On the single subject level, we modelled all four conditions of the paradigm (familiar faces, unfamiliar faces, familiar places, unfamiliar places) in the context of the general linear model (GLM).
Data from Experiment 1 are reported at the group level for all conditions and the single subject level for the one-back identity task that we predicted would show the strongest word selectivity effects.
In the single subject randomized alternation design, any session can be randomly allocated to any treatment condition.
Therefore, as in the unmasked conditions, there was no consistent or interpretable evidence, at the single subject level, that repetition suppression was greater within than between stimulus type.
To determine the across-subject consistency of the above findings, the data normalization process applied to the single subject case, as shown in Figure 2 and described above, was repeated for data collected under each condition across all subjects.
For each selected area (in the single subject ROI approach and in the averaged voxelwise approach) we extracted the event-related time course for each subject, each condition and each experiment separately.
Two relevant event-categories were used to compute the single-subject average: the neutral condition and the fear condition.
Statistical analysis was done in SPM2, using "Single-subject: conditions & covariates" to compare ventriclar volume between different groups.
The single-subject GLMs included 10 conditions corresponding to F-Hit, F-Miss, B-Hit, B-Miss and CR; separately for the two viewing conditions (bmC/mC).
At the single-subject level, event onsets from all 5 conditions (Evoked Laughter, Emitted Laughter, Disgust, Unintelligible Baseline, Rest Baseline) were modeled as instantaneous and convolved with the canonical hemodynamic response function.
We again used a GLM with averaged BOLD signal of all voxels within ROIs at the single-subject level and computed the value of the regression coefficient (beta) of V t) averaged across subjects for each tryptophan condition.
