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1دورية أكاديمية
المؤلفون: Prabhu, Pooja, Morise, Hirofumi, Kudo, Kiwamu, Beagle, Alexander, Mizuiri, Danielle, Syed, Faatimah, Kotegar, Karunakar A, Findlay, Anne, Miller, Bruce L, Kramer, Joel H, Rankin, Katherine P, Garcia, Paul A, Kirsch, Heidi E, Vossel, Keith, Nagarajan, Srikantan S, Ranasinghe, Kamalini G
المصدر: Brain Communications. 6(2)
مصطلحات موضوعية: Biomedical and Clinical Sciences, Neurosciences, Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Acquired Cognitive Impairment, Alzheimer's Disease, Aging, Neurodegenerative, Epilepsy, Biomedical Imaging, Clinical Research, Dementia, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, network hyperexcitability, gamma oscillations, magnetoencephalography, phase-amplitude coupling, Alzheimer's disease, Alzheimer’s disease, Clinical sciences, Biological psychology
الوصف: While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.
وصف الملف: application/pdf
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2دورية أكاديمية
المؤلفون: Kuroda, Naoto, Sonoda, Masaki, Miyakoshi, Makoto, Nariai, Hiroki, Jeong, Jeong-Won, Motoi, Hirotaka, Luat, Aimee F, Sood, Sandeep, Asano, Eishi
المصدر: Brain Communications. 3(2)
مصطلحات موضوعية: Biomedical and Clinical Sciences, Clinical Sciences, Neurosciences, Clinical Research, Epilepsy, Neurodegenerative, Brain Disorders, invasive recording, electrocorticography, high-frequency oscillation, modulation index, phase-amplitude coupling, Clinical sciences, Biological psychology
الوصف: Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3-4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.
وصف الملف: application/pdf
الوصول الحر: https://escholarship.org/uc/item/3m99m58bTest
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المؤلفون: Eishi Asano, Masaki Sonoda, Naoto Kuroda, Hiroki Nariai, Sandeep Sood, Aimee F. Luat, Hirotaka Motoi, Jeong-Won Jeong, Makoto Miyakoshi
المصدر: Brain communications, vol 3, iss 2
Brain Communicationsمصطلحات موضوعية: 0301 basic medicine, phase-amplitude coupling, electrocorticography (ECoG), modulation index (MI), modulation index, Modulation index, Neurodegenerative, Logistic regression, high-frequency oscillation (HFO), 03 medical and health sciences, high-frequency oscillation, 0302 clinical medicine, Neuroimaging, Clinical Research, Ictal, Epilepsy surgery, phase-amplitude coupling (PAC), electrocorticography, Mathematics, Epilepsy, AcademicSubjects/SCI01870, business.industry, Oscillation, Neurosciences, General Engineering, Subtraction, Pattern recognition, Brain Disorders, Coupling (physics), 030104 developmental biology, Original Article, AcademicSubjects/MED00310, Artificial intelligence, business, 030217 neurology & neurosurgery, invasive recording
الوصف: Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3–4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.
Kuroda et al. report the results of the computational analysis of intracranial EEG data from a cohort of 135 patients with drug-resistant focal epilepsy. Both interictal HFO and phase-amplitude coupling measures were found to improve the prediction of post-operative seizure outcome.
Graphical Abstract Graphical Abstractوصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c747a1149de03ae5f870bebf11a3bcbcTest
https://doi.org/10.1093/braincomms/fcab042Test -
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المؤلفون: Berj L. Bardakjian, Peter L. Carlen, Richard Wennberg, Vasily Grigorovsky, Vanessa L. Breton, Yotin Chinvarun, Uilki Tufa, Jose Martin del Campo, Christopher Lucasius, Daniel Jacobs
المصدر: Brain Communications
مصطلحات موضوعية: 0301 basic medicine, phase-amplitude coupling, SUDEP, seizure, Electroencephalography, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, Rhythm, medicine, Ictal, PGES, medicine.diagnostic_test, business.industry, AcademicSubjects/SCI01870, General Engineering, medicine.disease, 030104 developmental biology, medicine.anatomical_structure, Scalp, Connectome, epilepsy, Original Article, AcademicSubjects/MED00310, business, Neuroscience, 030217 neurology & neurosurgery, Phase amplitude coupling, Postictal state
الوصف: Postictal generalized EEG suppression is the state of suppression of electrical activity at the end of a seizure. Prolongation of this state has been associated with increased risk of sudden unexpected death in epilepsy, making characterization of underlying electrical rhythmic activity during postictal suppression an important step in improving epilepsy treatment. Phase-amplitude coupling in EEG reflects cognitive coding within brain networks and some of those codes highlight epileptic activity; therefore, we hypothesized that there are distinct phase-amplitude coupling features in the postictal suppression state that can provide an improved estimate of this state in the context of patient risk for sudden unexpected death in epilepsy. We used both intracranial and scalp EEG data from eleven patients (six male, five female; age range 21–41 years) containing 25 seizures, to identify frequency dynamics, both in the ictal and postictal EEG suppression states. Cross-frequency coupling analysis identified that during seizures there was a gradual decrease of phase frequency in the coupling between delta (0.5–4 Hz) and gamma (30+ Hz), which was followed by an increased coupling between the phase of 0.5–1.5 Hz signal and amplitude of 30–50 Hz signal in the postictal state as compared to the pre-seizure baseline. This marker was consistent across patients. Then, using these postictal-specific features, an unsupervised state classifier—a hidden Markov model—was able to reliably classify four distinct states of seizure episodes, including a postictal suppression state. Furthermore, a connectome analysis of the postictal suppression states showed increased information flow within the network during postictal suppression states as compared to the pre-seizure baseline, suggesting enhanced network communication. When the same tools were applied to the EEG of an epilepsy patient who died unexpectedly, ictal coupling dynamics disappeared and postictal phase-amplitude coupling remained constant throughout. Overall, our findings suggest that there are active postictal networks, as defined through coupling dynamics that can be used to objectively classify the postictal suppression state; furthermore, in a case study of sudden unexpected death in epilepsy, the network does not show ictal-like phase-amplitude coupling features despite the presence of convulsive seizures, and instead demonstrates activity similar to postictal. The postictal suppression state is a period of elevated network activity as compared to the baseline activity which can provide key insights into the epileptic pathology.
Phase-amplitude coupling analysis shows that a state of postictal generalized EEG suppression has increased delta-gamma coupling. These coupling features, used with an unsupervised hidden Markov model, reliably differentiated four substates in seizure episodes. A sudden unexpected death in epilepsy case study showed coupling activity similar to a postictal state.
Graphical Abstract Graphical Abstractالوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b41ff015491806768f0728dc9f62b3e6Test
https://pubmed.ncbi.nlm.nih.gov/33376988Test
