Wang Zhaoze, Di Tullio Ronald W, Rooke Spencer, Balasubramanian Vijay
Department of Computer and Information Science, University of Pennsylvania.
Department of Neuroscience, University of Pennsylvania.
ArXiv. 2025 Jul 9:arXiv:2408.05798v3.
The vertebrate hippocampus is believed to use recurrent connectivity in area CA3 to support episodic memory recall from partial cues. This brain area also contains place cells, whose location-selective firing fields implement maps supporting spatial memory. Here we show that place cells emerge in networks trained to remember temporally continuous sensory episodes. We model CA3 as a recurrent autoencoder that recalls and reconstructs sensory experiences from noisy and partially occluded observations by agents traversing simulated arenas. The agents move in realistic trajectories modeled from rodents and environments are modeled as continuously varying, high-dimensional, sensory experience maps (spatially smoothed Gaussian random fields). Training our autoencoder to accurately pattern-complete and reconstruct sensory experiences with a constraint on total activity causes spatially localized firing fields, i.e., place cells, to emerge in the encoding layer. The emergent place fields reproduce key aspects of hippocampal phenomenology: a) remapping (maintenance of and reversion to distinct learned maps in different environments), implemented via repositioning of experience manifolds in the network's hidden layer, b) orthogonality of spatial representations in different arenas, c) robust place field emergence in differently shaped rooms, with single units showing multiple place fields in large or complex spaces, and d) slow representational drift of place fields. We argue that these results arise because continuous traversal of space makes sensory experience temporally continuous. We make testable predictions: a) rapidly changing sensory context will disrupt place fields, b) place fields will form even if recurrent connections are blocked, but reversion to previously learned representations upon remapping will be abolished, c) the dimension of temporally smooth experience sets the dimensionality of place fields, including during virtual navigation of abstract spaces. Code for our experiments is available at.
脊椎动物的海马体被认为利用CA3区的循环连接来支持从部分线索中回忆情景记忆。这个脑区还包含位置细胞，其位置选择性放电场实现支持空间记忆的地图。在这里，我们表明位置细胞出现在经过训练以记住时间上连续的感官事件的网络中。我们将CA3建模为一个循环自动编码器，它通过遍历模拟竞技场的智能体的嘈杂和部分遮挡的观察来回忆和重建感官体验。智能体沿着从啮齿动物建模的真实轨迹移动，环境被建模为连续变化的高维感官体验地图（空间平滑的高斯随机场）。训练我们的数据自动编码器在总活动受到约束的情况下准确地进行模式完成和重建感官体验，会导致编码层中出现空间局部化的放电场，即位置细胞。出现的位置场再现了海马现象学的关键方面：a）重映射（在不同环境中维持并恢复到不同的学习地图），通过网络隐藏层中经验流形的重新定位来实现；b）不同竞技场中空间表征的正交性；c）在形状不同的房间中稳健地出现位置场，单个单元在大空间或复杂空间中显示多个位置场；d）位置场的缓慢表征漂移。我们认为这些结果的出现是因为空间的连续遍历使感官体验在时间上连续。我们做出了可测试的预测：a）快速变化的感官背景将扰乱位置场；b）即使循环连接被阻断，位置场也会形成，但重映射时恢复到先前学习表征的能力将被消除；c）时间平滑的经验维度决定了位置场的维度，包括在抽象空间的虚拟导航期间。我们实验的代码可在[具体网址]获取。
