Large-scale boundary transformation database ==================== [Wilma A. Bainbridge][1], [Chris I. Baker][2] National Institute of Mental Health, Bethesda, MD --------------------------------------------------- **If you use any of these data, please cite:** Bainbridge, W.A. & Baker, C.I. (2020). Boundaries extend and contract in scene memory depending on image properties. Current Biology, 30. --------------------------------------------------- This repository contains the following data: 1. [1000 Images used in the 1000-Image Set Experiment][3] 2. [Boundary Transformation scores from ~2000 participants on the 1000 Images][4], in an RSVP recognition paradigm 3. [Image metrics for each of the 1000 images][5]: # of objects , average object size, average object centricity, average subjective distance (depth) 4. [Boundary transformation scores for a smaller set of 60 images][6], including scores from an RSVP recognition paradigm as well as a memory drawing and copying drawing task. 5. **Added 8/24/20**: [Boundary transformation scores for immediate recall of the 60 images][7]. Participants drew images immediately after study, and these drawings were scored online for boundary transformations. [1]: http://wilmabainbridge.com [2]: https://www.nimh.nih.gov/research/research-conducted-at-nimh/research-areas/clinics-and-labs/lbc/slp/index.shtml [3]: https://osf.io/28nzt/wiki/1000-Images%20Set:%20Images/ [4]: https://osf.io/28nzt/wiki/1000-Images%20Set:%20Boundary%20Transformation%20Scores/ [5]: https://osf.io/28nzt/wiki/1000-Images%20Set:%20Image%20Metrics/ [6]: https://osf.io/28nzt/wiki/60-Images%20Set:%20Boundary%20Transformation%20Scores/ [7]: https://osf.io/28nzt/wiki/60-Images%20Set:%20Immediate%20Recall/