Sentence examples for exemplar identification from inspiring English sources

The number of voxels for which the cross-participant object exemplar identification accuracy was greatest ranged from 50 to 2000 voxels, depending on the participant (Table S1).

Other brain areas also carry reliable information about individual tools and dwellings, demonstrating that the exemplar identification can be based on the neural representations of higher-level facets of the object properties.

The locations of voxels that underpinned this accurate object exemplar identification (i.e., the diagnostic voxels), were similar (at a gyral level) across participants, and were distributed across the cortex (as shown in Figure 3).

The number of voxels (each 3.125×3.125×6 mm3 or 59 mm3 in volume) for which object exemplar identification accuracy was greatest (as plotted in Figure 2) ranged from 25 to 400 voxels, depending on the participant (Table S1).

For example, for one participant whose object exemplar identification accuracy based on the whole cortex was 0.94, the single-region accuracy was 0.77 for left superior extrastriate (SES), 0.77 for LIPL, and 0.82 for left inferior extrastriate cortex (IES).

The highest exemplar identification rank accuracy obtained in this leave-one-participant-out method was 0.81 for one of the participants (compared to an accuracy of 0.53 from random predictions).

As was the case for exemplar identification, the accuracies of the category identification using voxels from only a single anatomical region were high; in some cases, these approached the accuracy obtained when the whole cortex was used (0.93 for left IES cortex, 0.83 for left SES cortex, and 0.82 for LIPL, vs. 0.98 for the whole cortex, for one of the participants).

The information content within a number of individual anatomical regions is sufficient for exemplar and category identification, but the content of the representation appears to be somewhat different across regions.