意识和无意识视觉中的大脑表现
Ning Mei1, David Soto2,3
1School of Psychology, Shenzhen University, No. 3688, Nanhai Avenue, Shenzhen 518060, China.
Journal of cognition
|May 5, 2025
概括
这项研究揭示了人工智能模型可以预测大脑活动对于有意识和无意识的感知. 这些发现挑战了全球神经元工作空间理论,表明前额-双叶皮质可能会产生元表示.
科学领域:
- 意识的神经科学 意识的神经科学
- 认知神经科学 认知神经科学
- 计算神经科学是一种神经科学.
背景情况:
- 了解意识和无意识感知的神经表征对于推进意识研究至关重要.
- 以前的功能性MRI (fMRI) 研究表明,从大脑活动中解码无意识内容,但这并不能完全解释神经表征.
- 需要一种详细的,基于信息的方法来分析大脑如何在意识状态之间表示感知内容.
研究的目的:
- 通过使用先进的计算模型,研究意识和无意识的感知内容的神经表征.
- 将大脑活动模式与来自卷积神经网络 (CNN) 模型的表示进行比较.
- 探索前额外外皮质在意识感知中的功能作用.
主要方法:
- 重新分析高精度fMRI数据.
- 代表性相似分析 (RSA) 的应用.
- 利用计算机视觉中的卷积神经网络 (CNN) 模型来预测大脑反应.
主要成果:
- 对于有意识和无意识的内容,CNN模型的表现显著预测了脑内视觉皮层和前侧双侧区域的脑反应.
- 这些预测模式在不同参与者之间是一致的,即使模型被独立训练和测试.
- 这些发现甚至适用于没有可检测的感知灵敏度的参与者,这表明强大的无意识处理.
结论:
- 无意识信息的神经表现在大脑中广泛分布.
- 额头-双侧皮质在意识感知中的作用可能涉及生成元表示而不是广播信息,挑战全球神经元工作空间理论.
- 高阶意识理论为观察到的前额-双侧皮层功能提供了一个更合适的框架.
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