Early and late age of seizure onset have a differential impact on brain resting-state organization in temporal lobe epilepsy.
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ABSTRACT:
SUBMITTER: Doucet GE
PROVIDER: S-EPMC4291512 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We studied with functional magnetic resonance imaging (fMRI) differences in resting-state networks between patients with mesial temporal lobe epilepsy (MTLE) and healthy subjects. To avoid any a priori hypothesis, we use a data-driven analysis assessing differences between groups independently of structures involved. Shared and specific independent component analysis (SSICA) is an exploratory method based on independent component analysis, which performs between-group network comparison. It extracts and classifies components (networks) in those common between groups and those specific to one group. Resting fMRI data were collected from 10 healthy subjects and 10 MTLE patients. SSICA was applied multiple times with altered initializations and different numbers of specific components. This resulted in many components specific to patients and to controls. Spatial clustering identified the reliable resting-state networks among all specific components in each group. For each reliable specific network, power spectrum analysis was performed on reconstructed time-series to estimate connectivity in each group and differences between groups. Two reliable networks, corresponding to statistically significant clusters robustly detected with clustering were labeled as specific to MTLE and one as specific to the control group. The most reliable MTLE network included hippocampus and amygdala bilaterally. The other MTLE network included the postcentral gyri and temporal poles. The control-specific network included bilateral precuneus, anterior cingulate, thalamus, and parahippocampal gyrus. Results indicated that the two MTLE networks show increased connectivity in patients, whereas the control-specific network shows decreased connectivity in patients. Our findings complement results from seed-based connectivity analysis (1). The pattern of changes in connectivity between mesial temporal lobe structures and other areas may help us understand the cognitive impairments often reported in patients with MTLE.
| S-EPMC4095676 | biostudies-literature
Project description:IntroductionIt is now understood that in focal epilepsy, impacted neural regions are not limited to the epileptogenic zone. As such, further investigation into the underlying functional connectivity (FC) patterns in those enduring Temporal Lobe Epilepsy (TLE) with Mesial Temporal Sclerosis (MTS) is imperative to understanding the intricacies of the disease.MethodsThe rsfMRIs of 17 healthy participants, 10 left-sided TLE-MTS patients with a pre-operative history of focal impaired awareness seizures (FIA), and 13 left-sided TLE-MTS patients with a pre-operative history of focal aware seizures (FA) were compared to determine the existence of distinct FC patterns with respect to seizure types. Similarly, the rsfMRIs of the above-mentioned healthy participants, 16 left-sided TLE-MTS individuals who were seizure-free (SF) 12 months postoperatively, and 16 left-sided TLE-MTS persons without seizure freedom (nSF) were interrogated. The ROI-to-ROI connectivity analysis included a total of 175 regions of interest (ROIs) and accounted for both age and duration of epileptic activity. Significant correlations were determined via two-sample t-tests and Bonferroni correction (α = 0.05).ResultsComparisons of FA and FIA groups depicted significant correlations between the contralateral anterior cingulate gyrus, subgenual region, and the contralateral cerebellum, lobule III (p-value = 2.26e-4, mean z-score = -0.05 ± 0.28, T = -4.23). Comparisons of SF with nSF depicted two significantly paired-ROIs; the contralateral amygdala and the contralateral precuneus (p-value = 2.9e-5, mean z-score = -0.12 ± 0.19, T = 4.98), as well as the contralateral locus coeruleus and the ipsilateral intralaminar nucleus (p-value= 1.37e-4, mean z-score = 0.06 ± 0.17, T = -4.41).SignificanceFC analysis proves to be a lucrative modality for exploring unique signatures with respect to seizure types and postoperative outcomes. By furthering our understanding of the differences between epileptic phenotypes, we can achieve improvement in future treatment modalities not limited to targeting advancements.
| S-EPMC10665565 | biostudies-literature
Project description:Neuroticism, a core personality trait characterized by a tendency towards experiencing negative affect, has been reported to be higher in people with temporal lobe epilepsy (TLE) compared with healthy individuals. Neuroticism is a known predictor of depression and anxiety, which also occur more frequently in people with TLE. The purpose of this study was to identify abnormalities in whole-brain resting-state functional connectivity in relation to neuroticism in people with TLE and to determine the degree of unique versus shared patterns of abnormal connectivity in relation to elevated symptoms of depression and anxiety. Ninety-three individuals with TLE (55 females) and 40 healthy controls (18 females) from the Epilepsy Connectome Project (ECP) completed measures of neuroticism, depression, and anxiety, which were all significantly higher in people with TLE compared with controls. Resting-state functional connectivity was compared between controls and groups with TLE with high and low neuroticism using analysis of variance (ANOVA) and t-test. In secondary analyses, the same analytics were performed using measures of depression and anxiety and the unique variance in resting-state connectivity associated with neuroticism independent of symptoms of depression and anxiety identified. Increased neuroticism was significantly associated with hyposynchrony between the right hippocampus and Brodmann area (BA) 9 (region of prefrontal cortex (PFC)) (p < 0.005), representing a unique relationship independent of symptoms of depression and anxiety. Hyposynchrony of connection between the right hippocampus and BA47 (anterior frontal operculum) was associated with high neuroticism and with higher depression and anxiety scores (p < 0.05), making it a shared abnormal connection for the three measures. In conclusion, increased neuroticism exhibits both unique and shared patterns of abnormal functional connectivity with depression and anxiety symptoms between regions of the mesial temporal and frontal lobe.
| S-EPMC7483612 | biostudies-literature
Project description:PURPOSE:Temporal lobe epilepsy (TLE) affects resting state brain networks in adults. This study aims to correlate resting state functional MRI (rsMRI) signal latency in pediatric TLE patients with their laterality. METHODS:From 2006 to 2016, 26 surgical TLE patients (12 left, 14 right) with a mean age of 10.7 years (range 0.9-18) were prospectively studied. Preoperative rsMRI was obtained in patients with concordant lateralizing structural MRI, EEG, and PET studies. Standard preprocessing techniques and seed-based rsMRI analyses were performed. Additionally, the latency in rsMRI signal between each 6 mm voxel sampled was examined, compared to the global mean signal, and projected onto standard atlas space for individuals and the cohort. RESULTS:All but one of the 26 patients improved seizure frequency postoperatively with a mean follow-up of 2.9 years (range 0-7.7), with 21 patients seizure-free. When grouped for epileptogenic laterality, the latency map qualitatively demonstrated that the right TLE patients had a relatively early signal pattern, whereas the left TLE patients had a relatively late signal pattern compared to the global mean signal in the right temporal lobe. Quantitatively, the two groups had significantly different signal latency clusters in the bilateral temporal lobes (p?<?0.001). CONCLUSION:There are functional MR signal latency changes in medical refractory pediatric TLE patients. Qualitatively, signal latency in the right temporal lobe precedes the mean signal in right TLE patients and is delayed in left TLE patients. With larger confirmatory studies, preoperative rsMRI latency analysis may offer an inexpensive, noninvasive adjunct modality to lateralize pediatric TLE.
| S-EPMC5897166 | biostudies-literature
Project description:ObjectiveLocalization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients.MethodsA total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions.ResultsThe 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, and the resting state networks that colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with postsurgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel Class >I compared to Engel Class I.SignificanceNoninvasive techniques capable of localizing the seizure onset zone could improve presurgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.
| S-EPMC9177812 | biostudies-literature
Project description:The purpose of the present study was to identify abnormal areas of regional synchronization in patients with mesial temporal lobe epilepsy and hippocampus sclerosis (mTLE-HS) compared to healthy controls, by applying a relatively novel method, the Regional Homogeneity (ReHo) method to resting state fMRI (RS-fMRI) data.Eyes closed RS-fMRI data were acquired from 10 mTLE-HS patients (four right-side, six left-side) and 15 age- and gender-matched healthy subjects, and were analyzed by using ReHo. For group analysis, four right-side MTLE-HS patients' functional images were flipped, in order to make a homogeneous left MTLE-HS group (10 cases) and increase the sample size.Compared to the healthy control group, patients showed significantly increased ReHo in ipsilateral parahippocampal gyrus, midbrain, insula, corpus callosum, bilateral sensorimotor cortex, and frontoparietal subcortical structures, whereas decreased ReHo was observed mainly in default mode network (DMN) (including precuneus and posterior cingulate gyrus, bilateral inferior lateral parietal, and mesial prefrontal cortex) and cerebellum in patients relative to the control group.This study identified that ReHo pattern in mTLE-HS patients was altered compared to healthy controls. We consider decreased ReHo in DMN to be responsible for wide functional impairments in cognitive processes. We propose that the increased ReHo in specific regions may form a network that might be responsible for seizure genesis and propagation.
| S-EPMC4052837 | biostudies-literature
Project description:BackgroundTo date, no functional MRI (fMRI) studies have focused on brain entropy in right temporal lobe epilepsy (rTLE) patients. Here, we characterized brain entropy (BEN) alterations in patients with rTLE using resting-state functional MRI(rs-fMRI) and explored the relationship between BEN and alertness.MethodThirty-one rTLE patients and 33 controls underwent MRI scanning to investigate differences in BEN and resting-state functional connectivity (rs-FC) in regions of interest (ROIs) between patients and controls. Correlation analyses were performed to examine relationships between the BEN of each ROI and alertness reaction times (RTs) in rTLE patients.ResultsCompared with controls, the BEN of rTLE patients was significantly increased in the right middle temporal gyrus, inferior temporal gyrus, and other regions of the left hemisphere and significantly decreased in the right middle frontal gyrus and left supplementary motor area (p < .05). The rs-FCs between the ROIs (at p < .01, with the left superior parietal lobule and right precentral gyrus defined as ROI1 and ROI2, respectively) and the whole brain showed an increasing trend in rTLE patients. In addition, the BEN of ROI2 was associated with the intrinsic alertness and phasic alertness RTs of patients with rTLE.ConclusionsOur findings suggest that BEN is altered in patients with rTLE and that decreased BEN in the right precentral gyrus is positively related to intrinsic and phasic alertness; the abnormal FC in the brain regions with altered entropy suggests a reconstruction of brain functional connectivity. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to TLE.
| S-EPMC6851803 | biostudies-literature
Project description:Background/aimThe main purpose of this study is to evaluate the resting state hippocampal connectivity with language areas and to correlate them with laterality index calculations on single subject basis, hence to present hippocampal lateralization for language with rs-fMRI.Materials and methodsTask based and rs-fMRI data were gathered from a total of 45 subjects in 3T scanner. BrainVoyager QX, SPM, and CONN softwares were used for data analysis. LI score of each subject was calculated and converted into normalized LI score (nLI). Intrahemispheric rs-connectivity analysis was performed between hippocampus and Broca’s regions on both sides. Correlation between these variables was measured with SPSS software.ResultsRight-TLE patients were found to have highest whereas left-TLE group were found to have lowest mean LI scores. Regarding hippocampal-lingual networks; left intrahemispheric connectivity values showed strong positive correlation with nLI values in left, right-TLE patients and healthy controls (P = 0.035, 0.014, 0.047). There were no significant correlation between right intrahemispheric connectivity values and nLI scores in all groups.ConclusionsThis study seems to depict the existence of resting state hippocampal-lingual functional network which correlates well with lateralization of language function in the left hemisphere in both temporal lobe epilepsy patients and healthy controls.
| S-EPMC7491274 | biostudies-literature
Project description:We studied the graph topological properties of brain networks derived from resting-state functional magnetic resonance imaging in a kainic acid induced model of temporal lobe epilepsy (TLE) in rats. Functional connectivity was determined by temporal correlation of the resting-state Blood Oxygen Level Dependent (BOLD) signals between two brain regions during 1.5% and 2% isoflurane, and analyzed as networks in epileptic and control rats. Graph theoretical analysis revealed a significant increase in functional connectivity between brain areas in epileptic than control rats, and the connected brain areas could be categorized as a limbic network and a default mode network (DMN). The limbic network includes the hippocampus, amygdala, piriform cortex, nucleus accumbens, and mediodorsal thalamus, whereas DMN involves the medial prefrontal cortex, anterior and posterior cingulate cortex, auditory and temporal association cortex, and posterior parietal cortex. The TLE model manifested a higher clustering coefficient, increased global and local efficiency, and increased small-worldness as compared to controls, despite having a similar characteristic path length. These results suggest extensive disruptions in the functional brain networks, which may be the basis of altered cognitive, emotional and psychiatric symptoms in TLE.
| S-EPMC5133653 | biostudies-literature
Project description:There are no functional imaging based biomarkers for pharmacological treatment response in temporal lobe epilepsy (TLE). In this study, we investigated whether there is an association between resting state functional brain connectivity (RsFC) and seizure control in TLE. We screened a large database containing resting state functional magnetic resonance imaging (Rs-fMRI) data from 286 epilepsy patients. Patient medical records were screened for seizure characterization, EEG reports for lateralization and location of seizure foci to establish uniformity of seizure localization within patient groups. Rs-fMRI data from patients with well-controlled left TLE, patients with treatment-resistant left TLE, and healthy controls were analyzed. Healthy controls and cTLE showed similar functional connectivity patterns, whereas trTLE exhibited a significant bilateral decrease in thalamo-hippocampal functional connectivity. This work is the first to demonstrate differences in neural network connectivity between well-controlled and treatment-resistant TLE. These differences are spatially highly focused and suggest sites for the etiology and possibly treatment of TLE. Altered thalamo-hippocampal RsFC thus is a potential new biomarker for TLE treatment resistance.
| S-EPMC6483378 | biostudies-literature