To navigate through the environment, humans must be able to measure both the distance traveled in space, and the interval elapsed in time. Yet, how the brain holds both of these metrics simultaneously is less well known. One possibility is that participants measure how far and how long they have traveled relative to a known reference point. To measure this, we had human participants (n = 24) perform a distance estimation task in a virtual environment in which they were cued to attend to either the spatial or temporal interval traveled while responses were measured with multiband fMRI. We observed that both dimensions evoked similar frontoparietal networks, yet with a striking rostrocaudal dissociation between temporal and spatial estimation. Multivariate classifiers trained on each dimension were further able to predict the temporal or spatial interval traveled, with centers of activation within the SMA and retrosplenial cortex for time and space, respectively. Furthermore, a cross-classification approach revealed the right supramarginal gyrus and occipital place area as regions capable of decoding the general magnitude of the traveled distance. Altogether, our findings suggest the brain uses separate systems for tracking spatial and temporal distances, which are combined together along with dimension-nonspecific estimates.

为了在环境中导航，人类必须能够测量空间中行驶的距离和时间上经过的间隔。然而，大脑如何同时掌握这两个指标却鲜为人知。一种可能性是参与者测量他们相对于已知参考点行驶了多远和多长时间。为了测量这一点，我们让人类参与者（n = 24）在虚拟环境中执行距离估计任务，在虚拟环境中，他们被提示注意所行的空间或时间间隔，同时用多频带功能磁共振成像测量反应。我们观察到，这两个维度都引起了相似的额顶网络，但时间和空间估计之间存在显着的头尾分离。在每个维度上训练的多变量分类器能够进一步预测行进的时间或空间间隔，其中时间和空间的激活中心分别位于 SMA 和压后皮层内。此外，交叉分类方法揭示了右侧边缘上回和枕叶区域是能够解码行驶距离的一般大小的区域。总而言之，我们的研究结果表明，大脑使用单独的系统来跟踪空间和时间距离，并将这些系统与非特定维度的估计结合在一起。