Decreased functional connectivity and structural deficit in alertness network with right-sided temporal lobe epilepsy

Epilepsy-related white matter network changes in patients with frontal lobe glioma

PURPOSE

Epilepsy is a common symptom in patients with frontal lobe glioma. Tumor-related epilepsy was recently considered a type of network disease. Glioma can severely influence the integrity of the white matter network. The association between white matter network changes and presurgical epilepsy remains unclear in glioma patients. This study aims to identify alterations to the subcortical brain networks caused by glioma and glioma-related epilepsy.

METHODS

Sixty-one patients with frontal lobe gliomas were enrolled and stratified into the epileptic and non-epileptic groups. Additionally, 14 healthy participants were enrolled after matching for age, sex, and education level. All participants underwent diffusion tensor imaging. Graph theoretical analysis was applied to reveal topological changes in their white matter networks. Regions affected by tumors were excluded from the analysis.

RESULTS

Global efficiency was significantly decreased (p = 0.008), while the shortest path length increased (p = 0.02) in the left and right non-epileptic groups compared to the controls. A total of five edges exhibited decreased fiber count in the non-epileptic group (p < 0.05, false discovery rate-corrected). The topological properties and connectional edges showed no significant differences when comparing the epileptic groups and the controls. Additionally, the degree centrality of several nodes connected to the alternated edges was also diminished.

CONCLUSIONS

Compared to the controls, the epilepsy groups showed raletively intact WM networks, while the non-epileptsy groups had damaged network with lower efficiency and longer path length. These findings indicated that the occurrence of glioma related epilepsy have association with white matter network intergrity.

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 impact 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. Principal component analyses 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 MD-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 (1) the contribution of SLF and FAT to the multiple-demand network, and (2) 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.

The Bilateral Precuneus as a Potential Neuroimaging Biomarker for Right Temporal Lobe Epilepsy: A Support Vector Machine Analysis

Background and Objective

While evidence has demonstrated that the default-mode network (DMN) plays a key role in the broad-scale cognitive problems that occur in right temporal lobe epilepsy (rTLE), little is known about alterations in the network homogeneity (NH) of the DMN in TLE. In this study, we used the NH method to investigate the NH of the DMN in TLE at rest, and an support vector machine (SVM) method for the diagnosis of rTLE.

Methods

A total of 43 rTLE cases and 42 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Imaging data were analyzed with the NH and SVM methods.

Results

rTLE patients have a decreased NH in the right inferior temporal gyrus (ITG) and left middle temporal gyrus (MTG), but increased NH in the bilateral precuneus (PCu) and right inferior parietal lobe (IPL), compared with HCs. We found that rTLE had a longer performance reaction time (RT). No significant correlation was found between abnormal NH values and clinical variables of the patients. The SVM results showed that increased NH in the bilateral PCu as a diagnostic biomarker distinguished rTLE from HCs with an accuracy of 74.12% (63/85), a sensitivity 72.01% (31/43), and a specificity 72.81% (31/42).

Conclusion

These findings suggest that abnormal NH of the DMN exists in rTLE, and highlights the significance of the DMN in the pathophysiology of cognitive problems occurring in rTLE, and the bilateral PCu as a neuroimaging diagnostic biomarker for rTLE.

Attentional networks in neurodegenerative diseases: anatomical and functional evidence from the Attention Network Test

INTRODUCTION

Understanding alterations to brain anatomy and cognitive function associated with neurodegenerative diseases remains a challenge for neuroscience today. In experimental neuroscience, several computerised tests have been developed to contribute to our understanding of neural networks involved in cognition. The Attention Network Test (ANT) enables us to measure the activity of 3 attentional networks (alertness, orienting, and executive function).

OBJECTIVES

The main aim of this review is to describe all the anatomical and functional alterations found in diverse neurological diseases using the ANT.

MATERIAL AND METHODS

We collected studies published since 2010 in the PubMed database that employed the ANT in different neurological diseases. Thirty-two articles were obtained, addressing multiple sclerosis, epilepsy, and Parkinson's disease, among other disorders.

CONCLUSIONS

Some of the anatomical structures proposed in the 3 attentional networks model were confirmed. The most relevant structures in the alertness network are the prefrontal cortex, parietal region, thalamus, and cerebellum. The thalamus is also relevant in the orienting network, together with posterior parietal regions. The executive network does not depend exclusively on the prefrontal cortex and anterior cingulate cortex, but also involves such subcortical structures as the basal ganglia and cerebellum and their projections towards the entire cortex.

Decreased Connectivity in Precuneus of the Ventral Attentional Network in First-Episode, Treatment-Naïve Patients With Major Depressive Disorder: A Network Homogeneity and Independent Component Analysis

BACKGROUND AND OBJECTIVE

The ventral attentional network (VAN) can provide quantitative information on cognitive problems in patients with major depressive disorder (MDD). Nevertheless, little is known about network homogeneity (NH) changes in the VAN of these patients. The aim of this study was to examine the NH values in the VAN by independent component analysis (ICA) and compare the NH values between MDD patients and the normal controls (NCs).

METHODS

Attentional network test and resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 73 patients, and 70 NCs matched by gender, age, and education years. ICA and NH were employed to evaluate the data. Moreover, the NH values were compared, and Spearman's rank correlation analysis was used to assess the correlations with the executive control reaction time (ECRT).

RESULTS

Our results showed that the first-episode, treatment-naive MDD patients had decreased NH in the right precuneus (PCu) and abnormal ECRT compared with NCs. However, no significant correlation was found between the NH values and measured clinical variables.

CONCLUSION

Our results highlight the potential importance of VAN in the pathophysiology of cognitive problems in MDD, thus offering new directions for future research on MDD.

Abnormal Ventral Somatomotor Network Homogeneity in Patients With Temporal Lobe Epilepsy

BACKGROUND

Abnormalities of functional connectivity in the somatomotor network have been thought to play an essential role in the pathophysiology of epilepsy. However, there has been no network homogeneity (NH) study about the ventral somatomotor network (VSN) in patients with temporal lobe epilepsy (TLE). Therefore, we explored the NH of the VSN in TLE patients in this study.

METHODS

The sample included 52 patients with left temporal lobe epilepsy, 83 patients with right temporal lobe epilepsy, and 68 healthy controls. The NH method was utilized to analyze the resting-state functional magnetic resonance imaging data.

RESULTS

Compared to the controls, rTLE patients had significantly higher NH in the bilateral postcentral gyrus, and significantly lower NH in the bilateral Rolandic operculum and the right superior temporal gyrus (STG). The NH values of the left postcentral gyrus were significantly higher in lTLE patients than in the healthy controls, and lTLE patients had lower NH in the right Rolandic operculum. The altered NH in the postcentral gyrus was negatively correlated with the illness duration, and the decreased NH in the left Rolandic operculum was negatively correlated with the executive control reaction time (ECRT).

CONCLUSION

Our findings suggest that altered NH of the postcentral gyrus, Rolandic operculum and STG might be associated with the pathophysiology of TLE, and thus, highlight the contribution of the VSN to the pathophysiology of TLE.

Abnormal hubs in global network as neuroimaging biomarker in right temporal lobe epilepsy at rest

While abnormal neuroimaging features have been reported in patients suffering from right temporal lobe epilepsy (rTLE), the value of altered degree centrality (DC) as a diagnostic biomarker for rTLE has yet to be established. As such, the present study was designed to examine DC abnormalities in rTLE patients in order to gauge the diagnostic utility of these neuroimaging features. In total, 68 patients with rTLE and 73 healthy controls (HCs) participated in this study. Imaging data were analyzed using DC and receiver operating characteristic (ROC) methods. Ultimately, rTLE patients were found to exhibit reduced right caudate DC and increased left middle temporal gyrus, superior parietal gyrus, superior frontal gyrus, right precuneus, frontal gyrus Inferior gyrus, middle-superior frontal gyrus, and inferior parietal gyrus DC relative to HC. ROC analyses indicated that DC values in the right caudate nucleus could be used to differentiate between rTLE patients and HCs with a high degree of sensitivity and specificity. Together, these results thus suggest that rTLE is associated with abnormal DC values in the right caudate nucleus, underscoring the relevance of further studies of the underlying pathophysiology of this debilitating condition.

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.

Anomalous functional connectivity within the default-mode network in treatment-naive patients possessing first-episode major depressive disorder

BACKGROUND AND OBJECTIVE

Previous studies have shown that the default-mode network (DMN) has a substantial role in patients with major depressive disorder (MDD). However, there is a shortage of information regarding variations in the functional connectivity (FC) of the DMN of treatment-naive patients with first-episode MDD. The present study aims to explore the FC of the DMN in such patients.

METHODS

The study population consisted of 33 patients and 35 controls, paired regarding age, gender, education level, and health condition. Depression severity was assessed through the Hamilton Depression Scale (HAM-D), and subjects underwent evaluation during the resting-state through functional magnetic resonance imaging (rs-fMRI). To assess the result, we used FC and ICA. We used Spearman's correlation test to detect potential correlations between anomalous FC and severity of HAM-D scores.

RESULTS

We have found a decreased FC in the left medial orbitofrontal gyrus (MOFG) and right marginal gyrus (SMG) in depressive patients compared to controls. There was a negative correlation between abnormal FC in the right SMG and HAM-D scores. We have not found any increase in FC of the DMN in treatment-naive, first-episode of MDD patients.

CONCLUSIONS

Our study provided evidence of a negative correlation between abnormal FC in the DMN and severity of depression symptoms measured by HAM-D in treatment-naive MDD patients. This finding could shed some light on the relevance of DMN for understanding the pathophysiology of cognitive impairment in MDD.

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach

PURPOSE

Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

METHODS

Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE.

RESULTS

Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%.

CONCLUSION

Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.

The role of sleep disturbances in depressive-like behavior with emphasis on α-ketoglutarate dehydrogenase activity in rats

Sleep disorders may induce anxiety- and depressive-like behaviors. Furthermore, sleep disorders can alter the function of α-KGDH (α-ketoglutarate dehydrogenase), which is involved in the citric acid cycle. In this study, we evaluated the effect of two models of sleep deprivation (SD) including total SD (TSD) and partial SD (PSD), and two models of napping combined with each models of SD on rats' performance in Forced Swim Test (FST) and α-KGDH activity in both hemispheres of the amygdala. 64 male Wistar rats were used in this study. A modified water box was also used to induce SD. The results showed that, immobility was increased in 48-hour PSD group, indicating a possible depressive-like behavior. Swimming time was also increased following 48-hour TSD. However, climbing time was decreased in 48-hour PSD/TSD groups. Additionally, α-KGDH activity was increased in the left amygdala in 48-hour TSD and PSD groups. In conclusion, PSD may increase depressive-like behavior. TSD and PSD can decrease swimming time but increase climbing time, and these effects may be related to serotonergic and noradrenergic transmissions, respectively. Increase in α-KGDH activity in the left amygdala may be related to the brain's need for more energy during prolonged wakefulness. α-KGDH activity in the right amygdala was unaffected probably due to a decrease in alertness following SD.

Neurophysiological and behavioral correlates of alertness impairment and compensatory processes in ADHD evidenced by the Attention Network Test

In Attention Deficit Hyperactivity disorder (ADHD), fMRI studies show asymmetric alterations: widespread hypoactivation in anterior cortical areas and hyperactivation in some posterior regions, and the latter is considered to be related to compensatory processes. In Posner’s attentional networks, an important role is attributed to functional interhemispheric asymmetries. The psychophysiological Attention Network Test (ANT), which measures the efficiency of the alerting, orienting, and executive networks, seems particularly informative for ADHD. Potentials related to ANT stimuli (ANT-RPs) have revealed reduced cognitive potential P3 in ADHD. However, there are no studies associated with asymmetry of ANT-RPs. In the present study, conducted with 20 typically developing boys and 19 boys with ADHD, aged 11–13 years, the efficiency of the three Posner’s networks regarding performance and amplitude asymmetries in ANT-RPs was evaluated according to the arithmetic difference of these parameters between different cue and target presentation conditions. The results were correlated to Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) scores. Regarding accuracy and intraindividual variation in reaction time, ADHD subjects showed lower efficiency of executive and alerting network, and this effect was correlated with DSM. Regarding alerting network, ANT-RPs in ADHD did not have the right-side amplitude prevalence in the temporal regions, which was observed in controls. In all ANT conditions, significantly higher asymmetries were observed in ADHD than in controls in the occipital regions 40–200 ms after target onset. Their amplitude in ADHD subjects was inversely proportional to DSM scores of inattentiveness and directly proportional to accuracy and efficiency of the executive network. The results suggest impaired alerting and executive networks in ADHD and compensatory occipital mechanisms.