Seeing the future: connectome strength and network efficiency in visual network predict individual ability of episodic future thinking

Abstract

Episodic future thinking (EFT) refers to the critical ability that people construct vivid mental imagery about future events and pre-experience it, which helps with individual and group decision-making. Although EFT is generally believed to have a visual nature by theorists, little neuroscience evidence had been provided to verify this assumption. Here, by employing the approach of connectome-based predictive modeling (CPM) and graph-theoretical analysis, we analyzed resting-state functional brain image from 191 participants to predict their variability of EFT ability (leave-one-out cross-validation), and validated the results by applying different parcellation schemas and feature selection thresholds. At the connectome strength level, CPM-based analysis revealed that EFT ability could be predicted by the connectome strength of visual network. Further at the network level, graph-theoretical analysis showed that EFT ability could be predicted by the network efficiency of visual network. Moreover, these findings were replicated using different parcellation schemas and feature selection thresholds. These results robustly and collectively supported the visual network being the neural substrates underlying EFT ability from a comprehensive perspective of resting-state functional connectivity strength and the neural network. This study provides indications on how the function of visual network supports EFT ability, and helps to understand the EFT ability from a neural basis perspective.