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SUMMARY:End-to-end topographic networks as models of cortical map formatio
 n and human visual behaviour - Ivan Tomic
DTSTART:20250711T130000Z
DTEND:20250711T140000Z
UID:TALK234235@talks.cam.ac.uk
CONTACT:Adam Triabhall
DESCRIPTION:This week we will discuss and debate a very recent paper by Lu
  and colleagues (2025).\n\nAbstract: “A prominent feature of the primate
  visual system is its topographic organization. For understanding its orig
 ins\, its computational role and its behavioural implications\, computatio
 nal models are of central importance. Yet\, vision is commonly modelled us
 ing convolutional neural networks\, which are hard-wired to learn identica
 l features across space and thus lack topography. Here we overcome this li
 mitation by introducing all-topographic neural networks (All-TNNs). All-TN
 Ns develop several features reminiscent of primate topography\, including 
 smooth orientation and category selectivity maps\, and enhanced processing
  of regions with task-relevant information. In addition\, All-TNNs operate
  on a low energy budget\, suggesting a metabolic benefit of smooth topogra
 phic organization. To test our model against behaviour\, we collected a da
 taset of human spatial biases in object recognition and found that All-TNN
 s significantly outperform control models. All-TNNs thereby offer a promis
 ing candidate for modelling primate visual topography and its role in down
 stream behaviour” (Lu et al.\, 2025).\n\nReference: Lu\, Z.\, Doerig\, A
 .\, Bosch\, V.\, Krahmer\, B.\, Kaiser\, D.\, Cichy\, R. M.\, & Kietzmann\
 , T. C. (2025). End-to-end topographic networks as models of cortical map 
 formation and human visual behaviour. Nature Human Behaviour. https://doi.
 org/10.1038/s41562-025-02220-7\n
LOCATION:https://cam-ac-uk.zoom.us/j/92612577704?pwd=MUtqMjVQdXNmUTVIYjRkM
 G1NUW9GZz09
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