Altered Rich-Club Organization and Regional Topology Are Associated With Cognitive Decline in Patients With Frontal and Temporal Gliomas

Perioperative Neurocognitive Function in Glioma Surgery

PURPOSE OF REVIEW

This review provides a concise overview of the recent literature regarding preoperative and postoperative neurocognitive functioning (NCF) in patients with glioma. Brief discussion also covers contemporary intraoperative brain mapping work, with a focus on potential influence of mapping upon NCF outcomes following awake surgery.

RECENT FINDINGS

Most patients with glioma exhibit preoperative NCF impairment, with severity varying by germ line and tumoral genetics, tumor grade, and lesion location, among other characteristics. Literature regarding postoperative NCF changes is mixed, though numerous studies indicate a majority of patients exhibit immediate and short-term worsening. This is often followed by recovery over several months; however, a substantial portion of patients harbor persisting declines. Decline appears related to surgically-induced structural and functional brain alterations, both local and distal to the tumor and resection cavity. Importantly, NCF decline may be mitigated to some extent by intraoperative brain mapping, including mapping of both language-mediated and nonverbal functions. Research regarding perioperative NCF in patients with glioma has flourished over recent years. While this has increased our understanding of contributors to NCF and risk of decline associated with surgical intervention, more work is needed to better preserve NCF throughout the disease course.

The significance of structural rich club hubs for the processing of hierarchical stimuli

The brain's structural network follows a hierarchy that is described as rich club (RC) organization, with RC hubs forming the well-interconnected top of this hierarchy. In this study, we tested whether RC hubs are involved in the processing of hierarchically higher structures in stimulus sequences. Moreover, we explored the role of previously suggested cortical gradients along anterior-posterior and medial-lateral axes throughout the frontal cortex. To this end, we conducted a functional magnetic resonance imaging (fMRI) experiment and presented participants with blocks of digit sequences that were structured on different hierarchically nested levels. We additionally collected diffusion weighted imaging data of the same subjects to identify RC hubs. This classification then served as the basis for a region of interest analysis of the fMRI data. Moreover, we determined structural network centrality measures in areas that were found as activation clusters in the whole-brain fMRI analysis. Our findings support the previously found anterior and medial shift for processing hierarchically higher structures of stimuli. Additionally, we found that the processing of hierarchically higher structures of the stimulus structure engages RC hubs more than for lower levels. Areas involved in the functional processing of hierarchically higher structures were also more likely to be part of the structural RC and were furthermore more central to the structural network. In summary, our results highlight the potential role of the structural RC organization in shaping the cortical processing hierarchy.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients

Background

In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks.

Methods

The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy. Cognitive performance was assessed by 10 tests in 5 cognitive domains at a median of 14 months after treatment initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to a cross-validated machine-learning model to identify predictive fiber connections (edges), critical cortical regions (nodes), and the networks underlying cognitive performance.

Results

Compared to healthy controls (n = 121), patients' cognitive scores were significantly lower in 9 cognitive tests. The models predicted the scores of 7/10 tests (median correlation coefficient, 0.47; range, 0.39-0.57) from 0.6% to 5.4% of the matrix entries; 84% of the predictive edges were between nodes of different networks. Critically involved cortical regions (≥10 adjacent edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥15 edges) included the default mode network's left temporal and bilateral posterior cingulate cortex.

Conclusions

These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.

Multi-Modal Learning for Predicting the Genotype of Glioma

The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by integrating focal tumor image and geometric features with brain network features derived from MRI. Convolutional neural networks show reasonable performance in predicting IDH mutation, which, however, cannot learn from non-Euclidean data, e.g., geometric and network data. In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks. To mitigate the limited availability of diffusion MRI, we develop a self-supervised approach to generate brain networks from anatomical multi-sequence MRI. Moreover, to extract tumor-related features from the brain network, we design a hierarchical attention module for the brain network encoder. Further, we design a bi-level multi-modal contrastive loss to align the multi-modal features and tackle the domain gap at the focal tumor and global brain. Finally, we propose a weighted population graph to integrate the multi-modal features for genotype prediction. Experimental results on the testing set show that the proposed model outperforms the baseline deep learning models. The ablation experiments validate the performance of different components of the framework. The visualized interpretation corresponds to clinical knowledge with further validation. In conclusion, the proposed learning framework provides a novel approach for predicting the genotype of glioma.

Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease

This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (Eglob/Eloc) and decreased shortest path lengths (Lp), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (Eglob, Eloc, and Lp) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.

Graph Theory Measures and Their Application to Neurosurgical Eloquence

Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.

Neurovascular coupling changes in patients with magnetic resonance imaging negative focal epilepsy

Brain neuron activity is closely related to cerebral blood flow (CBF) changes. Alterations in the regional homogeneity (ReHo) and CBF occur in patients with magnetic resonance imaging negative focal epilepsy (FEP-MRI^-). However, the coupling alterations of ReHo and CBF in FEP-MRI^- remain unclear. The study aims to explore neurovascular coupling alterations and their clinical implication in FEP-MRI^-. We collected resting-state magnetic resonance imaging (MRI) data from 31 healthy controls (HCs) and 48 patients with FEP-MRI^-,including three-dimensional (3D) T1-weighted imaging, 3D arterial spin labeling (ASL) imaging,and resting-state functional MRI (rs-fMRI). The CBF and ReHo values were calculated from the ASL and rs-fMRI data, respectively. The CBF/ReHo ratio per voxel and whole-brain CBF-ReHo coupling were compared between the two groups. Correlation analysis involved the CBF/ReHo ratio and clinical indicators in FEP-MRI^-. Patients with FEP-MRI^- showed significantly increased cross-subject CBF-ReHo and global cross-voxel CBF-ReHo coupling. The CBF/ReHo ratio was higher in the bilateral orbitofrontal gyrus, right parietal lobe, and right middle frontal gyrus of patients with FEP-MRI^-. Nevertheless, this ratio was lower in the bilateral supplementary motor areas, the left middle and posterior cingulate gyrus, and the right central sulcus cover. The CBF/ReHo ratio was markedly correlated with cognitive function, memory, intelligence, and epilepsy duration in the above abnormal brain regions. CBF/ReHo ratio may be useful as an indicator of neuropathological mechanisms. These results support the hypothesis that CBF/ReHo ratio relates to the neuropathological mechanisms of FEP-MRI^-. Furthermore, it offers new perspectives for studying the mechanisms of MRI-negative epilepsy.

Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy

Introduction

Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment.

Methods

In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group.

Results

Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (E_glo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of E_glo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group.

Conclusion

These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.

Functional network alterations in young brain tumor patients with radiotherapy-induced memory impairments and vascular injury

Background

Cognitive impairment and cerebral microbleeds (CMBs) are long-term side-effects of cranial radiation therapy (RT). Previously we showed that memory function is disrupted in young patients and that the rate of cognitive decline correlates with CMB development. However, vascular injury alone cannot explain RT-induced cognitive decline. Here we use resting-state functional MRI (rsfMRI) to further investigate the complex mechanisms underlying memory impairment after RT.

Methods

Nineteen young patients previously treated with or without focal or whole-brain RT for a brain tumor underwent cognitive testing followed by 7T rsfMRI and susceptibility-weighted imaging for CMB detection. Global brain modularity and efficiency, and rsfMRI signal variability within the dorsal attention, salience, and frontoparietal networks were computed. We evaluated whether MR metrics could distinguish age- and sex-matched controls (N = 19) from patients and differentiate patients based on RT exposure and aggressiveness. We also related MR metrics with memory performance, CMB burden, and risk factors for cognitive decline after RT.

Results

Compared to controls, patients exhibited widespread hyperconnectivity, similar modularity, and significantly increased efficiency (p < 0.001) and network variability (p < 0.001). The most abnormal values were detected in patients treated with high dose whole-brain RT, having supratentorial tumors, and who did not undergo RT but had hydrocephalus. MR metrics and memory performance were correlated (R = 0.34–0.53), though MR metrics were more strongly related to risk factors for cognitive worsening and CMB burden with evidence of functional recovery.

Conclusions

MR metrics describing brain connectivity and variability represent promising candidate imaging biomarkers for monitoring of long-term cognitive side-effects after RT.

Stable functional compensation within hippocampal-subregion networks in patients with temporal glioma before and after surgery

Objective

To identify whether tumor invasion of the temporal lobe induces functional compensation of the hippocampal-subregion (HIPsub) network connectivity before surgery, and to further validate the stability of this functional compensation within the HIPsub network in patients with temporal glioma tumor (TTumor) after surgical resection of the tumor.

Methods

In the first cohort, analysis of HIPsub functional connectivity (FC) was conducted to identify the functional compensation of the altered HIPsub connectivity pattern in TTumor through a pattern classification approach. Then, the second cohort investigated whether functional compensation in TTumor patients changed after surgical resection of the tumor.

Results

In the first cohort, this study identified altered HIPsub network connectivity patterns and its functional compensation regions (i.e., left parahippocampal gyrus and bilateral cerebellum anterior lobe) in TTumor patients. Second, the altered HIPsub network connectivity patterns had the power to discriminate TTumor patients from healthy controls (CN) on an individual subject basis, with an AUC of 97.0%, sensitivity of 93.5%, and specificity of 90.3%. Finally, in the second cohort, we found that functional connectivities of functional compensation regions within the HIPsub network in TTumor patients did not change between before and after surgery.

Conclusion

This study provides novel evidence regarding functional compensation within the HIPsub network in TTumor patients. It has been suggested that the fine hippocampal subregion was more sensitive, which reveals functional compensation induced by tumor invasion of the temporal lobe. Furthermore, this study verified the stability and persistence of this functional compensation in TTumor patients after surgical resection of the tumor.

Interleukin-6-white matter network differences explained the susceptibility to depression after stressful life events

BACKGROUND

Stressful life events (SLEs) are well-established proximal predictors of the onset of depression. However, the fundamental causes of interindividual differences in depression outcomes are poorly understood. This study addressed this depression susceptibility mechanism using a well-powered sample of adults living in China.

METHODS

Healthy participants with SLEs (n = 185; mean = 47.51 years, 49.73% female), drawn from a longitudinal study on the development of depression, underwent diffusion tensor imaging, interleukin-6 (IL-6) level measurement, and trimonthly standardized clinical and scale evaluations within a two-year period.

RESULTS

Receiver operating characteristic analyses indicated that reduced feeder connection and HIP.R nodal efficiency improved the predictive accuracy of post-SLEs depression (OR_feeder = 0.623, AUC = 0.869, P < 0.001; OR_HIP = 0.459, AUC = 0.855, P < 0.001). The successfully established path analysis model confirmed the significant partial effect of SLEs-IL-6-white matter (WM) network differences-depression (onset and severity) (x²/8 = 1.453, goodness-of-fit [GFI] = 0.935, standard root-mean-square error of approximation [SRMR] = 0.024). Females, individuals with lower exercise frequency (EF) or annual household income (AHI) were more likely to have higher IL-6 level after SLEs (β_{int-female⁎SLEs} = -0.420, P < 0.001; β_{int-exercise⁎SLEs} = -0.412, P < 0.001; β_{int-income⁎SLEs} = -0.302, P = 0.005).

LIMITATIONS

The sample size was restricted due to the limited incidence rate and prospective follow-up design.

CONCLUSIONS

Our results suggested that among healthy adults after SLEs, those who exhibited abnormal IL-6-WM differences were susceptible to developing depression. Females, lower AHI or EF might account for an increased risk of developing these abnormal IL-6-WM differences.

Neuroplasticity of Glioma Patients: Brain Structure and Topological Network

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.

Altered static and dynamic voxel-mirrored homotopic connectivity in patients with frontal glioma

Contralateral regions play critical role in functional compensation in glioma patients. Voxel-mirrored homotopic connectivity (VMHC) characterizes the intrinsic functional connectivity (FC) of the brain, considered to have a regional functional basis. We aimed to investigate the alterations of brain regional function and VMHC in patients with frontal glioma, and further investigated the correlation between these alterations and cognition. We enrolled patients with frontal glioma and matched healthy controls (HC). We chose degree centrality (DC), regional homogeneity (ReHo), and VMHC to investigate the alterations of regional function and intrinsic FC in patients. Furthermore, partial correlation analyses were conducted to explore the relationship between imaging functional indicators and cognitions. Compared with HC, patients showed decreased static VMHC within right and left middle frontal gyrus (MFG.R, MFG.L), left superior frontal gyrus (SFG.L), right precuneus (PCUN.R), and left precuneus (PCUN.L), decreased static DC within left cingulate gyrus (CG.L), right superior frontal gyrus (SFG.R), and right postcentral gyrus (POCG.R), decreased static ReHo within CG.L, decreased dynamic ReHo within right inferior parietal lobule (IPL.R), but increased dynamic VMHC (dVMHC) within PCUN.R and PCUN.L. Furthermore, values of decreased VMHC within MFG.R, decreased DC within CG.L, decreased ReHo within CG.L, and increased dVMHC within PCUN.R were significantly positively correlated with cognitive functions. We preliminarily confirmed glioma causes regional dysfunction and disturbs long-distance FC, and long-distance FC showed strong instability in patients with frontal glioma. Meanwhile, the correlation analyses indicated directions for cognitive protection in patients with frontal glioma.

Decreased Functional Connectivities of Low-Degree Level Rich Club Organization and Caudate in Post-stroke Cognitive Impairment Based on Resting-State fMRI and Radiomics Features

Background

Stroke is an important cause of cognitive impairment. Rich club organization, a highly interconnected network brain core region, is closely related to cognition. We hypothesized that the disturbance of rich club organization exists in patients with post-stroke cognitive impairment (PSCI).

Methods

We collected data on resting-state functional magnetic resonance imaging (rs-fMRI) with 21 healthy controls (HC), 16 hemorrhagic stroke (hPSCI), and 21 infarct stroke (iPSCI). 3D shape features and first-order statistics of stroke lesions were extracted using 3D slicer software. Additionally, we assessed cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE).

Results

Normalized rich club coefficients were higher in hPSCI and iPSCI than HC at low-degree k-levels (k = 1–8 in iPSCI, k = 2–8 in hPSCI). Feeder and local connections were significantly decreased in PSCI patients versus HC, mainly distributed in salience network (SN), default-mode network (DMN), cerebellum network (CN), and orbitofrontal cortex (ORB), especially involving the right and left caudate with changed nodal efficiency. The feeder and local connections of significantly between-group difference were positively related to MMSE and MoCA scores, primarily distributed in the sensorimotor network (SMN) and visual network (VN) in hPSCI, SN, and DMN in iPSCI. Additionally, decreased local connections and low-degree ϕnorm(k) were correlated to 3D shape features and first-order statistics of stroke lesions.

Conclusion

This study reveals the disrupted low-degree level rich club organization and relatively preserved functional core network in PSCI patients. Decreased feeder and local connections in cognition-related networks (DMN, SN, CN, and ORB), particularly involving the caudate nucleus, may offer insight into pathological mechanism of PSCI patients. The shape and signal features of stroke lesions may provide an essential clue for the damage of functional connectivity and the whole brain networks.

Neurocognition and Health-Related Quality of Life Among Patients with Brain Tumors

Patients with brain tumors experience great symptom burden across various domains of functioning, with associated decreases in health-related quality of life and general well-being. Impaired neurocognitive functioning is among the primary concerns of these patients. Unfortunately, most patients will experience such impairment at some point in the disease. However, impaired neurocognitive functioning, symptom burden, and well-being vary according numerous patient-, tumor-, and treatment-related factors. Recent work has furthered our understanding of these contributors to patient functioning and health-related quality of life and also points to various potential targets for prevention and intervention strategies, though more efficacious treatments remain needed.

Impaired neurocognitive function in glioma patients: from pathophysiology to novel intervention strategies

PURPOSE OF REVIEW

This review succinctly summarizes the recent literature regarding etiological contributors to impaired neurocognitive function (NCF) in adult patients with glioma. A brief overview of intervention and prevention strategies is also provided.

RECENT FINDINGS

A majority of patients with glioma exhibit NCF deficits, most frequently in memory and executive functioning. Impairments are often disabling and associated with reduced quality of life and survival. Cause is multifactorial and includes the tumour itself, treatments received and associated comorbidities. Although modern techniques such as brain mapping, dosing modifications and prophylactic medication aim to improve the NCF outcomes following neurosurgical resection and radiation therapy, a sizeable proportion of patients continue to evidence treatment-related NCF declines related to adverse effects to both local and distributed cerebral networks. Numerous patient and tumour characteristics, including genetic markers and sociodemographic factors, influence the pattern and severity of NCF impairment. Some rehabilitative and pharmacologic approaches show promise in mitigating NCF impairment in this population, though benefits are somewhat modest and larger scale intervention studies are needed.

SUMMARY

Research regarding NCF in patients with glioma has dramatically proliferated, providing insights into the mechanisms underlying impaired NCF and pointing to potential interventions, though further work is needed.

Structural and Functional Reorganization Within Cognitive Control Network Associated With Protection of Executive Function in Patients With Unilateral Frontal Gliomas

Background: The cognitive control network (CCN) is widely considered to be a frontoparietal circuit that is involved in executive function. This study aimed to investigate the structural and functional plasticity within the CCN in unilateral frontal gliomas, which are associated with the protection of executive functions.

Methods: To detect structural and functional changes within the CCN, we measured gray matter (GM) volume, regional homogeneity, the amplitude of low-frequency fluctuation (ALFF), degree centrality, and functional connectivity within the CCN in 37 patients with gliomas invading the left frontal lobe (n = 16) or the right frontal lobe (n = 21) and 40 healthy controls (CNs). Partial correlation analysis was performed to assess the association between the altered structural and functional indices and executive function.

Results: When the tumor invaded the left frontal lobe, the patients showed reduced ALFF in the dorsal medial prefrontal cortex (dmPFC) within the CCN and increased ALFF in the right superior parietal cortex (rSP) within the CCN compared to the CNs. When the tumor invaded the right frontal lobe, the patients showed significantly increased GM volume and ALFF in the left superior parietal cortex (lSP) within the CCN compared to the CNs. Furthermore, the patients showed significantly increased functional connectivities between the lSP and the dmPFC and between the lSP and the rSP within the CCN compared to the CNs. Increased ALFF in the lSP within the CCN was positively correlated with executive function.

Conclusions: Tumors invading the frontal lobe induced contralesional structural and functional reorganization within the posterior CCN in patients with unilateral frontal gliomas. This further suggests that the contralesional superior parietal cortex acts as a functional compensation hub within the CCN, which may protect it against the detrimental effects of tumor invasion on executive functions.