Article Figures & Data
Figures
- Figure 1.
Task design of Experiment 1. A, In the perception phase, subjects viewed images of faces or scenes one at a time and judged whether each image was “old” (repeated within the run) or “new” (novel). The perception phase was similar in Experiment 2, with the main exception being that scene trials were not included. B, In the memory phase, subjects viewed two faces in a row, followed by a number cue indicating which of the two faces to maintain during the delay period. Following the delay period, a probe (partial face image) was presented and subjects indicated whether the probe matched the cued face or not.
- Figure 2.
Schematic of the face reconstruction analysis. A, Model training. First, PCA was run on a large set of training face images to extract a relatively small number of eigenfaces, so that any face image could be efficiently expressed as a weighted sum of the eigenfaces. A regularized linear regression was next applied to estimate a model that could predict the eigenface scores of the training faces from the voxel responses they evoked. B, Model testing. Voxel responses evoked by an independent test face were measured, and the eigenface scores of the test face were predicted by applying the weights estimated from the trained regression model to the measured responses. Finally, a reconstruction was generated by taking the linear combination of the eigenfaces using the predicted scores. C, Assessing reconstruction accuracy. The accuracy of a reconstruction was evaluated with 2AFC tests, which compared the Euclidean distance between the eigenface scores of the reconstructed face and those of its original image or other test images (“lures”). A reconstruction was counted as accurate when it was more similar (lower Euclidean distance) to the original image than to the lure image.
- Figure 3.
A, Anatomical and functional ROIs (orange represents ANG; blue represents SMG; yellow/green represents IPS; magenta represents SPL; turquoise represents probabilistic map of the 2500 most face-preferring voxels in OTC), visualized on the inflated surface of an averaged template brain supplied by FreeSurfer. Top, Right lateral view. Bottom, Ventral view. Turquoise color scale represents the percentage of sessions (computed from all sessions collapsed across experiments) where a voxel is included in the OTC functional ROI mask. Regions corresponding to the fusiform face area (FFA) and occipital face area (OFA) are included in the OTC functional ROI in most sessions. B, Mean reconstruction accuracies for each ROI in each experiment. Reconstructions were generated from the perception phase data using 300 eigenfaces. Error bars indicate SEM across subjects. C, Mean reconstruction accuracy for perceived faces in ANG and OTC as a function of the number of eigenfaces included in the reconstruction. Shaded areas represent SEM across subjects. ***p < 0.001.
- Figure 4.
Example face images and their reconstructions from a single subject's perception phase data. Top row, Original test faces. Middle row, Reconstructions from OTC. Bottom row, Reconstructions from ANG. The five left-most columns (with blue bars above the reconstructions) represent examples of successful reconstructions (>50% 2AFC accuracy). The two right-most columns (with gray bars above the reconstructions) represent examples of unsuccessful reconstructions (<50% 2AFC accuracy). Gray numbers at the upper right-hand corners of each reconstruction indicate the mean 2AFC accuracy for each reconstructed image (for the selected subject). Reconstructions were generated using 300 eigenfaces.
- Figure 5.
Correlations between z-scored subjective ratings for original faces and those for reconstructions from OTC (top row) and ANG (bottom row). Reconstructions were generated with the perception phase data using 300 eigenfaces. Each dot indicates a test face. Solid lines indicate fitted regression lines. Shaded areas represent 95% bootstrapping confidence intervals. +p < 0.1. *p < 0.05. ***p < 0.001.
- Figure 6.
A, Mean memory-based reconstruction accuracies for each ROI, combined across experiments. Reconstructions were generated with patterns averaged across 3–5 TRs from the cue onset using 300 eigenfaces. Error bars indicate SEM across subjects. B, Mean reconstruction accuracies in ANG and OTC over the course of the delay period. The first time window started with the onset of the sample faces and the last time window stopped 2 TRs before the probe onset (to avoid “contamination” by the partial-face probe image). Reconstructions for each time window were generated using fMRI activation patterns averaged within the window. The average accuracy in ANG was significantly above chance at the fourth time window (mean 54.3%, p = 0.0021) and marginally above chance at the third (mean 52.4%, p = 0.095) and the sixth time window (mean 52.6%, p = 0.065). Shaded areas represent SEM across subjects. Dotted line indicates chance level. +p < 0.1. *p < 0.05. **p < 0.01. C, Example target faces from the memory phase (left column) and corresponding reconstructions from ANG from a representative single subject's data (right column). The first three rows (with blue bars on the left) represent successful (more similar to the target than to the lure image) reconstructions, and the last row (with a gray bar on the left) represents an unsuccessful (more similar to the lure than to the target image) example for comparison. Reconstructions were generated with patterns averaged across 3–5 TRs from the cue onset using 300 eigenfaces.
- Figure 7.
Reconstruction accuracy in ventral PPC subregions defined from independent intrinsic functional connectivity analyses (Yeo et al., 2011). A, ROI visualization on the lateral surface of both hemispheres of the FreeSurfer template brain. White lines indicate the boundaries of each subregion from Yeo et al. (2011). Black numbers indicate the names of the networks from which each subregion is derived. Orange areas represent anatomically defined ANG based on FreeSurfer parcellation. B, Mean accuracies for the perception-based (left) and working memory-based (right) reconstructions. All reconstructions were generated using 300 eigenface components. Memory-based reconstructions were generated from activation patterns averaged across 3–5 TRs from the cue onset. A, B, Means and SEMs were computed from the data combined across experiments. Error bars indicate SEM across subjects. Significance is against chance. *p < 0.05. **p < 0.01. ***p < 0.001.
- Figure 8.
Correlations between predicted eigenface scores from OTC and PPC. For each reconstructed face, Pearson's correlation was computed between the 300 predicted eigenface scores from each region. The correlation coefficients were transformed to Fisher's z, and averaged across faces. Left, Correlations between OTC and each of the anatomically defined PPC subregions during the perception phase (ANG: 0.39, SMG: 0.36, IPS: 0.34, SPL: 0.38). OTC-ANG correlations were significantly higher than OTC-SMG or OTC-IPS correlations (p = 0.037 and p = 0.0017, respectively). OTC-SMG and OTC-SPL correlations were also higher than OTC-IPS correlation (p = 0.042 and p = 0.0008, respectively). Error bars indicate SEM across subjects. *p < 0.05. **p < 0.01. Right, Correlations between ANG and OTC during the working memory phase at each 3-TR-long time window over the course of the delay period. The first time window started with the onset of the sample faces. Correlations were significantly stronger during the last three time windows than the first three time windows (p = 0.029). Shaded areas represent SEM across subjects. In both panels, means and SEM were computed from the data combined across experiments.
- Figure 9.
Behavioral change-detection experiment. A, Trial structure of the experiment. Subjects studied a set of six sample face images, followed by masks generated from scrambled face images. The subjects' task was to remember all six faces during the following brief delay. After the delay, a single probe face was presented at one of the six locations, and subjects indicated whether or not the probe face matched the sample face that had been studied at that location. B, Example pairs of sample and probe faces with high (top row), medium (middle row), and low (bottom row) eigenface score similarity. The z-scored Euclidean distances between the eigenface scores were −2.23, 0.01, and 2.72, respectively. C, Logistic regression testing for the relationship between the probability of making a “match” response on nonmatch trials and eigenface score similarity between the sample and probe faces. The numbers of correct and incorrect trials were controlled to be identical within each subject. Each dot indicates a single trial in the nonmatch condition, and trials from all subjects are shown. A value of 1 on the y-axis represents a “match” response, and a value of 0 represents a “nonmatch” response. Smaller values on the x-axis represent higher similarity (lower Euclidean distance) between the faces. Solid line indicates the fitted logistic regression line. The shaded area represents 95% bootstrapping confidence intervals. **p < 0.01.
