AA’s visual, lexical and semantic abilities were investigated following the procedure described by Luzzatti and colleagues (1998).

Section A: visual and tactile naming. AA was asked to name 25 visually presented real manipulable objects (artifacts) that she saw in a prototypical perspective, and she was not allowed to touch. In a following session, she had to name the same objects after left-hand haptic exploration out of vision. A time limit of 10s was given for each item. AA’s performance on the object naming task for tactile exploration was significantly better than that on visual presentation (22/25 and 12/25, respectively; χ2(l) = 9.19; p < .01) (see Table 2A). A qualitative analysis of the naming responses after visual presentation revealed that the patient produced 10 perseverations, 1 semantic paraphasia, 1 semantic paraphasia/visual error and 1 visual error. In particular, perseverations were related, but not necessarily identical to previous responses. For example, she correctly named item 5 “pencil sharpener”, but then she answered: (i) item 7, tweezers → “pencil sharpener”; (ii) item 9 hammer → “used to sharpen the pencils”; (iii) item 14 bottle opener → “blade for sharpening pencils”; (iv) item 15 battery (electric pile) → “pencil sharpener”; (v) item 19 phone token (used in the past on public phones) → “pencil sharpener of the past” (this “of the past” specification suggests access to semantic features that are specific of the target item). After tactile presentation, she produced 2 verbal paraphasias and 1 efficacious circumlocution.

When tested with line drawings, AA’s oral naming abilities resulted to be impaired on both object and verb action naming (Batteria per l’Analisi dei Deficit Afasici, BADA, Miceli et al. 1994), with no difference between nouns and action verbs (23/30 and 20/28, respectively; χ2(l) = 0.21; p = .65). She also performed poorly on a living and non-living object naming task (15/48, Catricalà et al. 2013), without difference between living (9/24) and non-living (6/24) items (χ2(l) = 0.87; p = .35). On the other hand, AA’s performance on naming to definition (Novelli et al.,1986) fell within the normal range (36/38).

In this section, AA showed a naming deficit that is specific to the visual modality: she performed better on naming after haptic exploration and to definition, which is compatible with either OA or AVA.

In the next sections, each step of visual object naming, from early visual analysis to oral output, has been addressed.

Section B: visual analysis. AA’s ability to produce an on-line representation of visual stimuli was assessed by: (i) the Length, Size and Orientation match tasks of the Birmingham Object Recognition Battery (BORB, Humphreys and Riddoch 1993); (ii) the Poppelreuter-Gent overlapping figures test, where she had to identify three to five overlapping line drawings by pointing to each of the target drawings among 10 individual alternatives displayed underneath the overlapped images (Della Sala et al. 1995); (iii) the copy of geometric line drawings (Spinnler and Tognoni 1987). When tested on the BORB Length, Size and Orientation match tasks, the patient performed within the normal range. Her performance on the Poppelreuter-Ghent’s test was impaired for objects and abstract line drawings (predominant choice of left-side elements); her ability to copy geometrical line drawings was also mildly impaired (Table 2B). In these latter tasks, a qualitative error analysis showed one omission and one deformation on the right side of the stimuli, together with a tendency to copy figures more to left with respect to the objective midpoint of the sheet. We suggest that these data could be attributed to the presence of right hemianopia, which was not completely compensated by the patient, or to the additional presence of a mild right spatial neglect. Indeed, when tested through visuo-spatial tasks, she performed flawlessly at the line cancellation test (Albert 1973), but she exhibited 1 left-sided and 7 right-sided omissions at the Bell cancellation test (Gauthier et al. 1989), performing outside the established cut-off score (Vallar et al. 1994). Furthermore, she showed a large deviation to the left with respect to the objective midpoint of the stimulus in the Line bisection task and left position preference on the Raven’s Progressive Matrices test (Colombo et al. 1976).

In general, although AA’s performance was influenced by the presence of hemianopia and possibly right spatial neglect, her early visual processing abilities were substantially preserved.

Section C: access to the structural description system. After early visual processing, the episodic representation obtained from the image of an object needs to match its corresponding stored structural representation to allow identification (see Humphreys and Riddoch 1993; Marr 1980). To tap this function, AA was asked to decide whether items depicted by a line drawing (real animals or chimeric images, namely non-real animals consisting of two different types of animals, e.g., half camel/half giraffe, half cat/half chicken) were real animals or not. In this task she performed within normal range (Table 2C).

Section D: from an object name to the underlying visual representations. Word-to-picture matching tasks were used to investigate the relationship between words and pictures. AA showed a mild-to-minimal deficit in both the oral word comprehension task of the AAT (26/30; Luzzatti et al., 2023, 2024); and the oral noun comprehension task of the BADA (38/40; Miceli et al. 1994; Table 2D).

Figure 4 shows AA’s performance in drawing from memory, demonstrating, beyond some slight deformations on the right side, the global preservation of AA’s access to stored visual representations. Ten healthy subjects (7 F, 3 M; mean age = 32.3 years, SD = 4.32, range 26–39, and mean education = 18.70 years, SD = 2.31, range 15–22) correctly recognized AA’s drawings from memory (100% agreement, except for the drawing of a “glass”, whose agreement was 90%).

Example of AA’s drawings from memory

Section E: access to visual semantics. This section aimed at assessing the integrity of the access to semantic knowledge from structural description. In order to test AA’s access to semantics from pictures we used the Pyramids and Palm Trees Test (PPT) developed by Howard and Patterson (1992). Fifty-two picture triads were shown to AA, one at the top and two at the bottom of an A4 sheet. She was asked to select, through finger pointing, which of the two bottom items was semantically most related to that on the top. The score obtained by the patient (35/52) was below the lower tolerance limit (Gamboz et al. 2009; for normative data in Italian). Visual semantic memory was further assessed through the Semantic Association Test (SAT; Banco et al. 2023; Luzzatti et al. 2020), using a picture-to-picture matching paradigm. Once again, AA obtained a pathological score (41/76). However, performance in these tests could be invalidated by AA’s scarcely compensated right hemianopia and additional spatial neglect, since a qualitative analysis of errors indicated that, out of 35 errors on the SAT test, the patient committed 25 mistakes out of 38, choosing the picture on the left instead of the right side, and 10 errors out of 38, choosing the picture on the right instead of the left side (Fisher’s exact test, two-tailed: p = .001). Furthermore, it is worth mentioning that in a picture-to-picture matching task a participant may not necessarily employ a purely visual strategy bypassing language, as usually thought. Despite the purely visual characteristics of the stimuli, the task may become easier when a lexical-semantic association is used rather than a visual association of the two objects in a same context. For instance, when neurologically healthy individuals see a pyramid, they may associate this image with the lexical-semantic concept of Egypt and the concept of Egypt with a tuft of palm trees (“Pyramids are in Egypt – also palm trees are typical of Egypt”). Therefore, AA’s poor performance on the picture-to-picture matching task may be also interpreted as the result of a tentative impaired access to lexical and/or lexical-semantic knowledge from vision (Luzzatti et al. 1998; Luzzatti 2003).

Furthermore, spared semantic access was demonstrated by AA’s preserved ability in sorting pictures into categories, when the names of categories were supplied by the examiner, similarly to what occurred for patient AB (Luzzatti et al. 1998). When presented with 32 pictures, one at a time, and asked to categorize each item according to three classes (animals, vegetables, and tools), she performed flawlessly (score 32/32; see Table 2E).

In this section, AA showed evidence of spared semantic access from visual input that should be typically impaired in AVA (Bartolomeo 2022).

Section F: color naming and object color knowledge. Color naming is classically impaired in OA. AA was asked to name 10 patches of prototypical colors (the color naming section of the AAT), scoring 17/30. Errors were 3 perseverations and 2 semantic paraphasias (other color names). When she was asked to point to a color patch named by the examiner from 5 alternatives, she performed flawlessly (5/5). Object color knowledge was assessed by asking the patient to retrieve from memory the typical color of black and white line drawings. AA was given 40 items, 22 natural (fruits, vegetables) and 18 artificial objects (conventional colors of artifact objects, e.g., a fire truck = red). When AA was asked to give a verbal response (the name of the corresponding color), she performed flawlessly (Table 2F). The discrepancy found between color naming and object color knowledge is in line with pure lexical damage from visual stimuli that also extends to color names (see Siuda-Krzywicka et al. 2019; for a similar dissociation between color naming and color categorization).

Section G: limb and oral apraxia. AA’s abilities on visual imitation of meaningful and meaningless gestures were assessed through the limb-apraxia test devised by De Renzi et al. (1980) and an oral apraxia test (Spinnler and Tognoni 1987) (Table 2G). She presented deficits in motor programming for both the upper limb and oral districts. Her pantomime after visual presentation of an object, carried out with her right hand, was impaired (7/15), but she performed flawlessly on pantomime after verbal command (“show me how to use a hammer”).

Interim discussion. We described the case of a patient, AA, suffering from modality-specific deficit in naming line drawings and real objects from sight with much better tactile naming and spared naming to definition (Section A). Her naming deficit from visual modality was not caused by early identification problems, since AA was able to analyze visually presented stimuli adequately (Section B). Seemingly, unimpaired performance on the reality decision task indicates that AA was able to access the structural description of objects (Section C). AA performed flawlessly on a word-to-picture matching task and was able to draw objects from memory from verbal stimuli (Section D). The relatively accurate performance on these tasks indicates that AA was able to process visual knowledge of objects from verbal stimuli. Her minimal impairment on a word-to-picture matching task is consistent with that reported by Luzzatti et al. 1998 in a similar case of OA, but not with the performance of other OA cases (e.g., Beauvois 1982; Riddoch and Humphreys 1987), who were impaired on such task. Finally, naming of color patches was severely impaired, with spared comprehension of color names (name-to-color matching) and preserved object-color knowledge: this pattern of performance is in double dissociation with that observed in Luzzatti and Davidoff (1994), whose patient suffered from impaired retrieval of object-color knowledge with preserved color naming, and also confirms a relatively preserved access to stored visual knowledge of objects from the phonological input lexicon.

The aim of the present section is to quantify the extent to which brain regions and white-matter tracts are disconnected from the lesion site. Particular emphasis is placed on the analysis on the involvement of the callosal splenium as, according to Schnider and colleagues (1994), the greater the splenial disconnection, the more compatible the ensuing clinical outcome with OA rather than AVA. This was achieved by applying a structural disconnectome method to AA’s lesion (see Hajhajate et al. 2022; for a similar approach). Registration to the standard Montreal Neurological Institute (MNI) template of the skull-stripped T1-weighted structural MRI of the patient was performed using BCBtoolkit (Foulon et al. 2018) with the “classical” masking procedure to weigh the normalization with reference to the brain rather than non-brain tissue or lesions (Brett et al. 2001). The disconnectome map was then calculated using the patient’s lesion (Bonandrini et al. 2020). The disconnectome approach builds on diffusion-weighted images of healthy controls to track the fibers passing through the location of a lesion. In other words, based on structural connectivity in healthy controls, this method estimates the probability - from 0 to 1 - of each volume unit in the brain (voxel) of being disconnected from the lesion site (Thiebaut de Schotten et al. 2015). To do so, the lesion normalized to the MNI152 space is registered to each healthy control native space and used as a seed for tractography (estimated as in Thiebaut de Schotten et al. 2011) in Trackvis (Wang et al. 2007). Each tractography from each control subject is then converted into a visitation map, binarized and back-transformed in the MNI space. Finally, a percentage overlap map is produced by summing, for each voxel of the MNI space, the normalized visitation maps of the healthy subjects. It is worth noting that the disconnectome approach identifies (given a lesioned brain area A) a set of areas (each one can be labelled B) whose connections with the lesioned brain area A are interrupted. All other connections of each brain area B with other areas (each one can be labelled C) other than area A are spared.

Differently from Bonandrini et al. (2020), in which the disconnectome analysis was based on a reference sample of 10 healthy controls, in this analysis we used diffusion weighted images from 100 subjects of the package X (1 mm) available at https://storage.googleapis.com/bcblabweb/open_data.html (the list of track files is reported in the Supplementary Materials). The tracts involved in the disconnection with the lesion site were identified through computation of the voxels of overlap between the disconnectome map (thresholded at a probability of disconnection greater than 0.5) and of the masks from Rojkova and colleagues (2016). The disconnected brain regions were identified using the same approach, but with masks extracted from the HarvardOxford anatomical template. The same template was adopted to extract voxels of overlap with the normalized lesion. The disconnectome and lesion maps were eventually plotted through the FSLeyes software (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes). The normalized lesion was also plotted on the 2-dimensional medial sagittal plane. The map was masked to show the corpus callosum (through the callosal ROI derived from the JHU atlas), the anterior commissure (spherical ROI of 3 voxels radius centered on the coordinates x = 0, y = 2, z= -5 manually identified on the MNI152 template) and posterior commissure (spherical ROI of 3 voxels radius centered on the coordinates x = 0, y=-26, z= -1 manually identified on the MNI152 template).

Results and interim discussion. The lesion mainly involved posterior LH regions (Fig. 5a, Supplementary Table S1), namely the occipital pole, the lingual gyrus, the intracalcarine cortex, the lateral occipital gyrus, the fusiform and parahippocampal gyri, the posterior cingulum and the precuneus. The lesion also involved middle-inferior splenial fibers (Fig. 5b). The disconnectome analysis (Fig. 5c, Supplementary Tables S2 and S3) demonstrated the disconnection from the lesion site of the splenial fibers, together with a set of white matter tracts: the cingulum, the inferior fronto-occipital fasciculus, the optic radiations, the fornix, the long and posterior segments of the arcuate fasciculus, the superior and inferior longitudinal fasciculi.

(a) 3D rendering of the lesion after normalization to the standard MNI template; (b) 2D plot of the lesion at the level of the medial sagittal plane. Fluctuations in voxel intensity at the boundary of the lesion map are a byproduct of spatial normalization; (c) 3D rendering of the disconnectome map based on the patient’s lesion and structural connectivity estimates based on 100 healthy controls. For the original MRI scan see Bonandrini et al. (2020) (colors online and in PDF)