Siyang Li , Zhipeng Li , Qiuyi Liu , Peng Ren , Lili Sun , Zaixu Cui , Xia Liang
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引用次数: 0
Abstract
Just as navigating a physical environment, navigating through the landscapes of spontaneous brain states may also require an internal cognitive map. Contemporary computation theories propose modeling a cognitive map from a reinforcement learning perspective and argue that the map would be predictive in nature, representing each state as its upcoming states. Here, we used resting-state fMRI to test the hypothesis that the spaces of spontaneously reoccurring brain states are cognitive map-like, and may exhibit future-oriented predictivity. We identified two discrete brain states of the navigation-related brain networks during rest. By combining pattern similarity and dimensional reduction analysis, we embedded the occurrences of each brain state in a two-dimensional space. Successor representation modeling analysis recognized that these brain state occurrences exhibit place cell-like representations, akin to those observed in a physical space. Moreover, we observed predictive transitions of reoccurring brain states, which strongly covaried with individual cognitive and emotional assessments. Our findings offer a novel perspective on the cognitive significance of spontaneous brain activity and support the theory of cognitive map as a unifying framework for mental navigation.
期刊介绍:
Progress in Neurobiology is an international journal that publishes groundbreaking original research, comprehensive review articles and opinion pieces written by leading researchers. The journal welcomes contributions from the broad field of neuroscience that apply neurophysiological, biochemical, pharmacological, molecular biological, anatomical, computational and behavioral analyses to problems of molecular, cellular, developmental, systems, and clinical neuroscience.