Resting-state functional connectivity predicts the strength of hemispheric lateralization for language processing in temporal lobe epilepsy and normals.
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ABSTRACT:
SUBMITTER: Doucet GE
PROVIDER: S-EPMC4295620 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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:Background and purposeAlthough most studies on epilepsy have focused on the epileptogenic zone, epilepsy is a system-level disease characterized by aberrant neuronal synchronization among groups of neurons. Increasingly, studies have indicated that mesial temporal lobe epilepsy may be a network-level disease; however, few investigations have examined resting-state functional connectivity of the entire brain, particularly in patients with mesial temporal lobe epilepsy and hippocampal sclerosis. This study primarily investigated whole-brain resting-state functional connectivity abnormality in patients with mesial temporal lobe epilepsy and right hippocampal sclerosis during the interictal period.Materials and methodsWe investigated resting-state functional connectivity of 21 patients with mesial temporal lobe epilepsy with right hippocampal sclerosis and 21 neurologically healthy controls. A multivariate pattern analysis was used to identify the functional connections that most clearly differentiated patients with mesial temporal lobe epilepsy with right hippocampal sclerosis from controls.ResultsDiscriminative analysis of functional connections indicated that the patients with mesial temporal lobe epilepsy with right hippocampal sclerosis exhibited decreased resting-state functional connectivity within the right hemisphere and increased resting-state functional connectivity within the left hemisphere. Resting-state network analysis suggested that the internetwork connections typically obey the hemispheric lateralization trend and most of the functional connections that disturb the lateralization trend are the intranetwork ones.ConclusionsThe current findings suggest that weakening of the resting-state functional connectivity associated with the right hemisphere appears to strengthen resting-state functional connectivity on the contralateral side, which may be related to the seizure-induced damage and underlying compensatory mechanisms. Resting-state network-based analysis indicated that the compensatory mechanism among different resting-state networks may disturb the hemispheric lateralization.
| S-EPMC7964696 | biostudies-literature
Project description:Language deficits following brain tumors should consider the dynamic interactions between different tumor growth kinetics and functional network reorganization. We measured the resting-state functional connectivity of 126 patients with left cerebral gliomas involving language network areas, including 77 patients with low-grade gliomas (LGG) and 49 patients with high-grade gliomas (HGG). Functional network mapping for language was performed by construction of a multivariate machine learning-based prediction model of individual aphasia quotient (AQ), a summary score that indicates overall severity of language impairment. We found that the AQ scores for HGG patients were significantly lower than those of LGG patients. The prediction accuracy of HGG patients (R2 = 0.27, permutation P = 0.007) was much higher than that of LGG patients (R2 = 0.09, permutation P = 0.032). The rsFC regions predictive of LGG's AQ involved the bilateral frontal, temporal, and parietal lobes, subcortical regions, and bilateral cerebro-cerebellar connections, mainly in regions belonging to the canonical language network. The functional network of language processing for HGG patients showed strong dependence on connections of the left cerebro-cerebellar connections, limbic system, and the temporal, occipital, and prefrontal lobes. Together, our findings suggested that individual language processing of glioma patients links large-scale, bilateral, cortico-subcortical, and cerebro-cerebellar functional networks with different network reorganizational mechanisms underlying the different levels of language impairments in LGG and HGG patients.
| S-EPMC6838935 | biostudies-literature
Project description:Pre-operative assessment of language localization and lateralization is critical to preserving brain function after lesion or epileptogenic tissue resection. Task fMRI (t-fMRI) has been extensively and reliably used to this end, but resting state fMRI (rs-fMRI) is emerging as an alternative pre-operative brain mapping method that is independent of a patient's ability to comply with a task. We sought to evaluate if language lateralization obtained from rs-fMRI can replace standard assessment using t-fMRI. In a group of 43 patients scheduled for pre-operative fMRI brain mapping and 17 healthy controls, we found that existing methods of determining rs-fMRI lateralization by considering interhemispheric and intrahemispheric functional connectivity are inadequate compared to t-fMRI when applied to the language network. We determined that this was attributable to widespread but nuanced disturbances in the functional connectivity of the language network in patients. We found changes in interhemispheric and intrahemispheric functional connectivity that were dependent on lesion location, and particularly impacted patients with lesions in the left temporal lobe. We then tested whether a simpler measure of functional connectivity to the language network has a better relation to t-fMRI based language lateralization. Remarkably, we found that functional connectivity between the language network and the frontal pole, and superior frontal gyrus, as well as the supramarginal gyrus, significantly correlated to task based language lateralization indices in both patients and healthy controls. These findings are consistent with prior work with epilepsy patients, and provide a framework for evaluating language lateralization at rest.
| S-EPMC5114586 | biostudies-literature
Project description:In patients with temporal lobe epilepsy (TLE), assessment of language lateralization is important as anterior temporal lobectomy may lead to language impairments. Despite the widespread use of fMRI, evidence of its usefulness in predicting postsurgical language performance is scant. We investigated whether preoperative functional lateralization is related to the preoperative language performance, peri-ictal aphasia, and can predict language outcome one year post-surgery. We studied a total of 72 TLE patients (42 left, 30 right), by using three fMRI tasks: Naming, Verb Generation and Fluency. Functional lateralization indices were analyzed with neuropsychological scores and presence of peri-ictal aphasia. The key findings are:1)Both left and right TLE patients show decreased left lateralization compared to controls.2)Lateralization correlates with language performance before surgery. In left TLE, decreased left lateralization correlates with better fluency performance. In right TLE, increased left lateralization during the Naming task correlates with better naming.3)Left lateralization correlates with peri-ictal aphasia in left TLE patients.4)Lateralization correlates with language performance after surgery. In a subgroup of left TLE who underwent surgery (17 left), decreased left lateralization is predictive of better naming performance at 6 and 12 months after surgery. The present study highlights the clinical relevance of fMRI language lateralization in TLE, especially to predict language outcome one year post-surgery. We also underline the importance of using fMRI tasks eliciting frontal and anterior temporal activations, when studying left and right TLE patients.
| S-EPMC3807502 | 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:Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.
| S-EPMC4553409 | biostudies-literature
Project description:We have previously shown that the connectivity of the hippocampus to other regions of the default mode network (DMN) is a strong indicator of memory ability in people with temporal lobe epilepsy (TLE). Recent work in the cognitive neuroscience literature has suggested that the anterior and posterior aspects of the hippocampus have distinct connections to the rest of the DMN and may support different memory operations. Further, structural analysis of epileptogenic hippocampi has found greater atrophy, characterized by mesial temporal sclerosis, in the anterior region of the hippocampus. Here, we used resting state FMRI data to parcellate the hippocampus according to its functional connectivity to the rest of the brain in people with left lateralized TLE (LTLE) and right lateralized TLE (RTLE), and in a group of neurologically healthy controls. We found similar anterior and posterior compartments in all groups. However, there was weaker connectivity of the epileptogenic hippocampus to multiple regions of the DMN. Both TLE groups showed reduced connectivity of the posterior hippocampus to key hubs of the DMN, the posterior cingulate cortex (PCC) and the medial pre-frontal cortex (mPFC). In the LTLE group, the anterior hippocampus also showed reduced connectivity to the DMN, and this effect was influenced by the presence of mesial temporal sclerosis. When we explored brain-behavior relationships, we found that reduced connectivity of the left anterior hippocampus to the DMN hubs related to poorer verbal memory ability in people with LTLE, and reduced connectivity of the right posterior hippocampus to the PCC related to poorer visual memory ability in those with RTLE. These findings may inform models regarding functional distinctions of the hippocampal anteroposterior axis.
| S-EPMC6714062 | 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:Although language difficulties are common in children born prematurely, robust neuroanatomical correlates of these impairments remain to be established. This study investigated whether the greater prevalence of language problems in preterm (versus term-born) children might reflect injury to major intra- or interhemispheric white matter pathways connecting frontal and temporal language regions. To investigate this, we performed a comprehensive assessment of language and academic abilities in a group of adolescents born prematurely, some of whom had evidence of brain injury at birth (n = 50, mean age: 16 years, mean gestational age: 27 weeks) and compared them to a term-born control group (n = 30). Detailed structural magnetic resonance imaging and diffusion-tractography analyses of intrahemispheric and interhemispheric white matter bundles were performed. Analysis of intrahemispheric pathways included the arcuate fasciculus (dorsal language pathway) and uncinate fasciculus/extreme capsule (ventral language pathway). Analysis of interhemispheric pathways (in particular, connections between the temporal lobes) included the two major commissural bundles: the corpus callosum and anterior commissure. We found language impairment in 38% of adolescents born preterm. Language impairment was not related to abnormalities of the arcuate fasciculus (or its subsegments), but was associated with bilateral volume reductions in the ventral language pathway. However, the most significant volume reduction was detected in the posterior corpus callosum (splenium), which contains interhemispheric connections between the occipital, parietal and temporal lobes. Diffusion tractography showed that of the three groups of interhemispheric fibres within the splenium, only those connecting the temporal lobes were reduced. Crucially, we found that language impairment was only detectable if the anterior commissure (a second temporal lobe commissural pathway) was also small. Regression analyses showed that a combination of anatomical measures of temporal interhemispheric connectivity (through the splenium of the corpus callosum and anterior commissure) explained 57% of the variance in language abilities. This supports recent theories emphasizing the importance of interhemispheric connections for language, particularly in the developing brain.
| S-EPMC4031625 | biostudies-literature