1. Overlap among Spatial Memories Triggers Repulsion of Hippocampal Representations 
Avi J.H. Chanales, Ashima Oza, Serra E. Favila, Brice A. Kuhl 
Current Biology 
Volume 27, Issue 15, Pages e5 (August 2017)
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2. Figure 1 Route Stimuli and Experimental Design
(A) In the behavioral experiment and fMRI experiment 1, stimuli consisted of eight routes that traversed the New York University campus. Each subject learned four routes—either set 1 (routes 1–4) or set 2 (routes 5–8). Each set included pairs of routes that shared a common path (overlapping routes; e.g., routes 1 and 2) and pairs of routes with no common paths (non-overlapping routes; e.g., routes 1 and 3). Individual routes contained two segments: segment 1 refers to the portion of each route that shared a path with another route, and segment 2 refers to the unique portion of each route (after the overlapping routes diverged).
(B) In fMRI experiment 2 the stimuli again consisted of eight routes, with each subject learning four of the eight routes and with the four routes per set containing overlapping and non-overlapping pairs. However, some of the non-overlapping route pairs in experiment 2 terminated at the same destination (e.g., routes 1 and 3), whereas others terminated at distinct destinations (e.g., routes 1 and 4).
(C) In each experiment, each trial consisted of a series of rapidly presented pictures that lasted a total of 24 s.
See also Movies S1, S2, S3, and S4.
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3. Figure 2
Memory Performance for Segment 1 Pictures in the Behavioral Experiment
(A) After each learning round, subjects were shown static images sampled from each route and were asked to choose the corresponding destination from a set of four picture options: the target destination, destination associated with the overlapping route (competitor), and two destinations associated with non-overlapping routes (other). Subjects were significantly more likely to select the target destination than the competitor destination (F1,21 = 43.31, p = ) and significantly more likely to choose the competitor destination than other destinations (F1,21 = 41.39, p = ), despite the fact that “other” options were more prevalent (2/4) than competitor options (1/4).
(B) The relative percentage of target versus competitor responses markedly increased over learning rounds (F1,21 = 38.11, p = ).
(C) Discrimination between overlapping routes (percentage target responses − competitor responses) was significantly greater in the second half of learning than in the first half (t21 = 5.78, p = ).
Error bars reflect ± SEM. ∗∗∗p < See also Figure S1.
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4. Figure 3 Learning-Related Changes in Hippocampal Pattern Similarity
(A) Sample similarity matrices depicting analyses for experiments 1 and 2 (routes 5–8 are not shown). For each experiment, Pearson correlations were applied to spatiotemporal activity patterns to measure the similarity between repetitions of the same route (same route), routes with overlapping paths but distinct destinations (overlapping routes), and routes with non-overlapping paths and distinct destinations (non-overlapping routes). Experiment 2 included an additional comparison of routes with non-overlapping paths that ended at a common destination (same destination). All correlations were applied to spatiotemporal activity patterns from independent fMRI runs (odd versus even runs).
(B) Hippocampus and parahippocampal place area (PPA) regions of interest for a representative subject, displayed on their T1 anatomical scan.
(C) Within the hippocampus, the similarity of overlapping routes relative to the same routes decreased across learning (first versus second half; p = 0.009). Likewise, there was a learning-related decrease in the similarity of overlapping routes relative to non-overlapping routes (p = ).
(D) Within the PPA, there was no learning-related change in the relative similarity of overlapping versus the same routes (p = 0.96) nor in the relative similarity of overlapping versus non-overlapping routes (p = 0.13).
(E) Within the hippocampus, overlapping-route similarity decreased across learning (first versus second half; p = ), whereas non-overlapping-route similarity did not change with learning (p = 0.63).
(F) In the second half of learning, overlapping-route similarity was significantly lower than non-overlapping-route similarity within the hippocampus (p = ; reversal effect), whereas in the PPA the opposite was true: overlapping-route similarity was significantly greater than non-overlapping-route similarity (p = 0.038).
Error bars reflect ± SEM. ∗p < 0.05, ∗∗∗p < See also Figures S2–S4.
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5. Figure 4 Hippocampal Reversal Effect across Route Segments
(A) In the second half of learning, the hippocampal reversal effect (overlapping-route similarity < non-overlapping-route similarity) was significant for segment 1 (p = ) but not segment 2 (p = 0.58), and the interaction between overlap and segment was significant (p = 0.045).
(B) Time point by time point comparison of spatial pattern similarity for overlapping versus non-overlapping routes for each learning half. Spatial patterns analyzed at each time point (time to volume repetition; TR) were computed as the average pattern of a sliding three-TR window. Transition TRs reflect time points that included the end of segment 1 and beginning of segment 2.
Error bars reflect ± SEM. ∗p < 0.05.
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6. Figure 5
Hippocampal Reversal Effect as a Function of Memory-Based Discrimination
(A) Gray lines: time point by time point measures of mean memory-based route discrimination in the behavioral experiment. Colored lines: second-half hippocampal pattern similarity for overlapping/non-overlapping routes in fMRI experiment 1. Note: fMRI data were only used from fMRI experiment 1 because fMRI experiment 2 used different stimuli from the behavioral experiment. Error bars reflect ± SEM.
(B) Scatterplot showing the relationship between behavioral discrimination accuracy and hippocampal pattern similarity for overlapping/non-overlapping routes (each dot corresponds to data from one TR/time bin). There was a strong positive correlation (r = 0.87, p = ) between these measures, reflecting a weaker reversal effect for time points where behavioral discrimination was relatively easy (top-right corner of scatterplot) and a stronger reversal effect for time points where behavioral discrimination was relatively difficult (bottom-left corner of scatterplot). This correlation remains marginally significant if restricted to the time points within segment 1 (r = 0.58, p = 0.061).
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7. Figure 6 Voxel-Level Plasticity
(A) Time course similarity was defined as the correlation of a single voxel’s temporal pattern of activity across two different routes. For each voxel, time course similarity was separately computed for the first half and second half of learning. BOLD, blood-oxygen-level-dependent.
(B and C) Second-half time course similarity plotted as a function of first-half time course similarity, separately for the hippocampus (B) and PPA (C) and for overlapping (blue) and non-overlapping (orange) routes. Within the hippocampus, second-half time course similarity was markedly lower for overlapping than non-overlapping routes (reversal effect) for voxels that were moderately shared at the beginning of learning (p = ). Error bars reflect ± SEM. ∼p < 0.1, ∗∗∗p <
See also Figures S5 and S6.
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