Check our new Psych Science paper w/Daniil Azarov & Daniil Grigorev. Although an ability to recognize a familiar object among new ones clearly depends on how many and which objects there are, we show a remarkable stability of underlying "representational spaces"
journals.sagepub.com/doi/10.1177/...

We could accurately predict asymmetric performance from measuring “memorability” properties of individual items. The combination of items tendencies to cause true or false recognition drives their confusability when tested together. We found it with some fun signal-detection modeling. 3/4

In a new preprint with Nick Chiang and Wilma Bainbridge, we show that our visual recognition memory is often asymmetric, and sometimes even hugely asymmetric. These asymmetries are consistent across people, and we know how to predict them
osf.io/preprints/ps...
1/4

If you are still at #VSS come to listen to me Wednesday at 8:15am (Visual Memory session). I'll tell what we learned about the consequences of encoding speed for subsequent retrieval using ERP's (w/ Chong Zhao and Ed Vogel).

Check our new preprint about highly invariant recognition-memory spaces tested item-wise in over 1,200 participants (with a flavor of Signal-Detection Theory and Memorability):
osf.io/preprints/ps...

My talk at Psychonomics will take place on Sunday morning, session Recognition II. I will tell how we track visual memory strength with ERP's under manipulating the number of objects to remember and their similarity (w/ Chong Zhao & Ed Vogel)