treatment of semantic verb classes in aphasia: acquisition and generalization effects

Treatment of semantic verb classes in aphasia: acquisitionand generalization effects

YASMEEN FAROQI-SHAH & LAUREN E. GRAHAM

Department of Hearing and Speech Sciences, University of Maryland, College Park, MD, USA

(Received 10 June 2010; Accepted 4 December 2010)

AbstractVerb retrieval difficulties are common in aphasia; however, few successful treatments have beendocumented (e.g. Conroy, P., Sage, K., & Lambon Ralph, M. A. (2006). Towards theory-driventherapies for aphasic verb impairments: A review of current theory and practice. Aphasiology, 20,1159–1185). This study investigated the efficacy of a novel verb retrieval treatment in two individualswith aphasia who experience verb retrieval difficulty. It involved training verb classes with large (e.g. cutverbs) and limited (e.g. contact verbs) sets of semantic features. Based on action representation theories,semantically based training of cut verbs was predicted to generalize to retrieval of untrained cut andcontact verbs. One participant improved on trained verbs whereas the other participant did not. Neitherparticipant demonstrated within nor across-class generalization to untrained verbs. However, bothparticipants significantly improved in verb naming as measured by An Object and Action NamingBattery, and their predominant error pattern changed from noun to verb substitutions. Therefore, bothparticipants improved in overall verb retrieval strategies despite limited success with verbs trained in thistreatment. Implications for the design of future treatments are discussed.

Keywords: aphasia, verb, treatment, semantic features, generalization

Introduction

Difficulty in retrieving words is the most pervasive symptom of aphasia. Recent work on gram-matical class differences suggests that verb retrieval deficits may be more common than nounretrieval deficits (Zingeser and Berndt, 1990; Berndt,Mitchum,Haendiges, and Sandson, 1997;Kim and Thompson, 2000; 2004; Luzzatti, Raggi, Zonca, Pistarini, Contardi, and Pinna, 2002;Mätzig,Druks,Masterson, andVigliocco, 2009). For instance, in a naming study of a large groupof aphasic patients, 52 of 58 individuals were either worse with verbs or comparably affected fornouns and verbs (Luzzatti et al., 2002). Several authors agree that the higher complexity of verbsrelative to nouns at least partially accounts for their greater retrieval difficulty (Black and Chiat,2003; Conroy, Sage, and Lambon-Ralph, 2006). Factors that influence greater verb complexityinclude low imageability, a looser concept, typically more grammatical morphology and highersyntactic weight with argument structure information (Black and Chiat, 2003). Greater retrievaldifficulties have been observed with verbs requiring more arguments (dative versus intransitive

Correspondence: Yasmeen Faroqi-Shah, Department of Hearing and Speech Sciences, University of Maryland, 0141F, Lefrak Hall,College Park, MD 20742, USA. Tel: 301-405-4229. Fax: 301-314-2023. E-mail: [email protected]

ISSN 0269-9206 print/ISSN 1464-5076 online © 2011 Informa UK Ltd.DOI: 10.3109/02699206.2010.545964

Clinical Linguistics & Phonetics, May 2011; 25(5): 399–418

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verbs) despite intactness of grammatical and syntactic knowledge of verbs (Kim and Thompson,2000; 2004). Given that sentence structure is inherently dependent on the verb, unsurprisingly,moderate association has been reported between verb retrieval deficits and grammatical formula-tion deficits in non-fluent aphasia (Berndt, Mitchum, et al., 1997; Luzzatti et al., 2002).

In addition to the above-mentioned syntactic aspects, semantic factors are also known toinfluence verb retrieval. It is reported that aphasic patients are better able to retrieve semanticallycomplex ‘heavy’ verbs (e.g. run, bake) comparedwith general ‘light’ verbs (e.g. go,make; Berndt,Haendiges, Mitchum, and Sandson, 1997; Breedin, Saffran, and Schwartz, 1998; Kim andThompson, 2004; Barde, Schwartz, and Boronat, 2006). Errors involving substitutions withsemantically associated verbs (clean!wipe)/nouns (clean!soap) and difficulties differentiatingsubtle semantic differences between verbs are also reported (McCarthy andWarrington, 1985;Mitchum, Ritgert, Sandson, and Berndt, 1990; Breedin et al., 1998; Kemmerer and Tranel,2000b). Therefore, although verbs with a greater number of semantic features seem to bemoresuccessfully retrieved, they may still be off-target by one or two specific semantic features.

A few prior studies have targeted semantic aspects of verbs for the treatment of verb retrievaldeficits (McNeil, Dolye, Spencer, Goda, Flores, and Small 1998; Wambaugh, Linebaugh,Doyle, Martinez, Kalinyak-Fliszar, and Spencer 2001; Raymer and Ellsworth, 2002;Wambaugh and Ferguson, 2007). Wambaugh et al. (2001) and Wambaugh, Cameron,Kalinyak-Fliszar, Nessler, and Wright (2004) examined the use of semantic cueing for verbretrieval.McNeil et al. (1998) focused on the generation of synonyms and antonyms of the verbbeing trained using a hierarchy of cues to aid the retrieval of unsuccessfully named items.Another semantically based treatment is semantic feature analysis (SFA), initially proposed byBoyle and Coelho (1995) for nouns. Wambaugh and Ferguson (2007) modified SFA for verbretrieval, where they required their participants to generate the semantic characteristics of eachverb, such as the body part/tool used, agent of the action, its purpose and location.

Outcomes of these verb naming treatments have been mixed, and improvements aretraining-specific. That is, although the naming of trained verbs typically improves, general-ization to the retrieval of untrained verbs seldom occurs. Given that generalization tountrained stimuli is the gold standard in aphasia treatment, it is worth examining whetherany other treatment approachmight not only improve verb retrieval but also facilitate general-ization to related untrained verbs. It should be noted that syntactic, phonological and gesturaltreatments for verb retrieval have also reported the same lack of generalization to untrainedverbs (Raymer and Ellsworth, 2002; Schneider and Thompson, 2003; Raymer, Ciampitti,Holliway, Singletary, Blonder, Ketterson, Anderson, Lehnen, Heilman and Rothi 2007;Rose and Sussmilch, 2008; Conroy, Sage, and Lambon-Ralph, 2009; Edmonds, Nadeau,and Kiran, 2009; Boo and Rose, 2010; Links, Hurkmans, and Bastiaanse, 2010).

Although the potency of any treatment approach is determined by participants’ impairmentprofile and other prognostic indicators, few aspects of previous studies could have accounted atleast partly for the lack of generalization to untrained verbs. First, verbs that were used fortreatment were often selected from a list of unsuccessfully named items on a naming test such astheObject andActionNaming Battery (e.g.Kim, Adingono, andRevoir, 2007;Wambaugh andFerguson, 2007). This means that the verbs were often unrelated to each other in semantic,thematic or phonological features. Hence, during treatment, each verb likely stimulated (at leastpartially) non-overlapping semantic networks, diminishing the potential for neural plasticity(Kleim and Jones, 2008). Second, verbs used to test the generalization effects also often had littlesystematic relationship with the trained verbs, evidently yielding little treatment-relatedimprovement (Marshall, Pring, and Chiat, 1998). Training of restricted semantic classes andtesting of generalization to semantically related words have been examined for noun retrieval in

400 Y. Faroqi-Shah & L. E. Graham

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aphasia, with successful outcomes (see Kiran and Thompson, 2003; Kiran, 2007). But, to ourknowledge, the use of reinforcement of a cohesive set of semantic features within a single verbclass has not been applied to verb retrieval deficits in aphasia. As described later, in this study,training and generalization verbs were selected on the basis of semantic relatedness.

This study was motivated by theoretical frameworks of action representation such as thetwo-level theory, which assumes that verbs have two levels of semantic representation(Pinker, 1989; 2007; Levin, 1993; Levin and Rappaport Hovav, 2005; Wunderlich, 2006).One semantic level is suggested to be an event template generic to all verbs within a semanticclass and includes information about argument and predicative structure. The secondsemantic level represents the unique features of each verb that differentiate it from otherverbs of the same class. For example, the verb class cut in Levin’s (1993) classificationincludes numerous verbs, all of which share an event template – using a tool to break intopieces. Eachmember of this verb class –mince, chop, hack, saw, dice, etc. – possesses additionalunique and idiosyncratic features that specify themanner of cuttingmotion and the shape/sizeof the resultant pieces (Figure 1). Psycholinguistic, neuroimaging and neuropsychologicalinvestigations support this two-level semantic representation (Kable, Lease-Spellmeyer, andChatterjee, 2002; Kemmerer, 2003; Kemmerer, Castillo, Talavage, Patterson, and Wiley,2008). Interestingly, a neuroimaging study in which participants made semantic judgementsto verb triads (e.g. trudge-limp-stroll) found relatively distinct neural activations for semanticfeatures such as action, motion and contact (Kemmerer et al., 2008). This study lendssupport to the neural instantiation of action semantics.

Recent work on the mental representation of actions and their linguistic labels (i.e. verbs)strongly suggests that verbs trigger a complete or partial simulation of the action they refer to(Embodied Cognition; Tyler, Bright, Fletcher, and Stamatakis 2004; Bergen, 2007; Fisherand Zwaan, 2008; Kemmerer et al., 2008; Masson, Bub and Warren, 2008; see reviews byFaroqi-Shah, Wood, and Gassert (2010); Fernandino and Iacoboni, 2010; but see Hauk,

CUT (superordinate class) to make into pieces+motion, +action, +contact, +tool use, +change of state

MINCE+results in minute pieces, +rapid repetitive motion

CHOP +results in large pieces, +repetitive motion

SLICE +results in thin or flat pieces, +slow deliberate motion

CRUSH +results in a smashed mass, +heavy tool +downward motion

TEMPLATE

ROOT

Figure 1. Schematic illustration of the two-level theory of verb meaning using cut verbs in Levin’s (1993) taxonomy.Conceptual class-specific information is represented at the template level, whereas distinctive verb-specific featuresare represented at the root level.

Verb treatment for aphasia 401

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Johnsrude and Pulvermuller (2004) for a different view). Although deficits in verb compre-hension in aphasic individuals have been previously reported (Saygin, Wilson, Dronkers, andBates, 2004; Fazio, Cantagallo, Craighero, Ausilio, Roy, Pozzo, Calzolari, Granieri, andFadiga, 2009), it is noteworthy that at least some aspects of online action simulation arepreserved in verb-impaired aphasic individuals (Faroqi-Shah et al., 2010).

The implications of the two-level theory and the embodied cognition framework for thetreatment of aphasic verb retrieval deficits are explored in this study. The assumption is that ifverbs of the same semantic class are used for treatment, the same ‘template level’ semanticnetwork should be repeatedly activated, and thus strengthened. Subsequently, retrieval ofuntrained members of this verb class should be facilitated because of the shared templatefeatures. SFA, a treatment approachmentioned earlier, has a format that can incorporate trainingof template and root-level semantic features of verbs. SFA uses explicit practice of conceptualattributes of words such as their location, function and physical attributes by asking patients toverbally generate these features for each target word. Participants also sort a given list of featuresinto thosewhich are and are not attributes of the targetword. In this study, feature generation andsorting steps focused on template and root-level properties of verbs within a class (Levin, 1993).

Thecomplexityaccountof treatmentefficacy(Thompson,Shapiro,Kiran,andSobecks,2003)posits that treatment effects generalize to linguistically related but less complex structures.Complexity in word retrieval is marked by (1) the extent of shared semantic features and (2) theatypicalityof the itemto its semanticclass (Kiran,2007).AsperLevin’s (1993) taxonomyofverbs,distinct verb classesmay overlap in a subset of semantic features. For instance, cut verbs have fivetemplate features(þaction,þmotion,þcontact,þtooluseandþchangeofstate),ofwhichthefirstthree features also characterize contact verbs (e.g. nudge, tickle, kiss, bump; Table I). In contrast,some verb classes have no feature overlap (see verbs of non-verbal expression taken from Levin(1993) in Table I). As per the complexity account of treatment efficacy and the feature list inTable I, onemight expect treatment of cut verbs to generalize to untrained contact verbs (more toless complex), but not vice versa. Treatment of cut or contact verbs should produce no change innon-verbal expression verbs as the template features do not coincide.

Kiran and Thompson (2003) found that treatment of nouns with a larger number of (andless typical) semantic features improved naming of generic and more typical items thatencoded fewer semantic features. That is, semantically oriented treatment with birds suchas penguin and ostrich resulted in improved naming of robin (see also Kiran, 2007). To ourknowledge, no study has utilized a complexity framework for semantically oriented verbtreatment in aphasia (see Schneider and Thompson (2003), for a verb treatment based onargument structure complexity).

This study

The primary purpose of this study was to investigate verb retrieval following a novel treatmentapproach focusing on semantic features of verb classes. The treatment procedure was an

Table I. Verb classes and their semantic features.

Verb class Examples Contact Motion Action Tool use Change of state

Cut Dice, chop þ þ þ þ þContact Bump, scratch þ þ þ � �Non-verbal expression Yawn, smile � � � � �


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adaptation of SFA. Two verb classes, cut and contact, were selected for the treatment because ofpartial overlap in their semantic features (see Table I). The second purpose was to determinewhether treatment effectswould generalize to untrained verbs (1)within the same class that sharesall features of trained verbs (trained cut to untrained cut); (2) from a different class that sharessome, but not all, of the trained semantic features (trained cut to untrained contact; trained contactto untrained cut); and (3) in a different class that shares no semantic featureswith the trained verbs(trained cut to non-verbal expression; trained contact to non-verbal expression). It was predicted thattraining of cut verbs would generalize to contact verbs (Pashek, 1998; Wambaugh, Doyle,Martinez, and Kalinyak-Fliszar, 2002; Thompson et al., 2003), but generalization of trainedcontact verbs to cut verbs was not expected because of the larger number of semantic featuresencoded by cut verbs. Improvement of non-verbal expression verbs after cut or contact verb trainingwas not predicted due to the lack of feature overlap with the trained verb category. The additionalpurpose of including verbs of non-verbal expression was to establish the specificity of treatmenteffects to trained and semantically related verbs (as per a multiple baseline design). An additionalexploratory question was whether there would be change in verb retrieval in other measures,particularly the Object and Action Naming Battery (OANB) (Druks andMasterson, 2000).

Methods

Participants

Twomale participants with aphasia were recruited for the study. Participants provided informedconsent before participation, in accordancewith the ethical standards set forthby theDeclarationof Helsinki. P1, a 62-year-old male who was a native Chinese speaker, was also premorbidlyfluent in English for 30 years. P2, a 47-year-old male, was a native speaker of English. Bothparticipants had developed aphasia consequent to a single left-hemisphere cerebrovascularaccident of the middle cerebral artery territory, were at least one-year post-onset, had at leasthigh school education and had no premorbid history of psychiatric, neurological, cognitive orspeech-language deficits. Both participants passed binaural pure-tone audiometric screening(P1: aided; P2: unaided) at 500, 1000 and 2000 Hz at 25 dBHL (ANSI: 1969) and passed avision screen (at least 20/40 correctedoruncorrected vision and the absenceof spatial neglect andvisual field deficits). Similarly, both participants demonstrated adequate reading for singlewordsand short phrases, as determined by a screening test before initiation of treatment. Neitherparticipant showed significant signs of verbal apraxia (as per the criteria listed in ApraxiaBattery for Adults, 2nd ed., Dabul (2000)). Demographic details are given in Table II.

Bothparticipantsmet the following inclusionary languagecriteria,which are given inTable II:(1) A language profile consistent with Broca’s aphasia as per the Western Aphasia Battery(WAB; Kertesz, 1982). (2) Verb retrieval difficulty in narrative speech (evidenced by use of<50% of verbs produced by unimpaired speakers in picture description of the WAB).1

(3) Poorer naming of verbs than nouns in confrontation naming using the OANB (Druks andMasterson, 2000; Fisher’s exact, p< 0.05;Table II). (4) Relatively stable verb naming accuracyacross two baseline testing sessions, hence demonstrating no spontaneous improvement in verbretrieval abilities. (5) Spared comprehension of isolated verbs, defined as greater than 90%accuracy in verb recognition using a spoken word to picture-matching task. High performanceon this verb-comprehension task was taken as evidence of relatively spared access to semanticrepresentation of verbs. Overall, the language profile of both participants was marked bydecreased verbal fluency, mild-moderate difficulties with repetition and relatively spared audi-tory verbal comprehension. Both participants had an agrammatic speech production profile as


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determined from narratives (Narrative Story Cards; Helm-Estabrooks and Nicholas, 2003).This included syntactically fragmented utterances, errors in verb morphology and overallreduction in grammatical morphology. Narrative samples are given in Appendix 1.

Stimuli and materials

Thirty-five verbs were selected for the study: 14 cut verbs, 14 contact verbs and 7 non-verbalexpression verbs. Seven of each of the cut and contact verbs were used as stimuli for treatment,whereas the other seven were used to assess generalization effects of treatment. The completelist of verbs is given in Appendix 2. All stimuli were matched for argument structure acrosscategories. Due to the limited number of filmable verbs thatmet these semantic feature criteria,wewere restricted in our choice of stimuli.Hence, verbs across the three categories could not becompletely matched for the frequency of occurrences as per CELEX lemma frequency counts(Baayen, Piepenbrock, and van Rijn, 1993).Cut verbs (mean frequency ¼ 9 permillion words;range: 1–27) and contact verbs (mean frequency ¼ 27 permillion words; range: 4–110) differedsignificantly in frequency (t-test, p < 0.05). Cut and contact verbs did not differ from non-verbalexpression verbs (mean frequency ¼ 31 per million words; range: 4–161; t-test, p > 0.05).

Two 5-s long videos were developed to illustrate each of the 35 verbs so that different videoscould be used during the treatment steps and for testing the acquisition of treatment verbs. Allvideos showed an actor performing the target action on a recipient. For example, the verb chopwas filmed with amale actor chopping celery in one video and a female actor chopping onionsin another video. Naming accuracy for the videos was obtained by showing the videos to 15unimpaired non–brain-damaged, native English-speaking volunteers (8 males and 7 females;age mean ¼ 54.87 years, education mean ¼ 16.13 years). These participants were asked toprovide a name for the action and were prompted to provide a synonym in the case that thetarget verb was not elicited. Videos with less than 80% naming accuracy were re-filmed andnormed again. Verbs for which video naming accuracy failed to reach 80% following twonorming procedures were not used in the study. Still images of the actions obtained from each

Table II. Participants’ demographic information and language scores.

P1 P2

Age/gender 62/M 47/MEducation PhD High SchoolOccupation Self-owned business Bus driverTime post stroke 5 years 2 yearsNon-verbal memory span for digits 4 3Language scores Initial Post-treatment Initial Post-treatmentWestern Aphasia Battery (Kertesz, 1982)Aphasia quotient (max. ¼ 100) 77 87.7* 68.8 76.4*Information content (max. ¼ 10) 8 10 7 9Fluency (max. ¼ 10) 5 9 4 4Auditory comprehension (max. ¼ 10) 8.8 8.55 7.9 8.5Repetition (max. ¼ 10) 8.6 8.8 8.4 8.8Naming (max. ¼ 10) 7.1 7.5 7.1 7.9

Object and Action Naming Battery (Druks and Masterson, 2000)Objects (max. ¼ 100) 86 87 89 90Actions (max. ¼ 100) 61 84* 64 77*

Verb comprehension (pointing, max ¼ 20) 20 19

Note: *Statistical significance on McNemar’s change test (p < 0.05).


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video were used during two treatment steps (generation and analysis of semantic features) as avisual reminder of the action (Figure 2).

Treatment

Overall design. A multiple baseline alternating treatments (ABACA) single-participant designwas planned. For each participant, baseline testing (A), in which verb naming was elicitedwithout any direct treatment, was performed over two testing sessions to establish the lack ofspontaneous improvement.Hence each participant served as his own experimental control. Thiswas followed by a phase of treatment (B or C) during which participants received four 1-h

Figure 2. Images of the verbs (a) crush (a cut verb), and (b) nudge (a contact verb).


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treatment sessions everyweek (1h/day).Naming of treatment verbs (henceforth called treatmentprobes) was tested every treatment session to monitor the change in accuracy of trained verbs.Testing for accuracy of untreated verbs (henceforth generalization probes) was done once everythree sessions to minimize improvement due to repeated exposure (Fink, Schwartz, Sobel, andMyers, 1997).

Three a priori criteria were established for cessation of treatment: (1) accuracy of 6 of 7 onthree consecutive treatment probes; (2) less than 30% increase from baseline treatment verbnaming accuracy after eight sessions; or (3) maximum of 15 treatment sessions. Post-treatment testing, including treatment probes, generalization probes, the WAB (Kertesz,1982) and OANB (Druks andMasterson, 2000), was completed upon cessation of treatmentto determine the changes in language measures. Four weeks following the cessation oftreatment, maintenance (A) of verb naming for trained and untrained stimuli was tested.

To investigate whether the verb class used for treatment would influence the pattern ofgeneralization within and across verb classes, the study was planned such that each participantreceived treatment with a different verb class during the first treatment phase (P1 ¼ contactverbs; P2 ¼ cut verbs), followed by the other verb class during the second treatment phase(i.e. P1 ¼ cut verbs; P2 ¼ contact verbs). The second treatment phase was planned to beinitiated 2 weeks later to ensure the lack of carry-over from the previous treatment phase andall verb naming was tested before the onset of this second phase. Unfortunately, P2 wasunable to participate in his second treatment phase due to difficulties with transportation.Hence, P1 received an ABACA design, whereas P2 received an ACA design (B ¼ contactverbs, C ¼ cut verbs). During phase 1, P1 received treatment with 7 contact verbs, whereasgeneralization was tested to untrained contact, cut and non-verbal expression verbs. The treat-ment and generalization verbs for each participant are listed in Appendix 3.

Treatment protocol. Every treatment session began with the administration of treatmentprobes, in which the action names of the seven treatment verbs were elicited using videos.As mentioned earlier, generalization probes were administered once in every third session.Whenever the participant failed to produce the target verb during treatment andgeneralization probes, he was allowed to write the action name. If participants produced amore general verb (e.g. cut for slice), they were prompted to be more specific. No otherfeedback or prompting was given during probes.

Following elicitation of probes, four treatment steps (modified from SFA, Boyle andCoelho (1995)) were used for each of the seven treatment verbs.

(1) Naming of the action in a video: Incorrect responses were redirected with verbalcorrections and feedback until the correct response was produced. The next twotreatment steps focused on delineating template and root-level semantic features(as per the two-level theory described in the Introduction section).

(2) Generation of semantic features: A still image of the action was displayed, and theparticipant was instructed to independently generate three features for the targetverb. This was initially modelled to the participants so they had a clear understandingof the kinds of responses that were needed. The following are the examples offeatures: This action requires a tool/knife, or This action results in small/large pieces. Ifthe participant was unable to independently produce three features, the researcherprovided verbal yes/no prompts such as, Does it require a tool? The participantrepeated these prompted features to strengthen his repertoire of semantic character-istics for each treatment verb.


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(3) SFA: This step required the participant to determine whether a given set of semanticfeatures belonged or did not belong to the target verb. Four cards, each containing asemantic feature that was relevant or irrelevant to the verb, were placed in a row infront of the participant. In general, the semantic features listed in each of the fourcards were a template-level feature that characterized the entire treatment verb class(e.g. use a tool for cut verbs), a root-level feature unique to the specific target verb(e.g. results in small pieces for mince), one feature of another verb in the same classbut that did not apply to the target verb (e.g. results in large pieces for mince) and oneirrelevant feature (e.g. uses one’s legs for mince). The participant read each featureand responded by placing each card in a YES or NO column.

(4) Sentence generation: The video of the target action was replayed and the participantwas instructed to produce a sentence using the target verb (such asThe man is mincingthe onion). When responses did not contain the target verb or were incompletephrases, the researcher prompted the participant to use the target verb or use acomplete sentence. The purpose of sentence generation was to strengthen thesemantic network by activating the noun associates of the action (Edmonds,Nadeau, and Kiran, 2009). If the participant was still unable to provide a completesentence using the target verb, the researcher provided a sentence model.

The use of still images of the action in steps 2 and 3 is consistent with the procedures of SFAand is intended to enable visual imagery of the actionwhile the participant generates and analysessemantic features. In steps 1 and 4, videos of the actionwere used to facilitate retrieval of the verblabel and the corresponding verb arguments. These steps were repeated for each of the seventreatment verbs. The order of the treatment verbs was randomized each session. Treatment wasterminated whenever one of the three aforementioned predetermined criteria was met.

Scoring and data analysis

Verb naming responses were scored as accurate if the target verb was produced either orally orin written form. Minor phonemic paraphasias and spontaneous self-corrections within 10 swere accepted if the response was unambiguous. Verb naming errors (for probes and OANB)were classified as verb substitutions, noun substitutions, phonemic errors and others (I don’tknow or no response).

Given the single-subject design of this study, participants served as their own experimentalcontrol. Thus, the effects of treatment were determined by comparing each participant’s pre-and post-treatment performance in verb naming accuracy and other language measures. Effectsizes were calculated to determine the magnitude of treatment and generalization gains fortreatment and generalization probes using the following formula (Busk and Serlin, 1992):

Post�treatment naming accuracy �Mean pre�treatment naming accuracyStandard deviation of pre�treatment naming accuracy

Reliability

Every treatment session was audio- and video-recorded with participant consent for reliabilityscoring. A trained research assistant checked whether the predetermined treatment steps wereaccurately followed (independent variable) and scored the probes (dependent measures).Reliability was established for adherence to treatment procedures in 9 of 19 treatment sessions


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at 100%. Reliability for scoring of probes was completed for seven sessions and this exceeded90% (Cohen’s Kappa ¼ 0.97). Scoring differences between the original and reliability scorerswere resolved by listening to audio-recordings of the probes and arriving at a consensus.

Results

Both participants performed the treatment steps rapidly and typically completed two or moreiterations of the training verb set every treatment session. Both participants’ ability to generateeach verb’s semantic features, sort semantic features and produce the trained verbs in a sentenceimproved dramatically during the course of treatment, and they made no errors on thesetreatment steps after the first two to three treatment sessions. However, success in retrievingeach verb’s name, both during the treatment steps and in probes, was different for P1 and P2.The response of each participant to treatment is presented separately in the following sections.

Participant P1

P1 was trained on contact verbs during the first treatment phase and his naming accuracy oftreatment and generalization probes over different sessions is shown in the left side of Figure 3.His treatment probe accuracy changed from amean pre-treatment accuracy of 0 of 7 to 7 of 7 infive treatment sessions totalling 3.75 treatment hours (McNemar’s change test, p < 0.05).There was no generalization to untrained contact, cut or non-verbal expression verbs (pre- to post-treatment score changes are 0/7 to 1/7, 1.5/7 to 3/7 and 2/7 to 2/7, respectively).

The right side of Figure 3 shows P1’s response to the second treatment phase with cut verbs,whichwas initiated after awashout periodof 2weeks after treatmentwith contact verbs ended.P1achieved the criterion of 6 of 7 verbs in six treatment sessions (total of 4.5 h of treatment). P1was significantly more accurate with naming of trained cut verbs in post-treatment testingcompared with baseline (McNemar’s change test, p < 0.05; effect size ¼ 2.85). There wereno statistically significant changes for untrained cut verbs (pre-treatment ¼ 2/7, post-treatment3/7), untrained contact verbs (pre-treatment ¼ 0/7, post-treatment ¼ 1/7) or for verbs of non-

Contact-TxCut-TxContact-GenCut-GenNon-verbalexpresssion

Sessions

Figure 3. Naming accuracy of treatment and generalization probes for P1. SessionsT1–T5 show response to contact verbtreatment and sessions T6–T11 represent response to cut verb training. Treatment probes are connected by a solid line.Generalization probes were administered every third session (see text for details).


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verbal expression (pre-treatment ¼ 2/7, post-treatment ¼ 2/7) (McNemar’s change test, p > 1for all comparisons). P1 demonstrated maintenance of trained cut verbs when tested 4 weeksafter treatment, with accuracy of 5 of 7. To summarize, P1 improved significantly in naming oftrained verbs during both phases of treatment in a relatively short number of sessions andmaintained these effects. However, generalization to untrained verbs was not found.

Errors on treatment probes. P1’s errors were primarily semantically related verb substitutions(17/24 errors; compared with 3/24 noun substitutions and 4/24 other responses). Verbsubstitutions were distributed between substitutions of the superordinate verb class name(e.g. cut or contact) and within-class substitutions (e.g. crush for hack, punch for chip). Thepre-treatment pattern of noun substitutions changed to verb substitutions (Table III).

Participant P2

P2 participated in cut verb treatment only and his performance on treatment and general-ization probes is shown in Figure 4. P2 failed to reach the criterion of 6 of 7 verbs by the end ofeight sessions and hence his treatment was terminated. He participated in a total of 8 h ofdirect treatment. There was no significant change in verb naming accuracy from baseline topost-treatment of any verb category. Non-verbal expression verbs were produced at a higheraccuracy than other verbs even during baseline, and this category remained highly accurate(pre-treatment accuracy ¼ 5/7, post-treatment accuracy ¼ 6/7).

Errors on treatment probes. P2’s errors were primarily substitutions by the superordinate verbclass name (cut, 7/21 instances), or overuse of a single verb target (dice for slit, chip, shred, 11/21 instances), or no responses (see Table III).

Other language measures

Post-treatment scores of theWAB andOANB are given in Table II. Both participants increasedsignificantly in theWAB aphasia quotient post-treatment, specifically in the spontaneous speechsubtest. The pre- and post-treatment WAB narrative samples are given in Appendix 1. Bothparticipants also increased significantly for action naming on the OANB (McNemar’s (1969)change test;p<0.05).Therewasno change inobject namingon theOANBfor either participant.As seen in Table III, both participants’ errors showed a similar change from pre- to post-treatment, namely, an increase in verb substitutions and a decrease in noun substitutions.

Table III. Distribution of errors for each participant for the Object and Action Naming Battery (Druks andMasterson, 2000) responses and during treatment probes.

Error categories

Substitutions

P1

Verb Noun Phonemic Other

Object and Action Naming Battery (Pre-Tx) 21/39 17/39 1/39Object and Action Naming Battery (Post-Tx) 16/16Treatment probes 17/24 3/24 4/24

P2 Object and Action Naming Battery (Pre-Tx) 18/36 11/36 7/36Object and Action Naming Battery (Post-Tx) 18/23 2/23 3/23Treatment probes 35/43 8/43


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Discussion

This study investigated the efficacy of a verb retrieval treatment focusing on the identificationof template- and root-level semantic features unique to two verb classes, cut and contact verbs,in two aphasic individuals. Acquisition of trained verbs and generalization to untrained verbswithin and across verb classes were investigated. Training cut verbs was predicted to general-ize the retrieval of contact verbs, but not vice versa. No improvement in unrelated non-verbalexpression verbs was expected. This treatment was novel because exemplars of a specific verbclass were trained, and training emphasized recognition and generation of class-general andverb-specific semantic features.

A single-participant alternating treatments design was planned. P1 was trained on contactfollowed by cut verbs. He improved in both although generalization was negligible. P2 couldparticipate in only cut verb treatment, and his retrieval of trained and generalization stimuliremained unchanged. This mixed success has been previously reported (Kim et al., 2007;Wambaugh et al., 2004) and will be discussed later. Interestingly, both participants improvedin overall verb retrieval measured by naming accuracy in the OANB. And, their predominanterror pattern changed from noun to verb substitutions. The implications of these findings arediscussed in the following sections.

Treatment effects

P1’s improvement on trained cut and contact verbs indicates that this semantically orientedtreatment may be appropriate for some individuals with aphasia. On the basis of the two-leveltheory of action representation, we can suggest that strengthening of the repeatedly practisedevent template and verb-specific features may underlie this improvement (Pinker, 1989;2007; Levin, 1993; Levin and Rappaport Hovav, 2005; Wunderlich, 2006). However, P2’sfailure to improve was unexpected because he appeared to be a good candidate for the

Cut-TxContact-GenCut-GenNon-verbalexpresssion

Sessions

Figure 4. Naming accuracy of treatment and generalization probes for P2. P2 received training with cut verbs only(sessions T1–T8). Treatment probes are connected by a solid line. Generalization probes were administered everythird session (see text for details).


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treatment based on spared semantic knowledge of verbs, adequate auditory comprehension,absence of severe phonological paraphasias and young age.

There are several possible explanations for P2’s response. First, post hoc analysis of P2’sresponses in baseline and treatment probes revealed that he consistently produced errors on thesame items but demonstrated high accuracy on their treatment steps (e.g. chip, crush). This couldsuggest loss of phonological representations of these verbs as a result of brain damage(Butterworth, 1992). Verbs whose phonological representations have been erased are less likelyto respond to treatment because the phonological label has to be re-learned, rather than just re-accessed. P1, in contrast, was inconsistent in errored items, suggesting impaired access, henceaccounting for his rapid response to treatment. Or, the source of P2’s difficulty with verbs mayhave generally impaired access to phonological representations. Because phonological cueing orpracticewas not a part of this study, P2maynot have benefited from treatment.A secondplausibleexplanation is that P2 was unfamiliar with the training verbs because of lower premorbid educa-tion level than P1 (Table II). Even thoughmere exposure to verbs (with no explicit treatment) hasbeen shown to improve verb retrieval (Fink, Martin, Schwartz, Saffran, andMyers,1992; Fink etal., 1997), P2 demonstrated no such facilitatory effect suggesting that both phonological limita-tions and premorbid unfamiliarity with the vocabulary are plausible explanations for poor success.

Themixed treatment outcomes of this study are consistent with the variable outcomes of priorverb treatment studies (e.g. Wambaugh et al., 2004; Kim et al., 2007). For instance, inWambaugh et al.’s (2004) investigation of phonological and semantic cueing verb treatments infive aphasic individuals, two participants showed dramatic improvementwith treatment, whereastwo others showed only modest effects and one participant was unresponsive to treatment.

Generalization effects

The second question posed in this study was whether this treatment would facilitate theretrieval of closely related verbs within and across trained verb classes. Neither P1 nor P2improved on generalization verbs, although P1’s naming of untrained contact verbs showed animproving trend (4/7 during session T11 versus 0/7 at baseline; Figure 3). Hence, theprediction of spread of treatment was not supported. This lack of generalization is consistentwith previous verb treatment studies (Raymer and Ellsworth, 2002; Kim et al., 2007;Wambaugh and Ferguson, 2007; Edmonds, Nadaeu, and Kiran, 2009). SFA is shown toimprove the retrieval of untrained nouns but not verbs (Wambaugh and Ferguson, 2007). Inthis study, there are at least three explanations for this lack of generalization. First, practicewith class-general semantic features (event template) appears insufficient in facilitatingretrieval of specific exemplars within that verb class. That is, strengthening of features suchas tool use and results in small pieces with treatment of shred is insufficient in facilitating theretrieval of other verbs with the same event template, such as grind and dice. Based on the two-level theory of verb representation, P1’s successful acquisition of trained verbs and lack ofgeneralization to very similar untrained verbs implies that each verb’s specific features mayneed to be associated with its respective verb label for improvement in verb naming to occur.

A second explanation for the lack of generalization may be the content of the semanticfeature treatment itself, specifically the extent to which contrasts between verb-specificfeatures were (not) emphasized. The two crucial treatment steps that were aimed at strength-ening action representation were semantic feature generation and SFA. Perhaps, the numberof features generated (three in this study) and the number of features analysed (four in thisstudy) were insufficient to boost all relevant verb-specific features, resulting in limitedstrengthening of features crucial for generalization verbs. Aspects of action representation,


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such as the path, direction and speed of motion, could be more relevant than the featuresactually generated in this treatment (Wu, Morganti, and Chatterjee, 2008). Likewise, thetreatment and generalization verbs did not entirely overlap for the body part used, a featurethat is increasingly being recognized as relevant for action representation (Pulvermuller,2005; Faroqi-Shah et al., 2010). The importance of training verb-specific features is consis-tent with prior findings that individuals with aphasia experience difficulty in discerning subtlesemantic differences among verbs in the same class (Kemmerer and Tranel, 2000a; b).A third explanation may have been the subtlety of differences between various trained anduntrained verbs, both in terms of semantic features and filmability, especially for the cut verbs.However, this does not quite explain the lack of within-class generalization for contact verbs,which were more distinct from one another (e.g. bump and scratch).

Another generalization question that this study askedwas whether there would be any changein verb naming as measured by the OANB. Both participants improved significantly in verb,but not object naming, after treatment. Although prior research has shown that some aphasicparticipants improve in naming with repeated exposure (Fink et al., 1992), the specificity ofimprovement in verb rather than noun naming makes this an unlikely explanation of P1’s andP2’s improvements in OANB. The semantic feature treatment may have facilitated moreeffective use of some general retrieval strategies (Boyle and Coelho, 1995; Wambaugh andFerguson, 2007). Interestingly, the trained cut verb class encodes five features (Table I) thatoverlap with several verb classes, and especially with some verbs in the OANB. For example,pouring is characterized asþmotion andþaction (as well as being a hand verb, like all cut verbs).It is noteworthy that several OANB verbs that were accurately named by P1 and P2 post-treatment (P1: raking, ringing, watering, pouring; P2: waving, knitting, pulling, drawing) sharefeatures with cut verbs (þhand motion, þtool use, þaction, þmotion). The only exception iswaving, which is described as -tool use. Perhaps what were learned during treatment were notnecessarily the names of specific treatment verbs, but rather a strategy for accessing semanticfeatures to facilitate verb retrieval. The change in error patterns from pre- to post-treatmenttesting is noteworthy and further supports an improved verb retrieval strategy after treatment.

Limitations of the study and implications for future verb retrieval treatments

This is an exploratory Phase I treatment study, intended to test hypotheses about treatmentefficacy (Robey, 2004). Given the partial success of the treatment, future research for furtherreplication with more participants is warranted. It is also crucial to tease apart effects ofsemantic feature strengthening from those of mere repetition of the phonological form of theverb, which inadvertently occurs during naming trials. Although the improvements in OANBare promising, given the single treatment experimental design, it is yet to be determinedwhether other treatment approaches (e.g. phonological cueing or verb argument structuretherapy) using these same stimuli would have produced similar effects. In interpreting theverb-specific improvement in OANB scores, we note the possibility that noun naming mayhave had little room for improvement because of initial high performance on noun naming.P2’s unexpected failure to respond to treatment indicates the need to include more extensivepre-testing to understand candidacy for this treatment. Furthermore, P2 was unable tocomplete the second half of the alternating treatments design, providing an incompletepicture of this response to treatment. Future research with a larger group of participantsand using an alternating treatments design (where effects of different treatments are com-pared within the same participants) would address concerns about the replicability of thesetreatment outcomes and improve the generalizability of the findings.


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Treatment outcomesmay have also been impacted by certainmethodological aspects of thestudy. As already alluded, an aspect that could be improved in future research is the use ofmore extensive semantic analysis and feature generation, thereby tapping more aspects ofaction representation. A limitation of the study was the relatively small number of stimuli ineach verb category, making tests of statistical significance rather unreliable and limiting theability to observe clear generalization effects. As described earlier, the small numbers wereunavoidable due to the specificity of the verb classes being tested. However, there are otherpublished studies of small number of treatment verbs (Fink et al., 1997). Extensive testing oflinguistic and non-linguistic variables, such as premorbid language proficiency, digit span,motivation, access to phonological versus semantic representations and learning style, wouldalso be useful in interpreting treatment outcomes.

Conclusions

The results of this study suggest that selecting and training verbs based on semantic featuresmay improve verb retrieval for some individuals with aphasia. This training may also facilitatenaming of untrained stimuli due to an improved strategy for verb retrieval, as evidenced byincrease in the number of verb paraphasias. However, there are participant variables that mayinfluence treatment outcomes, such as the nature of the verb deficit and premorbid familiaritywith the stimuli, which warrant cautious interpretation of the generalizability of these findingsto other aphasic individuals. These need careful consideration to determine candidacy fortreatment. This study reiterates the findings of prior research that generalization effects aremore evasive with verb retrieval treatments when compared with similar noun retrieval treat-ments (e.g. Kiran and Thompson, 2003). This could be attributed to the widely acknowledgedrepresentational complexity of verbs compared with nouns (Gentner, 1981; Kemmerer andTranel, 2000a; b; Conroy et al., 2006; Mätzig et al., 2009; Vigliocco, Vinson, Druks, Barber,and Cappa, in press).WhenKemmerer andTranel (2000a) examined the influence of a varietyof psycholinguistic variables such as argument structure and instrumentality in the verbretrieval of 53 individuals with aphasia, they found high individual variability among theinfluence of these factors. Predictions of treatment outcomes are likely to improve in the futurewith improved knowledge of the nature of verb deficit across participants.

Acknowledgements

This study was completed as Lauren Graham’s master’s thesis at the University of Maryland,College Park. The authors thank Amanda Peterson andMohan Singh for help with reliabilityscoring and Erin Larter for help with error analysis. The authors are also grateful to theindividuals with aphasia and their families for their participation in this research.

Declaration of interest: The authors report no conflict of interest. The authors alone areresponsible for the content and writing of this paper.

Note

1. Normative data were obtained from descriptions of Western Aphasia Battery’s (Kertesz, 1982) picnic picture by12 age-matched unimpaired volunteers. These individuals produced an average of 14.58 verbs while describingthe picnic picture (range: 5–21).


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Appendix 1: Pre- and post-treatment narratives elicited from picture description ofthe WAB

Participant 1

Pre-treatment. Vacation study . . . make a picnic . . . son take it for a fly to watch the dog.Another . . . it’s another guy is fishing. Another guy . . . the two person . . . the . . . rises someboat. And the . . . um . . . the weather is beautiful . . . has a sun. The tree.

Post-treatment. The couple have a picnic . . . The boy flies, fly the flag. A dog. The . . . anothergirl is fishing. The boy . . . play the toy. And the other two people play the boat. And theweather is good. They have a picnic . . . family picnic.

Participant 2

Pre-treatment. I see reading the book book. Pourin’ the drink . . . kite flying . . . the flag. . . . thetree . . . the car . . . houses . . . the dog . . . um . . . ohmy . . . I do/n’t know {laughs} . . . Okay . . .(7 seconds pause) . . . a boat (8 s pause) . . . That’s it . . . Okay.

Post-treatment. A tree. A car. A kite. A dog. A boat. A book. A flag. Some trees. A car. A radio.A blanket. A book. Some sage? A dog. A boat.

Appendix 2: Verbs used in the study with their lemma frequencies based on CELEXdatabase (Baayen et al., 1993)

Verb class StimuliFrequency per

million of verb formFrequency per

million of noun form

CutChip 6 15Chop 19 6Crush 21 3Cube 2 9

(Continued)


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Appendix 2: (Continued)

Verb class StimuliFrequency per

million of verb formFrequency per

million of noun form

Dice 1 2Grind 27 2Hack 6 2Perforate 1 NAPunch 10 7Scrape 12 1Shred 4 4Slice 12 18Slit 3 5Spear 2 12

Mean frequency 9 6.61Contact

Bite 27 15Bump 11 5Kiss 59 17Knock 54 8Lick 11 1Nudge 5 1Pat 17 2Pinch 9 4Rap 4 2Scratch 24 7Stroke 19 25Tap 25 20Tickle 4 0Touch 110 57

Mean frequency 27 11.7Non-verbal expression

Cough 12 12Gasp 16 5Smile 161 83Sneeze 3 1Snore 4 1Whistle 13 9Yawn 8 2

Mean frequency 31 16

Appendix 3: Treatment and generalization verbs used in this study, sorted byparticipant and treatment phase

Participant 1 Participant 2

PHASE 1Treatment verbs Contact verbs

1. Bite2. Knock3. Lick4. Nudge

Cut verbs1. Chip2. Crush3. Hack4. Dice

(Continued)


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5. Pinch6. Tickle7. Touch

5. Punch6. Shred7. Slit

Generalization verbs Non-verbal expression verbs1. Cough2. Gasp3. Smile

Non-verbal expression verbs1. Cough2. Gasp3. Smile

4. Sneeze5. Snore6. Whistle7. Yawn

Cut verbs1. Chop2. Cube3. Grind4. Perforate5. Scrape6. Slice7. Spear

Contact verbs1. Bump2. Kiss3. Pat4. Rap5. Scratch6. Stroke7. Tap

4. Sneeze5. Snore6. Whistle7. Yawn



PHASE 2Treatment verbs Cut verbs

1. Chip2. Crush3. Hack4. Dice5. Punch6. Shred7. Slit

N/A

Generalization verbs Non-verbal expressionVerbs

1. Cough2. Gasp3. Smile4. Sneeze5. Snore6. Whistle7. Yawn




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treatment of semantic verb classes in aphasia: acquisition and generalization effects

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