Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning

2019 ◽  
Vol 193 ◽  
pp. 45-57 ◽  
Author(s):  
B.C. Munsell ◽  
G. Wu ◽  
J. Fridriksson ◽  
K. Thayer ◽  
N. Mofrad ◽  
...  
Author(s):  
B.C. Munsell ◽  
G. Wu ◽  
S. Keller ◽  
J. Fridriksson ◽  
B. Weber ◽  
...  

2018 ◽  
Vol 86 ◽  
pp. 58-65 ◽  
Author(s):  
Brandon Frank ◽  
Landon Hurley ◽  
Travis M. Scott ◽  
Pat Olsen ◽  
Patricia Dugan ◽  
...  

2016 ◽  
Vol 15 (1) ◽  
pp. 121-129 ◽  
Author(s):  
Kouhei KAMIYA ◽  
Shiori AMEMIYA ◽  
Yuichi SUZUKI ◽  
Naoto KUNII ◽  
Kensuke KAWAI ◽  
...  

2017 ◽  
Vol 7 (10) ◽  
pp. e00801 ◽  
Author(s):  
John Del Gaizo ◽  
Neda Mofrad ◽  
Jens H. Jensen ◽  
David Clark ◽  
Russell Glenn ◽  
...  

2019 ◽  
Author(s):  
Kunal Gupta ◽  
Eric Schnell

AbstractMouse models of mesial temporal lobe epilepsy recapitulate aspects of human epilepsy, which is characterized by neuronal network remodeling in the hippocampal dentate gyrus. Observational studies suggest that this remodeling is associated with altered Wnt pathway signaling, although this has not been experimentally examined. We used the well-characterized mouse intrahippocampal kainate model of temporal lobe epilepsy to examine associations between post-seizure hippocampal neurogenesis and altered Wnt signaling. Tissue was analyzed using immunohistochemistry and confocal microscopy, and transcriptome analysis was performed on RNA extracted from anatomically micro-dissected dentate gyri. Seizures increased neurogenesis and dendritic arborization of newborn hippocampal dentate granule cells in peri-ictal regions, and decreased neurogenesis in the ictal zone, 2-weeks after kainate injection. Interestingly, administration of the novel canonical Wnt pathway inhibitor XAV939 daily for 2-weeks after kainate injection further increased dendritic arborization in peri-ictal regions after seizure, without an effect on baseline neurogenesis in control animals. Transcriptome analysis of dentate gyri demonstrated significant canonical Wnt gene dysregulation in kainate-injected mice across all regions for Wnt3, 5a and 9a. Intriguingly, certain Wnt genes demonstrated differential patterns of dysregulation between the ictal and peri-ictal zones, most notably Wnt5B, 7B and DKK-1. Together, these results demonstrate regional variation in Wnt pathway dysregulation in the early post-ictal period, and surprisingly, suggest that some Wnt-mediated effects might actually temper aberrant neurogenesis after seizures. The Wnt pathway may therefore provide suitable targets for novel therapies that prevent network remodeling and the development of epileptic foci in high-risk patients.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaoxuan Fu ◽  
Youhua Wang ◽  
Abdelkader Nasreddine Belkacem ◽  
Qirui Zhang ◽  
Chong Xie ◽  
...  

The bottleneck associated with the validation of the parameters of the entropy model has limited the application of this model to modern functional imaging technologies such as the resting-state functional magnetic resonance imaging (rfMRI). In this study, an optimization algorithm that could choose the parameters of the multiscale entropy (MSE) model was developed, while the optimized effectiveness for localizing the epileptogenic hemisphere was validated through the classification rate with a supervised machine learning method. The rfMRI data of 20 mesial temporal lobe epilepsy patients with positive indicators (the indicators of epileptogenic hemisphere in clinic) in the hippocampal formation on either left or right hemisphere (equally divided into two groups) on the structural MRI were collected and preprocessed. Then, three parameters in the MSE model were statistically optimized by both receiver operating characteristic (ROC) curve and the area under the ROC curve value in the sensitivity analysis, and the intergroup significance of optimized entropy values was utilized to confirm the biomarked brain areas sensitive to the epileptogenic hemisphere. Finally, the optimized entropy values of these biomarked brain areas were regarded as the feature vectors input for a support vector machine to classify the epileptogenic hemisphere, and the classification effectiveness was cross-validated. Nine biomarked brain areas were confirmed by the optimized entropy values, including medial superior frontal gyrus and superior parietal gyrus ( p  < .01). The mean classification accuracy was greater than 90%. It can be concluded that combination of the optimized MSE model with the machine learning model can accurately confirm the epileptogenic hemisphere by rfMRI. With the powerful information interaction capabilities of 5G communication, the epilepsy side-fixing algorithm that requires computing power can be integrated into a cloud platform. The demand side only needs to upload patient data to the service platform to realize the preoperative assessment of epilepsy.


2020 ◽  
Vol 11 ◽  
Author(s):  
Iman Beheshti ◽  
Daichi Sone ◽  
Norihide Maikusa ◽  
Yukio Kimura ◽  
Yoko Shigemoto ◽  
...  

Author(s):  
Karin Trimmel ◽  
Lorenzo Caciagli ◽  
Fenglai Xiao ◽  
Louis A. van Graan ◽  
Matthias J. Koepp ◽  
...  

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