Back

Functional connectome contractions in temporal lobe epilepsy

Lariviere, S.; Wang, Y.; Vos de Wael, R.; Frauscher, B.; Wang, Z.; Bernasconi, A.; Bernasconi, N.; Schrader, D.; Zhang, Z.; Bernhardt, B.

2019-09-09 neuroscience
10.1101/756494 bioRxiv
Show abstract

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. While commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood. We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging analyses. We developed a novel framework that parameterizes functional connectivity distance, consolidating functional and geometric properties of macroscale networks. Compared to controls, TLE showed connectivity distance reductions in temporo-insular and prefrontal networks, suggesting topological segregation of functional networks. Our novel approach furthermore allowed for the testing of morphological and microstructural associations, and revealed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. All patients underwent a comparable resective surgery after our study and a regularized supervised machine learning paradigm with 5-fold cross-validation demonstrated that patient-specific functional anomalies predicted post-surgical seizure outcome with 74{+/-}8% accuracy, outperforming classifiers operating on clinical and structural imaging features. Our findings suggest connectivity distance contractions as a clinically relevant pathoconnectomic substrate of TLE. Functional topological isolation may represent a microstructurally mediated network mechanism that tilts the balance towards epileptogenesis.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.