神经调用于顺序处理:人类大脑和人工网络中的融合模式
Shir Hofstetter1,2, Marcus Daghlian1,2,3, Serge O Dumoulin4,2,3,5
1Spinoza Centre for Neuroimaging, Amsterdam, Netherlands.
概括
人类和动物使用神经元调来处理项目排名,而不是使用符号. 这个大脑机制支持非象征性的平凡感知,对决策和社会行为至关重要.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 比较心理学比较心理学
背景情况:
- 平凡性,在一个序列中对项目的排名的感知,是跨物种共享的基本认知技能.
- 这种能力对于决策,食和社会组织等行为至关重要,独立于象征系统.
- 以前的研究表明,数量处理的神经基础,但普通感知机制仍然不太了解.
研究的目的:
- 研究支持人类大脑中非象征性平凡感知的神经机制.
- 为了测试神经元调整的假设,神经元选择性地响应特定的等级,是平凡性处理的基础.
- 探索在人工神经网络中是否存在类似的普通性处理机制.
主要方法:
- 在人类参与者中利用超高场7特斯拉功能磁共振成像 (fMRI).
- 应用了人口受体场 (pRF) 建模,以识别调整到顺序位置的神经群体.
- 在视觉任务上训练有素的等级卷积神经网络,以观察平凡调的自发出现.
主要成果:
- 确定了在对面和前运动皮层中调整为非象征性顺序位置的神经群体.
- 观察到更高的顺序等级的调宽度增加和皮质区域减少,表明精度降低.
- 发现这些神经反应并没有将其概括为象征性的平凡性,并且在卷积神经网络中出现了类似的调整.
结论:
- 脊髓和前运动皮层的神经调特性支持非象征性的平凡感知.
- 这些发现表明,平凡性处理依赖于固有的神经处理特征,类似于其他数量表示.
- 人工神经网络中类似调整的出现表明了排名处理的基本计算原则.
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