease with distance from the network and this effect is more prominent for smaller area electrodes. Furthermore, the amplitude of the signal decreases strongly with increasing electrode surface area as a result of averaging. The relative decrease is more pronounced when the recording electrode is closer to the source of the activity. Through simulations of field potentials across a high-density microelectrode array, we demonstrate the importance of finding the ideal spatial resolution for capturing SPW-Rs with great sensitivity. Our work provides insights on contributions from spikes and synaptic potentials to SPW-Rs and describes the effect of measurement configuration on LFPs to guide experimental studies towards improved SPW-R recordings.
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Affiliation(s)
- Sadullah Canakci
- Electrical and Computer Engineering Department, Boston University, Boston, Massachusetts, United States of America
| | - Muhammed Faruk Toy
- Electrical and Computer Engineering Department, University of California San Diego, La Jolla, California, United States of America
- Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
| | - Ahmet Fatih Inci
- Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey
| | - Xin Liu
- Electrical and Computer Engineering Department, University of California San Diego, La Jolla, California, United States of America
| | - Duygu Kuzum
- Electrical and Computer Engineering Department, University of California San Diego, La Jolla, California, United States of America
- * E-mail:
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24
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Mechanisms for Selective Single-Cell Reactivation during Offline Sharp-Wave Ripples and Their Distortion by Fast Ripples. Neuron 2017. [PMID: 28641116 DOI: 10.1016/j.neuron.2017.05.032] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Memory traces are reactivated selectively during sharp-wave ripples. The mechanisms of selective reactivation, and how degraded reactivation affects memory, are poorly understood. We evaluated hippocampal single-cell activity during physiological and pathological sharp-wave ripples using juxtacellular and intracellular recordings in normal and epileptic rats with different memory abilities. CA1 pyramidal cells participate selectively during physiological events but fired together during epileptic fast ripples. We found that firing selectivity was dominated by an event- and cell-specific synaptic drive, modulated in single cells by changes in the excitatory/inhibitory ratio measured intracellularly. This mechanism collapses during pathological fast ripples to exacerbate and randomize neuronal firing. Acute administration of a use- and cell-type-dependent sodium channel blocker reduced neuronal collapse and randomness and improved recall in epileptic rats. We propose that cell-specific synaptic inputs govern firing selectivity of CA1 pyramidal cells during sharp-wave ripples.
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Jiruska P, Alvarado-Rojas C, Schevon CA, Staba R, Stacey W, Wendling F, Avoli M. Update on the mechanisms and roles of high-frequency oscillations in seizures and epileptic disorders. Epilepsia 2017; 58:1330-1339. [PMID: 28681378 DOI: 10.1111/epi.13830] [Citation(s) in RCA: 115] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/29/2017] [Indexed: 12/11/2022]
Abstract
High-frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge. Recent improvements in recording technology and the introduction of optogenetics into epilepsy research have intensified experimental work on HFOs. Using advanced computer models, new cellular substrates of epileptic HFOs were identified and the role of specific neuronal subtypes in HFO genesis was determined. Traditionally, the pathogenesis of HFOs was explored mainly in patients with temporal lobe epilepsy and in animal models mimicking this condition. HFOs have also been reported to occur in other epileptic disorders and models such as neocortical epilepsy, genetically determined epilepsies, and infantile spasms, which further support the significance of HFOs in the pathophysiology of epilepsy. It is increasingly recognized that HFOs are generated by multiple mechanisms at both the cellular and network levels. Future studies on HFOs combining novel high-resolution in vivo imaging techniques and precise control of neuronal behavior using optogenetics or chemogenetics will provide evidence about the causal role of HFOs in seizures and epileptogenesis. Detailed understanding of the pathophysiology of HFOs will propel better HFO classification and increase their information yield for clinical and diagnostic purposes.
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Affiliation(s)
- Premysl Jiruska
- Department of Developmental Epileptology, Institute of Physiology, The Czech Academy of Sciences, Prague, Czech Republic
| | | | | | - Richard Staba
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, U.S.A
| | - William Stacey
- Department of Neurology, Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, U.S.A
| | - Fabrice Wendling
- Laboratory of Signal and Image Processing, INSERM U1099, Rennes, France.,Laboratoire de Traitement du Signal et de l'Image, University of Rennes 1, Rennes, France
| | - Massimo Avoli
- Montreal Neurological Institute and Departments of Neurology & Neurosurgery and of Physiology, McGill University, Montréal, Québec, Canada.,Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
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Medina-Ceja L, García-Barba C. The glutamate receptor antagonists CNQX and MPEP decrease fast ripple events in rats treated with kainic acid. Neurosci Lett 2017; 655:137-142. [PMID: 28673833 DOI: 10.1016/j.neulet.2017.06.056] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Revised: 06/06/2017] [Accepted: 06/29/2017] [Indexed: 12/17/2022]
Abstract
Fast ripples (FR) are high frequency oscillations (250-600Hz) that have been associated with epilepsy. FR are assumed to be generated in small areas of the hippocampus (1mm3) that contain pathologically interconnected glutamate pyramidal cell clusters. Additionally, a relation between glutamate neurotransmission and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/kainite (AMPA/KA) and metabotropic mGluR5 receptors is well established. Therefore, we hypothesized that antagonism of these glutamate receptors would decrease FR activity. For this propose, we induced status epilepticus with a kainic acid injection in the posterior right hippocampus and performed intracranial EEG recordings to detect and evaluate the presence of FR 15days after the injection. The glutamate AMPA/KA receptor antagonist CNQX (10mg/kg) and the mGluR5 antagonist MPEP (20mg/kg) were administered intraperitoneally, and the effects of the drugs were evaluated for a period of three hours after their administration. The results show a decrease in the number of FR in the first hour after drug administration in both cases (CNQX, p=0.0125; MPEP, p=0.0132) and a return to basal values in the third hour of the experiment, but not significant differences in the number of oscillations per event of FR, and the frequency and duration of each event of FR. We therefore conclude that blockade of AMPA/KA and mGluR5 receptors transiently decreases the generation of FR; however, the mechanisms by which this effect is achieved are to be further analyzed in future experiments.
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Affiliation(s)
- Laura Medina-Ceja
- Laboratory of Neurophysiology, Department of Cellular and Molecular Biology, CUCBA, University of Guadalajara, Jalisco, Mexico.
| | - Carla García-Barba
- Laboratory of Neurophysiology, Department of Cellular and Molecular Biology, CUCBA, University of Guadalajara, Jalisco, Mexico
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What are the assets and weaknesses of HFO detectors? A benchmark framework based on realistic simulations. PLoS One 2017; 12:e0174702. [PMID: 28406919 PMCID: PMC5390983 DOI: 10.1371/journal.pone.0174702] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 03/13/2017] [Indexed: 01/10/2023] Open
Abstract
High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors. We constructed a dictionary of synthesized elements—HFOs and epileptic spikes—from different patients and brain areas by extracting these elements from the original data using discrete wavelet transform coefficients. These elements were then added to their corresponding simulated background activity (preserving patient- and region- specific spectra). We tested five existing detectors against this benchmark. Compared to other studies confronting detectors, we did not only ranked them according their performance but we investigated the reasons leading to these results. Our simulations, thanks to their realism and their variability, enabled us to highlight unreported issues of current detectors: (1) the lack of robust estimation of the background activity, (2) the underestimated impact of the 1/f spectrum, and (3) the inadequate criteria defining an HFO. We believe that our benchmark framework could be a valuable tool to translate HFOs into a clinical environment.
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Zweiphenning W, van ‘t Klooster M, van Diessen E, van Klink N, Huiskamp G, Gebbink T, Leijten F, Gosselaar P, Otte W, Stam C, Braun K, Zijlmans G. High frequency oscillations and high frequency functional network characteristics in the intraoperative electrocorticogram in epilepsy. Neuroimage Clin 2016; 12:928-939. [PMID: 27882298 PMCID: PMC5114532 DOI: 10.1016/j.nicl.2016.09.014] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 08/29/2016] [Accepted: 09/21/2016] [Indexed: 11/21/2022]
Abstract
OBJECTIVE High frequency oscillations (HFOs; > 80 Hz), especially fast ripples (FRs, 250-500 Hz), are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR generating tissue. Our aim was to determine the relation between brain areas showing FRs and 'baseline' functional connectivity within EEG networks, especially in the high frequency bands. METHODS We marked FRs, ripples (80-250 Hz) and spikes in the electrocorticogram of 14 patients with refractory temporal lobe epilepsy. We assessed 'baseline' functional connectivity in epochs free of epileptiform events within these recordings, using the phase lag index. We computed the Eigenvector Centrality (EC) per channel in the FR and gamma band network. We compared EC between channels that did or did not show events at other moments in time. RESULTS FR-band EC was higher in channels with than without spikes. Gamma-band EC was lower in channels with ripples and FRs. CONCLUSIONS We confirmed previous findings of functional isolation in the gamma-band and found a first proof of functional integration in the FR-band network of channels covering presumed epileptogenic tissue. SIGNIFICANCE 'Baseline' high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events. These findings can increase our understanding of the 'architecture' of epileptogenic networks and help unravel the pathophysiology of HFOs.
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Key Words
- (io)ECoG, (intra-operative) electrocorticography
- EC, eigenvector centrality
- EEG, electroencephalography
- Epilepsy
- Epilepsy surgery
- Epileptogenic zone
- FR, fast ripple, 250–500 Hz
- Functional network analysis
- HFO, high frequency oscillation, > 80 Hz
- High Frequency Oscillations
- IPSP, inhibitory postsynaptic potential
- PLI, phase lag index
- SOZ, seizure onset zone
- TLE, temporal lobe epilepsy
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Affiliation(s)
- W.J.E.M. Zweiphenning
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - M.A. van ‘t Klooster
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - E. van Diessen
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - N.E.C. van Klink
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - G.J.M. Huiskamp
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - T.A. Gebbink
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - F.S.S. Leijten
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - P.H. Gosselaar
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - W.M. Otte
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland, Heemstede, P.O. box 540, 2130 AM Hoofddorp, The Netherlands
| | - C.J. Stam
- Department of Clinical Neurophysiology, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB Amsterdam, The Netherlands
| | - K.P.J. Braun
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - G.J.M. Zijlmans
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland, Heemstede, P.O. box 540, 2130 AM Hoofddorp, The Netherlands
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Gliske SV, Stacey WC, Lim E, Holman KA, Fink CG. Emergence of Narrowband High Frequency Oscillations from Asynchronous, Uncoupled Neural Firing. Int J Neural Syst 2016; 27:1650049. [PMID: 27712456 DOI: 10.1142/s0129065716500490] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Previous experimental studies have demonstrated the emergence of narrowband local field potential oscillations during epileptic seizures in which the underlying neural activity appears to be completely asynchronous. We derive a mathematical model explaining how this counterintuitive phenomenon may occur, showing that a population of independent, completely asynchronous neurons may produce narrowband oscillations if each neuron fires quasi-periodically, without requiring any intrinsic oscillatory cells or feedback inhibition. This quasi-periodicity can occur through cells with similar frequency-current ([Formula: see text]-[Formula: see text]) curves receiving a similar, high amount of uncorrelated synaptic noise. Thus, this source of oscillatory behavior is distinct from the usual cases (pacemaker cells entraining a network, or oscillations being an inherent property of the network structure), as it requires no oscillatory drive nor any specific network or cellular properties other than cells that repetitively fire with continual stimulus. We also deduce bounds on the degree of variability in neural spike-timing which will permit the emergence of such oscillations, both for action potential- and postsynaptic potential-dominated LFPs. These results suggest that even an uncoupled network may generate collective rhythms, implying that the breakdown of inhibition and high synaptic input often observed during epileptic seizures may generate narrowband oscillations. We propose that this mechanism may explain why so many disparate epileptic and normal brain mechanisms can produce similar high frequency oscillations.
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Affiliation(s)
- Stephen V Gliske
- 1 Department of Neurology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - William C Stacey
- 2 Departments of Biomedical Engineering and Neurology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI 48109, USA
| | - Eugene Lim
- 3 Department of Physics, Ohio Wesleyan University, 61 S. Sandusky St., Delaware, OH 43015, USA
| | - Katherine A Holman
- 4 Department of Physics, Towson University, 8000 York Road, Towson, MD 21252, USA
| | - Christian G Fink
- 5 Department of Physics and Neuroscience Program, Ohio Wesleyan University, 61 S. Sandusky St., Delaware, OH 43015, USA
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Multiscale Aspects of Generation of High-Gamma Activity during Seizures in Human Neocortex. eNeuro 2016; 3:eN-NWR-0141-15. [PMID: 27257623 PMCID: PMC4876490 DOI: 10.1523/eneuro.0141-15.2016] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Revised: 04/19/2016] [Accepted: 04/21/2016] [Indexed: 01/14/2023] Open
Abstract
High-gamma (HG; 80-150 Hz) activity in macroscopic clinical records is considered a marker for critical brain regions involved in seizure initiation; it is correlated with pathological multiunit firing during neocortical seizures in the seizure core, an area identified by correlated multiunit spiking and low frequency seizure activity. High-gamma (HG; 80-150 Hz) activity in macroscopic clinical records is considered a marker for critical brain regions involved in seizure initiation; it is correlated with pathological multiunit firing during neocortical seizures in the seizure core, an area identified by correlated multiunit spiking and low frequency seizure activity. However, the effects of the spatiotemporal dynamics of seizure on HG power generation are not well understood. Here, we studied HG generation and propagation, using a three-step, multiscale signal analysis and modeling approach. First, we analyzed concurrent neuronal and microscopic network HG activity in neocortical slices from seven intractable epilepsy patients. We found HG activity in these networks, especially when neurons displayed paroxysmal depolarization shifts and network activity was highly synchronized. Second, we examined HG activity acquired with microelectrode arrays recorded during human seizures (n = 8). We confirmed the presence of synchronized HG power across microelectrode records and the macroscale, both specifically associated with the core region of the seizure. Third, we used volume conduction-based modeling to relate HG activity and network synchrony at different network scales. We showed that local HG oscillations require high levels of synchrony to cross scales, and that this requirement is met at the microscopic scale, but not within macroscopic networks. Instead, we present evidence that HG power at the macroscale may result from harmonics of ongoing seizure activity. Ictal HG power marks the seizure core, but the generating mechanism can differ across spatial scales.
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