scholarly journals Multidimensional Associations between Cognition and Connectome Organization in Temporal Lobe Epilepsy

2019 ◽  
Author(s):  
Raúl Rodríguez-Cruces ◽  
Boris C. Bernhardt ◽  
Luis Concha

AbstractObjectiveTemporal lobe epilepsy (TLE) is known to affect large-scale structural networks and cognitive function in multiple domains. The study of complex relations between structural network organization and cognition requires comprehensive analytical methods and a shift towards multivariate techniques. The current work sought to identify multidimensional associations between cognitive performance and structural network topology in TLE.MethodsWe studied 34 drug-resistant TLE patients and 25 age- and sex-matched healthy controls. All participants underwent a comprehensive neurocognitive battery and multimodal MRI, allowing for large-scale connectomics, and morphological evaluation of subcortical and neocortical regions. Using canonical correlation analysis, we identified a multivariate mode that links cognitive performance to a brain structural network. Our approach was complemented by bootstrap-based clustering to derive cognitive subtypes and associated patterns of macroscale connectome anomalies.ResultsBoth methodologies provided converging evidence for a close coupling between cognitive impairments across multiple domains and large-scale structural network compromise. Cognitive classes presented with an increasing gradient of abnormalities (increasing cortical and subcortical atrophy and less efficient white matter connectome organization in patients with increasing degrees of cognitive impairments). Notably, network topology characterized better the cognitive performance than morphometric measures. Thus, connectome characteristics featured as important markers of network reorganization and loss of inter-regional connectivity.ConclusionsThe multivariate approach emphasized the close interplay between cognitive impairment and large-scale network anomalies in TLE. Our findings contribute to understand the complexity of structural connectivity regulating the heterogeneous cognitive deficits found in epilepsy

2018 ◽  
Author(s):  
Hannelore Aerts ◽  
Michael Schirner ◽  
Ben Jeurissen ◽  
Dirk Van Roost ◽  
Rik Achten ◽  
...  

AbstractPresurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, non-invasive neuroimaging techniques such as functional MRI and diffusion weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex non-linear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics.As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed.Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.


2021 ◽  
Vol 115 ◽  
pp. 107699
Author(s):  
Alejandro Lozano-García ◽  
Kevin G. Hampel ◽  
Vicente Villanueva ◽  
Esperanza González-Bono ◽  
Irene Cano-López

2010 ◽  
Vol 206 (2) ◽  
pp. 171-177 ◽  
Author(s):  
L. Piccardi ◽  
A. Berthoz ◽  
M. Baulac ◽  
M. Denos ◽  
S. Dupont ◽  
...  

Brain ◽  
2006 ◽  
Vol 129 (3) ◽  
pp. 625-641 ◽  
Author(s):  
Sarah Jamali ◽  
Fabrice Bartolomei ◽  
Andrée Robaglia-Schlupp ◽  
Annick Massacrier ◽  
Jean-Claude Peragut ◽  
...  

2016 ◽  
Vol 37 (9) ◽  
pp. 3137-3152 ◽  
Author(s):  
Brunno Machado de Campos ◽  
Ana Carolina Coan ◽  
Clarissa Lin Yasuda ◽  
Raphael Fernandes Casseb ◽  
Fernando Cendes

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