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SUMMARY:High-level aftereffects reveal the role of statistical features in
  visual shape encoding - Ivan Tomic
DTSTART:20240320T140000Z
DTEND:20240320T150000Z
UID:TALK213454@talks.cam.ac.uk
CONTACT:Adam Triabhall
DESCRIPTION:This week we will discuss and debate a very recent paper by Mo
 rgenstern and colleagues\, published in Current Biology (2024).\n\nAbstrac
 t: “Visual shape perception is central to many everyday tasks\, from obj
 ect recognition to grasping and handling tools. Yet how shape is encoded i
 n the visual system remains poorly understood. Here\, we probed shape repr
 esentations using visual aftereffects—perceptual distortions that occur 
 following extended exposure to a stimulus. Such effects are thought to be 
 caused by adaptation in neural populations that encode both simple\, low-l
 evel stimulus characteristics and more abstract\, high-level object featur
 es. To tease these two contributions apart\, we used machine-learning meth
 ods to synthesize novel shapes in a multidimensional shape space\, derived
  from a large database of natural shapes.24 Stimuli were carefully selecte
 d such that low-level and high-level adaptation models made distinct predi
 ctions about the shapes that observers would perceive following adaptation
 . We found that adaptation along vector trajectories in the high-level sha
 pe space predicted shape aftereffects better than simple low-level process
 es. Our findings reveal the central role of high-level statistical feature
 s in the visual representation of shape. The findings also hint that human
  vision is attuned to the distribution of shapes experienced in the natura
 l environment” (Morgenstern et al.\, 2024).\n\nReference: Morgenstern\, 
 Y.\, Storrs\, K. R.\, Schmidt\, F.\, Hartmann\, F.\, Tiedemann\, H.\, Wage
 mans\, J.\, & Fleming\, R. W. (2024). High-level aftereffects reveal the r
 ole of statistical features in visual shape encoding. Current Biology\, 34
 (5)\, 1098–1106. https://doi.org/10.1016/j.cub.2023.12.039
LOCATION:https://cam-ac-uk.zoom.us/j/92612577704?pwd=MUtqMjVQdXNmUTVIYjRkM
 G1NUW9GZz09
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