The longitudinal relation between executive functioning and multilayer network topology in glioma patients

Predictors of cognition after glioma surgery: connectotomy, structure-function phenotype, plasticity

Determining preoperatively the maximal extent of resection that would preserve cognitive functions is the core challenge of brain tumour surgery. Over the past decade, the methodological framework to achieve this goal has been thoroughly renewed: the population-level topographically-focused voxel-based lesion-symptom mapping has been progressively overshadowed by machine learning (ML) algorithmics, in which the problem is framed as predicting cognitive outcomes in a patient-specific manner from a typically large set of variables. However, the choice of these predictors is of utmost importance, as they should be both informative and parsimonious. In this perspective, we first introduce the concept of connectotomy: instead of parameterizing resection topography through the status (intact/resected) of a huge number of voxels (or parcels) paving the whole brain in the Cartesian 3D-space, the connectotomy models the resection in the connectivity space, by computing a handful number of networks disconnection indices, measuring how the structural connectivity sustaining each network of interest was hit by the resection. This connectivity-informed reduction of dimensionality is a necessary step for efficiently implementing ML tools, given the relatively small number of patient-examples in available training datasets. We further argue that two other major sources of interindividual variability must be considered to improve the accuracy with which outcomes are predicted: the underlying structure-function phenotype and neuroplasticity, for which we provide an in-depth review and propose new ways of determining relevant predictors. We finally discuss the benefits of our approach for precision surgery of glioma.

Executive Functions in a Patient with Low-Grade Glioma of the Central Nervous System: A Case Report

Central nervous system tumors produce adverse outcomes in daily life, although low-grade gliomas are rare in adults. In neurological clinics, the state of impairment of executive functions goes unnoticed in the examinations and interviews carried out. For this reason, the objective of this study was to describe the executive function of a 59-year-old adult neurocancer patient. This study is novel in integrating and demonstrating biological effects and outcomes in performance evaluated by a neuropsychological instrument and psychological interviews. For this purpose, pre- and post-evaluations were carried out of neurological and neuropsychological functioning through neuroimaging techniques (iRM, spectroscopy, electroencephalography), hospital medical history, psychological interviews, and the Wisconsin Card Classification Test (WCST). There was evidence of deterioration in executive performance, as evidenced by the increase in perseverative scores, failure to maintain one's attitude, and an inability to learn in relation to clinical samples. This information coincides with the evolution of neuroimaging over time. Our case shows that the presence of the tumor is associated with alterations in executive functions that are not very evident in clinical interviews or are explicit in neuropsychological evaluations. In this study, we quantified the degree of impairment of executive functions in a patient with low-grade glioma in a middle-income country where research is scarce.

Linking structural and functional changes during aging using multilayer brain network analysis

Brain structure and function are intimately linked, however this association remains poorly understood and the complexity of this relationship has remained understudied. Healthy aging is characterised by heterogenous levels of structural integrity changes that influence functional network dynamics. Here, we use the multilayer brain network analysis on structural (diffusion weighted imaging) and functional (magnetoencephalography) data from the Cam-CAN database. We found that the level of similarity of connectivity patterns between brain structure and function in the parietal and temporal regions (alpha frequency band) is associated with cognitive performance in healthy older individuals. These results highlight the impact of structural connectivity changes on the reorganisation of functional connectivity associated with the preservation of cognitive function, and provide a mechanistic understanding of the concepts of brain maintenance and compensation with aging. Investigation of the link between structure and function could thus represent a new marker of individual variability, and of pathological changes.

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

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.