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      Separable Representations for Duration and Distance in Virtual Movements

      , , , ,
      Journal of Cognitive Neuroscience
      MIT Press

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          Abstract

          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.

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          Circular analysis in systems neuroscience: the dangers of double dipping.

          A neuroscientific experiment typically generates a large amount of data, of which only a small fraction is analyzed in detail and presented in a publication. However, selection among noisy measurements can render circular an otherwise appropriate analysis and invalidate results. Here we argue that systems neuroscience needs to adjust some widespread practices to avoid the circularity that can arise from selection. In particular, 'double dipping', the use of the same dataset for selection and selective analysis, will give distorted descriptive statistics and invalid statistical inference whenever the results statistics are not inherently independent of the selection criteria under the null hypothesis. To demonstrate the problem, we apply widely used analyses to noise data known to not contain the experimental effects in question. Spurious effects can appear in the context of both univariate activation analysis and multivariate pattern-information analysis. We suggest a policy for avoiding circularity.
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            Temporal context calibrates interval timing

            We use our sense of time to identify temporal relationships between events and to anticipate actions. How well we can exploit temporal contingencies depends on the variability of our measurements of time. We asked humans to reproduce time intervals drawn from different underlying distributions. As expected, production times were more variable for longer intervals. Surprisingly however, production times exhibited a systematic regression towards the mean. Consequently, estimates for a sample interval differed depending on the distribution from which it was drawn. A performance-optimizing Bayesian model that takes the underlying distribution of samples into account provided an accurate description of subjects’ performance, variability and bias. This finding suggests that the central nervous system incorporates knowledge about temporal uncertainty to adapt internal timing mechanisms to the temporal statistics of the environment.
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              The cognitive map in humans: spatial navigation and beyond

              The ‘cognitive map’ hypothesis proposes that brain builds a unified representation of the spatial environment to support memory and guide future action. Forty years of electrophysiological research in rodents suggests that cognitive maps are neurally instantiated by place, grid, border, and head direction cells in the hippocampal formation and related structures. Here we review recent work that suggests a similar functional organization in the human brain and reveals novel insights into how cognitive maps are used during spatial navigation. Specifically, these studies indicate that: (i) the human hippocampus and entorhinal cortex support map-like spatial codes; (ii) posterior brain regions such as parahippocampal and retrosplenial cortices provide critical inputs that allow cognitive maps to be anchored to fixed environmental landmarks; (iii) hippocampal and entorhinal spatial codes are used in conjunction with frontal lobe mechanisms to plan routes during navigation. We also discuss how these three basic elements of cognitive map based navigation spatial coding, landmark anchoring, and route planning might be applied to non-spatial domains to provide the building blocks for many core elements of human thought.
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                Author and article information

                Journal
                Journal of Cognitive Neuroscience
                MIT Press
                0898-929X
                1530-8898
                2024
                March 01 2024
                March 01 2024
                2024
                March 01 2024
                March 01 2024
                : 36
                : 3
                : 447-459
                Article
                10.1162/jocn_a_02097
                c643cd72-fba8-4432-8b88-e2587386e275
                © 2024
                History

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