Resting-State Electroencephalography Functional Connectivity Networks Relate to Pre- and Postoperative Language Functioning in Low-Grade Glioma and Meningioma Patients

Wolthuis, Nienke; Satoer, Djaina; Veenstra, Wencke S.; Smits, Marion; Wagemakers, Michiel; Vincent, Arnaud; Bastiaanse, Roelien; Cherian, Perumpillichira J.; Bosma, Ingeborg

doi:10.3389/fnins.2021.785969

Cited by 4 publications

(11 citation statements)

References 51 publications

(93 reference statements)

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“…To try and compensate, BOLD correlations between regions would rearrange themselves to spare the functionality. Network similarities and topologies across subjects would change, as found by previous studies [1, 2, 36, 3], without significantly altering their complexity. However, DASs could not disentangle whether the tumor altered the signal and that alteration spread to the DMN or the opposite.…”

Section: Discussionmentioning

confidence: 58%

“…The integrity of resting-state activity of the brain has been associated with cognitive function [6]. Based on this paradigm, numerous studies have explored how functional damage translates into cognitive impairment [4, 5, 1, 35, 3]. As a clear demonstration of the resilience of the brain to damage, all of them reported a continuous rather than binary decrease in cognitive performance.…”

Section: Discussionmentioning

confidence: 99%

“…For this purpose, we designed a Dynamics Alteration Score (DAS) that can capture not only how different two power distributions are, but also how these differences are related with the relative dynamics of those signals (see Methods; see also The integrity of resting-state activity of the brain has been associated with cognitive function [6]. Based on this paradigm, numerous studies have explored how functional damage translates into cognitive impairment [4,5,1,36,3]. As a clear demonstration of the resilience of the brain to damage, all of them reported a continuous rather than binary decrease in cognitive performance.…”

Section: Discussionmentioning

confidence: 99%

“…Brain networks undergo rearrangement to minimize the impact of lesions, and this rewiring follows specific constraints [24,36]. From electroencephalography recordings, Wolthuis and colleagues found the level of topological similarity to be predictive of post-surgery cognitive skills [35], suggesting once again that understanding how the brain responds to lesions is crucial to predict the impact of surgical procedures on cognitive function. To this purpose, we computed the complexity of the DMN and found significant alterations in magnitude with variable directionality across patients.…”

Section: Alterations In Local Oscillations Are Related To Distributed...mentioning

confidence: 99%

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Structural Reorganization Following a Brain Tumor: A Machine Learning Study Considering Desynchronized Functional Oscillations

Falcó-Roget¹,

Sambataro

Cacciola

et al. 2022

Preprint

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Neuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and oedema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals and structures and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find that intra-tumor signals do exist and are correlated with alterations present both in healthy tissue and resting-state networks. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patters of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.

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Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Alterations In Local Oscillations Are Related To Distributed...mentioning

confidence: 99%

See 2 more Smart Citations

Structural Reorganization Following a Brain Tumor: A Machine Learning Study Considering Desynchronized Functional Oscillations

Falcó-Roget¹,

Sambataro

Cacciola

et al. 2022

Preprint

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show abstract

“…The integrity of resting-state activity of the brain has been associated with cognitive function 6 . Based on this paradigm, numerous studies have explored how functional damage translates into cognitive impairment 1 , 3 – 5 , 35 . As a clear demonstration of the resilience of the brain to damage, all of them reported a continuous rather than binary decrease in cognitive performance.…”

Section: Discussionmentioning

confidence: 99%

Functional and structural reorganization in brain tumors: a machine learning approach using desynchronized functional oscillations

Falcó-Roget,

Cacciola,

Sambataro

et al. 2024

Commun Biol

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Neuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and edema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals, structures, and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore the functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find intertwined alterations in the frequency domain of local and spatially distributed resting-state functional signals, potentially arising within the tumor. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patterns of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.

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Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales

Maas,

Douw

2023

Neuro-Oncology Practice

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Network neuroscience refers to the investigation of brain networks across different spatial and temporal scales, and has become a leading framework to understand the biology and functioning of the brain. In neuro-oncology, the study of brain networks has revealed many insights into the structure and function of cells, circuits, and the entire brain, and their association with both functional status (e.g., cognition) and survival. This review connects network findings from different scales of investigation, with the combined aim of informing neuro-oncological healthcare professionals on this exciting new field and also delineating the promising avenues for future translational and clinical research that may allow for application of network methods in neuro-oncological care.

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Resting-State Electroencephalography Functional Connectivity Networks Relate to Pre- and Postoperative Language Functioning in Low-Grade Glioma and Meningioma Patients

Cited by 4 publications

References 51 publications

Structural Reorganization Following a Brain Tumor: A Machine Learning Study Considering Desynchronized Functional Oscillations

Structural Reorganization Following a Brain Tumor: A Machine Learning Study Considering Desynchronized Functional Oscillations

Functional and structural reorganization in brain tumors: a machine learning approach using desynchronized functional oscillations

Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales

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