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Drawings of real-world scenes during free recall reveal detailed object and spatial information in memory.

Wilma A BainbridgeElizabeth H HallChris Ian Baker
Published in: Nature communications (2019)
Understanding the content of memory is essential to teasing apart its underlying mechanisms. While recognition tests have commonly been used to probe memory, it is difficult to establish what specific content is driving performance. Here, we instead focus on free recall of real-world scenes, and quantify the content of memory using a drawing task. Participants studied 30 scenes and, after a distractor task, drew as many images in as much detail as possible from memory. The resulting memory-based drawings were scored by thousands of online observers, revealing numerous objects, few memory intrusions, and precise spatial information. Further, we find that visual saliency and meaning maps can explain aspects of memory performance and observe no relationship between recall and recognition for individual images. Our findings show that not only is it possible to quantify the content of memory during free recall, but those memories contain detailed representations of our visual experiences.
Keyphrases
  • working memory
  • deep learning
  • machine learning
  • health information
  • dna methylation
  • genome wide
  • single cell
  • convolutional neural network