Impaired prefrontal cortex-thalamus pathway in intractable temporal lobe epilepsy with aberrant executive control function: MRI evidence

Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy

Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

The role of the thalamus in modular functional networks in temporal lobe epilepsy with cognitive impairment

OBJECTIVE

Cognitive deficit is common in patients with temporal lobe epilepsy (TLE). Here, we aimed to investigate the modular architecture of functional networks associated with distinct cognitive states in TLE patients together with the role of the thalamus in modular networks.

METHODS

Resting-state functional magnetic resonance imaging scans were acquired from 53 TLE patients and 37 matched healthy controls. All patients received the Montreal Cognitive Assessment test and accordingly were divided into TLE patients with normal cognition (TLE-CN, n = 35) and TLE patients with cognitive impairment (TLE-CI, n = 18) groups. The modular properties of functional networks were calculated and compared including global modularity Q, modular segregation index, intramodular connections, and intermodular connections. Thalamic subdivisions corresponding to the modular networks were generated by applying a 'winner-take-all' strategy before analyzing the modular properties (participation coefficient and within-module degree z-score) of each thalamic subdivision to assess the contribution of the thalamus to modular functional networks. Relationships between network properties and cognitive performance were then further explored.

RESULTS

Both TLE-CN and TLE-CI patients showed lower global modularity, as well as lower modular segregation index values for the ventral attention network and the default mode network. However, different patterns of intramodular and intermodular connections existed for different cognitive states. In addition, both TLE-CN and TLE-CI patients exhibited anomalous modular properties of functional thalamic subdivisions, with TLE-CI patients presenting a broader range of abnormalities. Cognitive performance in TLE-CI patients was not related to the modular properties of functional network but rather to the modular properties of functional thalamic subdivisions.

CONCLUSIONS

The thalamus plays a prominent role in modular networks and potentially represents a key neural mechanism underlying cognitive impairment in TLE.

Altered local gyrification index and corresponding resting-state functional connectivity in individuals with high test anxiety

Previous studies have reported that test anxiety is closely related to unreasonable cognitive patterns and maladaptive emotional responses. However, its underlying brain structural and functional basis has not been thoroughly studied. This study aimed to evaluate the potential difference in local gyration index (LGI) and corresponding resting-state functional connectivity (RSFC) in individuals with high test anxiety (HTA) compared with low test anxiety (LTA). Twenty-six individuals with HTA and 28 individuals with LTA underwent T1-weighted structural and resting-state functional magnetic resonance imaging scans. Using FreeSurfer software, we contrasted the LGI between the HTA and LTA groups using a surface-based general linear model to map group contrasts on a vertex-by-vertex basis. By selecting the cortical regions with significant differences in the LGI analysis as the regions of interest, the seed-based RSFC analysis was further carried out using the Resting-State fMRI Data Analysis Toolkit to examine the differences in the functional connectivity of these cortical regions with the whole brain between the two groups. The results showed that the LGI in several cortical regions of the executive control network (ECN) and the right lateral occipital gyrus was lower in the HTA group than in the LTA group. Furthermore, compared with the LTA group, the HTA group exhibited abnormal RSFC within the ECN, between the ECN and the visual network, and between the ECN and the sensorimotor network. Our findings might provide preliminary evidence for brain morphology and functional alterations in individuals with HTA and contribute to a better understanding of the pathophysiology of TA. DATA STATEMENT: The data that support the findings of this study are available from the corresponding author upon reasonable request after completing a formal data sharing agreement.

Mechanisms for Cognitive Impairment in Epilepsy: Moving Beyond Seizures

There has been a major emphasis on defining the role of seizures in the causation of cognitive impairments like memory deficits in epilepsy. Here we focus on an alternative hypothesis behind these deficits, emphasizing the mechanisms of information processing underlying healthy cognition characterized as rate, temporal and population coding. We discuss the role of the underlying etiology of epilepsy in altering neural networks thereby leading to both the propensity for seizures and the associated cognitive impairments. In addition, we address potential treatments that can recover the network function in the context of a diseased brain, thereby improving both seizure and cognitive outcomes simultaneously. This review shows the importance of moving beyond seizures and approaching the deficits from a system-level perspective with the guidance of network neuroscience.

Characterization of Hippocampal-Thalamic-Cortical Morphometric Reorganization in Temporal Lobe Epilepsy

Introduction

Brain cortico-subcortical connectivity has been investigated in epilepsy using the functional MRI (MRI). Although structural images cannot demonstrate dynamic changes, they provide higher spatial resolution, which allows exploration of the organization of brain in greater detail.

Methods

We used high-resolution brain MRI to study the hippocampal-thalamic-cortical networks in temporal lobe epilepsy (TLE) using a volume-based morphometric method. We enrolled 22 right-TLE, 33 left-TLE, and 28 age/gender-matched controls retrospectively. FreeSurfer software was used for the thalamus segmentation.

Results

Among the 50 subfields, ipsilateral anterior, lateral, and parts of the intralaminar and medial nuclei, as well as the contralateral parts of lateral nuclei had significant volume loss in both TLE. The anteroventral nucleus was most vulnerable. Most thalamic subfields were susceptible to seizure burden, especially the left-TLE. SPM12 was used to conduct an analysis of the gray matter density (GMD) maps. Decreased extratemporal GMD occurred bilaterally. Both TLE demonstrated significant GMD loss over the ipsilateral inferior frontal gyrus, precentral gyrus, and medial orbital cortices.

Significance

Thalamic subfield atrophy was related to the ipsilateral inferior frontal GMD changes, which presented positively in left-TLE and negatively in right-TLE. These findings suggest prefrontal-thalamo-hippocampal network disruption in TLE.

Neurobehavioural comorbidities of epilepsy: towards a network-based precision taxonomy

Cognitive and behavioural comorbidities are prevalent in childhood and adult epilepsies and impose a substantial human and economic burden. Over the past century, the classic approach to understanding the aetiology and course of these comorbidities has been through the prism of the medical taxonomy of epilepsy, including its causes, course, characteristics and syndromes. Although this 'lesion model' has long served as the organizing paradigm for the field, substantial challenges to this model have accumulated from diverse sources, including neuroimaging, neuropathology, neuropsychology and network science. Advances in patient stratification and phenotyping point towards a new taxonomy for the cognitive and behavioural comorbidities of epilepsy, which reflects the heterogeneity of their clinical presentation and raises the possibility of a precision medicine approach. As we discuss in this Review, these advances are informing the development of a revised aetiological paradigm that incorporates sophisticated neurobiological measures, genomics, comorbid disease, diversity and adversity, and resilience factors. We describe modifiable risk factors that could guide early identification, treatment and, ultimately, prevention of cognitive and broader neurobehavioural comorbidities in epilepsy and propose a road map to guide future research.

Aberrant cerebral intrinsic activity and cerebro-cerebellar functional connectivity in right temporal lobe epilepsy: a resting-state functional MRI study

OBJECTIVE

Numerous neuroimaging studies have demonstrated that functional brain aberrations are associated with cognitive impairments in temporal lobe epilepsy (TLE). Here, we aimed to investigate the neural substrates of attention deficits by combining assessment of regional intrinsic brain activities with large-scale functional connectivity in patients with right TLE (rTLE).

METHODS

Thirty-five patients with rTLE and 33 matched healthy controls were recruited. All participants completed the Attention Network Test (ANT) and resting-sate functional MRI (rs-fMRI) scans. The z-standardized fractional amplitude of the low-frequency fluctuation (zfALFF) approach was applied to evaluate the brain's intrinsic activity. The cerebral regions with significant zfALFF values were selected as seeds for subsequent functional connectivity analyses. A correlation analysis was performed between functional activity and clinical variables.

RESULTS

Compared with the healthy control group, the patients showed decreased zfALFF in the right inferior temporal gyrus and bilateral superior parietal gyrus, and the right inferior temporal gyrus exhibited increased functional connectivity with the bilateral cerebellum-6/vermis-6 and decreased functional connectivity with right superior frontal gyrus. The ANT indicated that the rTLE group exhibited attention deficits. Furthermore, a positive correlation was found between the zfALFF value of the left superior parietal gyrus and alerting performance, while a negative correlation between the zfALFF value of the right superior parietal gyrus and disease duration.

CONCLUSION

This study demonstrated aberrant intrinsic cerebral activity and functional connectivity in the whole brain network, which may act as responsible and compensatory factors in attention deficits, especially further profoundly illuminated the compensatory role of cerebellum in patients with rTLE.

Mechanisms of cognitive impairment in temporal lobe epilepsy: A systematic review of resting-state functional connectivity studies

Temporal lobe epilepsy is the most common form of focal epilepsy and related cognitive dysfunction impacts significantly on quality of life in patients. Identifying the mechanisms of such impairment would assist in the management and treatment of patients. The study of perturbations in resting-state networks could shed light on this subject. The aim of this systematic review was to synthesize findings on the relationship between aberrant resting-state functional connectivity and cognitive performance in patients with TLE. Literature searches were conducted on Scopus and PubMed electronic databases and 17 relevant articles were extracted, all of which studied the association between resting-state functional connectivity (RSFC) and cognition in adults with TLE. Study findings were synthesized according to methods used to analyze resting-state data, cognitive domains tested, and neuropsychology tasks administered. Results show that increased RSFC in the primary epileptogenic hippocampus, and reduced intra-hemispheric RSFC, are associated with weaker memory performance. In left TLE, memory impairment may be compensated for by bilateral hippocampal connectivity, which is also predictive of better postoperative memory outcomes. In right TLE, memory loss may be compensated for by increased connectivity between the contralateral hippocampus and inferior frontal gyrus. There is also tentative evidence that working memory dysfunction is related to reduced RSFC between the medial frontal-insular parietal network and the medial temporal network, executive dysfunction is related to reduced RSFC between frontal and parietal lobes, and between the frontal lobe and subcortical regions and that language dysfunction is related to reduced RSFC within the left fronto-temporal language network. Multicenter studies could refute or support these findings by enrolling large samples of patients and employing multivariate regression analysis to control for the effects of anatomical disruption, interictal discharges, seizure frequency, medication, and mood. Systematic review registration: PROSPERO: 191323.

Methylphenidate for attention problems in epilepsy patients: Safety and efficacy

Children with attention deficit hyperactivity disorder (ADHD) have an increased risk of seizures, and children with epilepsy have an increased prevalence of ADHD. Adults with epilepsy often have varying degrees of attentional dysfunction due to multiple factors, including anti-seizure medications, frequent seizures, interictal discharges, underlying lesions, and psychiatric comorbidities. Currently, there are no approved medications for the treatment of epilepsy-related attentional dysfunction. Methylphenidate (MPH) is a stimulant, FDA-approved for the treatment of ADHD, and often used for ADHD in the setting of pediatric epilepsy. Large database and registry studies indicate safety of MPH in children with ADHD and epilepsy, with no significant effect on seizure frequency. Small single-dose and open-label studies suggest efficacy of MPH in adults with epilepsy-related attention deficits. Methylphenidate represents a possible treatment for attentional dysfunction due to epilepsy, but large, randomized, placebo-controlled, double-blinded studies are needed.

Longitudinal assessment of resting-state fMRI in temporal lobe epilepsy: A two-year follow-up study

In this study, we aimed to detect longitudinal alterations in local spontaneous brain activity and functional connectivity (FC) of the default mode network (DMN) in patients with temporal lobe epilepsy (TLE) over a two-year follow-up. We used amplitude of low-frequency fluctuation (ALFF) analysis and independent component analysis (ICA) to explore differences in local spontaneous brain activity and FC strength. In total, 33 participants (16 patients with TLE and 17 age- and gender-matched healthy controls (HCs)) were recruited in this study. All participants performed the Attention Network Test (ANT) for evaluation of the executive control function. Compared with healthy patients at baseline, patients with TLE at follow-up exhibited increased ALFF values in the left medial frontal gyrus, as well as reduced FC values in the left inferior parietal gyrus (IPG) within the DMN. Patients with TLE revealed executive dysfunction, but no progressive deterioration was observed during follow-up. This study revealed the abnormal distribution of ALFF values and Rs-FC changes over a two-year follow-up period in TLE, both of which demonstrated different reorganization trajectories and loss of efficiency.

Focal epilepsy caused by single cerebral cavernous malformation (CCM) is associated with regional and global resting state functional connectivity (FC) disruption

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To our knowledge, this is the first study to report resting state functional connectivity (FC) abnormalities associated with focal epilepsy caused by a single cerebral cavernous malformation (CCM).

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We show, by comparing to the data acquired from the age and gender matched control group, that this type of focal epilepsy is associated with the disruption of the normal regional and global FC. The disruption includes a decrease in the coactivation between the region surrounding the CCM lesion, i.e., the lesional region, and its homotopic counterpart, a reduction in FC between the lesional region and the rest of the brain, and decreased FC among the default mode network (DMN).

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These changes may be alleviated or reversed after the surgical resection of the CCM and the epileptogenic zone has successfully stopped recurrent seizures.

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Finally, the severity of the FC disruption in the brain tissue adjacent to the CCM may be used to delineate the epileptogenic zone and to aid the surgical resection.

Epilepsy, including the type with focal onset, is increasingly viewed as a disorder of the brain network. Here we employed the functional connectivity (FC) metrics estimated from the resting state functional MRI (rsfMRI) to investigate the changes of brain network associated with focal epilepsy caused by single cerebral cavernous malformation (CCM). Eight CCM subjects and 21 age and gender matched controls were enrolled in the study. Seven of 8 CCM subjects underwent surgical resection of the CCM and became seizure free and 4 of the surgical subjects underwent a repeat rsfMRI study. We showed that there was both regional and global disruption of the FC values among the CCM subjects including decreased in homotopic FC (HFC) and global FC (GFC) in the regions of interest (ROIs) where the CCMs were located. There was also the disruption of the default mode network (DMN) especially the FC between the middle prefrontal cortex (MPFC) and the right lateral parietal cortex (LPR) among these individuals. We observed the trend of alleviation of these disruptions after the individual has become seizure free from the surgical resection of the CCM. Using a voxel-based approach, we found the disruption of the HFC and GFC in the brain tissue immediately adjacent to the CCM and the severity of the disruption appeared inversely proportional to the distance of the brain tissue to the lesion. Our findings confirm the disruption of normal brain networks from focal epilepsy, a process that may be reversible with successful surgical treatments rendering patients seizure free. Some voxel-based metrics may help identify the epileptogenic zone and guide the surgical resection.

Dynamic Alterations of Spontaneous Neural Activity in Parkinson's Disease: A Resting-State fMRI Study

Objective: To investigate the dynamic amplitude of low-frequency fluctuations (dALFFs) in patients with Parkinson's disease (PD) and healthy controls (HCs) and further explore whether dALFF can be used to test the feasibility of differentiating PD from HCs. Methods: Twenty-eight patients with PD and 28 demographically matched HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and neuropsychological tests. A dynamic method was used to calculate the dALFFs of rs-fMRI data obtained from all subjects. The dALFF alterations were compared between the PD and HC groups, and the correlations between dALFF variability and disease duration/neuropsychological tests were further calculated. Then, the statistical differences in dALFF between both groups were selected as classification features to help distinguish patients with PD from HCs through a linear support vector machine (SVM) classifier. The classifier performance was assessed using a permutation test (repeated 5,000 times). Results: Significantly increased dALFF was detected in the left precuneus in patients with PD compared to HCs, and dALFF variability in this region was positively correlated with disease duration. Our results show that 80.36% (p < 0.001) subjects were correctly classified based on the SVM classifier by using the leave-one-out cross-validation method. Conclusion: Patients with PD exhibited abnormal dynamic brain activity in the left precuneus, and the dALFF variability could distinguish PD from HCs with high accuracy. Our results showed novel insights into the pathophysiological mechanisms of PD.