Deafness and sign language experience shift visual category representations
Daniel Hertz, E.; Gomez, J.
Show abstract
Childhood visual experiences shape our ability to rapidly recognize faces and objects. Across development, regions processing visual categories that lose relevance, such as hands, are recycled for others. How would visual cortex accommodate a childhood in which hands maintain significance? Through functional magnetic resonance imaging, we demonstrate that high-level visual cortex in Deaf signers develops a unique topography to accommodate the learning of sign language in childhood, with distinct but significant changes observed in hearing signers who acquired sign language in adulthood. These data suggest a new framework for human visual cortex in which the location of regions is not as fixed as once thought, and sociolinguistic experience outside the childhood plasticity period may be sufficient to alter the function of high-level visual cortex.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Holistic face recognition is an emergent phenomenon of spatial integration in face-selective regions 93%
- Comparing retinotopic maps of children and adults reveals a late-stage change in how V1 samples the visual field 93%
- Linking individual differences in human primary visual cortex to contrast sensitivity around the visual field 93%
Similar papers in this journal
- Spatial processing of limbs reveals the center-periphery bias in high level visual cortex follows a nonlinear topography 93%
- Variability of the Surface Area of the V1, V2, and V3 Maps in a Large Sample of Human Observers 92%
- Joint population coding and temporal coherence link an attended talker's voice and location features in naturalistic multi-talker scenes. 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.