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Automatic encoding of a target position relative to a natural scene
Author(s) -
Nobuyuki Nishimura,
Motoaki Uchimura,
Shigeru Kitazawa
Publication year - 2019
Publication title -
journal of neurophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 245
eISSN - 1522-1598
pISSN - 0022-3077
DOI - 10.1152/jn.00032.2018
Subject(s) - encoding (memory) , computer science , natural (archaeology) , communication , position (finance) , computer vision , artificial intelligence , psychology , biology , paleontology , finance , economics
We previously showed that the brain automatically represents a target position for reaching relative to a large square in the background. In the present study, we tested whether a natural scene with many complex details serves as an effective background for representing a target. In the first experiment, we used upright and inverted pictures of a natural scene. A shift of pictures significantly attenuated prism adaptation of reaching movements as long as they were upright. In one-third of participants, adaptation was almost completely cancelled whether the pictures were upright or inverted. It was remarkable that there were two distinct groups of participants, one who relies fully on the allocentric coordinate and the other who depended only when the scene was upright. In the second experiment, we examined how long it takes for a novel upright scene to serve as a background. A shift of the novel scene had no significant effects when it was presented for 500 ms before presenting a target, but significant effects were recovered when presented for 1,500 ms. These results show that a natural scene serves as a background against which a target is automatically represented once we spend 1,500 ms in the scene. NEW & NOTEWORTHY Prism adaptation of reaching was attenuated by a shift of natural scenes as long as they were upright. In one-third of participants, adaptation was fully canceled whether the scene was upright or inverted. When an upright scene was novel, it took 1,500 ms to prepare the scene for allocentric coding. These results show that a natural scene serves as a background against which a target is automatically represented once we spend 1,500 ms in the scene.

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