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Behavior, Cognition and Neuroscience
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Original Articles

Sensory-specific anomic aphasia following left occipital lesions: Data from free oral descriptions of concrete word meanings

, , , &
Pages 192-207 | Received 15 May 2012, Accepted 05 Oct 2012, Published online: 21 Feb 2013

Abstract

The present study investigated hierarchical lexical semantic structure in oral descriptions of concrete word meanings produced by a subject (ZZ) diagnosed with anomic aphasia due to left occipital lesions. The focus of the analysis was production of a) nouns at different levels of semantic specificity (e.g., “robin”–“bird”–“animal”) and b) words describing sensory or motor experiences (e.g., “blue,” “soft,” “fly”). Results show that in contrast to healthy and aphasic controls, who produced words at all levels of specificity and mainly vision-related sensory information, ZZ produced almost exclusively nouns at the most non-specific levels and words associated with sound and movement.

INTRODUCTION

Occipital lesions and modality-specific word problems

Concrete nouns (e.g., “table”) and verbs (e.g., “kick”) activate brain regions involved in experiencing their referred objects and actions (Hauk, Johnsrude, & Pulvermüller, Citation2004; Khader, Jost, Mertens, Bien, & Rösler, Citation2010; Martin, Haxby, Lalonde, Wiggs, & Ungerleider, Citation1995; Pulvermüller, Preissl, Lutzenberger, & Birbaumer, Citation1996; Sabsevitz, Medler, Seidenberg, & Binder, Citation2005; Shapiro, Moo, & Caramazza, Citation2006). This activation has been suggested to be either an effect of associative learning where words automatically activate sensory or motor neural circuits (Pulvermüller & Fadiga, Citation2010) or a post-lexical simulation of the words’ associated action (Tomasino et al., Citation2010). In both cases, it can be expected that lesions in areas involved in sensory processing may result in modality-specific word processing problems. The present study investigated word production in a man (ZZ) diagnosed with anomic aphasia due to occipital lesions, in order to see if the damage to visual areas would selectively affect production of words with visually related semantic content.

Left occipital lesions may lead to a syndrome known as optic aphasia, characterized by difficulties in naming visually presented stimuli, (e.g., pictures, objects and colors), whereas naming stimuli perceived through other sensory modalities (i.e., touch, hearing, taste or smell) as well as naming from verbal definitions is unimpaired (Gainotti, Citation2004; Girkin & Miller, Citation2001; Manning, Citation2000). However, although naming from visual presentation is selectively impaired in optic aphasia, naming from verbal definitions may be more or less successful depending on the sensory modality of their semantic content. At least two case studies indicate that individuals with optic aphasia seem to perform more poorly in tasks involving responding to verbal definitions rich in visual information (Forde, Francis, Riddoch, Rumiati, & Humphreys, Citation1997; Manning, Citation2000).

Degree of semantic specificity and visual information

Nouns with a relatively high degree of semantic specificity (e.g., “robin”) can be assumed to be more closely related to visual information as opposed to relatively abstract nouns belonging to the same lexical semantic hierarchy (e.g., “animal”) (Rosch, Citation1978). Although the effect of degree of specificity has not previously been investigated in persons with occipital lesions, studies of persons with lesions in other areas suggest that different brain regions are involved in processing words associated with subordinate, basic and superordinate semantic categories. For example, individuals with semantic dementia have shown an advantage in picture categorization using superordinate level words, in contrast to persons with aphasia due to lesions involving frontal or temporoparietal regions, who have been seen to perform better using subordinate level words. Both groups appear to differ from healthy controls, who have been observed to categorize stimuli at the basic level with greatest speed and accuracy (Crutch & Warrington, Citation2008; Rogers & Patterson, Citation2007). In semantic dementia, difficulties with processing more specific words can be explained by a loss of amodal semantic representations stored in the anterior temporal lobes (Crutch & Warrington, Citation2008; Jefferies & Lambon Ralph, Citation2007; Marques, Citation2007; Patterson, Nestor, & Rogers, Citation2007). In aphasia due to occipital lesions, problems with processing more specific words would also be expected; however, the difficulties would instead be assumed to be the result of deficits in activating modality-specific (visual) semantic representations.

The present study

The present study investigated content word production in a man (ZZ) diagnosed with anomic aphasia due to left occipital lesions. ZZ was compared to healthy speakers as well as persons diagnosed with aphasia following lesions in left perisylvian regions. In contrast to previous studies investigating the effect of presentation modality on naming performance, a purely verbal task (orally describing the meanings of concrete nouns) was used in order to see whether ZZ had problems accessing words with visual semantic content. Furthermore, in contrast to testing access to specific target words (e.g., by naming from definitions), word meanings were described freely, making it possible to analyze the lexical semantic content produced in running speech. Free oral descriptions of pictures have previously been used in a case study by Crutch and Warrington (Citation2003) to elicit running speech in an anomic participant, but to the authors’ knowledge, the study of free oral descriptions of test words presented orally has not previously been done.

A semantic analysis of the oral word descriptions was carried out where concrete words referring to more specific objects and entities, (e.g., “tulip,” “parrot”) as well as words directly describing visual properties (e.g., “red,” “round”) were assumed to be dependent on semantic processing in visual brain regions, whereas words referring to abstract, high-level categories (e.g., “thing,” “animal”) and words describing other sensory and motor experiences (e.g., “soft,” “sweet,” “buzz”) were assumed to not directly involve the visual cortex. The assumption that specific/subordinate level words used in the descriptions would also involve visual information was based on the fact that these words were hierarchically related to the highly imageable stimulus nouns, which all referred to visually perceivable entities. Following this, specific words throughout this paper will refer to nouns whose referents are visually mediated and not to specific words related to other modalities (e.g., words for specific smells, tactile experiences etc.).

Due to ZZ’s occipital lesion, he was expected to produce fewer words describing visual properties and nouns associated with specific (subordinate and basic) levels of categorization. In contrast, his production of more general nouns at higher (superordinate) levels of lexical semantic categorization was expected to be undisturbed. ZZ was also expected to rely on sensory modalities other than vision when processing semantic information associated with concrete nouns. Thus, ZZ was expected to produce fewer words with vision-related meaning components and a relatively greater number of words with meaning components from other sensory modalities as well as words with motor-related meaning components.

TABLE 1 Description of participants: occipital aphasic participant ZZ, perisylvian aphasic controls, and healthy controls. All data collection for the present study was carried out during 2009 and 2010

METHOD

Participants

The participants in the present study () were all native speakers of Swedish and informed consent was obtained from them prior to the test. The aphasic participants were recruited via the Stroke Clinic at Malmö University Hospital.

Case description

ZZ is a right-handed male born in Sweden in 1932. He was admitted to the stroke clinic at Malmö University Hospital on 1 April 2004, and diagnosed with a cerebral infarct due to a posterior cerebral artery stroke. A CT scan performed on 6 April 2004 showed a low attenuating area in the left occipital lobe. Neurological examinations revealed a right-sided homonymous hemianopia, but no visual perceptual deficits. Based on language testing after the stroke using PAPAP (Apt, Citation1997), the Swedish equivalent of the Boston Diagnostic Aphasia Examination and SBP (Apt, Citation1999), the Swedish equivalent of the Boston Naming Test, he was diagnosed with light to moderate anomic aphasia including semantic dyslexia (alexia without agraphia). ZZ’s auditory language comprehension was within normal limits and his speech was fluent, with normal syntax and phonology. He had a mild to moderate anomia with particular difficulties in finding proper names. He produced verbal (semantic) paraphasias. A full evaluation of his naming abilities could not be made since he discontinued the SBP test before it was completed.

In a previous study on word associations (Mårtensson, Roll, Apt, & Horne, Citation2011), ZZ was observed to produce mainly associations which were on an abstract superordinate level (13/30) in relation to test words (e.g., blomkål “cauliflower”→ mat “food,” leopard “leopard”→ djur “animal”). In several cases (7/30) he could not produce any association at all for concrete nouns and the remaining responses (9/30) were not categorically related to the test word.

TABLE 2 Examples of a test word and response words at different levels of semantic specificity (level 1 = most specific, level 5 = most general)

Materials and procedure

Participants were instructed to freely describe orally the meanings of orally presented Swedish nouns in as much detail as possible and told that there were no right or wrong answers. This approach was based on a method used by Barsalou and Wiemer-Hastings (Citation2005), who investigated descriptions of abstract and concrete concepts in healthy individuals. Compared to traditional methods such as naming tests, this method has the advantage that the participants have the possibility to respond more freely, thus providing the opportunity to gain insight into different strategies used to express word meanings involving different levels of semantic specificity as well as different sensory features.

Since the material analyzed in the present study was part of a larger study investigating the effect of words’ imageability and emotional arousal, the concrete test nouns were presented mixed with abstract and emotional nouns. Responses to 20 concrete nouns, i.e., nouns rated high in imageability (M = 641, SD = 26) (Mårtensson, Öberg, & Horne, manuscript, Citation2012, see Appendix A) were analyzed. The test words included mainly visually related nouns (e.g., fjäril “butterfly,” näckros “waterlily”) as well as nouns which, in addition to their salient visual features, could also be experienced through other sensory modalities (e.g., varg “wolf” [sound] and hasselnöt “hazelnut” [touch, taste] [Appendix A]). An approximately equal number of test words denoting living and non-living things were included (cf. Warrington, Citation1984).

The oral descriptions were recorded with a Marantz PMD660 Portable Solid State Recorder. Approximately one minute of speech produced as response to each test word was orthographically transcribed. Nouns belonging to the same lexical-semantic hierarchy as the test word were then analyzed with respect to their degree of specificity and content words describing the test word’s semantic properties were analyzed with respect to their sensory and motor features.

Data analysis

Content words (adjectives, verbs and nouns) in the participants’ descriptions were coded according to a coding scheme reflecting five degrees of semantic specificity. These are summarized below in . Words were coded as Level 1, the most specific level, if they were associated with specific sensory or motor related properties of the test words’ referents. Levels 2–5 correspond to increasingly higher levels of semantic generality (levels of categorization in Rosch’s (Citation1978) terms) in relation to Level 1. To allow for a more fine-grained analysis, the properties on one were further coded as regards the modality of their sensory and motor-related meaning components (vision, sound, touch, taste/smell, movement. See Appendix B and C for examples).

Descriptive data analysis was carried out using SPSS. ZZ’s and control participants’ words coded for different levels of specificity were compared using Fisher’s exact tests.Footnote1 The more specific levels (1–3), assumed to be associated with sensory and motor features, were compared to the more general levels (4–5), assumed not to be associated with sensory and motor information. The distribution of words related to different sensory and motor modalities was also investigated using two-tailed Fisher’s exact tests. A qualitative analysis of responses was also made.

RESULTS

Levels of semantic specificity

The majority of the test words were described by ZZ using words at the superordinate, most general level 5, e.g., mat “food,” djur “animal,” växt “plant,” art “species,” sak “thing,” instrument “instrument” or apparat “device.” For the test words diamant “diamond,” silver “silver,” tegelsten “brick,” ZZ could not access any information at all, and responded only by saying that he did not know those words or that he could not say anything about them. He produced very few nouns at the basic level 3 (hus “house” and blomma “flower”). The word blomma “flower” was produced only after having repeated the test word näckros “waterlily” together with other types of flowers in a song line several times (Appendix D).

Whereas 45–70% of the coded words produced by healthy as well as aphasic controls were at the lowest level (1 = property/part-of-whole), only 26% of ZZ’s were at level 1. However, over 60% of ZZ’s coded content words were level 5 (superordinate) words. This difference in distribution between ZZ and controls is visualized in . ZZ clearly stands out from the rest with his use of words at relatively high levels of semantic abstractness, mainly at the most general level (5). Comparing the production of words at the more specific, perceptually detailed levels (1–3) with words at the more general levels (4–5) using two-tailed Fisher’s exact tests, ZZ was seen to differ significantly from each of the healthy and aphasic controls. Whereas all controls produced more words at the lower levels, ZZ produced more words at the higher levels (p < .0001). ZZ produced relatively few related content word types per token (see ).

Figure 1a. Distribution of word tokens at different levels of semantic specificity (% of coded words produced by the individual subjects; ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls). Level 1 = most specific, level 5 = most general.

Figure 1a. Distribution of word tokens at different levels of semantic specificity (% of coded words produced by the individual subjects; ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls). Level 1 = most specific, level 5 = most general.

Figure 1b. Heat map showing the distribution of mean levels of semantic specificity associated with words produced in descriptions of each test word for the individual subjects (ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls). Level 1 = most specific, level 5 = most general. White cells indicate that no words coded as level 1–5 were used in the description.

Figure 1b. Heat map showing the distribution of mean levels of semantic specificity associated with words produced in descriptions of each test word for the individual subjects (ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls). Level 1 = most specific, level 5 = most general. White cells indicate that no words coded as level 1–5 were used in the description.

Some of ZZ’s responses which contain nouns from the same lexical semantic hierarchy as the test word were qualitatively different from the other responses and were thus excluded from the quantitative analysis. They are listed in Appendix D below, together with a motivation as to why they were excluded. In one case (example 1, Appendix D), ZZ produced a word belonging to the wrong superordinate category, växt “plant” as a response to the test word fjäril “butterfly,” but at the same time produced a correct motor-related property, kan flyga “can fly.” He also in some cases produced nouns at low levels of specificity that were embedded in song lines (examples 2–3, Appendix D) or in lexicalized phrases (example 4, Appendix D). This was the case for all subordinate level words he produced.

TABLE 3 Average number of types and tokens of produced content words for each test item

Modality of word properties

As a follow-up analysis, all words coded as being at the most detailed level (1) of specificity were subjected to a more fine-grained analysis in order to see which sensory and/or motor properties they expressed. ZZ produced a total number of 14 content word tokens (only nine different words) which were coded as belonging to level 1 (see Appendix C).

shows the distribution of sensory and/or motor features in relation to the total number of features represented in each participant’s word production. ZZ produced words whose meaning can be decomposed into a greater proportion of sound-related features (78.6%) than vision-related features (35.7%). This pattern differed from the aphasic as well as healthy controls, who all produced words associated with more vision-related than sound-related semantic features. Two-tailed Fisher’s exact tests showed significant differences between ZZ and eight of the nine controls (p < .005) as regards the distribution of visual- and auditory-related features. In control 2b, although his production was associated with a larger number of visual than auditory features, as was the case with the other controls, this difference did not reach significance compared to the feature distribution of ZZ (p > .05)Footnote2. Furthermore, ZZ produced a greater number of movement-related words (42.9%) than any other participant, relatively few words whose meaning contains features related to tactile experience (21.4%), and no words related to taste or smell. For the controls, the second most frequent semantic modality characterizing their analyzed words was touch, whereas words involving sound-related meaning components were relatively few and words related to taste or smell were rare.

When the cases where ZZ’s words with sensory or motor related features are put in context, it can be seen that the descriptions are rather vague, although ZZ does provide some sensory and motor based information. For example, he describes a “parrot” as an animal which “squeaks,” “says something,” “has a certain sound or euphony,” and that a “volcano” is something that “explodes” or “sounds.” Further examples are listed in Appendix E together with responses provided by control participants.

DISCUSSION

Sensory and motor related meaning properties

Despite the instructions to provide as much information as possible about the test words, ZZ produced very few words associated with sensory and motor features, indicating severe difficulties with this level of specificity. Looking at the distribution of feature modalities, he produced mostly sound-related words, with the next largest category being movement-related words, and only rarely words with vision-related meaning components. This differed from the healthy as well as aphasic control participants, who produced predominantly words with vision-related features, with the exception of one healthy control (2b), who produced mostly words with touch-related features. Further differing from the control participants, whose second most commonly produced meaning feature was touch, ZZ produced relatively few words with touch-related features. A possible explanation for the controls’ production of relatively many words with touch-related features as well as ZZ’s relatively sparse production of them is that words which are strongly vision-related are also often strongly related to touch (Lynott & Connell, Citation2009).

The auditory features associated with ZZ’s production provided fragmentary information about the meanings of the test words, but this was in most cases not enough to result in accurate descriptions (see e.g., responses for “volcano” and “parrot” in Appendix E). Somewhat similarly, the phrase kan flyga “can fly” was produced as response to the test word fjäril “butterfly,” although “butterfly” was referred to as a “plant,” suggesting that he had only partial access to the word’s meaning. The ability to fly was the only specific information about butterflies he could provide, possibly because the flight of a butterfly has movement-related semantic features in addition to visual features.

The most accurate descriptions produced by ZZ were those which included more abstract information or knowledge about what objects are used for, e.g., that a thermometer is used to measure temperature (see Appendix F for full descriptions). It could thus be expected that even though ZZ’s performance on concrete word descriptions was hampered due to occipital lobe damage, he could nevertheless be able to produce more detailed, normal descriptions for less concrete words, e.g., emotional and abstract words.

In order to obtain some indication as to whether ZZ’s descriptions of emotional and abstract test words could be judged to be relatively normal in comparison with his descriptions of concrete words, we carried out a follow-up test in which we asked 12 participants to guess which words the descriptions were about. This was done for descriptions produced by ZZ and control 5b who matches ZZ most closely in age and education level. All occurrences of target (test) words in the descriptions were hidden. Results showed that ZZ’s concrete word descriptions led to correct responses in significantly fewer cases (35/120) in comparison to control 5b’s descriptions (86/120) (c2 = 43.353, p < 0.001, df = 1). In contrast, the accuracy of guessing correct target words for ZZ’s descriptions of emotional and abstract words did not differ significantly from the target word guesses for 5b’s descriptions (emotional words: ZZ: 87/120, 5b: 86/120; abstract words: ZZ: 60/120, 5b: 72/120, (c2 = 2.424, p = 0.153, df = 1)). These results can be related to the case study of Crutch and Warrington (Citation2003), where, using a picture-description task, an individual with occipitotemporal lesions showed well-preserved propositional speech and abstract vocabulary, although suffering from severe anomic aphasia.

Taste and smell-related words were not used by ZZ and only to a minor degree by some of the controls. The sparse use of the olfactory and gustatory modalities may be due to the fact that the smells and tastes associated with the test nouns (vegetables, food, flowers, see Appendix A) are difficult to describe in terms of taste or smell; for example, it may be difficult to say what a hazelnut tastes like, other than that it tastes like hazelnut.

Since the material investigated in the present study was originally recorded for other purposes (comparing descriptions of abstract, emotional and concrete test words), the concrete part of the test was not designed to include words with a systematic variation in their associated sensory modalities. Nevertheless, there was a variation in the stimuli with some test words denoting entities which can be experienced through more than the visual modality (e.g., dragspel “accordion,” parrot “papegoja,” blomkål “cauliflower”). Although the test words’ sensory related modalities should ideally have been systematically varied, a clearly different semantic feature pattern could still be found in ZZ’s word descriptions as compared to all other participants.

Considering that the test words were concrete nouns with high imageability ratings, a strong association with visual information was expected to be reflected in the word descriptions as seen in the controls. ZZ’s lack of vision-related words and relative focus on sound and movement is consistent with the hypothesis that his occipital lesions would make visual semantic information difficult to access, whereas information from other modalities would be expected to remain more accessible.

Degree of semantic specificity

ZZ produced almost exclusively words coded for the highest, most general levels of semantic categorization (4–5). This pattern differed clearly from healthy as well as aphasic controls, whose word descriptions contained words at all levels of semantic specificity, including a large number of subordinate and basic level words. ZZ only produced subordinate level (2) words in song lines or lexicalized phrases (see Appendix D) which suggests that he is able to access their lexical forms in these specific contexts. There is no evidence, however, that he is able to explain their semantic content or that he would use these subordinate level words spontaneously. Results further showed that the largest proportion of words produced by all controls involved meanings at the most specific level (1 = sensory or motor properties), a pattern which can probably be explained by the nature of the task, i.e., to provide as much information about the meaning of each test word as possible. The fact that the task encourages production of specific descriptions makes the absence of detailed low-level information in ZZ’s responses even more striking. It could be argued, however, that speakers might tend to start their descriptions with general information and then move on to more specific information, and that the reason for ZZ’s high levels of generality is that he simply produces word descriptions with less information, thus staying at the general level. However, when measuring the average level of the first word related to the test word produced for each test item, controls were found to start out at mean levels close to subordinate (level 2) and basic (level 3) (M = 1.88–3.05), whereas ZZ was found to start out by producing words at the highest mean level (M = 3.73), closer to a superordinate level.

When comparing ZZ to the control participants, it could perhaps be thought that his high level of education contributes to his more abstract way of describing things. The control participants were of varying ages and levels of education with the majority of them being younger and with a lower level of education than ZZ. However, the statistical comparison between ZZ and control 5b (see ), who matches ZZ in age and level of education, showed that 5b responded in a manner similar to the other controls and differed significantly from ZZ. Furthermore, the concrete words used in the study are unlikely to be unfamiliar to any adult speaker of Swedish (mean rated familiarity = 568, sd = 49). Considering this, we tend not to think that ZZ’s results are influenced to any considerable degree by his relatively high age and education level.

CONCLUSIONS

Previous studies have shown that individuals with occipital lesions have difficulties accessing words related to the visual modality (Gainotti, Citation2004; Manning, Citation2000). In these studies, the effect of different modes of presentation (e.g., visual/tactile/verbal) was investigated. In the present study, a man (ZZ) with occipital lesions was shown to have selective difficulties with words with visual-related meanings, even though the stimuli were only presented verbally. In descriptions of concrete word meanings, ZZ exhibited a unique pattern producing mostly words with a low degree of lexical semantic specificity. At the level of sensory and motor related properties, ZZ produced very few vision-related words and a larger proportion of sound- and movement-related words. These results support the idea that not only the mode of presentation can affect task performance, but also the degree of visual semantic content in verbally presented stimuli (Forde et al., Citation1997; Manning, Citation2000). To the authors’ knowledge, this question has not been systematically investigated in previous studies of persons with occipital lesions.

This research has been supported by grants 421-2009-1773 and 349-2007-8695 from the Swedish Research Council.

Notes

2Looking outside the visual/auditory comparison, it can be seen that control 2b actually produces mainly touch-related words. This differs from the rest of the controls, who all produce mainly vision-related words.

Figure 2. Distribution of sensory and motor meaning components associated with the most specific words produced by individual subjects (ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls) expressed as percent of a particular sensory or motor feature in relation to each subjects’ total number of features associated with level-1 words.

Figure 2. Distribution of sensory and motor meaning components associated with the most specific words produced by individual subjects (ZZ = occipital; 1a–4a = aphasic controls; 1b–5b = healthy controls) expressed as percent of a particular sensory or motor feature in relation to each subjects’ total number of features associated with level-1 words.

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APPENDIX A List of concrete test words and possible associated sensory and motor parameters

APPENDIX B List of words with different levels of specificity (1 = most specific, 5 = most general) in test subjects’ descriptions of the test word papegoja “parrot”

APPENDIX C ZZ’s total production of words with sensory or motor related features. Presence/absence of sensory and motor meaning components are specified with 1/0, respectively

APPENDIX D Examples of content words belonging to the same lexical semantic hierarchy as the test word which were not included in the analysis. Pauses are marked with “#”

APPENDIX E Descriptions containing sensory and motor related words produced by occipital aphasic ZZ as well as aphasic and healthy controls. Pauses are marked with “#”

APPENDIX E (Continued)

APPENDIX F Responses containing abstract/functional information produced by ZZ and healthy and aphasic controls. Pauses marked with “#”

APPENDIX F (Continued)