局部横向连接性足以在深度神经网络中复制像皮层这样的地形组织
Xinyu Qian1, Amir Ozhan Dehghani2,3, Asa Borzabadi Farahani4
1Department of Computer Science, McGill University, Montreal, QC, Canada.
Nature communications
|March 17, 2026
概括
具有局部连接的人工神经网络自发地开发出类似大脑的视觉地图. 这表明局部连接驱动皮质组织,并增强模型对敌对攻击的稳定性.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 人工智能的人工智能
背景情况:
- 具有相似功能的神经元在灵长类大脑皮层空间聚集,形成用于感官处理的模块化组织.
- 这一原则在各个物种中都能观察到,特别是在视觉皮质中,在那里模块是根据特定的视觉特征调整的.
- 驱动这种地形组织的神经机制,特别是短距离连接的作用,仍然不完全理解.
研究的目的:
- 调查人工神经网络中的局部横向连接是否可以自我组织成类似灵长类视觉皮层的地形图.
- 探索局部反复结构在开发强大的视觉表示中的计算作用.
主要方法:
- 利用了人工深度神经网络,并集成了局部横向连接.
- 通过使用标准的自上而下的信用分配方法训练网络.
- 分析了新兴的地形组织,并将其与人类视觉皮层结构进行了比较.
主要成果:
- 网络自发地开发了类似于人类初级,中级和高级视觉皮层的地形图.
- 模块化组织出现了没有明确的地形诱导目标或学习规则.
- 包括局部横向连接在内,提高了对抗干扰的模型稳定性.
结论:
- 局部横向连接足以驱动人工神经网络中的皮质类地图的形成.
- 这种自我组织原理表明了生物视觉系统中拓绘制的基本机制.
- 局部反复结构在创建强大的视觉表示中发挥着至关重要的作用,为神经计算提供了洞察力.
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