A novel approach for extracting functional brain networks involved in mesial temporal lobe epilepsy based on self organizing maps

Dynamic Functional Connectivity Analysis Using Network-Based Brain State Identification, Application on Temporal Lobe Epilepsy

Epilepsy is a brain network disorder caused by discharges of interconnected groups of neurons and resulting brain dysfunction. The brain network can be characterized by intra- and inter-regional functional connectivity (FC). However, since the BOLD signal is inherently non-stationary, the FC is evidenced to be varying over time. Considering the dynamic characteristics of the functional network, we aimed to obtain dynamic brain states and their properties using network-based analyses for the comparison of healthy control and temporal lobe epilepsy (TLE) groups and also lateralization of TLE patients. We used dwelling time, transition time, and brain network connection in each state as the dynamic features for this purpose. Results showed a significant difference in dwelling time and transition time between the healthy control group and both left TLE and right TLE groups and also a significant difference in brain network connections between the left and right TLE groups.

Cortical thickness analysis in temporal lobe epilepsy using fully Bayesian spectral method in magnetic resonance imaging

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.

Multivariate statistical analysis of potentially toxic elements in the sediments of Quanzhou Bay, China: Spatial relationships, ecological toxicity and sources identification

In this paper, the spatial distribution, pollution degree, ecological toxicity and possible sources of seven potentially toxic elements (PTEs) collected from the surface sediments of Quanzhou Bay (QZB) were analyzed by obtaining concentration measurements. The results indicated that the areas with high Cu, Pb, Zn and Hg concentrations were mainly located in the Luoyang River estuary, while the areas with high contents of Cd and As appeared in the Luoyang River estuary area and in the southern part of QZB, respectively. The contamination indices showed that the Cd pollution degree was slight to serious, while other elements were slightly enriched. The calculation results of the potential ecological risk index (RI) and toxic risk index (TRI) indicated that Cd was the main element posing ecological risk among the PTEs of sediments in QZB, followed by Hg. Moreover, in approximately 30% of the surveyed sites, PTEs exhibited low toxicity to aquatic ecosystems. Finally, the self-organizing map (SOM) and positive matrix factorization (PMF) model were used to determine the PTEs sources. Natural sources, industrial emissions, and the combustion of fossil fuels were three main sources for PTEs in the surface sediments of QZB. This study provides a reference for assessing sediment pollution and managing marine pollution in QZB.