1
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Song C, Xie S, Zhang X, Han S, Lian Y, Ma K, Mao X, Zhang Y, Cheng J. Similarities and differences of dynamic and static spontaneous brain activity between left and right temporal lobe epilepsy. Brain Imaging Behav 2024; 18:352-367. [PMID: 38087148 DOI: 10.1007/s11682-023-00835-w] [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] [Accepted: 12/01/2023] [Indexed: 06/07/2024]
Abstract
To comprehensively investigate the potential temporal dynamic and static abnormalities of spontaneous brain activity (SBA) in left temporal lobe epilepsy (LTLE) and right temporal lobe epilepsy (RTLE) and to detect whether these alterations correlate with cognition. Twelve SBA metrics, including ALFF, dALFF, fALFF, dfALFF, ReHo, dReHo, DC, dDC, GSCorr, dGSCorr, VMHC, and dVMHC, in 46 LTLE patients, 43 RTLE patients, and 53 healthy volunteers were compared in the voxel-wise analysis. Correlation analyses between metrics in regions showing statistic differences and epilepsy duration, epilepsy severity, and cognition scores were also performed. Compared with the healthy volunteers, the alteration of SBA was identified both in LTLE and RTLE patients. The ALFF, fALFF, and dALFF values in LTLE, as well as the fALFF values in RTLE, increased in the bilateral thalamus, basal ganglia, mesial temporal lobe, cerebellum, and vermis. Increased dfALFF in the bilateral basal ganglia, increased ReHo and dReHo in the bilateral thalamus in the LTLE group, increased ALFF and dALFF in the pons, and increased ReHo and dReHo in the right hippocampus in the RTLE group were also detected. However, the majority of deactivation clusters were in the ipsilateral lateral temporal lobe. For LTLE, the fALFF, DC, dDC, and GSCorr values in the left lateral temporal lobe and the ReHo and VMHC values in the bilateral lateral temporal lobe all decreased. For RTLE, the ALFF, fALFF, dfALFF, ReHo, dReHo, and DC values in the right lateral temporal lobe and the VMHC values in the bilateral lateral temporal lobe all decreased. Moreover, for both the LTLE and RTLE groups, the dVMHC values decreased in the calcarine cortex. The most significant difference between LTLE and RTLE was the higher activation in the cerebellum of the LTLE group. The alterations of many SBA metrics were correlated with cognition and epilepsy duration. The patterns of change in SBA abnormalities in the LTLE and RTLE patients were generally similar. The integrated application of temporal dynamic and static SBA metrics might aid in the investigation of the propagation and suppression pathways of seizure activity as well as the cognitive impairment mechanisms in TLE.
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Affiliation(s)
- Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Shanshan Xie
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yajun Lian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Xinyue Mao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China.
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2
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Stasenko A, Lin C, Bonilha L, Bernhardt BC, McDonald CR. Neurobehavioral and Clinical Comorbidities in Epilepsy: The Role of White Matter Network Disruption. Neuroscientist 2024; 30:105-131. [PMID: 35193421 PMCID: PMC9393207 DOI: 10.1177/10738584221076133] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Epilepsy is a common neurological disorder associated with alterations in cortical and subcortical brain networks. Despite a historical focus on gray matter regions involved in seizure generation and propagation, the role of white matter (WM) network disruption in epilepsy and its comorbidities has sparked recent attention. In this review, we describe patterns of WM alterations observed in focal and generalized epilepsy syndromes and highlight studies linking WM disruption to cognitive and psychiatric comorbidities, drug resistance, and poor surgical outcomes. Both tract-based and connectome-based approaches implicate the importance of extratemporal and temporo-limbic WM disconnection across a range of comorbidities, and an evolving literature reveals the utility of WM patterns for predicting outcomes following epilepsy surgery. We encourage new research employing advanced analytic techniques (e.g., machine learning) that will further shape our understanding of epilepsy as a network disorder and guide individualized treatment decisions. We also address the need for research that examines how neuromodulation and other treatments (e.g., laser ablation) affect WM networks, as well as research that leverages larger and more diverse samples, longitudinal designs, and improved magnetic resonance imaging acquisitions. These steps will be critical to ensuring generalizability of current research and determining the extent to which neuroplasticity within WM networks can influence patient outcomes.
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Affiliation(s)
- Alena Stasenko
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Christine Lin
- School of Medicine, University of California, San Diego, CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Boris C Bernhardt
- Departments of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Carrie R McDonald
- Department of Psychiatry, University of California, San Diego, CA, USA
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego, CA, USA
- Center for Multimodal Imaging and Genetics (CMIG), University of California, San Diego, CA, USA
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3
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McDonald CR. A journey with Steve Schachter as Editor-in-Chief: From first submission to fiber tract cover model. Epilepsy Behav 2022; 137:108807. [PMID: 36463038 DOI: 10.1016/j.yebeh.2022.108807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 06/19/2022] [Indexed: 12/05/2022]
Affiliation(s)
- Carrie R McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, United States
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4
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Vinti V, Dell'Isola GB, Tascini G, Mencaroni E, Cara GD, Striano P, Verrotti A. Temporal Lobe Epilepsy and Psychiatric Comorbidity. Front Neurol 2021; 12:775781. [PMID: 34917019 PMCID: PMC8669948 DOI: 10.3389/fneur.2021.775781] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/28/2021] [Indexed: 12/14/2022] Open
Abstract
Most focal seizures originate in the temporal lobe and are commonly divided into mesial and lateral temporal epilepsy, depending upon the neuronal circuitry involved. The hallmark features of the mesial temporal epilepsy are aura, unconsciousness, and automatisms. Symptoms often overlap with the lateral temporal epilepsy. However, the latter present a less evident psychomotor arrest, frequent clones and dystonic postures, and common focal to bilateral tonic–clonic seizures. Sclerosis of the hippocampus is the most frequent cause of temporal lobe epilepsy (TLE). TLE is among all epilepsies the most frequently associated with psychiatric comorbidity. Anxiety, depression, and interictal dysphoria are recurrent psychiatric disorders in pediatric patients with TLE. In addition, these alterations are often combined with cognitive, learning, and behavioral impairment. These comorbidities occur more frequently in TLE with hippocampal sclerosis and with pharmacoresistance. According to the bidirectional hypothesis, the close relationship between TLE and psychiatric features should lead to considering common pathophysiology underlying these disorders. Psychiatric comorbidities considerably reduce the quality of life of these children and their families. Thus, early detection and appropriate management and therapeutic strategies could improve the prognosis of these patients. The aim of this review is to analyze TLE correlation with psychiatric disorders and its underlying conditions.
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Affiliation(s)
- Valerio Vinti
- Department of Pediatrics, University of Perugia, Perugia, Italy
| | | | - Giorgia Tascini
- Department of Pediatrics, University of Perugia, Perugia, Italy
| | | | | | - Pasquale Striano
- Pediatric Neurology and Muscular Diseases Unit, Istituto di Ricovero e Cura a Carattere Scientifico Giannina Gaslini (IRCCS "G. Gaslini") Institute, Genoa, Italy.,Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
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5
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Hermann BP, Struck AF, Busch RM, Reyes A, Kaestner E, McDonald CR. Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy. Nat Rev Neurol 2021; 17:731-746. [PMID: 34552218 PMCID: PMC8900353 DOI: 10.1038/s41582-021-00555-z] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2021] [Indexed: 02/06/2023]
Abstract
Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.
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Affiliation(s)
- Bruce P. Hermann
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,
| | - Aaron F. Struck
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,William S. Middleton Veterans Administration Hospital, Madison, WI, USA
| | - Robyn M. Busch
- Epilepsy Center and Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.,Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Anny Reyes
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
| | - Erik Kaestner
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
| | - Carrie R. McDonald
- Department of Psychiatry and Center for Multimodal Imaging and Genetics, University of California, San Diego, San Diego, CA, USA
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6
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Si X, Zhang X, Zhou Y, Chao Y, Lim SN, Sun Y, Yin S, Jin W, Zhao X, Li Q, Ming D. White matter structural connectivity as a biomarker for detecting juvenile myoclonic epilepsy by transferred deep convolutional neural networks with varying transfer rates. J Neural Eng 2021; 18. [PMID: 34507303 DOI: 10.1088/1741-2552/ac25d8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 09/10/2021] [Indexed: 11/12/2022]
Abstract
Objective. By detecting abnormal white matter changes, diffusion magnetic resonance imaging (MRI) contributes to the detection of juvenile myoclonic epilepsy (JME). In addition, deep learning has greatly improved the detection performance of various brain disorders. However, there is almost no previous study effectively detecting JME by a deep learning approach with diffusion MRI.Approach. In this study, the white matter structural connectivity was generated by tracking the white matter fibers in detail based on Q-ball imaging and neurite orientation dispersion and density imaging. Four advanced deep convolutional neural networks (CNNs) were deployed by using the transfer learning approach, in which the transfer rate searching strategy was proposed to achieve the best detection performance.Main results. Our results showed: (a) Compared to normal control, the white matter' neurite density of JME was significantly decreased. The most significantly abnormal fiber tracts between the two groups were found to be cortico-cortical connection tracts. (b) The proposed transfer rate searching approach contributed to find each CNN's best performance, in which the best JME detection accuracy of 92.2% was achieved by using the Inception_resnet_v2 network with a 16% transfer rate.Significance. The results revealed: (a) Through detection of the abnormal white matter changes, the white matter structural connectivity can be used as a useful biomarker for detecting JME, which helps to characterize the pathophysiology of epilepsy. (b) The proposed transfer rate, as a new hyperparameter, promotes the CNNs transfer learning performance in detecting JME.
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Affiliation(s)
- Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China.,Institute of Applied Psychology, Tianjin University, Tianjin 300350, People's Republic of China
| | - Xingjian Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
| | - Yu Zhou
- School of Microelectronics, Tianjin University, Tianjin 300072, People's Republic of China
| | - Yiping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Siew-Na Lim
- Department of Neurology, Chang Gung Memorial Hospital, Taoyuan 333, Taiwan
| | - Yulin Sun
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
| | - Shaoya Yin
- Department of Neurosurgery, Huanhu Hospital, Tianjin University, Tianjin 300072, People's Republic of China
| | - Weipeng Jin
- Department of Neurosurgery, Huanhu Hospital, Tianjin University, Tianjin 300072, People's Republic of China
| | - Xin Zhao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin 300072, People's Republic of China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, People's Republic of China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, People's Republic of China
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7
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Sone D. Making the Invisible Visible: Advanced Neuroimaging Techniques in Focal Epilepsy. Front Neurosci 2021; 15:699176. [PMID: 34385902 PMCID: PMC8353251 DOI: 10.3389/fnins.2021.699176] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/28/2021] [Indexed: 12/30/2022] Open
Abstract
It has been a clinically important, long-standing challenge to accurately localize epileptogenic focus in drug-resistant focal epilepsy because more intensive intervention to the detected focus, including resection neurosurgery, can provide significant seizure reduction. In addition to neurophysiological examinations, neuroimaging plays a crucial role in the detection of focus by providing morphological and neuroanatomical information. On the other hand, epileptogenic lesions in the brain may sometimes show only subtle or even invisible abnormalities on conventional MRI sequences, and thus, efforts have been made for better visualization and improved detection of the focus lesions. Recent advance in neuroimaging has been attracting attention because of the potentials to better visualize the epileptogenic lesions as well as provide novel information about the pathophysiology of epilepsy. While the progress of newer neuroimaging techniques, including the non-Gaussian diffusion model and arterial spin labeling, could non-invasively detect decreased neurite parameters or hypoperfusion within the focus lesions, advances in analytic technology may also provide usefulness for both focus detection and understanding of epilepsy. There has been an increasing number of clinical and experimental applications of machine learning and network analysis in the field of epilepsy. This review article will shed light on recent advances in neuroimaging for focal epilepsy, including both technical progress of images and newer analytical methodologies and discuss about the potential usefulness in clinical practice.
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Affiliation(s)
- Daichi Sone
- Department of Psychiatry, The Jikei University School of Medicine, Tokyo, Japan.,Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, United Kingdom
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8
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Zhou S, Xiong P, Ren H, Tan W, Yan Y, Gao Y. Aberrant dorsal attention network homogeneity in patients with right temporal lobe epilepsy. Epilepsy Behav 2020; 111:107278. [PMID: 32693375 DOI: 10.1016/j.yebeh.2020.107278] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 06/18/2020] [Accepted: 06/19/2020] [Indexed: 12/31/2022]
Abstract
The dorsal attention network (DAN) is involved in the process that causes wide-ranging cognitive damage resulted in right temporal lobe epilepsy (rTLE). Nevertheless, few studies have evaluated the relationship between DAN and rTLE. There has been little research on alterations in the network homogeneity (NH) of the DAN in rTLE. The aim of the present study was to investigate NH changes in DAN in patients with rTLE. We included 85 patients with rTLE and 69 healthy controls in this study, and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired. The NH method was used for data analysis. All subjects took the attention network test (ANT). Network homogeneity in the right superior parietal lobule (SPL) and right precuneus (PCU) was significantly higher in patients with rTLE than in healthy controls. The reaction time (RT) was significantly longer in patients with rTLE than in controls. Notably, we observed no significant relationship between the clinical variables and the abnormal NH. These results indicated that abnormal alterations in DAN existed in patients with rTLE and highlighted the crucial role of DAN in the pathophysiology of cognitive damage in rTLE. Our findings suggested that the executive function (EF) significantly weakened in patients with rTLE.
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Affiliation(s)
- Sangyu Zhou
- School of Medicine, Wuhan University of Science and Technology, Wuhan, Hubei 430000, China; Department of Psychiatry, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei 430000, China
| | - Pingan Xiong
- Department of Taihe Hospital Reproductive Medicine Center Affiliated to Hubei University of Medicine, Shiyan, Hubei 442000, China
| | - Hongwei Ren
- Department of Medical Imaging, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei 430000, China
| | - Wei Tan
- Hospital of Wuhan University of Science and Technology, Wuhan, Hubei 430000, China
| | - Yanguo Yan
- Department of Psychiatry, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei 430000, China
| | - Yujun Gao
- Department of Psychiatry, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei 430000, China.
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9
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Hatton SN, Huynh KH, Bonilha L, Abela E, Alhusaini S, Altmann A, Alvim MKM, Balachandra AR, Bartolini E, Bender B, Bernasconi N, Bernasconi A, Bernhardt B, Bargallo N, Caldairou B, Caligiuri ME, Carr SJA, Cavalleri GL, Cendes F, Concha L, Davoodi-bojd E, Desmond PM, Devinsky O, Doherty CP, Domin M, Duncan JS, Focke NK, Foley SF, Gambardella A, Gleichgerrcht E, Guerrini R, Hamandi K, Ishikawa A, Keller SS, Kochunov PV, Kotikalapudi R, Kreilkamp BAK, Kwan P, Labate A, Langner S, Lenge M, Liu M, Lui E, Martin P, Mascalchi M, Moreira JCV, Morita-Sherman ME, O’Brien TJ, Pardoe HR, Pariente JC, Ribeiro LF, Richardson MP, Rocha CS, Rodríguez-Cruces R, Rosenow F, Severino M, Sinclair B, Soltanian-Zadeh H, Striano P, Taylor PN, Thomas RH, Tortora D, Velakoulis D, Vezzani A, Vivash L, von Podewils F, Vos SB, Weber B, Winston GP, Yasuda CL, Zhu AH, Thompson PM, Whelan CD, Jahanshad N, Sisodiya SM, McDonald CR. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study. Brain 2020; 143:2454-2473. [PMID: 32814957 PMCID: PMC7567169 DOI: 10.1093/brain/awaa200] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/07/2020] [Accepted: 04/30/2020] [Indexed: 12/22/2022] Open
Abstract
The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.
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Affiliation(s)
- Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics,
University of California San Diego, La Jolla 92093 CA, USA
| | - Khoa H Huynh
- Center for Multimodal Imaging and Genetics, University of California San
Diego, La Jolla 92093 CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina,
Charleston 29425 SC, USA
| | - Eugenio Abela
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry,
Psychology and Neuroscience, Kings College London, London SE5 9NU UK
| | - Saud Alhusaini
- Neurology Department, Yale School of Medicine, New Haven 6510 CT,
USA
- Molecular and Cellular Therapeutics, The Royal College of Surgeons in
Ireland, Dublin, Ireland
| | - Andre Altmann
- Centre of Medical Image Computing, Department of Medical Physics and Biomedical
Engineering, University College London, London WC1V 6LJ, UK
| | - Marina K M Alvim
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Akshara R Balachandra
- Center for Multimodal Imaging and Genetics, UCSD School of
Medicine, La Jolla 92037 CA, USA
- Boston University School of Medicine, Boston 2118 MA, USA
| | - Emanuele Bartolini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- USL Centro Toscana, Neurology Unit, Nuovo Ospedale Santo Stefano,
Prato, Italy
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital
Tübingen, Tübingen 72076, Germany
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Boris Bernhardt
- Montreal Neurological Institute, McGill University, Montreal
H3A2B4 QC, Canada
| | - Núria Bargallo
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques
August Pi i Sunyer (IDIBAPS), Barcelona 8036 Barcelona, Spain
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, Montreal Neurological Institute, McGill
University, Montreal H3A 2B4 QC, Canada
| | - Maria E Caligiuri
- Neuroscience Research Center, University Magna Graecia, viale Europa,
Germaneto, 88100, Catanzaro, Italy
| | - Sarah J A Carr
- Neuroscience, Institute of Psychiatry, Psychology and
Neuroscience, De Crespigny Park, London SE5 8AF, UK
| | - Gianpiero L Cavalleri
- Royal College of Surgeons in Ireland, School of Pharmacy and Biomolecular
Sciences, Dublin D02 YN77 Ireland
- FutureNeuro Research Centre, Science Foundation Ireland, Dublin
D02 YN77, Ireland
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autonoma de
Mexico, Queretaro 76230, Mexico
| | - Esmaeil Davoodi-bojd
- Radiology and Research Administration, Henry Ford Hospital, 1
Detroit 48202 MI, USA
| | - Patricia M Desmond
- Department of Radiology, Royal Melbourne Hospital, University of
Melbourne, Melbourne 3050 Victoria, Australia
| | | | - Colin P Doherty
- Division of Neurology, Trinity College Dublin, TBSI, Pearce
Street, Dublin D02 R590, Ireland
- FutureNeuro SFI Centre for Neurological Disease, RCSI, St Stephen’s
Green, Dublin D02 H903, Ireland
| | - Martin Domin
- Functional Imaging Unit, University Medicine Greifswald,
Greifswald 17475 M/V, Germany
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of
Neurology, Queen Square, London WC1N 3BG, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire SL9 0RJ, UK
| | - Niels K Focke
- Clinical Neurophysiology, University Medicine Göttingen, 37099
Göttingen, Germany
- Department of Epileptology, University of Tübingen, 72076
Tübingen, Germany
| | | | - Antonio Gambardella
- Royal College of Surgeons in Ireland, School of Pharmacy and Biomolecular
Sciences, Dublin D02 YN77 Ireland
- Institute of Neurology, University Magna Graecia, 88100,
Catanzaro, Italy
| | | | - Renzo Guerrini
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Khalid Hamandi
- The Wales Epilepsy Unit, Cardiff and Vale University Health
Board, Cardiff CF144XW, UK
- Brain Research Imaging Centre, Cardiff University, Cardiff CF24
4HQ, UK
| | - Akari Ishikawa
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Simon S Keller
- Institute of Translational Medicine, University of Liverpool,
Liverpool L69 3BX, UK
- Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Peter V Kochunov
- Maryland Psychiatric Research Center, 55 Wade Ave, Baltimore
21228, MD, USA
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, University Hospital
Tübingen, Tübingen 72076 BW, Germany
- Department of Diagnostic and Interventional Neuroradiology, University Hospital
Tübingen, Tübingen 72076 BW, Germany
| | - Barbara A K Kreilkamp
- Institute of Translational Medicine, University of Liverpool,
Liverpool L69 3BX, UK
- Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
| | - Angelo Labate
- Neuroscience Research Center, University Magna Graecia, viale Europa,
Germaneto, 88100, Catanzaro, Italy
- Institute of Neurology, University Magna Graecia, 88100,
Catanzaro, Italy
| | - Soenke Langner
- Institute for Diagnostic Radiology and Neuroradiology, Ernst Moritz Arndt
University Greifswald Faculty of Medicine, Greifswald 17475, Germany
- Institute for Diagnostic and Interventional Radiology, Pediatric and
Neuroradiology, Rostock University Medical Centre, Rostock 18057, Germany
| | - Matteo Lenge
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and Laboratories,
Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Children’s Hospital A.
Meyer-University of Florence, Florence 50139, Italy
| | - Min Liu
- Department of Neurology, Montreal Neurological Institute,
Montreal H3A 2B4 QC, Canada
| | - Elaine Lui
- Department of Radiology, Royal Melbourne Hospital, University of
Melbourne, Melbourne 3050 Victoria, Australia
- Department of Medicine and Radiology, University of Melbourne,
3Parkville 3050 Victoria, Australia
| | - Pascal Martin
- Department of Epileptology, University of Tübingen, 72076
Tübingen, Germany
| | - Mario Mascalchi
- Meyer Children Hospital University of Florence, Florence 50130
Tuscany, Italy
| | - José C V Moreira
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Marcia E Morita-Sherman
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
- Cleveland Clinic, Cleveland 44195 OH, USA
| | - Terence J O’Brien
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne 3004 Victoria,
Australia
| | - Heath R Pardoe
- Department of Neurology, New York University School of Medicine,
New York City 10016 NY, USA
| | - José C Pariente
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques
August Pi i Sunyer (IDIBAPS), Barcelona 8036 Barcelona, Spain
| | - Letícia F Ribeiro
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Mark P Richardson
- Division of Neuroscience, King’s College London, Institute of
Psychiatry, London SE5 8AB, UK
| | - Cristiane S Rocha
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Raúl Rodríguez-Cruces
- Montreal Neurological Institute, McGill University, Montreal
H3A2B4 QC, Canada
- Institute of Neurobiology, Universidad Nacional Autonoma de
Mexico, Queretaro 76230, Mexico
| | - Felix Rosenow
- Epilepsy Center Frankfurt Rhine-Main, University Hospital Frankfurt,
Germany, Frankfurt 60528 Hesse, Germany
- Center for Personalized Translational Epilepsy Research (CePTER),
Goethe-University Frankfurt, Frankfurt a. M. 60528, Germany
| | - Mariasavina Severino
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa 16147
Liguria, Italy
| | - Benjamin Sinclair
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne 3004 Victoria,
Australia
| | - Hamid Soltanian-Zadeh
- Radiology and Research Administration, Henry Ford Health System,
Detroit 48202-2692 MI, USA
- School of Electrical and Computer Engineering, University of
Tehran, Tehran 14399-57131, Iran
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genoa 16147 Liguria, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal
and Child Health, University of Genova, Genova, Italy
| | - Peter N Taylor
- School of Computing, Newcastle University, Urban Sciences Building, Science
Square, Newcastle upon Tyne NE4 5TG, UK
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Newcastle
University, Newcastle upon Tyne NE2 4HH, UK
- Royal Victoria Infirmary, Newcastle upon Tyne NE1 4LP, UK
| | - Domenico Tortora
- Radiology and Research Administration, Henry Ford Health System,
Detroit 48202-2692 MI, USA
| | - Dennis Velakoulis
- Royal Melbourne Hospital, Melbourne 3050 Victoria, Australia
- University of Melbourne, Parkville, Melbourne 3050 Victoria,
Australia
| | - Annamaria Vezzani
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano
20156 Italy
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Monash
University, Melbourne 3004 Victoria, Australia
- Department of Medicine, University of Melbourne, Royal Melbourne
Hospital, Parkville 3050 Victoria, Australia
| | - Felix von Podewils
- Epilepsy Center, University Medicine Greifswald, Greifswald 17489
Mecklenburg-Vorpommern, Germany
| | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London,
London, WC1V 6LJ, UK
- Epilepsy Society, MRI Unit, Chalfont St Peter, Buckinghamshire,
SL9 0RJ, UK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University of
Bonn, Venusberg Campus 1, Bonn 53127 NRW, Germany
| | - Gavin P Winston
- Epilepsy Society, MRI Unit, Chalfont St Peter, Buckinghamshire,
SL9 0RJ, UK
- Department of Medicine, Division of Neurology, Queen's
University, Kingston K7L 3N6 ON, Canada
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire, SL9 0RJ UK
| | - Clarissa L Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas 13083-888
São Paulo, Brazil
| | - Alyssa H Zhu
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Christopher D Whelan
- Molecular and Cellular Therapeutics, The Royal College of Surgeons in
Ireland, Dublin, Ireland
- Research and Early Development (RED), Biogen Inc., Cambridge, MA
02139, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and
Informatics, USC Keck School of Medicine, Los Angeles 90232 CA, USA
| | - Sanjay M Sisodiya
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont-St-Peter,
Buckinghamshire, SL9 0RJ UK
- Chalfont Centre for Epilepsy, Chalfont-St-Peter, SL9 0RJ Bucks,
UK
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics,
University of California San Diego, La Jolla 92093 CA, USA
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10
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The effect of bilingualism on brain development from early childhood to young adulthood. Brain Struct Funct 2020; 225:2131-2152. [PMID: 32691216 PMCID: PMC7473972 DOI: 10.1007/s00429-020-02115-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 07/09/2020] [Indexed: 11/30/2022]
Abstract
Bilingualism affects the structure of the brain in adults, as evidenced by experience-dependent grey and white matter changes in brain structures implicated in language learning, processing, and control. However, limited evidence exists on how bilingualism may influence brain development. We examined the developmental patterns of both grey and white matter structures in a cross-sectional study of a large sample (n = 711 for grey matter, n = 637 for white matter) of bilingual and monolingual participants, aged 3–21 years. Metrics of grey matter (thickness, volume, and surface area) and white matter (fractional anisotropy and mean diffusivity) were examined across 41 cortical and subcortical brain structures and 20 tracts, respectively. We used generalized additive modelling to analyze whether, how, and where the developmental trajectories of bilinguals and monolinguals might differ. Bilingual and monolingual participants manifested distinct developmental trajectories in both grey and white matter structures. As compared to monolinguals, bilinguals showed: (a) more grey matter (less developmental loss) starting during late childhood and adolescence, mainly in frontal and parietal regions (particularly in the inferior frontal gyrus pars opercularis, superior frontal cortex, inferior and superior parietal cortex, and precuneus); and (b) higher white matter integrity (greater developmental increase) starting during mid-late adolescence, specifically in striatal–inferior frontal fibers. The data suggest that there may be a developmental basis to the well-documented structural differences in the brain between bilingual and monolingual adults.
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11
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Ren Y, Pan L, Du X, Hou Y, Li X, Song Y. Functional brain network mechanism of executive control dysfunction in temporal lobe epilepsy. BMC Neurol 2020; 20:137. [PMID: 32295523 PMCID: PMC7161158 DOI: 10.1186/s12883-020-01711-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 03/30/2020] [Indexed: 11/10/2022] Open
Abstract
Background Executive control dysfunction is observed in a sizable number of patients with temporal lobe epilepsy (TLE). Neural oscillations in the theta band are increasingly recognized as having a crucial role in executive control network. The purpose of this study was to investigate the alterations in the theta band in executive control network and explore the functional brain network mechanisms of executive control dysfunction in TLE patients. Methods A total of 20 TLE patients and 20 matched healthy controls (HCs) were recruited in the present study. All participants were trained to perform the executive control task by attention network test while the scalp electroencephalogram (EEG) data were recorded. The resting state signals were collected from the EEG in the subjects with quiet and closed eyes conditions. Functional connectivity among EEGs in the executive control network and resting state network were respectively calculated. Results We found the significant executive control impairment in the TLE group. Compared to the HCs, the TLE group showed significantly weaker functional connectivity among EEGs in the executive control network. Moreover, in the TLE group, we found that the functional connectivity was significantly positively correlated with accuracy and negatively correlated with EC_effect. In addition, the functional connectivity of the executive control network was significantly higher than that of the resting state network in the HCs. In the TLE group, however, there was no significant change in functional connectivity strengths between the executive control network and resting state network. Conclusion Our results indicate that the decreased functional connectivity in theta band may provide a potential mechanism for executive control deficits in TLE patients.
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Affiliation(s)
- Yanping Ren
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Liping Pan
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Xueyun Du
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Yuying Hou
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Xun Li
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Yijun Song
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China.
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12
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Nair S, Szaflarski JP. Neuroimaging of memory in frontal lobe epilepsy. Epilepsy Behav 2020; 103:106857. [PMID: 31937510 DOI: 10.1016/j.yebeh.2019.106857] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/04/2019] [Accepted: 12/13/2019] [Indexed: 10/25/2022]
Abstract
In a large percentage of epilepsies, seizures have focal onset. These epilepsies are associated with a wide range of behavioral and cognitive deficits sometimes limited to the functions encompassed within the ictal onset zone but, more frequently, expanding beyond it. The presence of impairments associated with neuroanatomical areas outside of the ictal onset zone suggests distal propagation of epileptic activity via brain networks and interconnected whole-brain neural circuitry. In patients with frontal lobe epilepsy (FLE), using functional magnetic resonance imaging (fMRI) to identify deficits in working, semantic, and episodic memory may provide a lens through which to understand typical and atypical network organization. A network approach to focal epilepsy is relevant in these patients because of the frequently noted early age of seizure onset. Early seizure-related disruption in healthy brain development may result in a significant brain reorganization, development of compensation-related mechanisms of dealing with function abnormalities and disruptions, and the propagation of epileptic activity from the focus to widespread brain areas (functional deficit zones). Benefits of a network approach in the study of focal epilepsy are discussed along with considerations for future neuroimaging studies of patients with FLE.
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Affiliation(s)
- Sangeeta Nair
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Jerzy P Szaflarski
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA; Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA; Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, USA
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13
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Aberrant topological organization of the default mode network in temporal lobe epilepsy revealed by graph-theoretical analysis. Neurosci Lett 2019; 708:134351. [DOI: 10.1016/j.neulet.2019.134351] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 05/31/2019] [Accepted: 06/22/2019] [Indexed: 12/16/2022]
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14
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Zhang C, Zhang H, Xu K, Yang H, Liu C, Yu T, Chen N, Li K. Impaired prefrontal cortex-thalamus pathway in intractable temporal lobe epilepsy with aberrant executive control function: MRI evidence. Clin Neurophysiol 2019; 130:484-490. [DOI: 10.1016/j.clinph.2018.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 11/19/2018] [Accepted: 12/16/2018] [Indexed: 01/03/2023]
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15
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Hwang G, Dabbs K, Conant L, Nair VA, Mathis J, Almane DN, Nencka A, Birn R, Humphries C, Raghavan M, DeYoe EA, Struck AF, Maganti R, Binder JR, Meyerand E, Prabhakaran V, Hermann B. Cognitive slowing and its underlying neurobiology in temporal lobe epilepsy. Cortex 2019; 117:41-52. [PMID: 30927560 DOI: 10.1016/j.cortex.2019.02.022] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 12/06/2018] [Accepted: 02/23/2019] [Indexed: 11/17/2022]
Abstract
Cognitive slowing is a known but comparatively under-investigated neuropsychological complication of the epilepsies in relation to other known cognitive comorbidities such as memory, executive function and language. Here we focus on a novel metric of processing speed, characterize its relative salience compared to other cognitive difficulties in epilepsy, and explore its underlying neurobiological correlates. Research participants included 55 patients with temporal lobe epilepsy (TLE) and 58 healthy controls from the Epilepsy Connectome Project (ECP) who were administered a battery of tests yielding 14 neuropsychological measures, including selected tests from the NIH Toolbox-Cognitive Battery, and underwent 3T MRI and resting state fMRI. TLE patients exhibited a pattern of generalized cognitive impairment with very few lateralized abnormalities. Using the neuropsychological measures, machine learning (Support Vector Machine binary classification model) classified the TLE and control groups with 74% accuracy with processing speed (NIH Toolbox Pattern Comparison Processing Speed Test) the best predictor. In TLE, slower processing speed was associated predominantly with decreased local gyrification in regions including the rostral and caudal middle frontal gyrus, inferior precentral cortex, insula, inferior parietal cortex (angular and supramarginal gyri), lateral occipital cortex, rostral anterior cingulate, and medial orbital frontal regions, as well as three small regions of the temporal lobe. Slower processing speed was also associated with decreased connectivity between the primary visual cortices in both hemispheres and the left supplementary motor area, as well as between the right parieto-occipital sulcus and right middle insular area. Overall, slowed processing speed is an important cognitive comorbidity of TLE associated with altered brain structure and connectivity.
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Affiliation(s)
- Gyujoon Hwang
- Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Kevin Dabbs
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Lisa Conant
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Veena A Nair
- Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Jed Mathis
- Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Dace N Almane
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Andrew Nencka
- Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Rasmus Birn
- Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Manoj Raghavan
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Edgar A DeYoe
- Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Aaron F Struck
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Rama Maganti
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Elizabeth Meyerand
- Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Radiology, University of Wisconsin-Madison, Madison, WI, USA; Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Vivek Prabhakaran
- Medical Physics, University of Wisconsin-Madison, Madison, WI, USA; Radiology, University of Wisconsin-Madison, Madison, WI, USA; Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Bruce Hermann
- Neurology, University of Wisconsin-Madison, Madison, WI, USA.
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16
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Abnormal neurite density and orientation dispersion in unilateral temporal lobe epilepsy detected by advanced diffusion imaging. NEUROIMAGE-CLINICAL 2018; 20:772-782. [PMID: 30268026 PMCID: PMC6169249 DOI: 10.1016/j.nicl.2018.09.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 09/12/2018] [Accepted: 09/20/2018] [Indexed: 01/09/2023]
Abstract
Background Despite recent advances in diffusion MRI (dMRI), there is still limited information on neurite orientation dispersion and density imaging (NODDI) in temporal lobe epilepsy (TLE). This study aimed to demonstrate neurite density and dispersion in TLE with and without hippocampal sclerosis (HS) using whole-brain voxel-wise analyses. Material and methods We recruited 33 patients with unilateral TLE (16 left, 17 right), including 14 patients with HS (TLE-HS) and 19 MRI-negative 18F-fluorodeoxyglucose positron emission tomography (FDG-PET)-positive patients (MRI-/PET+ TLE). The NODDI toolbox calculated the intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Conventional dMRI metrics, that is, fractional anisotropy (FA) and mean diffusivity (MD), were also estimated. After spatial normalization, all dMRI parameters (ICVF, ODI, FA, and MD) of the patients were compared with those of age- and sex-matched healthy controls using Statistical Parametric Mapping 12 (SPM12). As a complementary analysis, we added an atlas-based region of interest (ROI) analysis of relevant white matter tracts using tract-based spatial statistics. Results We found decreased neurite density mainly in the ipsilateral temporal areas of both right and left TLE, with the right TLE showing more severe and widespread abnormalities. In addition, etiology-specific analyses revealed a localized reduction in ICVF (i.e., neurite density) in the ipsilateral temporal pole in MRI-/PET+ TLE, whereas TLE-HS presented greater abnormalities, including FA and MD, in addition to a localized hippocampal reduction in ODI. The results of the atlas-based ROI analysis were consistent with the results of the SPM12 analysis. Conclusion NODDI may provide clinically relevant information as well as novel insights into the field of TLE. Particularly, in MRI-/PET+ TLE, neurite density imaging may have higher sensitivity than other dMRI parameters. The results may also contribute to better understanding of the pathophysiology of TLE with HS. We examined temporal lobe epilepsy (TLE) with or without hippocampal sclerosis (HS). Neurite orientation dispersion and density imaging (NODDI) was used. Ipsilateral reduction of neurite density was found in MRI-negative PET-positive TLE. More extensive abnormalities were presented in TLE with HS. NODDI may provide clinical relevance and novel insights into the field of TLE.
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17
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Reyes A, Paul BM, Marshall A, Chang YHA, Bahrami N, Kansal L, Iragui VJ, Tecoma ES, Gollan TH, McDonald CR. Does bilingualism increase brain or cognitive reserve in patients with temporal lobe epilepsy? Epilepsia 2018; 59:1037-1047. [PMID: 29658987 DOI: 10.1111/epi.14072] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2018] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Bilingual healthy adults have been shown to exhibit an advantage in executive functioning (EF) that is associated with microstructural changes in white matter (WM) networks. Patients with temporal lobe epilepsy (TLE) often show EF deficits that are associated with WM compromise. In this study, we investigate whether bilingualism can increase cognitive reserve and/or brain reserve in bilingual patients with TLE, mitigating EF impairment and WM compromise. METHODS Diffusion tensor imaging was obtained in 19 bilingual and 26 monolingual patients with TLE, 12 bilingual healthy controls (HC), and 21 monolingual HC. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated for the uncinate fasciculus (Unc) and cingulum (Cing), superior frontostriatal tract (SFS), and inferior frontostriatal tract (IFS). Measures of EF included Trail Making Test-B (TMT-B) and Delis-Kaplan Executive Function System Color-Word Inhibition/Switching. Analyses of covariance were conducted to compare FA and MD of the Unc, Cing, SFS, and IFS and EF performance across groups. RESULTS In bilingual patients, FA was lower in the ipsilateral Cing and Unc compared to all other groups. For both patient groups, MD of the ipsilateral Unc was higher relative to HC. Despite more pronounced reductions in WM integrity, bilingual patients performed similarly to monolingual TLE and both HC groups on EF measures. By contrast, monolingual patients performed worse than HC on TMT-B. In addition, differences in group means between bilingual and monolingual patients on TMT-B approached significance when controlling for the extent of WM damage (P = .071; d = 0.62), suggesting a tendency toward higher performance for bilingual patients. SIGNIFICANCE Despite poorer integrity of regional frontal lobe WM, bilingual patients performed similarly to monolingual patients and HC on EF measures. These findings align with studies suggesting that bilingualism may provide a protective factor for individuals with neurological disease, potentially through reorganization of EF networks that promote greater cognitive reserve.
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Affiliation(s)
- Anny Reyes
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Brianna M Paul
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.,University of California, San Francisco Comprehensive Epilepsy Center, San Francisco, CA, USA
| | - Anisa Marshall
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Yu-Hsuan A Chang
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Naeim Bahrami
- Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA
| | - Leena Kansal
- University of California, San Diego Comprehensive Epilepsy Center, San Diego, CA, USA
| | - Vicente J Iragui
- University of California, San Diego Comprehensive Epilepsy Center, San Diego, CA, USA
| | - Evelyn S Tecoma
- University of California, San Diego Comprehensive Epilepsy Center, San Diego, CA, USA
| | - Tamar H Gollan
- Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
| | - Carrie R McDonald
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.,Center for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA.,Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
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