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Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

ABSTRACT: Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

SUBMITTER: Fang P

PROVIDER: S-EPMC4375640 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

Fang Peng P An Jie J Zeng Ling-Li LL Shen Hui H Chen Fanglin F Wang Wensheng W Qiu Shijun S Hu Dewen D

NeuroImage. Clinical 20150107

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for e ...[more]

PMID: 25844312

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Project description:In mesial temporal lobe epilepsy (MTLE) the epileptogenic area is confined to the mesial temporal lobe, but other cortical and subcortical areas are also affected and cognitive and psychiatric impairments are usually documented. Functional connectivity methods are based on the correlation of the blood oxygen level dependent (BOLD) signal between brain regions, which exhibit consistent and reproducible functional networks from resting state data. The aim of this study is to compare functional connectivity of patients with MTLE during the interictal period with healthy subjects. We hypothesize that patients show reduced functional connectivity compared to controls, the interest being to determine which regions show this reduction.We selected electroencephalography-functional magnetic resonance imaging (EEG-fMRI) resting state data without EEG spikes from 16 patients with right and 7 patients with left MTLE. EEG-fMRI resting state data of 23 healthy subjects matched for age, sex, and manual preference were selected as controls. Four volumes of interest in the left and right amygdalae and hippocampi (LA, RA, LH, and RH) were manually segmented in the anatomic MRI of each subject. The averaged BOLD time course within each volume of interest was used to detect brain regions with BOLD signal correlated with it. Group differences between patients and controls were estimated.In patients with right MTLE, group difference functional connectivity maps (RMTLE - controls) showed for RA and RH decreased connectivity with the brain areas of the default mode network (DMN), the ventromesial limbic prefrontal regions, and contralateral mesial temporal structures; and for LA and LH, decreased connectivity with DMN and contralateral hippocampus. Additional decreased connectivity was found between LA and pons and between LH and ventromesial limbic prefrontal structures. In patients with left MTLE, functional connectivity maps (LMTLE - controls) showed for LA and LH decreased connectivity with DMN, contralateral hippocampus, and bilateral ventromesial limbic prefrontal regions; no change in connectivity was detected for RA; and for RH, there was decreased connectivity with DMN, bilateral ventromesial limbic prefrontal regions, and contralateral amygdala and hippocampus.In unilateral MTLE, amygdala and hippocampus on the affected and to a lesser extent on the healthy side are less connected, and are also less connected with the dopaminergic mesolimbic and the DMNs. Changes in functional connectivity between mesial temporal lobe structures and these structures may explain cognitive and psychiatric impairments often found in patients with MTLE.

Project description:Mesial temporal lobe epilepsy is the most common type of focal epilepsy and in its course often becomes refractory to anticonvulsant pharmacotherapy. A resection of the mesial temporal lobe structures is a promising option in these cases. However, approximately 30% of all patients remain with persistent seizures after surgery. In other words, reliable criteria for patients' outcome prediction are absent. To address this limitation, we investigated pre-surgical brain morphology of patients with unilateral left mesial temporal lobe epilepsy who underwent a selective amygdalohippocampectomy. Using support vector classification, we aimed to predict the post-surgical seizure outcome of each patient based on the pre-surgical T1-weighted structural brain images. Due to morphological gender differences and the evidence that men and women differ in onset, prevalence and symptomology in most neurological diseases, we investigated male and female patients separately. Thus, we benefitted from the capability to validate the reliability of our method in two independent samples. Notably, we were able to accurately predict the individual patients' outcome in the male (94% balanced accuracy) as well as in the female (96% balanced accuracy) group. In the male cohort relatively larger white matter volumes in the favorable as compared to the non-favorable outcome group were identified bilaterally in the cingulum bundle, fronto-occipital fasciculus and both caudate nuclei, whereas the left inferior longitudinal fasciculus showed relatively larger white matter volume in the non-favorable group. While relatively larger white matter volumes in the female cohort in the left inferior and right middle longitudinal fasciculus were associated with the favorable outcome, relatively larger white matter volumes in the non-favorable outcome group were identified bilaterally in the superior longitudinal fasciculi I and II. Here, we observed a clear lateralization and distinction of structures involved in the classification in men as compared to women with men exhibiting more alterations in the hemisphere contralateral to the seizure focus. In conclusion, individual post-surgical outcome predictions based on a single T1-weighted magnetic resonance image seem plausible and may thus support the routine pre-surgical workup of epilepsy patients.

Project description:Over the last decade, several methods for analysis of epileptiform signals in electroencephalography (EEG) have been proposed. These methods mainly use EEG signal features in either the time or the frequency domain to separate regular, interictal, and ictal brain activity. The aim of this work was to evaluate the feasibility of using functional connectivity (FC) based feature extraction methods for the analysis of epileptiform discharges in EEG signals. These signals were obtained from EEG-fMRI sessions of 10 patients with mesial temporal lobe epilepsy (MTLE) with unilateral hippocampal atrophy. The connectivity functions investigated were motif synchronization, imaginary coherence, and magnitude squared coherence in the alpha, beta, and gamma bands of the EEG. EEG signals were sectioned into 1-s epochs and classified according to (using neurologist markers): activity far from interictal epileptiform discharges (IED), activity immediately before an IED and, finally, mid-IED activity. Connectivity matrices for each epoch for each FC function were built, and graph theory was used to obtain the following metrics: strength, cluster coefficient, betweenness centrality, eigenvector centrality (both local and global), and global efficiency. The statistical distributions of these metrics were compared among the three classes, using ANOVA, for each FC function. We found significant differences in all global (p < 0.001) and local (p < 0.00002) graph metrics of the far class compared with before and mid for motif synchronization on the beta band; local betweenness centrality also pointed to a degree of lateralization on the frontotemporal structures. This analysis demonstrates the potential of FC measures, computed using motif synchronization, for the characterization of epileptiform activity of MTLE patients. This methodology may be helpful in the analysis of EEG-fMRI data applied to epileptic foci localization. Nonetheless, the methods must be tested with a larger sample and with other epileptic phenotypes.

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Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

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Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

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