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In order to navigate through the environment, humans must be able to measure both the distance traveled in space, and the interval covered in time. Yet, how these two dimensions are computed and interact across neural systems remains unknown. One possibility is that subjects measure how far and how long they have traveled relative to a known reference point, or anchor. 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 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 center of activation within the supplementary motor area (SMA) and retrosplenial cortex (RSC) for time and space, respectively. Further, a cross-classification approach revealed the right supramarginal gyrus (SMG) and occipital place area (OPA) as regions capable of decoding the general magnitude of traveled distance. Altogether, our findings suggest the brain uses separate systems for tracking spatial and temporal distance, which are combined together along with amodal estimates.

The perception and measurement of spatial and temporal dimensions have been widely studied. However, whether these two dimensions are processed independently is still being debated. Additionally, whether EEG components are uniquely associated with time or space, or whether they reflects a more general measure of magnitude remains unknown. While undergoing EEG, subjects traveled a randomly predetermined spatial or temporal interval and were then instructed to reproduce the interval traveled. In the task, the subject's travel speed varied for the estimation and reproduction phases of each trial, so that one dimension could not inform the other. Behaviorally, subject performance was more variable when reproducing time than space, but overall, just as accurate; notably, behavior was not correlated between tasks. EEG data revealed during estimation the contingent negative variation (CNV) tracked the probability of the upcoming interval, regardless of dimension. However, during reproduction, the CNV exclusively oriented to the upcoming temporal interval at the start of reproduction. Further, a dissociation between relatively early frontal beta and late posterior alpha oscillations was observed for time and space reproduction, respectively. Our findings indicate that time and space are neurally separable dimensions, yet are hierarchically organized across task contexts within the CNV signal.