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Bu J, Yin H, Ren N, Zhu H, Xu H, Zhang R, Zhang S. Structural and functional changes in the default mode network in drug-resistant epilepsy. Epilepsy Behav 2024; 151:109593. [PMID: 38157823 DOI: 10.1016/j.yebeh.2023.109593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/25/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). METHODS A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. RESULTS The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. CONCLUSIONS TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE.
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Affiliation(s)
- Jinxin Bu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Hangxing Yin
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Nanxiao Ren
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
| | - Shugang Zhang
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
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Allebone J, Kanaan RA, Rayner G, Maller J, O'Brien TJ, Mullen SA, Cook M, Adams SJ, Vogrin S, Vaughan DN, Kwan P, Berkovic SF, D'Souza WJ, Jackson G, Velakoulis D, Wilson SJ. Neuropsychological function in psychosis of epilepsy. Epilepsy Res 2023; 196:107222. [PMID: 37717505 DOI: 10.1016/j.eplepsyres.2023.107222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/25/2023] [Accepted: 09/13/2023] [Indexed: 09/19/2023]
Abstract
OBJECTIVE The neuropsychological profile of patients with psychosis of epilepsy (POE) has received limited research attention. Recent neuroimaging work in POE has identified structural network pathology in the default mode network and the cognitive control network. This study examined the neuropsychological profile of POE focusing on cognitive domains subserved by these networks. METHODS Twelve consecutive patients with a diagnosis of POE were prospectively recruited from the Comprehensive Epilepsy Programmes at The Royal Melbourne, Austin and St Vincent's Hospitals, Melbourne, Australia between January 2015 and February 2017. They were compared to 12 matched patients with epilepsy but no psychosis and 42 healthy controls on standardised neuropsychological tests of memory and executive functioning in a case-control design. RESULTS Mean scores across all cognitive tasks showed a graded pattern of impairment, with the POE group showing the poorest performance, followed by the epilepsy without psychosis and the healthy control groups. This was associated with significant group-level differences on measures of working memory (p = < 0.01); immediate (p = < 0.01) and delayed verbal recall (p = < 0.01); visual memory (p < 0.001); and verbal fluency (p = 0.02). In particular, patients with POE performed significantly worse than the healthy control group on measures of both cognitive control (p = .005) and memory (p < .001), whereas the epilepsy without psychosis group showed only memory difficulties (delayed verbal recall) compared to healthy controls (p = .001). CONCLUSION People with POE show reduced performance in neuropsychological functions supported by the default mode and cognitive control networks, when compared to both healthy participants and people with epilepsy without psychosis.
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Affiliation(s)
- James Allebone
- Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia; The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Richard A Kanaan
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Department of Psychiatry, University of Melbourne, Austin Health, Melbourne, Australia.
| | - Genevieve Rayner
- Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia; The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Comprehensive Epilepsy Program, Austin Health, University of Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Jerome Maller
- ANU College of Health and Medicine, Australian National University, Canberra, Victoria, Australia; Monash Alfred Psychiatry Research Centre, The Alfred and Monash University, Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Terence J O'Brien
- Royal Melbourne Hospital, Melbourne, Victoria, Australia; Department of Neuroscience, Alfred Hospital, Monash University, Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Saul A Mullen
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Mark Cook
- Graeme Clark Institute, University of Melbourne, Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Sophia J Adams
- Royal Melbourne Hospital, Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Simon Vogrin
- St Vincent's Hospital, Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - David N Vaughan
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Comprehensive Epilepsy Program, Austin Health, University of Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Patrick Kwan
- Royal Melbourne Hospital, Melbourne, Victoria, Australia; Department of Neuroscience, Alfred Hospital, Monash University, Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Samuel F Berkovic
- Comprehensive Epilepsy Program, Austin Health, University of Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Wendyl J D'Souza
- Department of Medicine, St Vincent's Hospital, The University of Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Graeme Jackson
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Comprehensive Epilepsy Program, Austin Health, University of Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne, Victoria, Australia; Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne, Health, Melbourne, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
| | - Sarah J Wilson
- Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia; The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia; Comprehensive Epilepsy Program, Austin Health, University of Melbourne, Victoria, Australia; Department of Clinical Neuropsychology, Austin Health, Heidelberg, Victoria, Australia
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Sarbisheh I, Tapak L, Fallahi A, Fardmal J, Sadeghifar M, Nazemzadeh M, Mehvari Habibabadi J. Cortical thickness analysis in temporal lobe epilepsy using fully Bayesian spectral method in magnetic resonance imaging. BMC Med Imaging 2022; 22:222. [PMID: 36544100 PMCID: PMC9768883 DOI: 10.1186/s12880-022-00949-5] [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: 05/19/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Temporal lobe epilepsy (TLE) is the most common type of epilepsy associated with changes in the cerebral cortex throughout the brain. Magnetic resonance imaging (MRI) is widely used for detecting such anomalies; nevertheless, it produces spatially correlated data that cannot be considered by the usual statistical models. This study aimed to compare cortical thicknesses between patients with TLE and healthy controls by considering the spatial dependencies across different regions of the cerebral cortex in MRI. METHODS In this study, T1-weighted MRI was performed on 20 healthy controls and 33 TLE patients. Nineteen patients had a left TLE and 14 had a right TLE. Cortical thickness was measured for all individuals in 68 regions of the cerebral cortex based on images. Fully Bayesian spectral method was utilized to compare the cortical thickness of different brain regions between groups. Neural networks model was used to classify the patients using the identified regions. RESULTS For the left TLE patients, cortical thinning was observed in bilateral caudal anterior cingulate, lateral orbitofrontal (ipsilateral), the bilateral rostral anterior cingulate, frontal pole and temporal pole (ipsilateral), caudal middle frontal and rostral middle frontal (contralateral side). For the right TLE patients, cortical thinning was only observed in the entorhinal area (ipsilateral). The AUCs of the neural networks for classification of left and right TLE patients versus healthy controls were 0.939 and 1.000, respectively. CONCLUSION Alteration of cortical gray matter thickness was evidenced as common effect of epileptogenicity, as manifested by the patients in this study using the fully Bayesian spectral method by taking into account the complex structure of the data.
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Affiliation(s)
- Iman Sarbisheh
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Leili Tapak
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Alireza Fallahi
- grid.411705.60000 0001 0166 0922Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran University of Medical Sciences, Tehran, Iran ,grid.459564.f0000 0004 0482 9174Biomedical Engineering Department, Hamedan University of Technology, Hamedan, Iran
| | - Javad Fardmal
- grid.411950.80000 0004 0611 9280Department of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Majid Sadeghifar
- grid.411807.b0000 0000 9828 9578Department of Statistics, Faculty of Science, Bu-Ali Sina University, Hamadan, Iran
| | - MohammadReza Nazemzadeh
- grid.411705.60000 0001 0166 0922Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran University of Medical Sciences, Tehran, Iran ,grid.411705.60000 0001 0166 0922Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
| | - Jafar Mehvari Habibabadi
- grid.411036.10000 0001 1498 685XDepartment of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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Sone D. Neurobiological mechanisms of psychosis in epilepsy: Findings from neuroimaging studies. Front Psychiatry 2022; 13:1079295. [PMID: 36506456 PMCID: PMC9728542 DOI: 10.3389/fpsyt.2022.1079295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 11/08/2022] [Indexed: 11/24/2022] Open
Abstract
Despite the high prevalence and clinical importance of comorbid psychosis in epilepsy, its neurobiological mechanisms remain understudied. This narrative mini-review aims to provide an overview of recent updates in in vivo neuroimaging studies on psychosis in epilepsy, including structural and diffusion magnetic resonance imaging (MRI) and functional and molecular imaging, and to discuss future directions in this field. While the conventional morphological analysis of structural MRI has provided relatively inconsistent results, advanced methods, including brain network analysis, hippocampal subregion volumetry, and machine learning models, have recently provided novel findings. Diffusion MRI, for example, has revealed a reduction in white matter integrity mainly in the frontal and temporal lobes, as well as a disruption of brain white matter networks. Functional neuroimaging, such as perfusion single-photon emission computed tomography (SPECT) or fluorodeoxyglucose positron emission tomography (FDG-PET), often identifies hyperactivity in various brain regions. The current limitations of these more recent studies may include small and sometimes heterogeneous samples, insufficient control groups, the effects of psychoactive drugs, and the lack of longitudinal analysis. Further investigations are required to establish novel treatments and identify clinical diagnostic or disease-monitoring biomarkers in psychosis in epilepsy.
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Affiliation(s)
- Daichi Sone
- Department of Psychiatry, Jikei University School of Medicine, Tokyo, Japan
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