Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness

Joint impact on attention, alertness and inhibition of lesions at a frontal white matter crossroad

In everyday life, information from different cognitive domains-such as visuospatial attention, alertness and inhibition-needs to be integrated between different brain regions. Early models suggested that completely segregated brain networks control these three cognitive domains. However, more recent accounts, mainly based on neuroimaging data in healthy participants, indicate that different tasks lead to specific patterns of activation within the same, higher-order and 'multiple-demand' network. If so, then a lesion to critical substrates of this common network should determine a concomitant impairment in all three cognitive domains. The aim of the present study was to critically investigate this hypothesis, i.e. to identify focal stroke lesions within the network that can concomitantly affect visuospatial attention, alertness and inhibition. We studied an unselected sample of 60 first-ever right-hemispheric, subacute stroke patients using a data-driven, bottom-up approach. Patients performed 12 standardized neuropsychological and oculomotor tests, four per cognitive domain. A principal component analysis revealed a strong relationship between all three cognitive domains: 10 of 12 tests loaded on a first, common component. Analysis of the neuroanatomical lesion correlates using different approaches (i.e. voxel-based and tractwise lesion-symptom mapping, disconnectome maps) provided convergent evidence on the association between severe impairment of this common component and lesions at the intersection of superior longitudinal fasciculus II and III, frontal aslant tract and, to a lesser extent, the putamen and inferior fronto-occipital fasciculus. Moreover, patients with a lesion involving this region were significantly more impaired in daily living cognition, which provides an ecological validation of our results. A probabilistic functional atlas of the multiple-demand network was performed to confirm the potential relationship between patients' lesion substrates and observed cognitive impairments as a function of the multiple-demand network connectivity disruption. These findings show, for the first time, that a lesion to a specific white matter crossroad can determine a concurrent breakdown in all three considered cognitive domains. Our results support the multiple-demand network model, proposing that different cognitive operations depend on specific collaborators and their interaction, within the same underlying neural network. Our findings also extend this hypothesis by showing (i) the contribution of superior longitudinal fasciculus and frontal aslant tract to the multiple-demand network; and (ii) a critical neuroanatomical intersection, crossed by a vast amount of long-range white matter tracts, many of which interconnect cortical areas of the multiple-demand network. The vulnerability of this crossroad to stroke has specific cognitive and clinical consequences; this has the potential to influence future rehabilitative approaches.

A study of brain functional network and alertness changes in temporal lobe epilepsy with and without focal to bilateral tonic-clonic seizures

BACKGROUND

Temporal lobe epilepsy (TLE) is commonly refractory. Epilepsy surgery is an effective treatment strategy for refractory epilepsy, but patients with a history of focal to bilateral tonic-clonic seizures (FBTCS) have poor outcomes. Previous network studies on epilepsy have found that TLE and idiopathic generalized epilepsy with generalized tonic-clonic seizures (IGE-GTCS) showed altered global and nodal topological properties. Alertness deficits also were found in TLE. However, FBTCS is a common type of seizure in TLE, and the implications for alertness as well as the topological rearrangements associated with this seizure type are not well understood.

METHODS

We obtained rs-fMRI data and collected the neuropsychological assessment data from 21 TLE patients with FBTCS (TLE- FBTCS), 18 TLE patients without FBTCS (TLE-non- FBTCS) and 22 controls, and constructed their respective functional brain networks. The topological properties were analyzed using the graph theoretical approach and correlations between altered topological properties and alertness were analyzed.

RESULTS

We found that TLE-FBTCS patients showed more serious impairment in alertness effect, intrinsic alertness and phasic alertness than the patients with TLE-non-FBTCS. They also showed significantly higher small-worldness, normalized clustering coefficient (γ) and a trend of higher global network efficiency (gE) compared to TLE-non-FBTCS patients. The gE showed a significant negative correlation with intrinsic alertness for TLE-non-FBTCS patients.

CONCLUSION

Our findings show different impairments in brain network information integration, segregation and alertness between the patients with TLE-FBTCS and TLE-non-FBTCS, demonstrating that impairments of the brain network may underlie the disruptions in alertness functions.

Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses

BACKGROUND

Prior reports revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE to determine whether these changes can be used to guide rTLE diagnosis.

METHODS

The resultant imaging data of resting-state functional MRI (rs-fMRI) analyses of 59 patients with rTLE and 60 normal control individuals were analyzed using VMHC and support vector machine (SVM) approaches.

RESULTS

Relative to normal controls, patients with rTLE were found to exhibit decreased VMHC values in the bilateral superior and the middle temporal pole (STP and MTP), the bilateral middle and inferior temporal gyri (MTG and ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), the postcentral gyrus (PoCG), and the supplemental motor area (SMA). The ROC curve of MTG VMHC values showed a great diagnostic efficacy in the diagnosis of rTLE with AUCs, sensitivity, specificity, and optimum cutoff values of 0.819, 0.831, 0.717, and 0.465. These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59).

CONCLUSION

In summary, patients with rTLE exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.

Integrating Optimized Multiscale Entropy Model with Machine Learning for the Localization of Epileptogenic Hemisphere in Temporal Lobe Epilepsy Using Resting-State fMRI

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.

Increased resting-state brain entropy of parahippocampal gyrus and dorsolateral prefrontal cortex in manic and euthymic adolescent bipolar disorder

BACKGROUND

Alterations of brain signal complexity may reflect brain functional abnormalities. In adolescent bipolar disorder (ABD) distribution of brain regions showing abnormal complexity in different mood states remains unclear. We aimed to analyze brain entropy (BEN) alteration of functional magnetic resonance imaging (fMRI) signal to observe spatial distribution of complexity in ABD patients, as well as the relationship between this variation and clinical variables.

METHODS

Resting-state fMRI data were acquired from adolescents with bipolar disorder (BD) who were in manic (n = 19) and euthymic (n = 20) states, and from healthy controls (HCs, n = 17). The differences in BEN among the three groups, and their associations with clinical variables, were examined.

RESULTS

Compared to HCs, manic and euthymic ABD patients showed increased BEN in right parahippocampal gyrus (PHG) and left dorsolateral prefrontal cortex (DLPFC). There was no significant difference of BEN between the manic and the euthymic ABD groups. In manic ABD patients, right PHG BEN exhibited significantly positive relationship with episode times.

CONCLUSIONS

Increased BEN in right PHG and left DLPFC in ABD patients may cause dysfunction of corticolimbic circuitry which is important to emotional processing and cognitive control. The positive correlation between PHG BEN and episode times of manic ABD patients further expressed a close association between brain complexity and clinical symptoms. From the perspective of brain temporal dynamics, the present study complements previous findings that have reported corticolimbic dysfunction as an important contributor to the pathophysiology of BD. BEN may provide valuable evidences for understanding the underlying mechanism of ABD.

Application of Functional Magnetic Resonance Imaging in the Diagnosis of Parkinson's Disease: A Histogram Analysis

This study aimed to investigate the value of amplitude of low-frequency fluctuation (ALFF)-based histogram analysis in the diagnosis of Parkinson's disease (PD) and to investigate the regions of the most important discriminative features and their contribution to classification discrimination. Patients with PD (n = 59) and healthy controls (HCs; n = 41) were identified and divided into a primary set (80 cases, including 48 patients with PD and 32 HCs) and a validation set (20 cases, including 11 patients with PD and nine HCs). The Automated Anatomical Labeling (AAL) 116 atlas was used to extract the histogram features of the regions of interest in the brain. Machine learning methods were used in the primary set for data dimensionality reduction, feature selection, model construction, and model performance evaluation. The model performance was further validated in the validation set. After feature data dimension reduction and feature selection, 23 of a total of 1,276 features were entered in the model. The brain regions of the selected features included the frontal, temporal, parietal, occipital, and limbic lobes, as well as the cerebellum and the thalamus. In the primary set, the area under the curve (AUC) of the model was 0.974, the sensitivity was 93.8%, the specificity was 90.6%, and the accuracy was 93.8%. In the validation set, the AUC, sensitivity, specificity, and accuracy were 0.980, 90.9%, 88.9%, and 90.0%, respectively. ALFF-based histogram analysis can be used to classify patients with PD and HCs and to effectively identify abnormal brain function regions in PD patients.

Feature of cognitive dysfunction in patients with temporal lobe epilepsy and its clinical influencing factors

OBJECTIVES

To comprehensively analyze the characteristics of cognitive impairment of temporal lobe epilepsy (TLE), and to explore the effects of different lateral patients' cognitive impairment and different clinical factors on cognitive impairment of TLE.

METHODS

A total of 84 patients, who met the diagnostic criteria for TLE in the Department of Neurology, Xiangya Hospital, were collected as a patient group, with 36 cases of left TLE and 48 cases of right TLE. A total of 79 healthy volunteers with matching gender, age and education level were selected as a control group. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and the scores of Arithmetic Test, Information Test, Digit Symbol Substitution Test (DSST), Block Design Test (BDT), Hayling Test and Verbal Fluency Test (VFT) of the revised Chinese Adult Wechsler Intelligence scale were retrospectively analyzed in the 2 groups.Multiple regression analysis was used to analyze the relationship between the clinical factors and the cognitive impairment score.

RESULTS

Compared with the control group, the TLE patient group had low scores in all neuropsychological tests, with significant difference (all P<0.05). Compared with the control group, there was significant difference in different neuropsychological tests in the patients with TLE on different sides (all P<0.05). In the left TLE, there were low scores in Information Test, arithmetic, VFT, the completion time of Hayling Test part A, the completion time of Hayling Test part B, the correct number of Hayling Test part A, the correct number of Hayling Test part B, BDT, Forward Digit Span Test (FDST) and Backward Digit Span Test (BDST). While in the right TLE, there were low scores in Information Test, arithmetic, DSST, VFT, the completion time of Hayling Test part A, the correct number of Hayling Test part A, the completion time of Hayling Test part B, the correct number of Hayling Test part B, BDT, FDST and BDST.

CONCLUSIONS

There are multiple cognitive domain dysfunctions in TLE, including language, short-term memory, long-term memory, attention, working memory, executive function and visual space function. Left TLE has greater impairment of executive function and right TLE has greater damage in working memory. Long pathography of disease, hippocampal sclerosis and a history of febrile convulsions may lead to more severe cognitive impairment. Earlier identification and earlier intervention are needed to improve prognosis of patients.

Comparison of topological properties of functional brain networks with graph theory in temporal lobe epilepsy with different duration of disease

Background

Our study was performed to measure the alterations in topological properties of the functional brain network of temporal lobe epilepsy (TLE) at different durations, exploring the potential progression and neuropathophysiological mechanisms of TLE.

Methods

Fifty-eight subjects, including 17 TLE patients with a disease duration of ≤5 years (TLE-SD), 20 TLE patients with a disease duration of >5 years (TLE-LD), and 21 healthy controls firstly underwent the Attention Network Test (ANT) to assess the alertness function and received the resting-state functional magnetic resonance imaging (rs-fMRI). Next, a functional brain network was set up, and then the related graph of theoretical network analysis was conducted. Finally, the correlation between network property and the neuropsychological score was analyzed.

Results

The global and local efficiencies of functional brain networks in TLE-SD patients significantly decreased and tended toward random alterations. Also, the degree centrality (DC) and nodal efficiency (Ne) in right medial pre-frontal thalamus (mPFtha) and right rostral temporal thalamus (rTtha) of TLE-SD patients significantly reduced. Further analysis showed that alertness was positively associated with the characteristic path length but negatively related to the global and local efficiencies in TLE-SD patients; alertness was negatively related to the Ne of mPFtha in TLE-LD patients.

Conclusions

Our study showed that the functional brain network of TLE patients might undergo compensatory reorganization as the disease progresses, which provides useful insights into the progression and mechanism of TLE.

Resting-state brain entropy in right temporal lobe epilepsy and its relationship with alertness

BACKGROUND

To 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.

METHOD

Thirty-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.

RESULTS

Compared 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.

CONCLUSIONS

Our 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.