The 16 predefined line segments of McClelland and Rumelhart (1981) and five example letters

Summary of the meg results obtained by Vartiainen et al. (2011).

A: Examples of stimuli used in the meg experiment. Each stimulus contained 7–8 letters or symbols.

B: Source estimate of the evoked meg activity, using mne-dspm. The grand-average activity to word stimuli, averaged for three time intervals, is shown in orange hues. For each time interval, white circles indicate the location of the most representative left-hemisphere ecd for each participant, as determined by Vartiainen et al. (2011).

C: Grand-average time course of signal strength for each group of ecds in response to the different stimulus types. The traces are color-coded to indicate the stimulus type as shown in A. Shaded regions indicate time periods over which statistical analysis was performed.

D: For each group of ecds shown in B, and separately for each stimulus type (different colors, see A), the distribution (and mean) of the grand-average response amplitudes to the different stimulus types, obtained by integrating the ecd signal strength over the time intervals highlighted in C. Whenever there is a significant difference (linear mixed effects (lme) model, p < 0.05, false discovery rate (fdr) corrected) between two adjacent distributions, the corresponding difference in means is shown.

Overview of the proposed computational model of visual word recognition in the brain.

A: The vgg-11 model architecture, consisting of five convolution layers, two fully connected layers and one output layer.

B: Examples of the images used to train the model.

Response profiles obtained from the models.

For each layer, the response profile, i.e. the z-scored magnitude of relu activations in response to the same stimuli as used in the meg experiment, is shown. Whenever there is a significant difference (t-test, p < 0.05, fdr corrected) between two adjacent distributions, the corresponding difference in means is shown.

Correlations between all models and MEG responses.

For each model, the maximum correlation between the response profiles obtained from all layers of the model and the response profiles of the type-i, type-ii and n400m evoked meg components. This was evaluated on both the grandaverage level and for each individual subject. Estimated noise ceilings are indicated with vertical lines. The grand average analysis only has a single estimate, for the single subject analysis the shaded area indicates the range between pessimistic estimate and the optimistic estimate, in between which the true noise ceiling should lie. Significant differences between neighboring distributions are indicated with stars (paired t-test, *p < 0.05, **p < 0.01, ***p < 0.001, fdr corrected).

A closer look at the relationship between the final model and MEG responses.

A: Relationship between the response profiles obtained from evoked meg activity, quantified using three ecd groups, and the response profiles obtained from three layers of the model. Kernel density distributions are shown at the borders.

B: Correlation between the mne-dspm source estimate and the model. Grandaverage source estimates were obtained in response to each stimulus. The correlation map was obtained by correlating the activity at each source point with that for three layers of the model. The correlation map is shown at the time of peak correlation (within the time windows indicated in Figure 2C). Only positive correlations are shown.

Post-hoc exploration of various experimental contrasts.

For each contrast, four sample stimuli are shown to demonstrate the effect of the manipulated stimulus property and below are the correlation between the manipulation and the amount of activity in each layer of the final model. For the experimental contrasts indicated with a number, one or more confounding factors were corrected for (partial correlation). Different colors indicate convolution layers (blue), fully connected layers (orange) and the output layer (green).