Functional compensation after lesions: Predicting site and extent of recovery

TL;DR

This study investigates how similarity in connectivity patterns can predict which brain areas compensate for lesions, specifically analyzing visual cortex recovery in kittens using local and global connectivity measures.

Contribution

It introduces a method to predict compensating brain regions based on connectivity similarity, highlighting the effectiveness of global measures like NMDS.

Findings

Global connectivity comparison better predicts compensation in kittens.

Similarity measures could indicate potential for functional recovery.

NMDS outperforms local matching index in prediction accuracy.

Abstract

In some cases, the function of a lesioned area can be compensated for by another area. However, it remains unpredictable if and by which other area a lesion can be compensated. We assume that similar incoming and outgoing connections are necessary to encode the same function as the damaged region. The similarity can be measured both locally using the matching index and looking at a more global scale by non-metric multidimensional scaling (NMDS). We tested how well both measures can predict the compensating area for the loss of the visual cortex in kittens. For this case study, the global comparison of connectivity turns out to be a better method for predicting functional compensation. In future studies, the extent of the similarity between the lesioned and compensating regions might be a measure of the extent to which function can be successfully recovered.