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Bosl W, Enlow MB, Nelson C. A QR Code for the Brain: A dynamical systems framework for computing neurophysiological biomarkers. RESEARCH SQUARE 2024:rs.3.rs-4927086. [PMID: 39372924 PMCID: PMC11451722 DOI: 10.21203/rs.3.rs-4927086/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Neural circuits are often considered the bridge connecting genetic causes and behavior. Whereas prenatal neural circuits are believed to be derived from a combination of genetic and intrinsic activity, postnatal circuits are largely influenced by exogenous activity and experience. A dynamical neuroelectric field maintained by neural activity is proposed as the fundamental information processing substrate of cognitive function. Time series measurements of the neuroelectric field can be collected by scalp sensors and used to mathematically quantify the essential dynamical features of the neuroelectric field by constructing a digital twin of the dynamical system phase space. The multiscale nonlinear values that result can be organized into tensor data structures, from which latent features can be extracted using tensor factorization. These latent features can be mapped to behavioral constructs to derive digital biomarkers. This computational framework provides a robust method for incorporating neurodynamical measures into neuropsychiatric biomarker discovery.
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Boddeti U, Langbein J, McAfee D, Altshuler M, Bachani M, Zaveri HP, Spencer D, Zaghloul KA, Ksendzovsky A. Modeling seizure networks in neuron-glia cultures using microelectrode arrays. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1441345. [PMID: 39290793 PMCID: PMC11405204 DOI: 10.3389/fnetp.2024.1441345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 08/20/2024] [Indexed: 09/19/2024]
Abstract
Epilepsy is a common neurological disorder, affecting over 65 million people worldwide. Unfortunately, despite resective surgery, over 30 % of patients with drug-resistant epilepsy continue to experience seizures. Retrospective studies considering connectivity using intracranial electrocorticography (ECoG) obtained during neuromonitoring have shown that treatment failure is likely driven by failure to consider critical components of the seizure network, an idea first formally introduced in 2002. However, current studies only capture snapshots in time, precluding the ability to consider seizure network development. Over the past few years, multiwell microelectrode arrays have been increasingly used to study neuronal networks in vitro. As such, we sought to develop a novel in vitro MEA seizure model to allow for study of seizure networks. Specifically, we used 4-aminopyridine (4-AP) to capture hyperexcitable activity, and then show increased network changes after 2 days of chronic treatment. We characterize network changes using functional connectivity measures and a novel technique using dimensionality reduction. We find that 4-AP successfully captures persistently elevated mean firing rate and significant changes in underlying connectivity patterns. We believe this affords a robust in vitro seizure model from which longitudinal network changes can be studied, laying groundwork for future studies exploring seizure network development.
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Affiliation(s)
- Ujwal Boddeti
- Surgical Neurology Branch, NINDS, National Institutes of Health, Baltimore, MD, United States
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jenna Langbein
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Darrian McAfee
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Marcelle Altshuler
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, United States
| | - Muzna Bachani
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Hitten P Zaveri
- Department of Neurology, Yale University, New Haven, CT, United States
| | - Dennis Spencer
- Department of Neurosurgery, Yale University, New Haven, CT, United States
| | - Kareem A Zaghloul
- Surgical Neurology Branch, NINDS, National Institutes of Health, Baltimore, MD, United States
| | - Alexander Ksendzovsky
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
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Fleury MN, Binding LP, Taylor P, Xiao F, Giampiccolo D, Caciagli L, Buck S, Winston GP, Thompson PJ, Baxendale S, Koepp MJ, Duncan JS, Sidhu MK. Predictors of long-term memory and network connectivity 10 years after anterior temporal lobe resection. Epilepsia 2024. [PMID: 38990127 DOI: 10.1111/epi.18058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/25/2024] [Accepted: 06/25/2024] [Indexed: 07/12/2024]
Abstract
OBJECTIVE Anterior temporal lobe resection (ATLR) effectively controls seizures in medically refractory temporal lobe epilepsy but risks significant episodic memory decline. Beyond 1 year postoperatively, the influence of preoperative clinical factors on episodic memory and long-term network plasticity remain underexplored. Ten years post-ATLR, we aimed to determine biomarkers of successful memory network reorganization and establish presurgical features' lasting impact on memory function. METHODS Twenty-five ATLR patients (12 left-sided) and 10 healthy controls underwent a memory-encoding functional magnetic resonance imaging paradigm alongside neuropsychometry 10 years postsurgery. Generalized psychophysiological interaction analyses modeled network functional connectivity of words/faces remembered, seeding from the medial temporal lobes (MTLs). Differences in successful memory connectivity were assessed between controls and left/right ATLR. Multivariate regressions and mixed-effect models probed preoperative phenotypes' effects on long-term memory outcomes. RESULTS Ten years post-ATLR, lower baseline functioning (verbal and performance intelligence quotient) and a focal memory impairment preoperatively predicted worse long-term memory outcomes. Poorer verbal memory was significantly associated with longer epilepsy duration and earlier onset age. Relative to controls, successful word and face encoding involved increased functional connectivity from both or remnant MTL seeds and contralesional parahippocampus/hippocampus after left/right ATLR. Irrespective of surgical laterality, successful memory encoding correlated with increased MTL-seeded connectivity to frontal (bilateral insula, right anterior cingulate), right parahippocampal, and bilateral fusiform gyri. Ten years postsurgery, better memory performance was correlated with contralateral frontal plasticity, which was disrupted with longer epilepsy duration. SIGNIFICANCE Our findings underscore the enduring nature of functional network reorganizations to provide long-term cognitive support. Ten years post-ATLR, successful memory formation featured stronger connections near resected areas and contralateral regions. Preoperative network disruption possibly influenced effectiveness of postoperative plasticity. These findings are crucial for enhancing long-term memory prediction and strategies for lasting memory rehabilitation.
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Affiliation(s)
- Marine N Fleury
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
| | - Lawrence P Binding
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
- Department of Computer Science, UCL Centre for Medical Image Computing, London, UK
| | - Peter Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, Newcastle, UK
| | - Fenglai Xiao
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
| | - Davide Giampiccolo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Department of Neurosurgery, Institute of Neurosciences, Cleveland Clinic London, London, UK
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
- Department of Neurology, Inselspital, Sleep-Wake-Epilepsy Center, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Sarah Buck
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
| | - Gavin P Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
- Division of Neurology, Department of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Pamela J Thompson
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Psychology Department, Epilepsy Society, Buckinghamshire, UK
| | - Sallie Baxendale
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Psychology Department, Epilepsy Society, Buckinghamshire, UK
| | - Matthias J Koepp
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
| | - Meneka K Sidhu
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Buckinghamshire, UK
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Allendorfer JB, Nenert R, Goodman AM, Kakulamarri P, Correia S, Philip NS, LaFrance WC, Szaflarski JP. Brain network entropy, depression, and quality of life in people with traumatic brain injury and seizure disorders. Epilepsia Open 2024; 9:969-980. [PMID: 38507279 PMCID: PMC11145610 DOI: 10.1002/epi4.12926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 01/29/2024] [Accepted: 02/29/2024] [Indexed: 03/22/2024] Open
Abstract
OBJECTIVE Traumatic brain injury (TBI) often precedes the onset of epileptic (ES) or psychogenic nonepileptic seizures (PNES) with depression being a common comorbidity. The relationship between depression severity and quality of life (QOL) may be related to resting-state network complexity. We investigated these relationships in adults with TBI-only, TBI + ES, or TBI + PNES using Sample Entropy (SampEn), a measure of physiologic signals complexity. METHODS Adults with TBI-only (n = 60), TBI + ES (n = 21), or TBI + PNES (n = 56) completed the Beck Depression Inventory-II (BDI-II; depression symptom severity) and QOL in Epilepsy (QOLIE-31) assessments and underwent resting-state functional magnetic resonance imaging (rs-fMRI). SampEn values derived from six resting state functional networks were calculated per participant. Effects of group, network, and group-by-network-interactions for SampEn were investigated with a mixed-effects model. We examined relationships between BDI-II, QOL, and SampEn of each of the networks. RESULTS Groups did not differ in age, but there was a higher proportion of women with TBI + PNES (p = 0.040). TBI + ES and TBI-only groups did not differ in BDI-II or QOLIE-31 scores, while the TBI + PNES group scored worse on both measures. The fixed effects of the model revealed significant differences in SampEn values across networks (lower SampEn for the frontoparietal network compared to other networks). The likelihood ratio test for group-by-network-interactions was significant (p = 0.033). BDI-II was significantly negatively associated with Overall QOL scale scores in all groups, and significantly negatively associated with network SampEn values only in the TBI + PNES group. SIGNIFICANCE Only TBI + PNES had significant relationships between depression symptom severity and network SampEn values indicating that the resting state network complexity is related to depression severity in this group but not in TBI + ES or TBI-only. PLAIN LANGUAGE SUMMARY The brain has a complex network of internal connections. How well these connections work may be affected by TBI and seizures and may underlie mental health symptoms including depression; the worse the depression, the worse the quality of life. Our study compared brain organization in people with TBI, people with epilepsy after TBI, and people with nonepileptic seizures after TBI. Only people with nonepileptic seizures after TBI showed a relationship between how organized their brain connections were and how bad was their depression. We need to better understand these relationships to develop more impactful, effective treatments.
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Affiliation(s)
- Jane B. Allendorfer
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurobiologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Rodolphe Nenert
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Adam M. Goodman
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Pranav Kakulamarri
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Stephen Correia
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
| | - Noah S. Philip
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
- Department of Psychiatry and Human BehaviorBrown UniversityProvidenceRhode IslandUSA
| | - W. Curt LaFrance
- VA RR&D Center for Neurorestoration and NeurotechnologyVA Providence Healthcare SystemProvidenceRhode IslandUSA
- Department of Psychiatry and Human BehaviorBrown UniversityProvidenceRhode IslandUSA
- Department of NeurologyBrown UniversityProvidenceRhode IslandUSA
- Division of Neuropsychiatry and Behavioral NeurologyRhode Island HospitalProvidenceRhode IslandUSA
| | - Jerzy P. Szaflarski
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurobiologyUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- UAB Epilepsy CenterUniversity of Alabama at BirminghamBirminghamAlabamaUSA
- Department of NeurosurgeryUniversity of Alabama at BirminghamBirminghamAlabamaUSA
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Lin J, Smith GC, Gliske SV, Zochowski M, Shedden K, Stacey WC. High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery. Brain Commun 2024; 6:fcae032. [PMID: 38384998 PMCID: PMC10881100 DOI: 10.1093/braincomms/fcae032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/28/2023] [Accepted: 02/05/2024] [Indexed: 02/23/2024] Open
Abstract
High frequency oscillations are a promising biomarker of outcome in intractable epilepsy. Prior high frequency oscillation work focused on counting high frequency oscillations on individual channels, and it is still unclear how to translate those results into clinical care. We show that high frequency oscillations arise as network discharges that have valuable properties as predictive biomarkers. Here, we develop a tool to predict patient outcome before surgical resection is performed, based on only prospective information. In addition to determining high frequency oscillation rate on every channel, we performed a correlational analysis to evaluate the functional connectivity of high frequency oscillations in 28 patients with intracranial electrodes. We found that high frequency oscillations were often not solitary events on a single channel, but part of a local network discharge. Eigenvector and outcloseness centrality were used to rank channel importance within the connectivity network, then used to compare patient outcome by comparison with the seizure onset zone or a proportion within the proposed resected channels (critical resection percentage). Combining the knowledge of each patient's seizure onset zone resection plan along with our computed high frequency oscillation network centralities and high frequency oscillation rate, we develop a Naïve Bayes model that predicts outcome (positive predictive value: 100%) better than predicting based upon fully resecting the seizure onset zone (positive predictive value: 71%). Surgical margins had a large effect on outcomes: non-palliative patients in whom most of the seizure onset zone was resected ('definitive surgery', ≥ 80% resected) had predictable outcomes, whereas palliative surgeries (<80% resected) were not predictable. These results suggest that the addition of network properties of high frequency oscillations is more accurate in predicting patient outcome than seizure onset zone alone in patients with most of the seizure onset zone removed and offer great promise for informing clinical decisions in surgery for refractory epilepsy.
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Affiliation(s)
- Jack Lin
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
| | - Garnett C Smith
- Department of Pediatrics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen V Gliske
- Department of Neurosurgery, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Michal Zochowski
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Physics and Biophysics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kerby Shedden
- Department of Statistics and Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - William C Stacey
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Biomedical Engineering, BioInterfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
- Division of Neurology, Ann Arbor VA Health System, Ann Arbor, MI 48109, USA
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Miao Y, Suzuki H, Sugano H, Ueda T, Iimura Y, Matsui R, Tanaka T. Causal Connectivity Network Analysis of Ictal Electrocorticogram With Temporal Lobe Epilepsy Based on Dynamic Phase Transfer Entropy. IEEE Trans Biomed Eng 2024; 71:531-541. [PMID: 37624716 DOI: 10.1109/tbme.2023.3308616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2023]
Abstract
Temporallobe epilepsy (TLE) has been conceptualized as a brain network disease, which generates brain connectivity dynamics within and beyond the temporal lobe structures in seizures. The hippocampus is a representative epileptogenic focus in TLE. Understanding the causal connectivity in terms of brain network during seizures is crucial in revealing the triggering mechanism of epileptic seizures originating from the hippocampus (HPC) spread to the lateral temporal cortex (LTC) by ictal electrocorticogram (ECoG), particularly in high-frequency oscillations (HFOs) bands. In this study, we proposed the unified-epoch dynamic causality analysis method to investigate the causal influence dynamics between two brain regions (HPC and LTC) at interictal and ictal phases in the frequency range of 1-500 Hz by introducing the phase transfer entropy (PTE) out/in-ratio and sliding window. We also proposed PTE-based machine learning algorithms to identify epileptogenic zone (EZ). Nine patients with a total of 26 seizures were included in this study. We hypothesized that: 1) HPC is the focus with the stronger causal connectivity than that in LTC in the ictal state at gamma and HFOs bands. 2) Causal connectivity in the ictal phase shows significant changes compared to that in the interictal phase. 3) The PTE out/in-ratio in the HFOs band can identify the EZ with the best prediction performance.
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Castellano JF, Singla S, Barot N, Aronson JP. Stereoelectroencephalography-Guided Radiofrequency Thermocoagulation: Diagnostic and Therapeutic Implications. Brain Sci 2024; 14:110. [PMID: 38391685 PMCID: PMC10887298 DOI: 10.3390/brainsci14020110] [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: 12/28/2023] [Revised: 01/15/2024] [Accepted: 01/21/2024] [Indexed: 02/24/2024] Open
Abstract
Despite recent medical therapeutic advances, approximately one third of patients do not attain seizure freedom with medications. This drug-resistant epilepsy population suffers from heightened morbidity and mortality. In appropriate patients, resective epilepsy surgery is far superior to continued medical therapy. Despite this efficacy, there remain drawbacks to traditional epilepsy surgery, such as the morbidity of open neurosurgical procedures as well as neuropsychological adverse effects. SEEG-guided Radiofrequency Thermocoagulation (SgRFTC) is a minimally invasive, electrophysiology-guided intervention with both diagnostic and therapeutic implications for drug-resistant epilepsy that offers a convenient adjunct or alternative to ablative and resective approaches. We review the international experience with this procedure, including methodologies, diagnostic benefit, therapeutic benefit, and safety considerations. We propose a framework in which SgRFTC may be incorporated into intracranial EEG evaluations alongside passive recording. Lastly, we discuss the potential role of SgRFTC in both delineating and reorganizing epilepsy networks.
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Affiliation(s)
- James F Castellano
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Shobhit Singla
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Niravkumar Barot
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Joshua P Aronson
- Department of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
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Zanao TA, Seitz‐Holland J, O'Donnell LJ, Zhang F, Rathi Y, Lopes TM, Pimentel‐Silva LR, Yassuda CL, Makris N, Shenton ME, Bouix S, Lyall AE, Cendes F. Exploring the impact of hippocampal sclerosis on white matter tracts and memory in individuals with mesial temporal lobe epilepsy. Epilepsia Open 2023; 8:1111-1122. [PMID: 37469213 PMCID: PMC10472386 DOI: 10.1002/epi4.12793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 07/14/2023] [Indexed: 07/21/2023] Open
Abstract
OBJECTIVE To investigate how the presence/side of hippocampal sclerosis (HS) are related to the white matter structure of cingulum bundle (CB), arcuate fasciculus (AF), and inferior longitudinal fasciculus (ILF) in mesial temporal lobe epilepsy (MTLE). METHODS We acquired diffusion-weighted magnetic resonance imaging (MRI) from 86 healthy and 71 individuals with MTLE (22 righ-HS; right-HS, 34 left-HS; left-HS, and 15 nonlesional MTLE). We utilized two-tensor tractography and fiber clustering to compare fractional anisotropy (FA) of each side/tract between groups. Additionally, we examined the association between FA and nonverbal (WMS-R) and verbal (WMS-R, RAVLT codification) memory performance for MTLE individuals. RESULTS White matter abnormalities depended on the side and presence of HS. The left-HS demonstrated widespread abnormalities for all tracts, the right-HS showed lower FA for ipsilateral tracts and the nonlesional MTLE group did not differ from healthy individuals. Results indicate no differences in verbal/nonverbal memory performance between the groups, but trend-level associations between higher FA of visual memory and the left CB (r = 0.286, P = 0.018), verbal memory (RAVLT) and -left CB (r = 0.335, P = 0.005), -right CB (r = 0.286, P = 0.016), and -left AF (r = 0.287, P = 0.017). SIGNIFICANCE Our results highlight that the presence and side of HS are crucial to understand the pathophysiology of MTLE. Specifically, left-sided HS seems to be related to widespread bilateral white matter abnormalities. Future longitudinal studies should focus on developing diagnostic and treatment strategies dependent on HS's presence/side.
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Affiliation(s)
- Tamires A. Zanao
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | - Johanna Seitz‐Holland
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lauren J. O'Donnell
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tátila M. Lopes
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | | | - Clarissa L. Yassuda
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
| | - Nikos Makris
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Sylvain Bouix
- Département de génie logiciel et TI, École de technologie supérieureUniversité du QuébecMontrealQuebecCanada
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fernando Cendes
- Neuroimaging Laboratory, School of Medical SciencesUniversity of CampinasCampinasSão PauloBrazil
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Yu H, Gao J, Chang RSK, Mak W, Thach TQ, Cheung RTF. Inhibitory dysfunction may cause prospective memory impairment in temporal lobe epilepsy (TLE) patients: an event-related potential study. Front Hum Neurosci 2023; 17:1006744. [PMID: 37565055 PMCID: PMC10410078 DOI: 10.3389/fnhum.2023.1006744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 07/10/2023] [Indexed: 08/12/2023] Open
Abstract
Introduction Prospective memory (PM) is the ability to remember future intentions, and PM function is closely related to independence in daily life, particularly in patients with temporal lobe epilepsy (TLE). As PM involves various cognitive components of attention, working memory, inhibition and other executive functions, this study investigated how TLE may affect PM components and the underlying neural mechanisms. Methods Sixty-four subjects were recruited, including 20 refractory TLE patients, 18 well-controlled TLE patients and 26 age-matched healthy controls. A set of neuropsychological tests was administered to assess specific brain functions. An event-related potential (ERP) task was used to further explore how PM and its components would be differentially affected in the two TLE types. Results Our findings revealed that: (1) refractory TLE patients scored lower than the healthy controls in the digit span, Verbal Fluency Test and Symbol Digit Modalities Test; (2) refractory TLE patients exhibited impaired PM performance and reduced prospective positivity amplitudes over the frontal, central and parietal regions in ERP experiments when compared to the healthy controls; and (3) decreased P3 amplitudes in the nogo trials were observed over the frontal-central sites in refractory but not in well-controlled TLE patients. Discussion To our knowledge, this is the first ERP study on PM that has specifically identified PM impairment in refractory but not in well-controlled TLE patients. Our finding of double dissociation in PM components suggests that inhibition dysfunction may be the main reason for PM deficit in refractory TLE patients. The present results have clinical implications for neuropsychological rehabilitation in TLE patients.
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Affiliation(s)
- Hemei Yu
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Junling Gao
- Centre of Buddhist Studies, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Richard Shek-Kwan Chang
- Division of Neurology, Department of Medicine, Queen Mary Hospital, Hong Kong, Hong Kong SAR, China
| | - Windsor Mak
- Division of Neurology, Department of Medicine, Queen Mary Hospital, Hong Kong, Hong Kong SAR, China
| | - Thuan-Quoc Thach
- Department of Psychiatry, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Raymond Tak Fai Cheung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
- Division of Neurology, Department of Medicine, Queen Mary Hospital, Hong Kong, Hong Kong SAR, China
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Fountain C, Ghuman H, Paldino M, Tamber M, Panigrahy A, Modo M. Acquisition and Analysis of Excised Neocortex from Pediatric Patients with Focal Cortical Dysplasia Using Mesoscale Diffusion MRI. Diagnostics (Basel) 2023; 13:1529. [PMID: 37174921 PMCID: PMC10177920 DOI: 10.3390/diagnostics13091529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/01/2023] [Accepted: 04/15/2023] [Indexed: 05/15/2023] Open
Abstract
Non-invasive classification of focal cortical dysplasia (FCD) subtypes remains challenging from a radiology perspective. Quantitative imaging biomarkers (QIBs) have the potential to distinguish subtypes that lack pathognomonic features and might help in defining the extent of abnormal connectivity associated with each FCD subtype. A key motivation of diagnostic imaging is to improve the localization of a "lesion" that can guide the surgical resection of affected tissue, which is thought to cause seizures. Conversely, surgical resections to eliminate or reduce seizures provided unique opportunities to develop magnetic resonance imaging (MRI)-based QIBs by affording long scan times to evaluate multiple contrast mechanisms at the mesoscale (0.5 mm isotropic voxel dimensions). Using ex vivo hybrid diffusion tensor imaging on a 9.4 T MRI scanner, the grey to white matter ratio of scalar indices was lower in the resected middle temporal gyrus (MTG) of two neuropathologically confirmed cases of FCD compared to non-diseased control postmortem fixed temporal lobes. In contrast, fractional anisotropy was increased within FCD and also adjacent white matter tracts. Connectivity (streamlines/mm3) in the MTG was higher in FCD, suggesting that an altered connectivity at the lesion locus can potentially provide a tangible QIB to distinguish and characterize FCD abnormalities. However, as illustrated here, a major challenge for a robust tractographical comparison lies in the considerable differences in the ex vivo processing of bioptic and postmortem samples. Mesoscale diffusion MRI has the potential to better define and characterize epileptic tissues obtained from surgical resection to advance our understanding of disease etiology and treatment.
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Affiliation(s)
- Chandler Fountain
- Department of Radiology and Medical Imaging, University of Virginia Health System, 1215 Lee St, Chartlottesville, VA 22903, USA
| | - Harmanvir Ghuman
- Department of Bioengineering, University of Pittsburgh, 302 Benedum Hall, 3700 O’Hara Street, Pititsburgh, PA 15260, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, 450 Technology Drive, Suite 300, Pittsburgh, PA 15219, USA
| | - Michael Paldino
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Mandeep Tamber
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, Suite B 400, Pittsburgh, PA 15213, USA
| | - Ashok Panigrahy
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Michel Modo
- Department of Bioengineering, University of Pittsburgh, 302 Benedum Hall, 3700 O’Hara Street, Pititsburgh, PA 15260, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, 450 Technology Drive, Suite 300, Pittsburgh, PA 15219, USA
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
- Centre for the Neural Basis of Behavior, University of Pittsburgh and Carnegie Mellon University, 4074 Biomedical Science Tower 3, Pittsburgh, PA 15261, USA
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11
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Chauvière L. Early cognitive comorbidities before disease onset: A common symptom towards prevention of related brain diseases? Heliyon 2022; 8:e12259. [PMID: 36590531 PMCID: PMC9800323 DOI: 10.1016/j.heliyon.2022.e12259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 12/15/2022] Open
Abstract
Brain diseases are very heterogeneous; however they also display multiple common risk factors and comorbidities. With a paucity of disease-modifying therapies, prevention became a health priority. Towards prevention, one strategy is to focus on similar symptoms of brain diseases occurring before disease onset. Cognitive deficits are a promising candidate as they occur across brain diseases before disease onset. Based on recent research, this review highlights the similarity of brain diseases and discusses how early cognitive deficits can be exploited to tackle disease prevention. After briefly introducing common risk factors, I review common comorbidities across brain diseases, with a focus on cognitive deficits before disease onset, reporting both experimental and clinical findings. Next, I describe network abnormalities associated with early cognitive deficits and discuss how these abnormalities can be targeted to prevent disease onset. A scenario on brain disease etiology with the idea that early cognitive deficits may constitute a common symptom of brain diseases is proposed.
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12
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Fleury M, Buck S, Binding LP, Caciagli L, Vos SB, Winston GP, Thompson P, Koepp MJ, Duncan JS, Sidhu MK. Episodic memory network connectivity in temporal lobe epilepsy. Epilepsia 2022; 63:2597-2622. [PMID: 35848050 PMCID: PMC9804196 DOI: 10.1111/epi.17370] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 07/14/2022] [Accepted: 07/15/2022] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) affects brain networks and is associated with impairment of episodic memory. Temporal and extratemporal reorganization of memory functions is described in functional magnetic resonance imaging (fMRI) studies. Functional reorganizations have been shown at the local activation level, but network-level alterations have been underinvestigated. We aim to investigate the functional anatomy of memory networks using memory fMRI and determine how this relates to memory function in TLE. METHODS Ninety patients with unilateral TLE (43 left) and 29 controls performed a memory-encoding fMRI paradigm of faces and words with subsequent out-of-scanner recognition test. Subsequent memory event-related contrasts of words and faces remembered were generated. Psychophysiological interaction analysis investigated task-associated changes in functional connectivity seeding from the mesial temporal lobes (MTLs). Correlations between changes in functional connectivity and clinical memory scores, epilepsy duration, age at epilepsy onset, and seizure frequency were investigated, and between connectivity supportive of better memory and disease burden. Connectivity differences between controls and TLE, and between TLE with and without hippocampal sclerosis, were explored using these confounds as regressors of no interest. RESULTS Compared to controls, TLE patients showed widespread decreased connectivity between bilateral MTLs and frontal lobes, and increased local connectivity between the anterior MTLs bilaterally. Increased intrinsic connectivity within the bilateral MTLs correlated with better out-of-scanner memory performance in both left and right TLE. Longer epilepsy duration and higher seizure frequency were associated with decreased connectivity between bilateral MTLs and left/right orbitofrontal cortex (OFC) and insula, connections supportive of memory functions. TLE due to hippocampal sclerosis was associated with greater connectivity disruption within the MTL and extratemporally. SIGNIFICANCE Connectivity analyses showed that TLE is associated with temporal and extratemporal memory network reorganization. Increased bilateral functional connectivity within the MTL and connectivity to OFC and insula are efficient, and are disrupted by greater disease burden.
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Affiliation(s)
- Marine Fleury
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
| | - Sarah Buck
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
| | - Lawrence P. Binding
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
- Department of Computer Science, Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Lorenzo Caciagli
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
- Department of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sjoerd B. Vos
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
- Neuroradiological Academic Unit, University College London Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Gavin P. Winston
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
- Division of Neurology, Department of MedicineQueen's UniversityKingstonOntarioCanada
| | - Pamela J. Thompson
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
| | - Matthias J. Koepp
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
| | - John S. Duncan
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
| | - Meneka K. Sidhu
- Department of Clinical and Experimental EpilepsyUniversity College London Queen Square Institute of NeurologyLondonUK
- MRI UnitEpilepsy SocietyBuckinghamshireUK
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13
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Godoy LD, Prizon T, Rossignoli MT, Leite JP, Liberato JL. Parvalbumin Role in Epilepsy and Psychiatric Comorbidities: From Mechanism to Intervention. Front Integr Neurosci 2022; 16:765324. [PMID: 35250498 PMCID: PMC8891758 DOI: 10.3389/fnint.2022.765324] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 01/24/2022] [Indexed: 12/22/2022] Open
Abstract
Parvalbumin is a calcium-binding protein present in inhibitory interneurons that play an essential role in regulating many physiological processes, such as intracellular signaling and synaptic transmission. Changes in parvalbumin expression are deeply related to epilepsy, which is considered one of the most disabling neuropathologies. Epilepsy is a complex multi-factor group of disorders characterized by periods of hypersynchronous activity and hyperexcitability within brain networks. In this scenario, inhibitory neurotransmission dysfunction in modulating excitatory transmission related to the loss of subsets of parvalbumin-expressing inhibitory interneuron may have a prominent role in disrupted excitability. Some studies also reported that parvalbumin-positive interneurons altered function might contribute to psychiatric comorbidities associated with epilepsy, such as depression, anxiety, and psychosis. Understanding the epileptogenic process and comorbidities associated with epilepsy have significantly advanced through preclinical and clinical investigation. In this review, evidence from parvalbumin altered function in epilepsy and associated psychiatric comorbidities were explored with a translational perspective. Some advances in potential therapeutic interventions are highlighted, from current antiepileptic and neuroprotective drugs to cutting edge modulation of parvalbumin subpopulations using optogenetics, designer receptors exclusively activated by designer drugs (DREADD) techniques, transcranial magnetic stimulation, genome engineering, and cell grafting. Creating new perspectives on mechanisms and therapeutic strategies is valuable for understanding the pathophysiology of epilepsy and its psychiatric comorbidities and improving efficiency in clinical intervention.
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Affiliation(s)
- Lívea Dornela Godoy
- Department of Psychology, Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Tamiris Prizon
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Matheus Teixeira Rossignoli
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - João Pereira Leite
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- João Pereira Leite,
| | - José Luiz Liberato
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- *Correspondence: José Luiz Liberato,
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14
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Longitudinal analysis of interictal electroencephalograms in patients with temporal lobe epilepsy with hippocampal sclerosis. Seizure 2021; 90:141-144. [DOI: 10.1016/j.seizure.2021.02.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/05/2021] [Accepted: 02/06/2021] [Indexed: 12/14/2022] Open
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15
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Shan W, Yang H, Wang Q. Neuronal Surface Antibody-Medicated Autoimmune Encephalitis (Limbic Encephalitis) in China: A Multiple-Center, Retrospective Study. Front Immunol 2021; 12:621599. [PMID: 33679765 PMCID: PMC7928315 DOI: 10.3389/fimmu.2021.621599] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 01/27/2021] [Indexed: 12/15/2022] Open
Abstract
Objective: The epidemiological characteristics of patients with antibody-medicated autoimmune encephalitis in China remain unclear, and a large-scale epidemiological survey is necessary. Methods: A multiple-center retrospective study was performed. We collected 1,047 patients with suspected autoimmune encephalitis and ultimately enrolled 778 defined patients across centers in China. All patients were positive for serum [or cerebrospinal fluid (CSF)] antibodies. Demographic information and clinical data from January 2014 to January 2019 from 22 centers in China were reviewed. Results: A total of 778 patients with autoimmune encephalitis were enrolled in the study. In general, the ratio of males to females was ~1.2:1. The main subtypes of autoimmune encephalitis were NMDAR-AE (61.35%), LGI-1-AE (20.61%), and GABAbR-AE (12.40%). According to the characteristics of age of onset, the incidence of autoimmune encephalitis showed a “double peak” distribution entailing a 20-year-old age group and a 60-year-old age group. We next analyzed the proportion of patients with tumors in this cohort. More specifically, there were 34 patients with tumors and 85 with tumor marker positivity. Relapse occurred in 81 patients within at least 1 year's follow up study: 52 with NMDAR-AE (18.2%); 19 with LGI-1-AE (16.8%); 5 with GABAbR-AE (9%); and 3 with CASPR2-AE. Interpretation: Due to the vast differences in demographic features, the incidence of cancer and the genetic characteristics between the populations in China and Western countries, the demographics, sex distribution, concomitant tumor rate, clinical features, and relapse characteristics associated with autoimmune encephalitis in China shows a similar profile with Western countries with some minor differences.
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Affiliation(s)
- Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Center for Clinical Medicine of Neurological Diseases, Beijing, China.,Beijing Institute for Brain Disorders, Beijing, China
| | - Huajun Yang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Center for Clinical Medicine of Neurological Diseases, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,National Center for Clinical Medicine of Neurological Diseases, Beijing, China.,Beijing Institute for Brain Disorders, Beijing, China
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16
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Aroor A, Brewster AL. Seizing the Alzheimer's Brain: A Role for Sirtuin 3 in Hyperexcitability. Epilepsy Curr 2020; 20:224-226. [PMID: 34025234 PMCID: PMC7427166 DOI: 10.1177/1535759720932157] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
[Box: see text]
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17
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Chauvière L. Potential causes of cognitive alterations in temporal lobe epilepsy. Behav Brain Res 2020; 378:112310. [DOI: 10.1016/j.bbr.2019.112310] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/15/2019] [Accepted: 10/15/2019] [Indexed: 12/11/2022]
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18
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Salpekar JA, Mula M. Common psychiatric comorbidities in epilepsy: How big of a problem is it? Epilepsy Behav 2019; 98:293-297. [PMID: 30149996 DOI: 10.1016/j.yebeh.2018.07.023] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 07/24/2018] [Indexed: 11/28/2022]
Abstract
Psychiatric illness and epilepsy commonly co-occur in adults and in children and adolescents. Theories of comorbidity are complex, but recurring associations between the conditions suggest overlap that is more than simple co-occurrence. Common underlying pathophysiology may imply that epilepsy itself may constituently include psychiatric symptoms. Conditions such as depression or cognitive difficulties commonly occur and in some cases, are considered to be associated with specific epilepsy characteristics such as localization or seizure type. Regardless of etiologic attributions to psychiatric comorbidity, it is clear today that treatment for epilepsy needs to target psychiatric illness. In many cases, quality-of-life improvements depend more upon addressing psychiatric symptoms than seizures themselves. This article is part of the Special Issue "Obstacles of Treatment of Psychiatric Comorbidities in Epilepsy".
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Affiliation(s)
- Jay A Salpekar
- Kennedy Krieger Institute, Johns Hopkins University, USA.
| | - Marco Mula
- Institute of Medical and Biomedical Education, St George's University of London, United Kingdom; Atkinson Morley Regional Neuroscience Centre, St George's University Hospitals NHS Foundation Trust, London, United Kingdom
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19
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Fitzgerald PJ, Watson BO. Gamma oscillations as a biomarker for major depression: an emerging topic. Transl Psychiatry 2018; 8:177. [PMID: 30181587 PMCID: PMC6123432 DOI: 10.1038/s41398-018-0239-y] [Citation(s) in RCA: 155] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 08/05/2018] [Indexed: 01/16/2023] Open
Abstract
Identifying biomarkers for major depression is of high importance for improving diagnosis and treatment of this common and debilitating neuropsychiatric disorder, as the field seeks to move toward both personalized and more effective treatments. Here we focus on electroencephalography (EEG) or direct scalp voltage recordings as such a biomarker, with an emphasis on gamma and high gamma oscillations (or "rhythms"). In the last several decades, alpha and theta band rhythms have been found to provide information on depressive state as well as recovery, but the gamma band is less well characterized with respect to depression. We summarize some key findings on gamma rhythms (especially their amplitude) as a biomarker or endophenotype for major depression. These studies suggest: (1) under certain conditions gamma rhythms can distinguish subjects with major depression from healthy controls, (2) gamma may distinguish bipolar disorder from unipolar depression, (3) various pharmacological and non-pharmacological treatments that counteract depression also alter gamma, (4) animal models of depression-like behavior show gamma abnormalities, with changes in gamma associated with therapeutic recovery. The most informative approaches in the future may combine profiles of gamma band power across the brain to assess ratios of activity across regions. Overall we have good evidence to suggest that gamma rhythms may provide objective information on major depressive disease status, but we will need further work to better define the precise measures to follow.
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Affiliation(s)
- Paul J Fitzgerald
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109-5720, USA
| | - Brendon O Watson
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109-5720, USA.
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