Representational integration and differentiation in the human hippocampus following goal-directed navigation

  1. Corey Fernandez  Is a corresponding author
  2. Jiefeng Jiang
  3. Shao-Fang Wang
  4. Hannah Lee Choi
  5. Anthony D Wagner
  1. Graduate Program in Neurosciences, Stanford University, United States
  2. Wu Tsai Neurosciences Institute, Stanford University, United States
  3. Department of Psychological and Brain Sciences, University of Iowa, United States
  4. Department of Psychology, Stanford University, United States
14 figures, 41 tables and 1 additional file

Figures

Study design.

(A) Overview of the 3-day experimental paradigm. (B) First-person view from an example training trial (left); virtual fog limited the distance viewed, ensuring that no two landmark buildings could be seen at any one time. Overhead view of the virtual environment (right). The environment consisted of three oval tracks. Colored boxes indicate the approximate locations of landmarks, circles approximate goal locations for an individual study participant. (C) fMRI paradigm. Participants viewed images of the 12 landmarks and 15 fractals that were used in their unique virtual environment, while performing a perceptual decision-making task. On each trial, the stimulus appeared on a gray background for 1.8 s, followed by a fixation cross for 5.4 s; participants were instructed to attend to the stimuli and to determine whether a feature of the stimulus was ‘bleached out’; on ‘catch’ trials (8% of trials), a red fixation cross appeared after image offset and participants indicated a response. (D) Schematic illustration of potential representational changes driven by learning. Following goal-directed navigation, the distance between landmarks in neural state-space could have increased (differentiation) or decreased (integration).

Navigation performance on the Local and Global Navigation Tasks.

(A) Local Navigation accuracy on test trials was near ceiling across runs on Day 1 and Day 2 (top). Participants’ navigational efficiency improved over learning trials, and they navigated efficiently across test trials (bottom). (B) During the Global Navigation Task, participants navigated more accurately (top) and efficiently (bottom) on within- vs. across-track trials. Participants were more accurate for within-track trials during learning and during early test runs, but improved on across-track trials over the course of test runs on Day 2 (top). Accuracy improved for both trial types on Day 3, such that performance did not significantly differ between within-track and across-track trials. Participants were significantly more efficient on both trial types on Day 3 relative to Day 2. (*** p < 0.001, paired t-test. Error bars denote SEM. Local Navigation Task, n = 23; Global Navigation Task, n = 21. Learning trials = trials on which the fractal marking the goal location was visible on the track; Test trials = trials on which participants had to rely on memory for the goal location, as the fractals were removed from the track).

Context representations in hippocampus and entorhinal cortex (EC).

(A) Contrast estimates for models predicting landmark similarity in left and right hippocampus. Right hippocampus differentiates landmarks located on the same track following Global Navigation, such that those experienced within the same track became less similar. A similar pattern of findings was observed in left hippocampus but did not reach statistical significance. (B) Contrast estimates for models predicting fractal similarity in left and right hippocampus. Interactions between scan session and context were not significant. (C) Contrast estimates for models in left and right EC that include both landmark and fractal stimuli. Left EC differentiates items located on the same track following Local Navigation, such that items experienced within the same track became less similar. Following Global Navigation, pattern similarity remained lower for within-track items, but the interaction between context and scan session did not reach statistical significance. A similar pattern of findings was observed in right EC, but interactions between context and scan session did not reach statistical significance (a priori predicted effects: * p < 0.05, uncorrected. Error bars denote SE of the estimates. Hippocampus: Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21; Left EC: n = 20; Right EC: n = 18).

Hippocampal pattern similarity reflects distance in local environments.

(A) Examples of landmarks at link distances 1 and 2 on the same track. (B) Hippocampal pattern similarity for within-track landmarks Pre-Learning (left), after the Local Navigation Task (center), and after the Global Navigation Task (right). Interactions between distance and scan session were significant from Pre-Learning to Post Local and Global Navigation. (C–D) Pattern similarity for within-track landmarks in the left (C) and right (D) EC. Interactions between distance and scan session were not significant. (a priori predicted effects: ** p < 0.01, * p < 0.05, uncorrected. Error bars denote SE of the estimates. Hippocampus: Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21; Left EC: n = 20; Right EC: n = 18).

Distance representations in the Global environment.

(A) Examples of landmarks at different link distances on different tracks. (B) Hippocampal pattern similarity for landmarks on different tracks Pre-Learning (left), after the Local Navigation Task (center), and after the Global Navigation Task (right). The interaction between distance and scan session was significant from Pre-Learning to Post Local Navigation, but not to Post Global Navigation. (C) A similar pattern of findings was observed in Entorhinal Cortex, but the interaction between distance and scan session was not significant from Pre-Learning to Post Local Navigation (a priori predicted effects: ** p < 0.01, uncorrected. Error bars denote SE of the estimates. Hippocampus: Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21; EC: n = 18).

Path inefficiency on the Global Navigation Task varies with across-track distance-related hippocampal pattern similarity after the Local Navigation Task.

To qualitatively visualize the relationship between pattern similarity, link distance, and path inefficiency, we split participants into two groups – More Efficient and Less Efficient – based on their median path inefficiency on across-track trials in the first four test runs of the Global Task on Day 2. (A) Path inefficiency (%) for each across-track trial during the first four test runs of the Global Navigation Task, plotted for each participant and colored by performance group. (B) We used a linear mixed-effects model to formally test this relationship (see main text for details). The linear model revealed a significant interaction between path inefficiency and link distance, with the direction of the effect being unexpected. To qualitatively depict this effect, we plot hippocampal pattern similarity for landmarks on different tracks prior to the Global Navigation Task for the Less Efficient and More Efficient median-split data. Data are split by participants’ subsequent navigation performance as shown in (A). (Error bars denote SE of the estimates. More Efficient, n = 11; Less Efficient, n = 10).

Appendix 1—figure 1
Trial structure for all navigation tasks.

Each behavioral run contained 10 navigation trials. At the start of each run, participants were placed at a location on the track and rotated 360 degrees (6 s). Trials then proceeded as follows: (1) a fractal cue appeared onscreen (1 s) indicating the goal to which the participant should navigate; (2) participants chose their heading direction and (3) navigated to the cued goal location, pressing the spacebar when they arrived; (4) feedback appeared onscreen revealing whether the participant was at the correct location and whether they had navigated via the shortest path (2 s); and (5) the camera panned down and a fixation cross appeared (1 s) before the next trial began. On learning trials, goal locations were marked by fractal images appearing on the track. On test trials, fractals were not visible on the track and participants had to rely on memory to navigate.

Appendix 1—figure 2
Performance improves across the Global Navigation Task.

Individual participants’ performance on across-track navigation trials at the start (first four test runs; left) and end (last two test runs; center) of the task on Day 2, and at the end (last two test runs; right) of Day 3. (A) Percent of across-track trials where participants switched to the correct track. (B) Percent of across-track trials where participants navigated in the correct direction once switching (n = 21).

Appendix 1—figure 3
Hippocampal pattern similarity for landmark buildings on different tracks.

To visualize the relationship between pattern similarity, link distance, and path inefficiency, we split participants into two groups – More Efficient and Less Efficient – based on their median path inefficiency on across-track trials in the first four test runs of the Global Task on Day 2. Pattern similarity relationships did not differ between participants who are more or less efficient on the Global Navigation Task, (A) Pre-Learning (Day 1) and (B) Post Global Navigation (Day 3). (Error bars denote SE of the estimates. More Efficient, n = 11; Less Efficient, n = 10).

Appendix 1—figure 4
Hippocampal pattern similarity (Post Local Navigation) relates to trial-level performance on the subsequent Global Navigation Task.

We observed trend-level evidence that greater hippocampal pattern similarity predicted more efficient paths at the start of Global Navigation for both trial types. (Solid lines = estimated linear fit to the data, gray = 95% CI).

Appendix 1—figure 5
Contrast estimates from a model in vmPFC that includes both landmark and fractal stimuli.

Interactions between scan session and context were not significant. (Error bars denote SE of the estimates. Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21).

Appendix 1—figure 6
Pattern similarity for landmark buildings at different link distances in vmPFC.

(A) Pattern similarity for landmarks on the same track Pre-Learning (left), after the Local Navigation Task (center), and after the Global Navigation Task (right). Interactions between link distance and scan session were not significant. (B) Pattern similarity for landmarks on different tracks. Interactions between link distance and scan session were not significant. (Error bars denote SE of the estimates. Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21).

Appendix 1—figure 7
Contrast estimates for context models fit to data in a visual region serving as a control (calcarine).

Within - across context similarity for landmark buildings. Interactions between scan session and context were not significant. (Error bars denote SE of the estimates. Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21).

Appendix 1—figure 8
Pattern similarity for landmark buildings at different link distances in a visual region serving as a control (calcarine).

(A) Pattern similarity for landmarks on the same track Pre-Learning (left), after the Local Navigation Task (center), and after the Global Navigation Task (right). Interactions between link distance and scan session were not significant. (B) Pattern similarity for landmarks on different tracks. Interactions between link distance and scan session were not significant (Error bars denote SE of the estimates. Day 2 > Day 1, n = 23; Day 3 > Day 1, n = 21).

Tables

Appendix 1—table 1
Linear mixed-effects model results for an omnibus context model predicting neural pattern similarity, fit to data in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 18 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.0350.0093.8588.11e–4
Day 20.0020.0110.1360.892
Day 3–0.0060.012–0.5420.588
stimulus type (landmark > fractal)0.0070.0032.4220.015
context (same track > different tracks)–0.0010.003–0.2540.800
hemisphere0.0060.0022.7560.006*
Day 2 × stimulus type–0.0030.004–0.7150.475
Day 3 × stimulus type–0.0110.004–2.6040.009*
Day 2 × context–0.0020.004–0.3650.715
Day 3 × context–0.0010.004–0.3340.739
stimulus type × context0.0010.0060.2460.806
Day 2 × hemisphere–0.0110.003–3.4775.08e–4*
Day 3 × hemisphere0.0120.0033.7951.48e–4*
stimulus type × hemisphere0.0040.0040.8660.387
context × hemisphere0.0050.0041.0660.287
Day 2 × stimulus type × context–0.0020.009–0.2160.829
Day 3 × stimulus type × context–0.0080.009–0.9200.357
Day 2 × stimulus type × hemisphere–0.0020.006–0.3200.749
Day 3 × stimulus type × hemisphere–0.0010.006–0.1920.848
Day 2 × context × hemisphere–0.0050.006–0.8990.369
Day 3 × context × hemisphere–0.0050.006–0.7670.443
stimulus type × context × hemisphere0.0040.0090.4970.619
Day 2×stimulus type×context × hemisphere–0.0040.012–0.3220.747
Day 3 × stimulus type × context × hemisphere–0.0060.012–0.5110.610
Appendix 1—table 2
Linear mixed-effects model results for a context model predicting neural pattern similarity for landmark buildings, fit to data in left hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.0510.0491.0430.297
Day 20.0010.0140.0580.954
Day 3–0.0110.016–0.6860.493
context (same track > different tracks)0.0000.0050.0030.998
Day 2 × context–0.0030.007–0.4000.689
Day 3 × context–0.0060.007–0.8340.404
Appendix 1—table 3
Linear mixed-effects model results for a context model predicting neural pattern similarity for landmark buildings, fit to data in right hippocampus.

SE = standard error. No correction for multiple comparisons was applied. To correct for multiple comparisons, we adjusted the α-value for 16 tests. No findings survived FDR correction.

VariableβSEtp
(Intercept)0.0620.0491.2600.208
Day 2–0.0110.015–0.7470.455
Day 3–0.0020.017–0.0990.921
context (same track > different tracks)0.0060.0051.3850.166
Day 2 × context–0.0100.007–1.5020.133
Day 3 × context–0.0130.007–2.0140.044
Appendix 1—table 4
Linear mixed-effects model results for a context model predicting neural pattern similarity for fractals, fit to data in left hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.0290.0300.9450.345
Day 20.0030.0120.2620.794
Day 3–0.0020.011–0.1500.881
context (same track > different tracks)–0.0010.004–0.3630.717
Day 2 × context–0.0010.005–0.1110.911
Day 3 × context0.0030.0050.4720.637
Appendix 1—table 5
Linear mixed-effects model results for a context model predicting neural pattern similarity for fractals, fit to data in right hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.1000.0293.3986.89e–4
Day 2–0.0030.012–0.2680.789
Day 30.0110.0140.8170.414
context (same track > different tracks)0.0010.0040.3260.745
Day 2 × context–0.0040.005–0.8230.411
Day 3 × context0.0010.0050.1660.868
Appendix 1—table 6
Linear mixed-effects model results for an omnibus context model predicting neural pattern similarity, fit to data in EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 18 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.0490.0172.9120.004
Day 2–0.0370.020–1.8740.061
Day 3–0.0230.020–1.1780.239
stimulus type (landmark > fractal)0.0080.0051.6070.108
context (same track > different tracks)0.0020.0050.4610.645
hemisphere–0.0220.004–6.0601.37e–9*
Day 2 × stimulus type0.0100.0071.4570.145
Day 3 × stimulus type–0.0030.007–0.3580.720
Day 2 × context–0.0140.007–2.0460.041
Day 3 × context–0.0100.007–1.3940.163
stimulus type × context–0.0010.010–0.1390.889
Day 2 × hemisphere0.0220.0054.1922.77e–5*
Day 3 × hemisphere0.0560.00510.552<2e–16*
stimulus type × hemisphere0.0000.0070.0360.971
context × hemisphere0.0040.0070.5240.600
Day 2 × stimulus type × context0.0020.0140.1320.895
Day 3 × stimulus type × context–0.0050.014–0.3870.699
Day 2 × stimulus type × hemisphere–0.0110.010–1.1320.258
Day 3 × stimulus type × hemisphere–0.0030.010–0.3190.749
Day 2 × context × hemisphere0.0030.0100.2630.793
Day 3 × context × hemisphere0.0010.0100.1170.907
stimulus type × context × hemisphere–0.0090.014–0.6330.527
Day 2 × stimulus type × context × hemisphere–0.0010.020–0.0500.960
Day 3 × stimulus type×context × hemisphere0.0220.0201.0570.291
Appendix 1—table 7
Linear mixed-effects model results for a context model predicting neural pattern similarity, fit to data in left EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests. No findings survived FDR correction.

VariableβSEtp
(Intercept)0.0820.0402.0250.043
Day 2–0.0360.024–1.4900.136
Day 3–0.0260.021–1.2230.221
context (same track > different tracks)0.0030.0040.6560.512
Day 2 × context–0.0140.006–2.3390.019
Day 3 × context–0.0090.006–1.4570.145
Appendix 1—table 8
Linear mixed-effects model results for a context model predicting neural pattern similarity, fit to data in right EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.0670.0491.3620.173
Day 20.0020.0220.0710.943
Day 30.0440.0241.8360.066
context (same track > different tracks)0.0080.0051.4550.146
Day 2 × context–0.0120.007–1.5680.117
Day 3 × context–0.0110.008–1.4040.160
Appendix 1—table 9
Linear mixed-effects model results for a context model predicting neural pattern similarity that included EC and hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 5 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.0740.0213.6233.66e–4
Day 2–0.0120.013–0.8830.377
Day 3–0.0100.013–0.7800.436
context (same track > different tracks)0.0010.0030.4730.636
region–0.0150.002–7.3601.85e–13*
Day 2 × context–0.0040.004–0.9560.339
Day 3 × context–0.0020.004–0.5940.553
Day 2 × region–0.0170.003–5.7578.58e–9*
Day 3 × region0.0140.0034.5924.40e–6*
context × region0.0040.0040.9070.364
Day 2 × context × region–0.0090.006–1.6350.102
Day 3 × context × region–0.0070.006–1.2780.201
Appendix 1—table 10
Linear mixed-effects model results for an omnibus model of local (within-track) distance, predicting neural pattern similarity for landmark buildings in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 5 tests.

VariableβSEtp
(Intercept)0.0440.0123.6219.12e–4
Day 2–0.0160.015–1.0410.298
Day 3–0.0200.016–1.2360.217
distance (link distance 2 > link distance 1)–0.0140.015–0.9740.330
hemisphere0.0060.0110.5280.598
Day 2 × distance0.0360.0211.7210.085
Day 3 × distance0.0330.0211.5200.129
Day 2 × hemisphere–0.0110.015–0.7230.470
Day 3 × hemisphere0.0040.0150.2880.774
distance × hemisphere–0.0030.021–0.1240.901
Day 2 × distance × hemisphere0.0080.0300.2800.780
Day 3 × distance × hemisphere0.0040.0300.1210.904
Appendix 1—table 11
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for landmarks buildings in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests. No results survived FDR correction.

VariableβSEtp
(Intercept)–0.0370.088–0.4190.675
Day 2–0.0210.013–1.5970.110
Day 3–0.0180.014–1.2470.213
distance (link distance 2 > link distance 1)–0.0160.010–1.5100.131
Day 2 × distance0.0400.0152.7000.007
Day 3 × distance0.0340.0152.2590.024
Appendix 1—table 12
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for fractals in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.0380.0470.8020.422
Day 20.0010.0100.0680.946
Day 30.0050.0120.4560.653
distance (link distance 2 > link distance 1)0.0030.0060.4880.625
Day 2 × distance–0.0030.008–0.3680.713
Day 3 × distance–0.0030.008–0.3380.735
Appendix 1—table 13
Linear mixed-effects model results in an omnibus model of global (across-track) distance, predicting neural pattern similarity for landmark buildings in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 5 tests.

VariableβSEtp
(Intercept)0.0330.0162.0230.043
Day 20.0180.0230.7790.436
Day 3–0.0100.023–0.4450.657
distance0.0020.0070.3690.712
hemisphere–0.0120.018–0.6590.510
Day 2 × distance–0.0120.010–1.2970.195
Day 3 × distance0.0000.0100.0440.965
Day 2 × hemisphere0.0190.0250.7630.445
Day 3 × hemisphere0.0160.0260.6320.527
distance × hemisphere0.0110.0101.1590.246
Day 2 × distance × hemisphere–0.0150.013–1.0820.279
Day 3 × distance × hemisphere–0.0070.014–0.4850.628
Appendix 1—table 14
Linear mixed-effects model results in a model of global (across-track) distance, predicting neural pattern similarity for landmark buildings in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.0760.0641.1810.238
Day 20.0570.0272.1260.034
Day 30.0020.0270.0770.939
distance0.0070.0051.5670.117
Day 2 × distance–0.0200.007–2.8910.004*
Day 3 × distance–0.0030.007–0.4130.679
Appendix 1—table 15
Linear mixed-effects model results in a model of global (across-track) distance, predicting neural pattern similarity for fractals in the hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)0.0140.0320.4320.666
Day 2–0.0050.013–0.4120.682
Day 3–0.0030.014–0.1920.849
distance (link distance 2 > link distance 1)–0.0020.002–0.9440.345
Day 2 × distance0.0040.0031.4710.141
Day 3 × distance0.0030.0031.0810.280
Appendix 1—table 16
Linear mixed-effects model results in an omnibus model of local (within-track) distance, predicting neural pattern similarity for landmark buildings in EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 5 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.0530.0212.5210.012
Day 2–0.0570.023–2.5030.012
Day 3–0.0400.024–1.6620.097
distance (link distance 2 > link distance 1)0.0110.0240.4750.635
hemisphere–0.0300.017–1.7750.076
Day 2 × distance0.0060.0330.1910.849
Day 3 × distance0.0080.0340.2260.821
Day 2 × hemisphere0.0500.0242.0930.036
Day 3 × hemisphere0.0690.0242.8350.005*
distance × hemisphere–0.0340.033–1.0310.303
Day 2 × distance × hemisphere0.0290.0470.6200.535
Day 3 × distance × hemisphere0.0260.0480.5450.586
Appendix 1—table 17
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for landmark buildings in left EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.1090.1800.6040.546
Day 2–0.0570.022–2.5290.012
Day 3–0.0430.023–1.9200.055
distance (link distance 2 > link distance 1)0.0110.0210.5080.611
Day 2 × distance0.0070.0300.2380.812
Day 3 × distance0.0070.0310.2320.816
Appendix 1—table 18
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for landmark buildings in right EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)–0.4100.213–1.9210.055
Day 2–0.0010.024–0.0600.952
Day 30.0290.0281.0560.291
distance (link distance 2 > link distance 1)–0.0250.025–0.9770.329
Day 2 × distance0.0340.0360.9370.349
Day 3 × distance0.0380.0371.0430.297
Appendix 1—table 19
Linear mixed-effects model results in an omnibus model of global (across-track) distance, predicting neural pattern similarity for landmark buildings in EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 5 tests.

VariableβSEtp
(Intercept)0.0620.0262.3930.017
Day 20.0030.0360.0910.928
Day 3–0.0360.035–1.0420.297
distance0.0020.0110.1940.846
hemisphere–0.0310.028–1.0960.273
Day 2 × distance–0.0240.015–1.5550.120
Day 3 × distance0.0010.0160.0840.933
Day 2 × hemisphere0.0080.0400.2080.835
Day 3 × hemisphere0.0550.0411.3360.182
distance × hemisphere0.0010.0150.0690.945
Day 2 × distance × hemisphere0.0130.0210.6140.540
Day 3 × distance × hemisphere0.0030.0220.1390.889
Appendix 1—table 20
Linear mixed-effects model results in a model of global (across-track) distance, predicting neural pattern similarity for landmark buildings in EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)0.1390.1021.3610.174
Day 20.0340.0420.8120.417
Day 3–0.0140.041–0.3280.743
distance0.0020.0080.2010.841
Day 2 × distance–0.0170.011–1.6070.108
Day 3 × distance0.0030.0110.2600.795
Appendix 1—table 21
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for fractals in left EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.0940.0980.9650.334
Day 2–0.0410.024–1.6640.110
Day 3–0.0230.027–0.8510.404
distance–0.0150.012–1.2660.205
Day 2 × distance–0.0070.017–0.4220.673
Day 3 × distance0.0160.0170.9460.344
Appendix 1—table 22
Linear mixed-effects model results in a model of local (within-track) distance, predicting neural pattern similarity for fractals in right EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.1160.1141.0210.307
Day 2–0.0160.018–0.9190.368
Day 30.0200.0220.9060.374
distance–0.0040.014–0.2530.800
Day 2 × distance–0.0150.020–0.7690.442
Day 3 × distance0.0030.0200.1470.883
Appendix 1—table 23
Linear mixed-effects model results in a model of global (across-track) distance, predicting neural pattern similarity for fractals in EC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)0.1210.0532.2930.022
Day 2–0.0340.024–1.4150.165
Day 30.0070.0260.2840.778
distance–0.0040.003–1.1020.271
Day 2 × distance0.0080.0051.6550.098
Day 3 × distance0.0040.0050.7780.436
Appendix 1—table 24
Linear mixed-effects model results from a model predicting hippocampal pattern similarity Post Local Navigation (Day 2), with performance on subsequent Global Navigation trials (median path inefficiency for across-track trials in the first four test runs of Global Navigation on Day 2) and link distance as predictors.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 3 tests. No results survived FDR correction.

VariableβSEtp
(Intercept)0.0380.0301.2640.208
distance0.0060.0070.8140.416
path inefficiency0.0010.0011.1740.241
distance × path inefficiency–0.0000.000–1.9830.048
Appendix 1—table 25
Linear mixed-effects model results from a model predicting hippocampal pattern similarity Pre-Learning (Day 1), with performance on subsequent Global Navigation trials (median path inefficiency for across-track trials in the first four test runs of Global Navigation on Day 2) and link distance as predictors.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 3 tests.

VariableβSEtp
(Intercept)0.0730.0262.7860.006
distance–0.0000.007–0.0520.959
path inefficiency–0.0010.001–1.8250.070
distance × path inefficiency0.0000.0001.5230.128
Appendix 1—table 26
Linear mixed-effects model results from a model predicting hippocampal pattern similarity Post Global Navigation (Day 3), with performance on subsequent Global Navigation trials (median path inefficiency for across-track trials in the first four test runs of Global Navigation on Day 2) and link distance as predictors.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 3 tests.

VariableβSEtp
(Intercept)0.0560.0301.8470.067
distance–0.0030.007–0.3470.729
path inefficiency–0.0010.001–1.0680.288
distance × path inefficiency0.0000.0001.3790.168
Appendix 1—table 27
Linear mixed-effects model results from a model predicting median path inefficiency across first four test runs of Global Navigation on Day 2, with hippocampal pattern similarity Post Local Navigation (Day 2) for landmark pairs and the length of the optimal path as predictors.

SE = standard error.

VariableβSEtp
(Intercept)75.94412.7435.9603.07e-8
hippocampal pattern similarity (LMA, LMB)–41.24524.163–1.7070.088
length of optimal path20.5516.2453.2910.001
trial type (within-track > across-track)–0.6630.183–3.6310.0003
hippocampal pattern similarity × length of optimal path54.61843.4891.2560.210
Appendix 1—table 28
Linear mixed-effects model results from a model predicting median path inefficiency across first four test runs of Global Navigation on Day 2, with hippocampal pattern similarity Post Local Navigation (Day 2) for fractal pairs and the length of the optimal path as predictors.

SE = standard error.

VariableβSEtp
(Intercept)71.85512.3525.8173.98e-8
hippocampal pattern similarity (FRA, FRB)3.02627.6870.1090.913
length of optimal path27.2896.1964.4041.23e-5
trial type (within-track > across-track)–0.6460.184–3.5190.0005
hippocampal pattern similarity × length of optimal path–68.10748.915–1.3920.164
Appendix 1—table 29
Linear mixed-effects model results for a context model predicting neural pattern similarity that included vmPFC and hippocampus.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 6 tests. No results survived FDR correction.

VariableβSEtp
(Intercept)0.0540.0183.0170.003
Day 2–0.0050.010–0.5280.603
Day 3–0.0020.009–0.2390.813
context (same track > different tracks)0.0010.0020.5250.600
region–0.0050.002–2.1950.028
Day 2 × context–0.0040.003–1.1560.248
Day 3 × context–0.0020.003–0.7200.471
Day 2 × region0.0050.0031.7610.078
Day 3 × region–0.0050.003–1.6600.097
context × region0.0020.0040.3860.700
Day 2 × context × region–0.0000.006–0.0080.993
Day 3 × context × region0.0050.0060.8450.398
Appendix 1—table 30
Linear mixed-effects model results from a context model predicting neural pattern similarity that included the hippocampus, EC, vmPFC and a visual control region.

The visual control region served as a baseline. SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 18 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.5910.01930.662<2e-16
Day 2–0.0420.014–3.0530.005
Day 3–0.0390.016–2.4000.024
context (same track > different tracks)0.0020.0040.4250.670
region (hippocampus)–0.4990.003–176.735<2e-16*
region (EC)–0.5130.003–181.929<2e-16*
region (vmPFC)–0.4800.003–144.553<2e-16*
Day 2 × context–0.0030.006–0.4600.645
Day 3 × context–0.0040.006–0.5870.557
Day 2 × region (hippocampus)0.0270.0047.2334.74e-13*
Day 3 × region (hippocampus)0.0300.0047.6731.68e-14*
Day 2 × region (EC)0.0120.0043.0240.002*
Day 3 × region (EC)0.0390.0049.957<2e-16*
Day 2 × region (vmPFC)0.0310.0047.0292.09e-12*
Day 3 × region (vmPFC)0.0120.0042.6330.008*
context × region (hippocampus)–0.0010.005–0.1160.908
context × region (EC)0.0030.0050.5670.570
context × region (vmPFC)0.0010.0060.1560.876
Day 2 × context × region (hippocampus)–0.0010.008–0.1170.907
Day 3 × context × region (hippocampus)0.0010.0080.1820.855
Day 2 × context × region (EC)–0.0100.008–1.3490.177
Day 3 × context × region (EC)–0.0060.008–0.7800.435
Day 2 × context × region (vmPFC)–0.0010.009–0.1090.913
Day 3 × context × region (vmPFC)0.0060.0090.7250.468
Appendix 1—table 31
Linear mixed-effects model results for a context model predicting neural pattern similarity, fit to data in vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.0490.0361.3660.172
Day 2–0.0040.015–0.2440.809
Day 3–0.0150.015–0.9810.340
context (same track > different tracks)0.0030.0040.7480.455
Day 2 × context–0.0040.005–0.7310.465
Day 3 × context0.0020.0050.4630.643
Appendix 1—table 32
Linear mixed-effects model results from a distance model predicting neural pattern similarity for landmark buildings that included the hippocampus and vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 6 tests.

VariableβSEtp
(Intercept)0.0360.0370.9820.326
Day 20.0020.0140.1380.890
Day 3–0.0030.012–0.2050.837
distance0.0040.0021.8530.064
region–0.0050.010–0.5440.587
Day 2 × distance–0.0030.003–1.0250.306
Day 3 × distance–0.0020.003–0.5720.567
Day 2 × region0.0220.0141.5430.123
Day 3 × region–0.0020.014–0.1260.900
distance × region–0.0020.004–0.5250.600
Day 2 × distance × region–0.0030.005–0.6630.508
Day 3 × distance × region0.0010.0050.1560.876
Appendix 1—table 33
Linear mixed-effects model results from a distance model predicting neural pattern similarity for landmark buildings that included the hippocampus, vmPFC, and a visual control region.

The visual control region served as a baseline. SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 12 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)0.5370.03714.413<2e-16
Day 2–0.0870.020–4.3296.55e-5
Day 3–0.0590.022–2.7120.009
distance–0.0020.003–0.6280.530
region (hippocampus)–0.5060.011–46.889<2e-16*
region (vmPFC)–0.4830.013–38.294<2e-16*
Day 2 × distance0.0080.0051.6550.098
Day 3 × distance–0.0010.005–0.2330.816
Day 2 × region (hippocampus)0.0770.0155.1023.38e-7*
Day 3 × region (hippocampus)0.0470.0153.0790.002*
Day 2 × region (vmPFC)0.0890.0175.1292.92e-7*
Day 3 × region (vmPFC)0.0280.0181.5490.121
distance × region (hippocampus)0.0060.0041.3870.165
distance × region (vmPFC)0.0050.0051.0730.283
Day 2 × distance × region (hippocampus)–0.0100.006–1.8210.069
Day 3 × distance × region (hippocampus)–0.0000.006–0.0410.967
Day 2 × distance × region (vmPFC)–0.0150.007–2.2960.022*
Day 3 × distance × region (vmPFC)–0.0010.007–0.0860.931
Appendix 1—table 34
Linear mixed-effects model results from a model of local (within-track) distance, predicting neural pattern similarity for landmark buildings in vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.1440.1670.8660.387
Day 2–0.0050.027–0.1740.862
Day 3–0.0240.027–0.8670.386
distance (link distance 2 > link distance 1)–0.0050.020–0.2340.815
Day 2 × distance0.0250.0280.9100.363
Day 3 × distance0.0210.0290.7450.456
Appendix 1—table 35
Linear mixed-effects model results from the model of global (across-track) distance, predicting neural pattern similarity for landmark buildings in vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)0.0550.1190.4620.644
Day 20.0430.0440.9930.321
Day 3–0.0010.046–0.0120.990
distance0.0080.0090.9550.340
Day 2 × distance–0.0130.013–1.0710.284
Day 3 × distance–0.0040.013–0.3200.749
Appendix 1—table 36
Linear mixed-effects model results from the model of local (within-track) distance, predicting neural pattern similarity for fractals in vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)–0.0090.085–0.1070.914
Day 20.0040.0210.1720.864
Day 3–0.0020.022–0.0940.926
distance0.0090.0100.8650.387
Day 2 × distance–0.0050.015–0.3470.729
Day 3 × distance–0.0210.015–1.4030.161
Appendix 1—table 37
Linear mixed-effects model results from the model of global (across-track) distance, predicting neural pattern similarity for fractals in vmPFC.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)–0.0550.058–0.9580.338
Day 20.0010.0230.0220.982
Day 3–0.0460.024–1.9740.053
distance0.0020.0040.4320.666
Day 2 × distance–0.0010.006–0.1360.892
Day 3 × distance0.0090.0061.6320.103
Appendix 1—table 38
Linear mixed-effects model results from a model predicting neural pattern similarity between pairs of items in vmPFC, with scan session, hippocampal pattern similarity, and pattern similarity in a visual control region (calcarine) as predictors.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 2 tests. An asterisk (*) denotes findings that survived FDR correction.

VariableβSEtp
(Intercept)–0.0070.022–0.3310.743
Day 2–0.0060.019–0.2980.768
Day 30.0040.0200.1990.844
hippocampal pattern similarity (ItemA, ItemB)0.4140.02914.3871.25e-14
calcarine pattern similarity (ItemA, ItemB)0.1080.0205.4654.83e-6
Day 2 × hippocampal pattern similarity (ItemA, ItemB)–0.0940.016–5.7131.11e-8
Day 3 × hippocampal pattern similarity (ItemA, ItemB)–0.0760.017–4.3551.34e-5
Day 2 × calcarine pattern similarity (ItemA, ItemB)0.0190.0131.4270.154
Day 3 × calcarine pattern similarity (ItemA, ItemB)–0.0200.014–1.4330.152
Appendix 1—table 39
Linear mixed-effects model results from a context model predicting neural pattern similarity, fit to data from a visual control region.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 16 tests.

VariableβSEtp
(Intercept)0.5540.04313.030<2e-16
Day 2–0.0210.025–0.8200.412
Day 3–0.0390.041–0.9440.345
stimulus type (landmark > fractal)–0.0240.003–7.0092.45e-12
context (same track > different tracks)0.0010.0030.2450.806
Day 2 × stimulus type0.0050.0051.0880.277
Day 3 × stimulus type–0.0020.005–0.4070.684
Day 2 × context–0.0030.005–0.7170.474
Day 3 × context–0.0020.005–0.4160.678
stimulus type × context–0.0080.007–1.2520.211
Day 2 × stimulus type × context–0.0040.009–0.3770.706
Day 3 × stimulus type × context0.0140.0101.5090.131
Appendix 1—table 40
Linear mixed-effects model results from a model of local (within-track) distance predicting neural pattern similarity, fit to data from a visual control region.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 10 tests.

VariableβSEtp
(Intercept)0.3170.1352.3430.019
Day 2–0.0400.030–1.3510.177
Day 3–0.0250.044–0.5770.564
distance (link distance 2 > link distance 1)0.0140.0160.8700.384
Day 2 × distance0.0070.0220.3040.761
Day 3 × distance–0.0350.022–1.5700.117
Appendix 1—table 41
Linear mixed-effects model results from a model of global (across-track) distance predicting neural pattern similarity, fit to data from a visual control region.

SE = standard error. To correct for multiple comparisons, we adjusted the α-value for 8 tests.

VariableβSEtp
(Intercept)0.4180.0954.3791.31e-5
Day 2–0.0030.040–0.0820.935
Day 3–0.0610.051–1.1900.234
distance–0.0050.007–0.7830.434
Day 2 × distance–0.0030.010–0.2610.794
Day 3 × distance0.0070.0100.7270.468

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  1. Corey Fernandez
  2. Jiefeng Jiang
  3. Shao-Fang Wang
  4. Hannah Lee Choi
  5. Anthony D Wagner
(2023)
Representational integration and differentiation in the human hippocampus following goal-directed navigation
eLife 12:e80281.
https://doi.org/10.7554/eLife.80281