A network of regions in the human brain involved in processing familiarity

Journal of Vision(2023)

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摘要
Our ability to recall familiar people or places is crucial for guiding future behaviour. For example, when we encounter a familiar person we need to be able to recall who they are, why we know them and how we feel about them. A limitation of previous studies of the neural basis of familiarity is the use of controlled experimental settings that have limited resemblance to real life. To address this issue, we have used a natural viewing paradigm, in which participants viewed clips from Game of Thrones (GoT) while brain responses were measured using fMRI. The similarity of the time-course of fMRI response between participants was measured in corresponding regions of the brain. Regions involved in familiarity were defined as having a more similar time-course of response between participants who were familiar with GoT compared to participants who were unfamiliar with GoT. This analysis revealed a network of regions beyond the core face-selective and scene-selective regions that were associated with familiarity. Next, we explored differences in connectivity between familiar and unfamiliar participants. We found a similar network of regions, beyond the core face-selective and scene-selective regions, that showed greater connectivity in familiar participants. Finally, we measured neural responses in participants with developmental prosopagnosia (DP), in which the recognition of faces is impaired. In contrast to controls, participants with DP showed a significantly reduced network of regions associated with familiarity and a minimal effect of familiarity on the functional connectivity between regions. Together, these findings show that brain regions, beyond the core face-selective and scene-selective regions, are important for processing familiarity. The implication is that for past experiences to be useful, visual information about people and places needs to be linked with relevant non-visual knowledge.
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human brain involved,processing,network
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