• Figure 2.
    Download figureOpen in new tabFigure 2. Stimulus-evoked population tuning curves.

    (A) Average population tuning curve, 50–300 ms after stimulus onset. (B) Time-resolved population tuning curve, showing a sharp increase in the tuning curve slope shortly after stimulus onset, tapering off within 500 ms.

    DOI: http://dx.doi.org/10.7554/eLife.09000.005

    Figure 3.
    Download figureOpen in new tabFigure 3. Task variable representation using population tuning curves (see Figure 2).

    (A) Stimulus orientation was represented in the early visual response. We fit weights (using linear regression of stimulus orientation on the neural response) using all trials in all training blocks and estimated virtual channel responses in the test block. Orientation-specific coding was estimated by calculating the linear slope of the tuning curve (between 0° and 90°). Consistent positive slopes indicate orientation selectivity at a given time point. Shading indicates between-subject standard error of the mean. Black bars denote significant time points (cluster-corrected). (B) Univariate sensitivity for stimulus orientation, calculated at each sensor and time point. Topography shows the shuffle-corrected orientation sensitivity (z-scored against a distribution generated from permuting stimulus orientations 1000 times), averaged across sensor triplets (two orthogonal planar gradiometers and one magnetometer) and across the stimulus-decoding window. Color coding denotes the z-score, averaged across observers. (C) Tuning curve slope and topography (D) for template orientation sensitivity. E and F show the same analyses, sorting trials by the angular distance between template and stimulus (i.e., the decision value).

    DOI: http://dx.doi.org/10.7554/eLife.09000.006

    Figure 4.
    Download figureOpen in new tabFigure 4. Cross-temporal generalization of orientation decoding.

    (A) Tuning curve amplitude for stimulus orientation, estimated by calculating weights at one time point and applying them to test data at all time points in a trial. While decoding is consistently high along the diagonal (in the time window that contains significant stimulus information, between 52 and 544 ms, significant cluster indicated by color saturation/opacity), the slope drops sharply at off-diagonal train-test time coordinates. This indicates that the discriminative patterns are not consistent across time—rather they change rapidly, even while the stimulus can be readily decoded (i.e. off-diagonal decoding is significantly lower than on-diagonal decoding, black outline). B and C show the same analyses as in A, but sorting all trials by the template angle and the decision-relevant angular distance, respectively.

    DOI: http://dx.doi.org/10.7554/eLife.09000.007

    Figure 5.
    Download figureOpen in new tabFigure 5. Cross-generalization from template-discriminative patterns to stimulus-discriminative patterns.

    (A) Calculating tuning-curve weights relative to the template orientations in a training data set (in window from –150 to +300 ms around stimulus onset), applying these weights on test data, and sorting them relative to the stimulus orientation, showed decoding early after stimulus onset that quickly returned to baseline. (B) Calculating population weights only on the pre-stimulus period (with respect to the template orientations) yielded a population tuning curve with a significant peak around the presented stimulus orientation (e.g. a significant peak above the average response around 0º, and a significant positive tuning curve slope between ± 90º and 0º). Shading indicates the standard error of the mean. Black bars indicate significant time points or orientations (p < 0.05).

    DOI: http://dx.doi.org/10.7554/eLife.09000.008

    Figure 6.
    Download figureOpen in new tabFigure 6. Cross-temporal generalization of representational similarity.

    (A) Pearson correlations between stimulus-orientation-sorted distance matrices, calculated at different time points and on independent data sets. Color saturation shows significant cluster at the group level (permutation test). The cluster extends off the diagonal in a square, indicating substantial cross-temporal generalization. In addition, there is a small dynamic cluster (black outline), meaning that pairs of time points within the black outline showed significantly lower correlations than their corresponding time points on the diagonal (even though they were still significantly greater than 0). (B) shows the same analysis as in A, but sorting all trials by the decision-relevant angular distance. There were no significant dynamic clusters. RSA, representational similarity analysis.

    DOI: http://dx.doi.org/10.7554/eLife.09000.009

    Figure 7.
    Download figureOpen in new tabFigure 7. Geometry of stimulus and template coding.

    (A) The representational similarity structures between template- and stimulus-ordered responses were significantly correlated in the early stimulus-processing window (saturated colors indicate significant cluster). (B) The within-time comparison also showed a significant correlation in the representational similarity structure from 104 to 176 ms. Values correspond to the mean regression coefficient across all observers. Shading is between-subjects standard error of the mean. (C) Multi-dimensional scaling of the distances between stimulus orientations was not visible before stimulus onset. (D) Shortly after stimulus onset, the circular structure indicated that responses used a circular geometry. (E To quantify the representational structure over time, we fit (using regression) to the neural distance matrix between all angles (16 different angles, split randomly into two sets of trials, resulting in a 32×32 distance matrix of Mahalanobis distances) the distance matrix of a 16-point circular simplex, shown in (F). (G) Similarly, relationships between the eight template orientations fit a circular structure, particularly around stimulus onset time. (H) An example of a simplex from one session, with the eight chosen template angles highlighted in color, and the eight stimulus orientations which were never targets shown in gray.

    DOI: http://dx.doi.org/10.7554/eLife.09000.010

  • The following datasets were generated:

    Myers N, Rohenkohl G, Wyart V, Woolrich M, Nobre A, Stokes M, 2015,Data from: Testing sensory evidence against mnemonic templates, http://datadryad.org/review?doi=doi:10.5061/dryad.m57sd, Available at Dryad Digital Repository under a CC0 Public Domain Dedication