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SUMMARY:Contrastive learning explains the emergence and function of visual
  category-selective regions - Ivan Tomic
DTSTART:20241212T140000Z
DTEND:20241212T150000Z
UID:TALK225598@talks.cam.ac.uk
CONTACT:Adam Triabhall
DESCRIPTION:This week we will discuss and debate a very recent paper by Pr
 ince and colleagues (2024). \n\nAbstract: “Modular and distributed codin
 g theories of category selectivity along the human ventral visual stream h
 ave long existed in tension. Here\, we present a reconciling framework—c
 ontrastive coding—based on a series of analyses relating category select
 ivity within biological and artificial neural networks. We discover that\,
  in models trained with contrastive self-supervised objectives over a rich
  natural image diet\, category-selective tuning naturally emerges for face
 s\, bodies\, scenes\, and words. Further\, lesions of these model units le
 ad to selective\, dissociable recognition deficits\, highlighting their di
 stinct functional roles in information processing. Finally\, these pre-ide
 ntified units can predict neural responses in all corresponding face-\, sc
 ene-\, body-\, and word-selective regions of human visual cortex\, under a
  highly constrained sparse positive encoding procedure. The success of thi
 s single model indicates that brain-like functional specialization can eme
 rge without category-specific learning pressures\, as the system learns to
  untangle rich image content. Contrastive coding\, therefore\, provides a 
 unifying account of object category emergence and representation in the hu
 man brain” (Prince et al.\, 2024).\n\nReference: Prince\, J. S.\, Alvare
 z\, G. A.\, & Konkle\, T. (2024). Contrastive learning explains the emerge
 nce and function of visual category-selective regions. Science Advances\, 
 10(39)\, eadl1776. https://doi.org/10.1126/sciadv.adl1776\n\n\n
LOCATION:https://cam-ac-uk.zoom.us/j/92612577704?pwd=MUtqMjVQdXNmUTVIYjRkM
 G1NUW9GZz09
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