Color invariant object recognition using entropic graphs

2006 ◽  
Vol 16 (5) ◽  
pp. 146-153 ◽  
Author(s):  
Jan C. van Gemert ◽  
Gertjan J. Burghouts ◽  
Frank J. Seinstra ◽  
Jan-Mark Geusebroek
1996 ◽  
Vol 14 (7) ◽  
pp. 473-483 ◽  
Author(s):  
H.W. Tang ◽  
V. Srinivasan ◽  
S.H. Ong

2020 ◽  
Author(s):  
Alexander J.E. Kell ◽  
Sophie L. Bokor ◽  
You-Nah Jeon ◽  
Tahereh Toosi ◽  
Elias B. Issa

The marmoset—a small monkey with a flat cortex—offers powerful techniques for studying neural circuits in a primate. However, it remains unclear whether brain functions typically studied in larger primates can be studied in the marmoset. Here, we asked whether the 300-gram marmosets’ perceptual and cognitive repertoire approaches human levels or is instead closer to rodents’. Using high-level visual object recognition as a testbed, we found that on the same task marmosets substantially outperformed rats and generalized far more robustly across images, all while performing ∼1000 trials/day. We then compared marmosets against the high standard of human behavior. Across the same 400 images, marmosets’ image-by-image recognition behavior was strikingly human-like—essentially as human-like as macaques’. These results demonstrate that marmosets have been substantially underestimated and that high-level abilities have been conserved across simian primates. Consequently, marmosets are a potent small model organism for visual neuroscience, and perhaps beyond.


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