Results for key language measures are shown in . The Western Aphasia Battery identified 6 of the 64 patients as ‘recovered’ (AQ > 93.8) (Kertesz, 1979
), although all 6 scored outside the control range on other tests in the battery. The remaining 58 were classified as follows: anomic (n
= 24), Broca's (n
= 19), conduction (n
= 10), Wernicke's (n
= 4), transcortical motor (n
= 1). The under-representation of Wernicke's aphasia (7%) and transcortical sensory aphasia (0%) is to be expected in chronic, unselected samples and reflects the tendency for these subtypes to evolve into anomic or conduction aphasia as the early symptoms—neologistic jargon and profound comprehension deficit—recover (Kertesz and Benson, 1970
; Kertesz and McCabe, 1977
; Goodglass and Kaplan, 1983
Language test data and control norms
On the Philadelphia Naming Test, there was a wide range in the proportion of items correct (0.02–0.97), with the median falling at 0.80, which is outside the normal range. The proportion of semantic errors (SemErr) produced was maximal at 0.12. This is roughly comparable with other large, unbiased aphasia samples (e.g. Dell et al.
; Schwartz et al.
). Not surprisingly, studies that select for semantic error production or employ criteria that bias towards semantic impairment tend to report higher semantic error frequencies (Ruml et al.
; DeLeon et al.
). Relative to total errors (instead of total trials), semantic error production ranged from 0.00 to 0.77 (SemErr/TotErr in ). The purest semantic error patterns (0.30 or more SemErr/TotErr) occurred exclusively in the most accurate patients (0.70 or more correct).
The four comprehension tests all yielded scores below the mean for healthy elderly controls, as shown in . The two non-verbal tests correlated strongly with one another, (r = 0.79, P < 0.001), as did the two verbal tests (r = 0.64, P < 0.001). The correlation between NVcomp and SemErr was −0.44 (P < 0.001) and that between Vcomp and SemErr, −0.27 (P = 0.03).
Characterization of lesion data
After excluding voxels with fewer than five lesions, the number of voxels that qualified for analysis was 404 565, or 55% of the 738 535 voxels in the left hemisphere (using counts from the electronic AAL atlas) (Tzourio-Mazoyer et al.
). This included 83 096 distinct patient-lesion patterns, in which each such pattern is defined by the subset of patients lesioned in a voxel. The number of distinct voxels is maximal for lesion counts around 16, a quarter of the total patients. The number of voxels with between 27 and 37 lesions (37 was the maximum) was 47 558, representing 11 482 patterns.
In voxel-based lesion-symptom mapping, differences in power between regions are due to differences in the frequency with which lesions impinge the region. Maximal power is achieved in voxels lesioned in half the patients (32 in the present dataset). shows a colour map of the number of patients with lesions in each voxel and suggests the relative (not absolute) power of each voxel for detecting an association, if one exists, between lesioned status and the behavioural measures.
Figure 2 Maps depicting lesion overlaps of the 64 subjects in the left hemisphere. Maps (A—D) are at MNI x coordinates of −60, −54, −48 and −42, respectively. Map (E) is a single axial slice at z = −27. The regions (more ...)
There are obvious and predictable limitations in our coverage. As aphasia is typically associated with strokes in the middle cerebral artery territory, we are unable to explore the contribution of brain regions typically supplied by the posterior or anterior cerebral arteries. These regions include the mesial portions of the hemisphere as well as the occipital lobe, posterior inferior temporal lobe and mesial temporal lobe. On the other hand, the entire peri sylvian region had good coverage. For example, in the left inferior frontal gyrus (Brodmann area 44/45) voxels with as many as 35 lesions were identified. The maximum number of lesions in the posterior superior temporal lobe and the superior portion of Brodmann area 37 were 28 and 24, respectively. Finally, it is important to note that voxels with substantial numbers of lesions were identified in the temporal pole (Brodmann area 38) and anterior middle temporal gyrus (Brodmann area 21); in the former, the maximal lesion count was 19, 16 in the latter.
The map in depicts t-values for the difference in total lesion volume between patients with and without damage at each voxel. It shows that local lesion status is highly predictive of overall lesion volume in most of the left hemisphere—the relationship is no stronger in the anterior temporal lobe than elsewhere in the anterior half of the left hemisphere. In effect, lesion size was not strongly predicted by lesion location in this sample.
Figure 3 Maps of the reliability (t-statistic) of the difference in lesion volume between patients with and without lesions in each voxel (rendered on the MNI-space ch2 volume). Voxels exceeding an arbitrary threshold of 4 are rendered in a red (t = 4) to yellow (more ...)
In the analysis performed to explore the anatomic basis of the variable SemErr, we found 35 466 voxels for which a significant correlation between lesion status and impaired performance on the SemErr measure was identified. As indicated in , the voxels with the highest t-values were located in the anterior temporal lobe. The highest concentration of significant voxels (19 411 voxels) was in the anterior half of the middle temporal gyrus and the temporal pole, in Brodmann area regions 21 and 38, respectively. A second distinct cluster of significant voxels was located in the posterior portion of the middle temporal gyrus, corresponding to the lateral and superior portion of Brodmann area 37 at approximately the termination of the middle temporal gyrus/occipital junction. There was also a smaller cluster of significant voxels in the left lateral prefrontal cortex; they were primarily located in the inferior and middle frontal gyri, corresponding to Brodmann areas 45 and 46. There were also a small number of significant voxels in the deep white matter. As indicated in , there were no significant voxels in the posterior superior temporal gyrus, corresponding to Wernicke's area; indeed, the peak t-values observed in this region were around 1.8, far below the critical t (3.27).
Figure 4 Maps of the reliability (t-statistic) of the difference in SemErr between patients with and without lesions in each voxel (rendered on the MNI-space ch2 volume). Voxels exceeding the false discovery rate threshold (q = 0.01) are rendered in a red (t = (more ...)
Filtering out Vcomp, as described above, changed the strength of effects slightly but not the overall pattern (). The major change was a reduction in the number of significant voxels in the lateral prefrontal cortex (Brodmann area 45/46). Of the 26 771 voxels that exceeded the critical threshold after the filtering, the majority (16 427) were concentrated in the anterior temporal lobe and middle portion of the middle temporal gyrus, defined arbitrarily as that portion of the temporal lobe anterior to a y-value of −35.
Figure 5 Maps of the reliability (t-statistic) of the difference in SemErr, after factoring out VComp, between patients with and without lesions in each voxel (rendered on the MNI-space ch2 volume). Voxels exceeding the false discovery rate threshold (q = 0.01) (more ...)
Filtering out NVcomp had a more substantial impact on the strength and pattern of results (). No voxels exceeded threshold in either Brodmann area 45/46 or Brodmann area 37. Of the 6366 voxels exceeding threshold, the majority (4361) were in the anterior temporal lobe region described above.
Figure 6 Maps of the reliability (t-statistic) of the difference in SemErr, after factoring out NVcomp, between patients with and without lesions in each voxel (rendered on the MNI-space ch2 volume). Voxels exceeding the false discovery rate threshold (q = 0.01) (more ...)
We investigated the anterior temporal lobe effect further, first by inspecting all the raw (pre-registered) scans for evidence of lesions within the anterior temporal lobe region defined in the unfiltered analysis. Thirty-four, more than half the sample, had readily identified damage here (see for examples).
Figure 7 (A) CT scan demonstrating infarction of the left anterior and mid temporal lobe, insula and inferior frontal lobe; (B) CT scan demonstrating infarction of the left anterior temporal lobe and portions of the insula; (C) T1-weighted MRI scan demonstrating (more ...)
Second, we pulled out the 20 patients with the most semantic errors and the 18 with the fewest (to avoid ties) and constructed an overlap map showing, in each voxel, the proportion of lesions in the high SemErr group minus the proportion of lesions in the low SemErr group. As shows, the voxels with large differences occupy the previously identified anterior temporal lobe and lateral prefrontal areas. Although the threshold for the overlap map is arbitrary, these two regions show the most robust, coherent overlap differences. Some additional voxels in primary sensory-motor cortices are also apparent.
Figure 8 Maps depicting, for each voxel, the difference between the proportion of patients with lesions in the high-SemErr group (20 highest SemErr scores) and the proportion of patients with lesions in the low-SemErr group (18 lowest SemErr scores). Differences (more ...)
In the final set of analyses, we further investigated the partial confound between anterior temporal lobe damage and lesion size. The strong association between total lesion volume and localized damage (in most of the covered voxels, including the anterior temporal lobe) means that partialing out volume would result in very low statistical power to detect independent effects at a voxel-wise level. However, as a first approximation, we carried out that analysis—regressing out total lesion volume from SemErr—and mapped the voxels that exceeded the critical threshold without correction (cf
Karnath et al.
). Once again, the anterior temporal lobe involvement was most prominent (), although the frontal involvement was somewhat reduced. Moreover, we statistically confirmed the independent contribution of anterior temporal lobe in a regional analysis, in which we calculated the percentage of damage within Brodmann areas 38 (temporal pole) and 21 (middle temporal gyrus) and computed partial correlations with SemErr, controlling for total lesion volume. Results were significant for both areas (Brodmann area 21: r
= 0.34, P
= 0.006; Brodmann area 38: r
= 0.33, P
= 0.008), indicating that damage here correlated with semantic error production above and beyond the contribution of lesion size.
Figure 9 Maps of the reliability (t-statistic) of the difference in SemErr, after factoring out total lesion volume, between patients with and without lesions in each voxel (rendered on the MNI-space ch2 volume). Voxels exceeding an uncorrected t-test threshold (more ...)