• Zheng Zhang, Delong Zhang, Zengjian Wang, Junchao Li, Yuting Lin, Song Chang, Ruiwang Huang, and Ming Liu.
• Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, South China Normal University, Guangzhou, China; Department of Special Education and Communication Disorders, University of Nebraska, Lincoln 68583, USA.
• Neuroscience. 2018 May 21; 379: 13-21.

AbstractPrevious studies have reported the essence of the sensory-based properties of human brain function, in which mental imagery is of great importance. In this study, we explored the association between the activities of two special regions, i.e., the primary visual area (PVA), which is the classically dominant sensory region, and the default mode network (DMN), which is the classical supra-sensory region, with a focus on their linkage in visual mental imagery. For this purpose, we collected fMRI data from 30 healthy participants (15 males; 22.37 ± 2.52 years) during the resting state and a mental rotation task state. By using a critical time point analysis (CTPA), we investigated the association between the activities of the PVA and the DMN. As the results showed, there existed a PVA-related (i.e., prefrontal cortex, DMN, sensorimotor areas and medial temporal lobe (MTL)) and a DMN-related neural association pattern (i.e., PVA, prefrontal cortex and the MTL) in the human brain. Furthermore, the results showed the steady and tight intrinsic association between the activities of the PVA and the DMN, with the prefrontal cortex and the MTL regions being found to be consistently involved in the resting-state brain. It also was suggested that the observed association between the PVA and the DMN was highly reproducible for the mental rotation task. Together, these observations, from the perspective of visual mental imagery, provided experimental evidence for the robustness and stability of the detailed map of the associations between the activities of the PVA and the DMN.Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

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