它们看起来几乎是相同的:在虚拟现实中对称性的外网膜表示
Elena Karakashevska1, Michael Batterley1, Yuxin Yao1
1Institute of Population Health, University of Liverpool, United Kingdom.
概括
大脑构建视觉对称性的视图不变表示,即使视角发生变化. 这种能力得到了深度线索的支持,特别是在规律差异化任务中.
科学领域:
- 神经科学是一个神经科学.
- 视觉感知 视觉感知 视觉感知
- 认知心理学 认知心理学
背景情况:
- 大脑必须识别物体,尽管由于不同的观点,视网膜图像的变化.
- 网外表达对于保持对象的恒定性至关重要.
- 视觉对称性处理涉及到外层视觉皮层,并产生特定的事件相关潜力 (ERP),持续后部消极性 (SPN).
研究的目的:
- 为了研究大脑构建视觉对称性的视觉不变,超视网膜表征的条件.
- 为了确定3D虚拟环境中的深度线索是否可以降低与对称感知相关的"视角成本".
主要方法:
- 使用基于虚拟现实 (VR) 的3D环境.
- 招募了48名参与者来执行两个任务:规律性歧视 (对称与不对称) 和亮度歧视.
- 通过计算前沿平行和视角视图之间的SPN幅度差异来衡量视角成本.
主要成果:
- 在规律性任务中,预期成本远低于先验值,表明没有显著的预期成本.
- 在光度任务中,SPN成本与零没有显著差异,但也没有显著低于值,产生模两可的结果.
- 外层皮质在存在足够的深度线索时,表现出形成外网膜对称性表示的能力.
结论:
- 外层皮质可以在有足够的视觉深度线索的情况下构建外层皮质对称性表示.
- 这种视图不变对称性表示的构建发生在正规性歧视任务中.
- 它也可能在其他视觉任务中自动发生,例如光度歧视,当有深度线索时.
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