混的感知分辨:一个分裂的规范化对整眼色彩分组和差异增强的计算
Jaelyn R Peiso1,2, Stephanie E Palmer3,4, Steven K Shevell5,6
1Department of Psychology, Institute for Mind & Biology, University of Chicago, Chicago, IL, USA.
Journal of vision
|January 13, 2026
概括
神经群体竞争解决视觉模两可的问题. 分裂性正常化框架解释了大脑如何灵活地增强刺激之间的相似性或差异,在双眼竞争中统一相反的感知结果.
科学领域:
- 神经科学是一个神经科学.
- 计算机视觉 计算机视觉
- 感知 感知 感知 感知
背景情况:
- 视觉系统通常会创造出一个单一的,功能性的世界表现.
- 模两可的视觉刺激可以导致相互竞争的神经解释,感知在可能性之间转移.
- 语境会影响如何解决这些模两可的问题,有时会增强相似性或差异性.
研究的目的:
- 调查双眼竞争期间感知选择背后的机制.
- 要确定一个统一的框架是否可以解释相反的感知结果 (相似性与差异增强).
- 测试分裂正常化在解决视觉模糊性的作用.
主要方法:
- 开发并模拟了一个调整的,分裂的正常化模型.
- 分析了双眼对抗的经验数据.
- 将模型预测与实验结果进行比较.
主要成果:
- 分裂性规范化框架成功地解释了感知选择如何产生基于相似性的分组或基于差异的增强感知.
- 该模型解释了双眼对抗期间的灵活感知结果.
- 结果使色彩视觉非线性与基于亮度的模型相协调.
结论:
- 分分规范化为理解双眼竞争中的感知选择提供了一个统一的计算框架.
- 这个框架解释了如何从同一个模两可的视觉输入中产生相反的感知结果.
- 该模型提供了关于视觉模两可的解决方案的神经基础的见解.
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