Modifications of default-mode network connectivity in patients with cerebral glioma

Local Glioma Cells Are Associated with Vascular Dysregulation

BACKGROUND AND PURPOSE

Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level-dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level-dependent biomarker of vascular dysregulation.

MATERIALS AND METHODS

Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level-dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level-dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density.

RESULTS

Biopsies corresponded to a range of blood oxygen level-dependent signals, ranging from relatively normal (z = -4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level-dependent signal abnormality (P = .013, R² = 0.19), while the neuronal labeling index was inversely related to blood oxygen level-dependent signal abnormality (P = .016, R² = 0.21). The blood oxygen level-dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045).

CONCLUSIONS

The relationship between local, neoplastic characteristics and a blood oxygen level-dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.

Neuroaging through the Lens of the Resting State Networks

Resting state functional magnetic resonance imaging (rs-fMRI) allows studying spontaneous brain activity in absence of task, recording changes of Blood Oxygenation Level Dependent (BOLD) signal. rs-fMRI enables identification of brain networks also called Resting State Networks (RSNs) including the most studied Default Mode Network (DMN). The simplicity and speed of execution make rs-fMRI applicable in a variety of normal and pathological conditions. Since it does not require any task, rs-fMRI is particularly useful for protocols on patients, children, and elders, increasing participant's compliance and reducing intersubjective variability due to the task performance. rs-fMRI has shown high sensitivity in identification of RSNs modifications in several diseases also in absence of structural modifications. In this narrative review, we provide the state of the art of rs-fMRI studies about physiological and pathological aging processes. First, we introduce the background of resting state; then we review clinical findings provided by rs-fMRI in physiological aging, Mild Cognitive Impairment (MCI), Alzheimer Dementia (AD), and Late Life Depression (LLD). Finally, we suggest future directions in this field of research and its potential clinical applications.

How much is enough-Can resting state fMRI provide a demarcation for neurosurgical resection in glioma?

This study represents a systematic review of the insights provided by resting state functional MRI (rs-fMRI) use in the glioma population. Following PRISMA guidelines, 45 studies were included in the review and were classified in glioma-related neuronal changes (n=28) and eloquent area localization (n=17). Despite the heterogeneous nature of the studies, there is considerable evidence of diffuse functional reorganization occurring in the setting of gliomas with local and interhemispheric functional connectivity alterations involving different functional networks. The studies showed evidence of decreased long distance functional connectivity and increased global local efficiency occurring in the setting of gliomas. The tumour grade seems to correlate with distinct functional connectivity changes. Overall, there is a potential clinical utility of rs-fMRI for identifying the functional brain network disruptions occurring in the setting of gliomas. Further studies utilizing standardized analytical methods are required to elucidate the mechanism through which gliomas induce global changes in brain connectivity.

Functional MRI for Surgery of Gliomas

PURPOSE OF REVIEW

Advanced neuroimaging techniques such as functional MRI (fMRI) and diffusion MR tractography have been increasingly used at every stage of the surgical management of brain gliomas, as a means to improve tumor resection while preserving brain functions. This review provides an overview of the last advancements in the field of functional MRI techniques, with a particular focus on their current clinical use and reliability in the preoperative and intraoperative setting, as well as their future perspectives for personalized multimodal management of patients with gliomas.

RECENT FINDINGS

fMRI and diffusion MR tractography give relevant insights on the anatomo-functional organization of eloquent cortical areas and subcortical connections near or inside a tumor. Task-based fMRI and diffusion tensor imaging (DTI) tractography have proven to be valid and highly sensitive tools for localizing the distinct eloquent cortical and subcortical areas before surgery in glioma patients; they also show good accuracy when compared with intraoperative stimulation mapping data. Resting-state fMRI functional connectivity as well as new advanced HARDI (high angular resolution diffusion imaging) tractography methods are improving and reshaping the role of functional MRI for surgery of gliomas, with potential benefit for personalized treatment strategies. Noninvasive functional MRI techniques may offer the opportunity to perform a multimodal assessment in brain tumors, to be integrated with intraoperative mapping and clinical data for improving surgical management and oncological and functional outcome in patients affected by gliomas.

The Temporal Pattern of a Lesion Modulates the Functional Network Topology of Remote Brain Regions

Focal brain lesions can alter the morphology and function of remote brain areas. When the damage is inflicted more slowly, the functional compensation by and structural reshaping of these areas seem to be more effective. It remains unclear, however, whether the momentum of lesion development also modulates the functional network topology of the remote brain areas. In this study, we compared resting-state functional connectivity data of patients with a slowly growing low-grade glioma (LGG) with that of patients with a faster-growing high-grade glioma (HGG). Using graph theory, we examined whether the tumour growth velocity modulated the functional network topology of remote areas, more specifically of the hemisphere contralateral to the lesion. We observed that the contralesional network topology characteristics differed between patient groups. Based only on the connectivity of the hemisphere contralateral to the lesion, patients could be classified in the correct tumour-grade group with 70% accuracy. Additionally, LGG patients showed smaller contralesional intramodular connectivity, smaller contralesional ratio between intra- and intermodular connectivity, and larger contralesional intermodular connectivity than HGG patients. These results suggest that, in the hemisphere contralateral to the lesion, there is a lower capacity for local, specialized information processing coupled to a higher capacity for distributed information processing in LGG patients. These results underline the utility of a network perspective in evaluating effects of focal brain injury.

Functional Connectivity in Frontoparietal Network: Indicator of Preoperative Cognitive Function and Cognitive Outcome Following Surgery in Patients with Glioma

BACKGROUND

Patients with diffuse glioma are known to have impaired cognitive functions preoperatively. However, the mechanism of these cognitive deficits remains unclear. Resting-state functional connectivity in the frontoparietal network (FPN) is associated with cognitive performance in healthy subjects. For this reason, it was hypothesized that functional connectivity of the FPN would be related to cognitive functioning in patients with glioma. To assess this relationship, preoperative cognitive status was correlated to patient-specific connectivity within the FPN. Further, we assessed whether connectivity could predict neuropsychologic outcome following surgery.

METHODS

Sixteen patients with diffuse glioma underwent neuropsychologic assessment and preoperative functional magnetic resonance imaging using task (n-back) and resting-state scans. Thirteen patients had postoperative cognitive assessment. An index of patient-specific functional connectivity in the FPN was derived by averaging connectivity values between 2 prefrontal and 2 parietal cortex regions defined by activation during the n-back task. The relationship of these indices with cognitive performance was assessed.

RESULTS

Higher average connectivity within the FPN is associated with lower composite cognitive scores. Higher connectivity of the parietal region of the tumor-affected hemisphere is associated specifically with lower fluid cognition. Lower connectivity of the parietal region of the nontumor hemisphere is associated with worse neuropsychologic outcome 1 month after surgery.

CONCLUSION

Resting-state functional connectivity between key regions of the FPN is associated with cognitive performance in patients with glioma and is related to cognitive outcome following surgery.

Network Plasticity and Intraoperative Mapping for Personalized Multimodal Management of Diffuse Low-Grade Gliomas

Gliomas are the most frequent primary brain tumors and include a variety of different histological tumor types and malignancy grades. Recent achievements in terms of molecular and imaging fields have created an unprecedented opportunity to perform a comprehensive interdisciplinary assessment of the glioma pathophysiology, with direct implications in terms of the medical and surgical treatment strategies available for patients. The current paradigm shift considers glioma management in a comprehensive perspective that takes into account the intricate connectivity of the cerebral networks. This allowed significant improvement in the outcome of patients with lesions previously considered inoperable. The current review summarizes the current theoretical framework integrating the adult human brain plasticity and functional reorganization within a dynamic individualized treatment strategy for patients affected by diffuse low-grade gliomas. The concept of neuro-oncology as a brain network surgery has major implications in terms of the clinical management and ensuing outcomes, as indexed by the increased survival and quality of life of patients managed using such an approach.

Connectomic profile and clinical phenotype in newly diagnosed glioma patients

Gliomas are primary brain tumors, originating from the glial cells in the brain. In contrast to the more traditional view of glioma as a localized disease, it is becoming clear that global brain functioning is impacted, even with respect to functional communication between brain regions remote from the tumor itself. However, a thorough investigation of glioma-related functional connectomic profiles is lacking. Therefore, we constructed functional brain networks using functional MR scans of 71 glioma patients and 19 matched healthy controls using the automated anatomical labelling (AAL) atlas and interregional Pearson correlation coefficients. The frequency distributions across connectivity values were calculated to depict overall connectomic profiles and quantitative features of these distributions (full-width half maximum (FWHM), peak position, peak height) were calculated. Next, we investigated the spatial distribution of the connectomic profile. We defined hub locations based on the literature and determined connectivity (1) between hubs, (2) between hubs and non-hubs, and (3) between non-hubs. Results show that patients had broader and flatter connectivity distributions compared to controls. Spatially, glioma patients particularly showed increased connectivity between non-hubs and hubs. Furthermore, connectivity distributions and hub-non-hub connectivity differed within the patient group according to tumor grade, while relating to Karnofsky performance status and progression-free survival. In conclusion, newly diagnosed glioma patients have globally altered functional connectomic profiles, which mainly affect hub connectivity and relate to clinical phenotypes. These findings underscore the promise of using connectomics as a future biomarker in this patient population.

A method for safely resecting anterior butterfly gliomas: the surgical anatomy of the default mode network and the relevance of its preservation

OBJECTIVE

Gliomas invading the anterior corpus callosum are commonly deemed unresectable due to an unacceptable risk/benefit ratio, including the risk of abulia. In this study, the authors investigated the anatomy of the cingulum and its connectivity within the default mode network (DMN). A technique is described involving awake subcortical mapping with higher attention tasks to preserve the cingulum and reduce the incidence of postoperative abulia for patients with so-called butterfly gliomas.

METHODS

The authors reviewed clinical data on all patients undergoing glioma surgery performed by the senior author during a 4-year period at the University of Oklahoma Health Sciences Center. Forty patients were identified who underwent surgery for butterfly gliomas. Each patient was designated as having undergone surgery either with or without the use of awake subcortical mapping and preservation of the cingulum. Data recorded on these patients included the incidence of abulia/akinetic mutism. In the context of the study findings, the authors conducted a detailed anatomical study of the cingulum and its role within the DMN using postmortem fiber tract dissections of 10 cerebral hemispheres and in vivo diffusion tractography of 10 healthy subjects.

RESULTS

Forty patients with butterfly gliomas were treated, 25 (62%) with standard surgical methods and 15 (38%) with awake subcortical mapping and preservation of the cingulum. One patient (1/15, 7%) experienced postoperative abulia following surgery with the cingulum-sparing technique. Greater than 90% resection was achieved in 13/15 (87%) of these patients.

CONCLUSIONS

This study presents evidence that anterior butterfly gliomas can be safely removed using a novel, attention-task based, awake brain surgery technique that focuses on preserving the anatomical connectivity of the cingulum and relevant aspects of the cingulate gyrus.

Transient effects of tumor location on the functional architecture at rest in glioblastoma patients: three longitudinal case studies

Background

The cognitive function of brain tumor patients is affected during the treatment. There is evidence that gliomas and surgery alter the functional brain connectivity but studies on the longitudinal effects are lacking.

Methods

We acquired longitudinal (pre- and post-radiotherapy) resting-state functional magnetic resonance imaging on three selected glioblastoma patients. These cases were selected to study three models: a lesion involving a functional hub within a central system, a lesion involving a peripheral node within a central system and a lesion involving a peripheral node of a non-central system.

Results

We found that, as expected, the tumor lesion affects connections in close vicinity, but when the lesion relates to a functional hub, these changes involve long-range connections leading to diverse connectivity profiles pre- and post-radiotherapy. In particular, a global but temporary improvement in the post-radiotherapy connectivity was obtained when treating a lesion close to a network hub, such as the posterior Cingulate Cortex.

Conclusions

This suggests that this node re-establishes communication to nodes further away in the network. Eventually, these observed effects seem to be transient and on the long-term the tumor burden leads to an overall decline of connectivity following the course of the pathology. Furthermore, we obtained that the link between hubs, such as the Supplementary Motor Area and posterior Cingulate Cortex represents an important backbone by means of which within and across network communication is handled: the disruption of this connection seems to imply a strong decrease in the overall connectivity.

Altered Vision-Related Resting-State Activity in Pituitary Adenoma Patients with Visual Damage

Objective

To investigate changes of vision-related resting-state activity in pituitary adenoma (PA) patients with visual damage through comparison to healthy controls (HCs).

Methods

25 PA patients with visual damage and 25 age- and sex-matched corrected-to-normal-vision HCs underwent a complete neuro-ophthalmologic evaluation, including automated perimetry, fundus examinations, and a magnetic resonance imaging (MRI) protocol, including structural and resting-state fMRI (RS-fMRI) sequences. The regional homogeneity (ReHo) of the vision-related cortex and the functional connectivity (FC) of 6 seeds within the visual cortex (the primary visual cortex (V1), the secondary visual cortex (V2), and the middle temporal visual cortex (MT+)) were evaluated. Two-sample t-tests were conducted to identify the differences between the two groups.

Results

Compared with the HCs, the PA group exhibited reduced ReHo in the bilateral V1, V2, V3, fusiform, MT+, BA37, thalamus, postcentral gyrus and left precentral gyrus and increased ReHo in the precuneus, prefrontal cortex, posterior cingulate cortex (PCC), anterior cingulate cortex (ACC), insula, supramarginal gyrus (SMG), and putamen. Compared with the HCs, V1, V2, and MT+ in the PAs exhibited decreased FC with the V1, V2, MT+, fusiform, BA37, and increased FC primarily in the bilateral temporal lobe (especially BA20,21,22), prefrontal cortex, PCC, insular, angular gyrus, ACC, pre-SMA, SMG, hippocampal formation, caudate and putamen. It is worth mentioning that compared with HCs, V1 in PAs exhibited decreased or similar FC with the thalamus, whereas V2 and MT+ exhibited increased FCs with the thalamus, especially pulvinar.

Conclusions

In our study, we identified significant neural reorganization in the vision-related cortex of PA patients with visual damage compared with HCs. Most subareas within the visual cortex exhibited remarkable neural dysfunction. Some subareas, including the MT+ and V2, exhibited enhanced FC with the thalamic pulvinar, which indicates an important role in the compensatory mechanism following visual impairment. In addition, neural dysfunction within the visual cortex was associated with neural activity alternation in the higher-order cognitive cortex, especially subareas in default mode network (DMN) and salience network (SN).

The Influence of Frontal Lobe Tumors and Surgical Treatment on Advanced Cognitive Functions

Brain cognitive functions affect patient quality of life. The frontal lobe plays a crucial role in advanced cognitive functions, including executive function, meta-cognition, decision-making, memory, emotion, and language. Therefore, frontal tumors can lead to serious cognitive impairments. Currently, neurosurgical treatment is the primary method to treat brain tumors; however, the effects of the surgical treatments are difficult to predict or control. The treatment may both resolve the effects of the tumor to improve cognitive function or cause permanent disabilities resulting from damage to healthy functional brain tissue. Previous studies have focused on the influence of frontal lesions and surgical treatments on patient cognitive function. Here, we review cognitive impairment caused by frontal lobe brain tumors.

Use of Network Analysis to Establish Neurosurgical Parameters in Gliomas and Epilepsy

Cutting-edge neuroimaging technologies can facilitate preoperative evaluation in various neurosurgical settings. Surgery for gliomas and epilepsy requires precise localization for resection due to the need to preserve (or perhaps improve) higher cognitive functions. Accordingly, a hodological approach should be taken that considers subcortical networks as well as cortical functions within various functional domains. Resting state functional magnetic resonance imaging (fMRI) has the potential to provide new insights that are valuable for this approach. In this review, we describe recent developments in network analysis using resting state fMRI related to factors in glioma and epilepsy surgery: the identification of functionally dominant areas, evaluation of cognitive function by alteration of resting state networks (RSNs), glioma grading, and epileptic focus detection. One particular challenge that is close to realization is using fMRI for the identification of sensorimotor- and language-dominant areas during a task-free resting state. Various RSNs representative of the default mode network demonstrated at least some alterations in both patient groups, which correlated with behavioral changes including cognition, memory, and attention, and the development of psychosis. Still challenging is the detection of epileptic foci and propagation pathways when using only network analysis with resting state fMRI; however, a combined method with simultaneous electroencephalography has produced promising results. Consequently, network analysis is expected to continue to advance as neuroimaging technology improves in the next decade, and preoperative evaluation for neurosurgical parameters through these techniques should improve parallel with them.

Neural network alterations underlie cognitive deficits in brain tumor patients

PURPOSE OF REVIEW

Brain tumor patients suffer from cognitive deficits, regardless of tumor grade or location. Deficits have a general character, falling in the domains of attention, working memory, information processing speed, and executive functioning. This review explores a new, brain network-based view of these deficits in brain tumor patients.

RECENT FINDINGS

Network theory has evolved within the fields of mathematics and sociology and has resulted in its application to many complex systems, such as social networks, traffic flow networks, and biological protein networks. In the brain, a network can be constructed by assessing either functional or anatomical connections between brain areas, and subsequently extracting their overarching network patterns. Important brain network features are local specialization, operationalized by local clustering, and global integration or path length. Widespread disturbances in network topology are found in brain tumor patients, which relate to their cognitive problems. Furthermore, changes in network topology in response to oncological interventions, particularly tumor resection, go hand in hand with cognitive outcome.

SUMMARY

Cognitive deficits in brain tumor patients are reflected in whole-brain network disturbances. Possible future clinical use of these findings mostly concerns prognostics and tailoring treatment strategies.

Evaluation of resting state networks in patients with gliomas: connectivity changes in the unaffected side and its relation to cognitive function

In this study, we investigated changes in resting state networks (RSNs) in patients with gliomas located in the left hemisphere and its relation to cognitive function. We hypothesized that long distance connection, especially between hemispheres, would be affected by the presence of the tumor. We further hypothesized that these changes would correlate with, or reflect cognitive changes observed in patients with gliomas. Resting state functional MRI datasets from 12 patients and 12 healthy controls were used in the analysis. The tumor’s effect on three well-known RSNs including the default mode network (DMN), executive control network (ECN), and salience network (SN) identified using independent component analysis were investigated using dual regression analysis. Scores of neuropsychometric testing (WAIS-III and WMS-R) were also compared. Compared to the healthy control group, the patient group showed significant decrease in functional connectivity in the right angular gyrus/inferior parietal lobe of the ventral DMN and in the dorsolateral prefrontal cortex of the left ECN, whereas a significant increase in connectivity in the right ECN was observed in the right parietal lobe. Changes in connectivity in the right ECN correlated with spatial memory, while that on the left ECN correlated with attention. Connectivity changes in the ventral DMN correlated with attention, working memory, full IQ, and verbal IQ measures. Although the tumors were localized in the left side of the brain, changes in connectivity were observed in the contralateral side. Moreover, these changes correlated with some aspects of cognitive function indicating that patients with gliomas may undergo cognitive changes even in the absence of or before the onset of major symptoms. Evaluation of resting state networks could be helpful in advancing our hodological understanding of brain function in glioma cases.

Resting state fMRI feature-based cerebral glioma grading by support vector machine

PURPOSE : Tumor grading plays an essential role in the optimal selection of solid tumor treatment. Noninvasive methods are needed for clinical grading of tumors. This study aimed to extract parameters of resting state blood oxygenation level-dependent functional magnetic resonance imaging (RS-fMRI) in the region of glioma and use the extracted features for tumor grading. METHODS : Tumor segmentation was performed with both conventional MRI and RS-fMRI. Four typical parameters, signal intensity difference ratio, signal intensity correlation (SIC), fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), were defined to analyze tumor regions. Mann-Whitney [Formula: see text] test was employed to identify statistical difference of these four parameters between low-grade glioma (LGG) and high-grade glioma (HGG), respectively. Support vector machine (SVM) was employed to assess the diagnostic contributions of these parameters. RESULTS : Compared with LGG, HGG had more complex anatomical morphology and BOLD-fMRI features in the tumor region. SIC [Formula: see text], fALFF ([Formula: see text]) and ReHo ([Formula: see text]) were selected as features for classification according to the test [Formula: see text] value. The accuracy, sensitivity and specificity of SVM classification were better than 80, where SIC had the best classification accuracy (89). CONCLUSION : Parameters of RS-fMRI are effective to classify the tumor grade in glioma cases. The results indicate that this technique has clinical potential to serve as a complementary diagnostic tool.

Motor network plasticity and low-frequency oscillations abnormalities in patients with brain gliomas: a functional MRI study

Brain plasticity is often associated with the process of slow-growing tumor formation, which remodels neural organization and optimizes brain network function. In this study, we aimed to investigate whether motor function plasticity would display deficits in patients with slow-growing brain tumors located in or near motor areas, but who were without motor neurological deficits. We used resting-state functional magnetic resonance imaging to probe motor networks in 15 patients with histopathologically confirmed brain gliomas and 15 age-matched healthy controls. All subjects performed a motor task to help identify individual motor activity in the bilateral primary motor cortex (PMC) and supplementary motor area (SMA). Frequency-based analysis at three different frequencies was then used to investigate possible alterations in the power spectral density (PSD) of low-frequency oscillations. For each group, the average PSD was determined for each brain region and a nonparametric test was performed to determine the difference in power between the two groups. Significantly reduced inter-hemispheric functional connectivity between the left and right PMC was observed in patients compared with controls (P<0.05). We also found significantly decreased PSD in patients compared to that in controls, in all three frequency bands (low: 0.01-0.02 Hz; middle: 0.02-0.06 Hz; and high: 0.06-0.1 Hz), at three key motor regions. These findings suggest that in asymptomatic patients with brain tumors located in eloquent regions, inter-hemispheric connection may be more vulnerable. A comparison of the two approaches indicated that power spectral analysis is more sensitive than functional connectivity analysis for identifying the neurological abnormalities underlying motor function plasticity induced by slow-growing tumors.

Structural and functional effects of metastases in rat brain determined by multimodal MRI

Metastasis to the brain results in significant impairment of brain function and poor patient survival. Currently, magnetic resonance imaging (MRI) is under-utilised in monitoring brain metastases and their effects on brain function. Here, we sought to establish a model of focal brain metastasis in the rat that enables serial multimodal structural and functional MRI studies, and to assess the sensitivity of these approaches to metastatic growth. Female Berlin-Druckrey-IX rats were injected intracerebrally with metastatic ENU1564 cells in the ventroposterior medial nucleus (VPM) of the thalamus, a relay node of the whisker-to-barrel cortex pathway. Animals underwent multimodal structural and vascular MRI, as well as functional MRI of the cortical blood oxygenation level dependent (BOLD) responses to whisker pad stimulation. T2 , diffusion, magnetisation transfer and perfusion weighted MRI enabled differentiation between a central area of more advanced metastatic growth and penumbral regions of co-optive perivascular micrometastatic growth, with magnetisation transfer MRI being the most sensitive to micrometastatic growth. Areas of cortical BOLD activation in response to whisker pad stimulation were significantly reduced in the hemisphere containing metastases in the VPM. The reduction in BOLD response correlated with metastatic burden in the thalamus, and was sensitive to the presence of smaller metastases than currently detectable clinically. Our findings suggest that multimodal MRI provides greater sensitivity to tumour heterogeneity and micrometastatic growth than single modality contrast-enhanced MRI. Understanding the relationships between these MRI parameters and the underlying pathology may greatly enhance the utility of MRI in diagnosis, staging and monitoring of brain metastasis.

Pathological neural attractor dynamics in slowly growing gliomas supports an optimal time frame for white matter plasticity

Neurological function in patients with slowly growing brain tumors can be preserved even after extensive tumor resection. However, the global process of cortical reshaping and cerebral redistribution cannot be understood without taking into account the white matter tracts. The aim of this study was to predict the functional consequences of tumor-induced white matter damage by computer simulation. A computational model was proposed, incorporating two cortical patches and the white matter connections of the uncinate fasciculus. Tumor-induced structural changes were modeled such that different aspects of the connectivity were altered, mimicking the biological heterogeneity of gliomas. The network performance was quantified by comparing memory pattern recall and the plastic compensatory capacity of the network was analyzed. The model predicts an optimal level of synaptic conductance boost that compensates for tumor-induced connectivity loss. Tumor density appears to change the optimal plasticity regime, but tumor size does not. Compensatory conductance values that are too high lead to performance loss in the network and eventually to epileptic activity. Tumors of different configurations show differences in memory recall performance with slightly lower plasticity values for dense tumors compared to more diffuse tumors. Simulation results also suggest an optimal noise level that is capable of increasing the recall performance in tumor-induced white matter damage. In conclusion, the model presented here is able to capture the influence of different tumor-related parameters on memory pattern recall decline and provides a new way to study the functional consequences of white matter invasion by slowly growing brain tumors.