Within-category representational stability through the lens of manipulable objects
نویسندگان
چکیده
Our ability to recognize an object amongst many exemplars is one of our most important features, and that putatively distinguishes humans from non-human animals potentially (current) computational artificial intelligence models. We can objects consistently regardless when we see them suggesting have stable representations across time different contexts. Importantly, little known about how replicate within-category time. Here, investigate neural stability by computing the similarity between representational geometries activity patterns for 80 images tools obtained on functional magnetic resonance imaging (fMRI) scanning days. show observable in regions span lateral ventral temporal cortex, inferior superior parietal premotor cortex – typically associated with tool processing visuospatial processing. then focus what kinds best explain within these regions. test those coming layers a convolutional network, perceived veridical visual find supporting stronger relationship higher-level visual/semantic replicability derived information. Within category may thus originate long-range cross talk category-specific (and this case strongly cortex) over more abstract, rather than veridical/lower-level, (sensorial) representations, perhaps service object-centered representations.
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ژورنال
عنوان ژورنال: Cortex
سال: 2021
ISSN: ['1973-8102', '0010-9452']
DOI: https://doi.org/10.1016/j.cortex.2020.12.026