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Park KM, Park S, Hur YJ. Brain network reconstruction of abnormal functional connectivity in Lennox-Gastaut syndrome according to drug responsiveness: A retrospective study. Epilepsy Res 2024; 200:107312. [PMID: 38309034 DOI: 10.1016/j.eplepsyres.2024.107312] [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: 11/30/2023] [Revised: 01/08/2024] [Accepted: 01/25/2024] [Indexed: 02/05/2024]
Abstract
OBJECTIVE Functional network effects of resective or palliative epilepsy surgery in Lennox-Gastaut syndrome (LGS) patients are different according to the seizure outcome. This study aimed to clarify whether the response to antiseizure medications (ASM) can affect to alteration of brain network connectivity. METHODS In this retrospective study, 37 patients with LGS who underwent 1st electroencephalography (EEG) and 40 healthy controls were enrolled. Among them, 24 LGS patients had follow-up EEG data and were classified as drug responders and non-responders according to the ASM response. Graphical theoretical analysis was used to assess functional connectivity using resting-state EEG. RESULTS The 1st EEG showed a decreased radius in patients with LGS compared with that in healthy controls (3.987 vs. 4.279, P = 0.003). Follow-up EEG data of patients with LGS revealed significant differences in functional connectivity depending on the ASM response. On follow-up EEG, non-responders (n = 11) demonstrated significant increases in global network parameters, whereas responders (n = 13) showed no significant difference in functional connectivity compared with healthy controls. CONCLUSIONS The functional connectivity patterns in patients with LGS differed from those in healthy controls. Functional connectivity in drug-responsive patients with LGS tended to preserve the network of brain connections in a pattern similar to that in healthy controls, whereas non-responders showed more disrupted functional connectivity.
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Affiliation(s)
- Kang Min Park
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Pusan, Republic of Korea
| | - Soyoung Park
- Department of Pediatrics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Republic of Korea; Yonsei University College of Medicine, Graduate School, Seoul, Republic of Korea
| | - Yun Jung Hur
- Department of Pediatrics, Haeundae Paik Hospital, Inje University College of Medicine, Pusan, Republic of Korea.
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Duma GM, Pellegrino G, Rabuffo G, Danieli A, Antoniazzi L, Vitale V, Scotto Opipari R, Bonanni P, Sorrentino P. Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study. Brain Commun 2023; 6:fcad348. [PMID: 38162897 PMCID: PMC10754317 DOI: 10.1093/braincomms/fcad348] [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: 07/24/2023] [Revised: 11/11/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Giovanni Pellegrino
- Epilepsy Program, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada
| | - Giovanni Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Lisa Antoniazzi
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza 36100, Italy
| | | | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Conegliano 31015, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille 13005, France
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
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Duma GM, Danieli A, Mento G, Vitale V, Opipari RS, Jirsa V, Bonanni P, Sorrentino P. Altered spreading of neuronal avalanches in temporal lobe epilepsy relates to cognitive performance: A resting-state hdEEG study. Epilepsia 2023; 64:1278-1288. [PMID: 36799098 DOI: 10.1111/epi.17551] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 02/18/2023]
Abstract
OBJECTIVE Large aperiodic bursts of activations named neuronal avalanches have been used to characterize whole-brain activity, as their presence typically relates to optimal dynamics. Epilepsy is characterized by alterations in large-scale brain network dynamics. Here we exploited neuronal avalanches to characterize differences in electroencephalography (EEG) basal activity, free from seizures and/or interictal spikes, between patients with temporal lobe epilepsy (TLE) and matched controls. METHOD We defined neuronal avalanches as starting when the z-scored source-reconstructed EEG signals crossed a specific threshold in any region and ending when all regions returned to baseline. This technique avoids data manipulation or assumptions of signal stationarity, focusing on the aperiodic, scale-free components of the signals. We computed individual avalanche transition matrices to track the probability of avalanche spreading across any two regions, compared them between patients and controls, and related them to memory performance in patients. RESULTS We observed a robust topography of significant edges clustering in regions functionally and structurally relevant for the TLE, such as the entorhinal cortex, the inferior parietal and fusiform area, the inferior temporal gyrus, and the anterior cingulate cortex. We detected a significant correlation between the centrality of the entorhinal cortex in the transition matrix and the long-term memory performance (delay recall Rey-Osterrieth Complex Figure Test). SIGNIFICANCE Our results show that the propagation patterns of large-scale neuronal avalanches are altered in TLE during the resting state, suggesting a potential diagnostic application in epilepsy. Furthermore, the relationship between specific patterns of propagation and memory performance support the neurophysiological relevance of neuronal avalanches.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Giovanni Mento
- Department of General Psychology, University of Padova, Padova, Italy.,Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza, Italy
| | | | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
| | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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Ren Z, Zhao Y, Han X, Yue M, Wang B, Zhao Z, Wen B, Hong Y, Wang Q, Hong Y, Zhao T, Wang N, Zhao P. An objective model for diagnosing comorbid cognitive impairment in patients with epilepsy based on the clinical-EEG functional connectivity features. Front Neurosci 2023; 16:1060814. [PMID: 36711136 PMCID: PMC9878185 DOI: 10.3389/fnins.2022.1060814] [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: 10/15/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023] Open
Abstract
Objective Cognitive impairment (CI) is a common disorder in patients with epilepsy (PWEs). Objective assessment method for diagnosing CI in PWEs would be beneficial in reality. This study proposed to construct a diagnostic model for CI in PWEs using the clinical and the phase locking value (PLV) functional connectivity features of the electroencephalogram (EEG). Methods PWEs who met the inclusion and exclusion criteria were divided into a cognitively normal (CON) group (n = 55) and a CI group (n = 76). The 23 clinical features and 684 PLV EEG features at the time of patient visit were screened and ranked using the Fisher score. Adaptive Boosting (AdaBoost) and Gradient Boosting Decision Tree (GBDT) were used as algorithms to construct diagnostic models of CI in PWEs either with pure clinical features, pure PLV EEG features, or combined clinical and PLV EEG features. The performance of these models was assessed using a five-fold cross-validation method. Results GBDT-built model with combined clinical and PLV EEG features performed the best with accuracy, precision, recall, F1-score, and an area under the curve (AUC) of 90.11, 93.40, 89.50, 91.39, and 0.95%. The top 5 features found to influence the model performance based on the Fisher scores were the magnetic resonance imaging (MRI) findings of the head for abnormalities, educational attainment, PLV EEG in the beta (β)-band C3-F4, seizure frequency, and PLV EEG in theta (θ)-band Fp1-Fz. A total of 12 of the top 5% of features exhibited statistically different PLV EEG features, while eight of which were PLV EEG features in the θ band. Conclusion The model constructed from the combined clinical and PLV EEG features could effectively identify CI in PWEs and possess the potential as a useful objective evaluation method. The PLV EEG in the θ band could be a potential biomarker for the complementary diagnosis of CI comorbid with epilepsy.
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Affiliation(s)
- Zhe Ren
- Department of Neurology, Zhengzhou University People’s Hospital, Zhengzhou, Henan, China
| | - Yibo Zhao
- Department of Neurology, Zhengzhou University People’s Hospital, Zhengzhou, Henan, China
| | - Xiong Han
- Department of Neurology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, China,*Correspondence: Xiong Han,
| | - Mengyan Yue
- Department of Rehabilitation, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China
| | - Bin Wang
- Department of Neurology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, Henan, China
| | - Bin Wen
- School of Life Sciences and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Yang Hong
- Department of Neurology, People’s Hospital of Henan University, Zhengzhou, Henan, China
| | - Qi Wang
- Department of Neurology, Zhengzhou University People’s Hospital, Zhengzhou, Henan, China
| | - Yingxing Hong
- Department of Neurology, People’s Hospital of Henan University, Zhengzhou, Henan, China
| | - Ting Zhao
- Department of Neurology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Na Wang
- Department of Neurology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Pan Zhao
- Department of Neurology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, China
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