Lee J Quinn, Keinath Alexandra T, Cianfarano Erica, Brandon Mark P
Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Montreal, QC, Canada.
Department of Psychiatry, Douglas Hospital Research Centre, McGill University, Montreal, QC, Canada; Department of Psychology, University of Illinois Chicago, Chicago, IL, USA.
Neuron. 2025 Jan 22;113(2):307-320.e5. doi: 10.1016/j.neuron.2024.10.027. Epub 2024 Nov 22.
Decades of theoretical and empirical work have suggested the hippocampus instantiates some form of a cognitive map. Yet, tests of competing theories have been limited in scope and largely qualitative in nature. Here, we develop a novel framework to benchmark model predictions against observed neuronal population dynamics as animals navigate a series of geometrically distinct environments. In this task space, we show a representational structure in the dynamics of hippocampal remapping that generalizes across brains, discriminates between competing theoretical models, and effectively constrains biologically viable model parameters. With this approach, we find that accurate models capture the correspondence in spatial coding of a changing environment. The present dataset and framework thus serve to empirically evaluate and advance theories of cognitive mapping in the brain.
数十年来的理论和实证研究表明，海马体实现了某种形式的认知地图。然而，对相互竞争理论的测试在范围上有限，且在很大程度上是定性的。在此，我们开发了一个新颖的框架，用于在动物在一系列几何形状不同的环境中导航时，将模型预测与观察到的神经元群体动态进行基准比较。在这个任务空间中，我们展示了海马体重映射动态中的一种表征结构，这种结构在不同大脑中具有普遍性，能够区分相互竞争的理论模型，并有效地约束生物学上可行的模型参数。通过这种方法，我们发现准确的模型捕捉到了变化环境中空间编码的对应关系。因此，当前的数据集和框架有助于从实证角度评估和推进大脑中认知映射的理论。
