Distinct Representational Structure and Localization for Visual Encoding and Recall during Visual Imagery.
TLDR
Using ultra-high-field functional magnetic resonance imaging with an item-based visual recall task, an in-depth comparison of encoding and recall along a spectrum of granularity is conducted, suggesting visual recall is not merely a reactivation of encoding patterns, displaying a different representational structure and localization from encoding, despite some overlap.Abstract:
During memory recall and visual imagery, reinstatement is thought to occur as an echoing of the neural patterns during encoding. However, the precise information in these recall traces is relatively unknown, with previous work primarily investigating either broad distinctions or specific images, rarely bridging these levels of information. Using ultra-high-field (7T) functional magnetic resonance imaging with an item-based visual recall task, we conducted an in-depth comparison of encoding and recall along a spectrum of granularity, from coarse (scenes, objects) to mid (e.g., natural, manmade scenes) to fine (e.g., living room, cupcake) levels. In the scanner, participants viewed a trial-unique item, and after a distractor task, visually imagined the initial item. During encoding, we observed decodable information at all levels of granularity in category-selective visual cortex. In contrast, information during recall was primarily at the coarse level with fine-level information in some areas; there was no evidence of mid-level information. A closer look revealed segregation between voxels showing the strongest effects during encoding and those during recall, and peaks of encoding-recall similarity extended anterior to category-selective cortex. Collectively, these results suggest visual recall is not merely a reactivation of encoding patterns, displaying a different representational structure and localization from encoding, despite some overlap.read more
Citations
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Neural similarity between overlapping events at learning differentially affects reinstatement across the cortex
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Covariance-based decoding reveals content-specific feature integration and top-down processing during visual imagery
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