The ScreeLing: Detecting Semantic, Phonological, and Syntactic Deficits in the Clinical Subtypes of Frontotemporal and Alzheimer's Dementia.

The ScreeLing is a screening instrument developed to assess post-stroke aphasia, via the linguistic levels Syntax, Phonology, and Semantics. It could also be a useful test for the clinical subtypes of frontotemporal dementia (FTD) and Alzheimer's dementia (AD), as specific and often selective disorders are expected. Its ability to differentiate between the clinical subtypes of FTD and AD is, however, still unknown. We investigated differences in ScreeLing total and subscores, linguistic-level disorders' relationship with disease severity, and classification abilities, in patients with behavioral variant FTD (bvFTD; n = 46), patients with primary progressive aphasia (PPA; n = 105) (semantic variant primary progressive aphasia [svPPA], non-fluent variant primary progressive aphasia [nfvPPA], and logopenic variant primary progressive aphasia [lvPPA], AD [n = 20] and controls [n = 35]). We examined group differences in ScreeLing total and subscores, and one-, two- or three-level linguistic disorders using one-way analyses of covariance (ANCOVAs) or Quade's rank ANCOVA. We used frequency analyses to obtain the occurrence of the linguistic-level disorders. We determined sensitivity and specificity by the area under the curve by receiver-operating characteristics analyses to investigate classification abilities. The total score was lower in patients (bvFTD: 63.8 ± 8.5, svPPA: 58.8 ± 11.3, nfvPPA: 63.5 ± 8.4, lvPPA: 61.7 ± 6.6, AD: 63.8 ± 5.5) than controls (71.3 ± 1.0) (p < .001). Syntax subscores were lower in svPPA (19.4 ± 4.6; p < .001) and lvPPA (20.3 ± 3.2; p = .002) than controls (23.8 ± 0.4). Phonology subscores were lower in lvPPA (19.8 ± 2.6) than bvFTD (21.7 ± 2.8) (p = .010). Semantics subscores were lowest in svPPA (17.8 ± 5.0; p < .002). A selective phonological disorder was most prevalent in lvPPA (34.9%). The higher the disease severity, the more linguistic-level disorders. The optimal cutoff for the total score was 70, and 23 for all three subscores. Good classification abilities were found for the Semantics (svPPA vs. bvFTD), Phonology (lvPPA vs. svPPA), and Syntax (nfvPPA vs. lvPPA) subscores. This easy to administer test gives information about language processing with the potential to improve differential diagnosis in memory clinics and in the future potentially also clinical trial planning.

Validation of a prediction model for long-term outcome of aphasia after stroke.

BACKGROUND: About 30% of stroke patients suffer from aphasia. As aphasia strongly affects daily life, most patients request a prediction of outcome of their language function. Prognostic models provide predictions of outcome, but external validation is essential before models can be used in clinical practice. We aim to externally validate the prognostic model from the Sequential Prognostic Evaluation of Aphasia after stroKe (SPEAK-model) for predicting the long-term outcome of aphasia caused by stroke. METHODS: We used data from the Rotterdam Aphasia Therapy Study - 3 (RATS-3), a multicenter RCT with inclusion criteria similar to SPEAK, an observational prospective study. Baseline assessment in SPEAK was four days after stroke and in RATS-3 eight days. Outcome of the SPEAK-model was the Aphasia Severity Rating Scale (ASRS) at 1 year, dichotomized into good (ASRS-score of 4 or 5) and poor outcome (ASRS-score < 4). In RATS-3, ASRS-scores at one year were not available, but we could use six month ASRS-scores as outcome. Model performance was assessed with calibration and discrimination. RESULTS: We included 131 stroke patients with first-ever aphasia. At six months, 86 of 124 (68%) had a good outcome, whereas the model predicted 88%. Discrimination of the model was good with an area under the receiver operation characteristic curve of 0.87 (95%CI: 0.81-0.94), but calibration was unsatisfactory. The model overestimated the probability of good outcome (calibration-in-the-large α = - 1.98) and the effect of the predictors was weaker in the validation data than in the derivation data (calibration slope ß = 0.88). We therefore recalibrated the model to predict good outcome at six months. CONCLUSION: The original model, renamed SPEAK-12, has good discriminative properties, but needs further external validation. After additional external validation, the updated SPEAK-model, SPEAK-6, may be used in daily practice to discriminate between patients with good and patients with poor outcome of aphasia at six months after stroke. TRIAL REGISTRATION: RATS-3 was registered on January 13th 2012 in the Netherlands Trial Register: NTR3271 . SPEAK was not listed in a trial registry.

Efficacy of early cognitive-linguistic treatment for aphasia due to stroke: A randomised controlled trial (Rotterdam Aphasia Therapy Study-3).

INTRODUCTION: One third of patients with acute stroke have aphasia. The majority receive speech and language therapy. There is evidence for a beneficial effect of speech and language therapy on restoring communication, but it is unknown whether and how efficacy of speech and language therapy is influenced by timing of treatment. We studied whether speech and language therapy early after stroke by way of intensive cognitive-linguistic treatment is more effective than no speech and language therapy in the Rotterdam Aphasia Therapy Study-3, a multicentre randomised single-blind trial. METHODS AND PATIENTS: Stroke patients with first-ever aphasia were randomised within 2 weeks of onset to either 4 weeks of early intensive cognitive-linguistic treatment (1 h/day) or no language treatment. Hereafter, both groups received regular speech and language therapy. Primary outcome was the score on the Amsterdam-Nijmegen Everyday Language Test, measuring everyday verbal communication, 4 weeks after randomisation. Secondary outcomes were Amsterdam-Nijmegen Everyday Language Test at 3 and 6 months. The study was powered to detect a clinically relevant difference of four points on the Amsterdam-Nijmegen Everyday Language Test. RESULTS: Of the 152 included patients, 80 patients were allocated to intervention. Median treatment intensity in the intervention-group was 24.5 h. The adjusted difference between groups in mean Amsterdam-Nijmegen Everyday Language Test-scores 4 weeks after randomisation was 0.39, 95% confidence interval: [-2.70 to 3.47], p = 0.805. No statistically significant differences were found at 3 and 6 months after randomisation either. CONCLUSION: Four weeks of intensive cognitive-linguistic treatment initiated within 2 weeks of stroke is not more effective than no language treatment for the recovery of post-stroke aphasia. Our results exclude a clinically relevant effect of very early cognitive-linguistic treatment on everyday language.

Screening tests for aphasia in patients with stroke: a systematic review.

Aphasia has a large impact on the quality of life and adds significantly to the costs of stroke care. Early recognition of aphasia in stroke patients is important for prognostication and well-timed treatment planning. We aimed to identify available screening tests for differentiating between aphasic and non-aphasic stroke patients, and to evaluate test accuracy, reliability, and feasibility. We searched PubMed, EMbase, Web of Science, and PsycINFO for published studies on screening tests aimed at assessing aphasia in stroke patients. The reference lists of the selected articles were scanned, and several experts were contacted to detect additional references. Of each screening test, we estimated the sensitivity, specificity, likelihood ratio of a positive test, likelihood ratio of a negative test, and diagnostic odds ratio (DOR), and rated the degree of bias of the validation method. We included ten studies evaluating eight screening tests. There was a large variation across studies regarding sample size, patient characteristics, and reference tests used for validation. Many papers failed to report on the consecutiveness of patient inclusion, time between aphasia onset and administration of the screening test, and blinding. Of the three studies that were rated as having an intermediate or low risk of bias, the DOR was highest for the Language Screening Test and ScreeLing. Several screening tools for aphasia in stroke are available, but many tests have not been verified properly. Methodologically sound validation studies of aphasia screening tests are needed to determine their usefulness in clinical practice.

Early effect of intra-arterial treatment in ischemic stroke on aphasia recovery in MR CLEAN.

OBJECTIVE: To investigate the effect of intra-arterial treatment (IAT) on early recovery from aphasia in acute ischemic stroke. We hypothesized that the early effect of IAT on aphasia is smaller than the effect on motor deficits. METHODS: We included patients with aphasia from the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN), in which 500 patients with a proximal anterior circulation stroke were randomized to usual care plus IAT (<6 hours after stroke, mainly stent retrievers) or usual care alone. We estimated the effect of IAT on the shift on the NIH Stroke Scale (NIHSS) item language and the NIHSS item motor arm at 24 hours and 1 week after stroke with multivariable ordinal logistic regression as a common odds ratio, adjusted for prognostic variables (acOR). Differences between the effect of IAT on aphasia and on motor deficits were tested in a multilevel model with a multiplicative interaction term. RESULTS: Of the 288 patients with aphasia, 126 were assigned to IAT and 162 to usual care alone. The acOR for improvement of language score at 24 hours was 1.65 (95% confidence interval [CI] 1.05-2.60), and at 1 week 1.86 (95% CI 1.18-2.94). The acOR for improvement of motor deficit at 24 hours was 2.44 (95% CI 1.54-3.88), and at 1 week 2.32 (95% CI 1.43-3.77). The effect of IAT on language deficits was significantly different from the effect on motor deficits at 24 hours and 1 week (p = 0.005 and p = 0.011). CONCLUSIONS: IAT results in better early recovery from aphasia than usual care alone. The early effect of IAT on aphasia is smaller than the effect on motor deficits. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that for patients with acute ischemic stroke IAT increases early recovery from aphasia and that the early effect on aphasia, as measured by the NIHSS, is smaller than the effect on motor deficits.

Optimal timing of speech and language therapy for aphasia after stroke: more evidence needed.

Aphasia due to stroke affects communication and quality of life. Most stroke survivors with aphasia receive speech and language therapy. Although an early start of treatment is advocated in clinical practice, evidence for "The earlier, the better" in aphasia rehabilitation is weak. Hence, clinicians are faced with the dilemma of when to initiate intensive treatment: as early as possible, when most of the spontaneous recovery occurs but when patients are often ill, or later, when the patients' condition is more stabilized. Here we discuss whether aphasia outcome is affected by timing of treatment in relation to stroke onset and whether there is evidence for an optimal window of time during which language therapy should be provided. Findings from various rehabilitation research fields are discussed and combined to provide principles for future research.

The Efficacy and Timing of Melodic Intonation Therapy in Subacute Aphasia.

Background Little is known about the efficacy of language production treatment in subacute severe nonfluent aphasia. Although Melodic Intonation Therapy (MIT) is a language production treatment for this disorder, until now MIT effect studies have focused on chronic aphasia. Purpose This study examines whether language production treatment with MIT is effective in subacute severe nonfluent aphasia. Methods A multicenter, randomized controlled trial was conducted in a waiting-list control design: patients were randomly allocated to the experimental group (MIT) or the control group (control intervention followed by delayed MIT). In both groups, therapy started at 2 to 3 months poststroke and was given intensively (5 h/wk) during 6 weeks. In a second therapy period, the control group received 6 weeks of intensive MIT. The experimental group resumed their regular treatment. Assessment was done at baseline (T1), after the first intervention period (T2), and after the second intervention period (T3). Efficacy was evaluated at T2. The impact of delaying MIT on therapy outcome was also examined. Results A total of 27 participants were included: n = 16 in the experimental group and n = 11 in the control group. A significant effect in favor of MIT on language repetition was observed for trained items, with mixed results for untrained items. After MIT there was a significant improvement in verbal communication but not after the control intervention. Finally, delaying MIT was related to less improvement in the repetition of trained material. Conclusions In these patients with subacute severe nonfluent aphasia, language production treatment with MIT was effective. Earlier treatment may lead to greater improvement.

Nonlinguistic cognitive impairment in poststroke aphasia: a prospective study.

BACKGROUND AND OBJECTIVES: Information on cognitive impairment in aphasic patients is limited. Our aim was to investigate the prevalence and course of nonlinguistic cognitive impairments in the first year after stroke and their association with aphasia and functional outcome. METHODS: We included 147 patients with acute aphasia. At 3 months and 1 year, we assessed cognition with a nonlinguistic cognitive examination including abstract reasoning, visual memory, visual perception and construction, and executive functioning. We assessed language with a verbal communication rating (Aphasia Severity Rating Scale), the ScreeLing (a linguistic-level screening test), and the Token Test. We evaluated functional outcome with the modified Rankin scale and registered the use of antidepressants. RESULTS: In total, 107 (88%) patients had impairments in at least one nonlinguistic cognitive domain at 3 months and 91 (80%) at 1 year. The most frequently observed impairment concerned visual memory (83% at 3 months; 78% at 1 year) and the least frequent visual perception and construction (19% at 3 months; 14% at 1 year). There was improvement on all cognitive domains including language, except for abstract reasoning. Patients with persisting aphasia had lower cognitive domain scores, worse functional outcome, and were more often depressed than patients who had recovered from aphasia. CONCLUSIONS: Standard nonlinguistic cognitive examination is recommended in aphasic stroke patients. Nonlinguistic cognitive impairments are common and associated with poor functional outcome and depression, especially in patients with persisting aphasia.

Rotterdam Aphasia Therapy Study (RATS)-3: "The efficacy of intensive cognitive-linguistic therapy in the acute stage of aphasia"; design of a randomised controlled trial.

BACKGROUND: Aphasia is a severely disabling condition occurring in 20 to 25% of stroke patients. Most patients with aphasia due to stroke receive speech and language therapy. Methodologically sound randomised controlled trials investigating the effect of specific interventions for patients with aphasia following stroke are scarce. The currently available evidence suggests that intensive speech and language therapy is beneficial for restoration of communication, but the optimal timing of treatment is as yet unclear.In the Rotterdam Aphasia Therapy Study-3 we aim to test the hypothesis that patients with aphasia due to stroke benefit more from early intensive cognitive-linguistic therapy than from deferred regular language therapy. METHODS/DESIGN: In a single blinded, multicentre, randomised controlled trial, 150 patients with first ever aphasia due to stroke will be randomised within two weeks after stroke to either early intensive cognitive-linguistic therapy (Group A) or deferred regular therapy (Group B). Group A will start as soon as possible, at the latest two weeks after stroke, with a four week period of one hour a day treatment with cognitive-linguistic therapy. In Group B professional speech and language therapy is deferred for four weeks. After this period, patients will follow the conventional procedure of speech and language therapy. Participants will be tested with an extensive linguistic test battery at four weeks, three months and six months after inclusion. Primary outcome measure is the difference in score between the two treatment groups on the Amsterdam-Nijmegen Everyday Language Test, a measure of everyday verbal communication, four weeks after randomisation. TRIAL REGISTRATION: This trial is registered in the Dutch Trial Register (http://www.trialregister.nl), NTR3271.

Recovery of aphasia after stroke: a 1-year follow-up study.

Semantics, phonology, and syntax are essential elements of aphasia diagnosis and treatment. Until now, these linguistic components have not been specifically addressed in follow-up studies of aphasia recovery after stroke. The aim of this observational prospective follow-up study was to investigate semantic, phonological, and syntactic recovery in aphasic stroke patients. In addition, we investigated the recovery of verbal communication and of aphasia severity. We assessed 147 aphasic patients at 1, 2, and 6 weeks, 3 and 6 months, and 1 year after stroke with the ScreeLing, a screening test for detecting deficits on the three main linguistic components, the aphasia severity rating scale (ASRS), a measure of verbal communication, and the Token test, a measure of aphasia severity. We investigated the differences in scores between the six time points with mixed models. Semantics and syntax improved up to 6 weeks (p < 0.001) after stroke, and phonology up to 3 months (p ≤ 0.001). ASRS improved up to 6 months (p < 0.05) and the Token test up to 3 months (p < 0.001). We conclude that in aphasia after stroke, various linguistic components have a different recovery pattern, with phonology showing the longest period of recovery that paralleled aphasia severity, as measured with the Token test. The improvement of verbal communication continues after the stabilization of the recovery of the linguistic components.

Long-term prognosis of aphasia after stroke.

BACKGROUND: The long-term functional outcome of aphasia after stroke is uncertain, even though this information is needed as early as possible for adequate patient care and support. This observational prospective study was aimed at predicting functional outcome at 1 year after stroke. METHODS: We examined linguistic components (ScreeLing) and functional verbal communication (Aphasia Severity Rating Scale, ASRS) in 147 aphasic patients. The ScreeLing was administered at 1, 2 and 6 weeks after stroke; the ASRS at 1 week and 1 year. The relationships between linguistic, demographic and stroke characteristics, and good functional outcome at 1 year (ASRS 4 or 5) were examined with logistic regression analyses. RESULTS: The baseline linguistic components (ie, semantics, phonology and syntax) were significant predictors (p<0.001) for 1-year outcome in univariable analyses. In multivariable analysis, these variables explained 46.5% of the variance, with phonology being the only significant predictor (p=0.003). Age, Barthel Index score, educational level and haemorrhagic stroke were identified as other significant predictors of outcome. A prognostic model of these five baseline predictors explained 55.7% of the variance. The internally validated area under the receiver operating characteristic curve (AUC) was 0.89, indicating good predictive performance. Adding the degree of phonological recovery between 1 and 6 weeks after stroke to this model increased the explained variance to 65% and the AUC to 0.91. CONCLUSIONS: The outcome of aphasia at 1 year after stroke can be predicted in the first week by the phonology score, the Barthel Index score, age, educational level and stroke subtype, with phonology being the strongest predictor.

Expert versus proxy rating of verbal communicative ability of people with aphasia after stroke.

In randomized clinical trials of aphasia treatment, a functional outcome measure like the Amsterdam-Nijmegen Everyday Language Test (ANELT), administered by speech-language therapists, is often used. However, the agreement between this expert rating and the judgment of the proxy about the quality of the daily life communication of the person with aphasia is largely unknown. We examined the association between ANELT scores by speech-language therapists and proxy judgments on the Partner Communication Questionnaire both at 3 and 6 months in 39 people with aphasia after stroke. We also determined which factors affected the level of agreement between expert and proxy judgment of the communicative ability at 6 months in 53 people with aphasia. We found moderate agreement (at 3 months r = .662; p = < .0001 and at 6 months r = .565; p = .0001), with proxies rating slightly higher than experts. Less severe aphasia, measured with the Aphasia Severity Rating Scale, was associated with better agreement. In conclusion, although proxies were slightly more positive than experts, we found moderate agreement between expert and proxy rating of verbal communicative ability of people with aphasia after stroke, especially in milder cases.

The ScreeLing: occurrence of linguistic deficits in acute aphasia post-stroke.

OBJECTIVE: To investigate the occurrence of semantic, phonological and syntactic deficits in acute aphasia with the ScreeLing after the establishment of its psychometric properties. To examine the relationship between these deficits and: (i) overall aphasia severity; and (ii) quality of Spontaneous Speech. METHODS: The reliability and validity of the ScreeLing was established by investigating 141 subjects with acute aphasia (2 weeks after stroke), 23 with chronic aphasia, and 138 healthy controls. In addition, the acute patients were assessed with the Token Test and a Spontaneous Speech rating (Aphasia Severity Rating Scale). RESULTS: The ScreeLing was found to be valid and reliable for assessing the presence and severity of aphasia and linguistic deficits at 12 days after stroke. In 22.4% of the patients deficits were found in only 1 of the 3 linguistic levels; phonology was most frequently disturbed (16.3%), compared with semantics (2.7%), and syntax (3.4%). The number of impaired linguistic levels was related to aphasia severity: patients with a 3-level disorder had the lowest Token Test scores; patients with a selective phonological disorder had the highest Spontaneous Speech ratings. Phonology alone explained 54.6% of the variance in the Spontaneous Speech rating. CONCLUSION: In the acute stage, linguistic-level deficits are already present independently of each other, with phonology affected most frequently.

Advanced magnetic resonance neuroimaging of language function recovery after aphasic stroke: a technical review.

Two advanced magnetic resonance neuroimaging techniques, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), have recently made their way into clinically oriented research and hold great promise to study the brain's adaptive changes of function and structure after aphasic stroke, respectively. Such functional and structural neuroplasticity is thought to underlie the recovery of language function, occurring spontaneously and/or in the context of therapeutic intervention. With fMRI, brain activity can be visualized. Spontaneous brain activity, present in multiple brain networks, is measured with resting-state fMRI and language-related brain activity by having the subject perform a language task during scanning (task-based fMRI). With DTI the major white matter tracts, such as the dorsal and ventral language pathways and the commissural fibers, can be visualized and quantified. Both techniques are entirely noninvasive and thus offer the unique opportunity to perform multiple assessments within the same subject. To gain more insight in functional and structural neuroplasticity after aphasic stroke, advanced magnetic resonance neuroimaging studies in specific patient populations, at several stages after stroke and in the course of language recovery, are needed. Such studies will help to clarify the influence of the many factors that play a role in the recovery of language function and are thus vital to further the development of aphasia therapy. Application of these techniques in aphasic stroke patients, however, is not without challenge. The purpose of this article is to discuss the methodologic challenges of fMRI and DTI in the assessment of language recovery after aphasic stroke.

A 3-year evolution of linguistic disorders in aphasia after stroke.

Aphasia recovery after stroke has been the subject of several studies, but in none the deficits on the various linguistic levels were examined, even though in the diagnosis and treatment of aphasia the emphasis lays more and more on these linguistic level disorders. In this observational prospective follow-up study, we explored whether it is meaningful to investigate the recovery of semantics, phonology, and syntax separately. Fifteen patients with aphasia poststroke were assessed at 3 and 10 days, 7 weeks, 4 and 7 months, and 3 years postonset with the ScreeLing, a linguistic level test, the Aphasia Severity Rating Scale (spontaneous speech) and the Token Test. Group results showed improvement for the overall ScreeLing (P<0.01) and its subparts semantics (P<0.01) and syntax (P<0.01) up to 7 weeks, just as the Token Test (P<0.01). Phonology improved up to 4 months (P<0.05) and spontaneous speech up to 7 months (P<0.05). The recovery pattern of the three linguistic levels did not follow a parallel course, with a great deal of variability in linguistic recovery curves between and within patients. These results suggest that it is meaningful to assess the recovery of the linguistic levels separately, starting from the acute stage poststroke.

MAAS (Multi-axial Aphasia System): realistic goal setting in aphasia rehabilitation.

Treatment success in aphasia is influenced by various factors. Clinical decisions, including patient selection and decisions on frequency and content, are often guided by a clinician's implicit opinions. The Multi-axial Aphasia System (MAAS) was developed to structure linguistic, somatic, neuropsychological, psychosocial and socio-economic information on five separate axes, enabling an explicit and interdisciplinary process of clinical decision-making. The objectives of this study were to investigate the potentialities of MAAS in predicting the outcome of cognitive-linguistic treatment. A group of 58 aphasic patients were investigated prospectively. All received cognitive-linguistic treatment during a randomized, controlled study on the efficacy of lexical semantic treatment. An interdisciplinary aphasia team rated the pretreatment MAAS profiles of all patients. The team was blinded for treatment allocation and outcome. A multiple linear regression analysis was performed with the posttreatment verbal communication score as the variable to be predicted and the overall MAAS rating, age and type of treatment as predictor variables. In a second multiple regression analysis, the ratings for each of the five MAAS axes were used as candidate predictors. The team's overall rating contributed significantly to the prediction of verbal communicative ability after linguistic treatment. Of the five MAAS axes, the neuropsychological axis contributed to the prediction. An interdisciplinary approach to aphasia assessment may contribute to realistic goal setting in aphasia rehabilitation. The results of this study stress the importance of neuropsychological assessment of aphasic patients before treatment.

Effects of semantic treatment on verbal communication and linguistic processing in aphasia after stroke: a randomized controlled trial.

BACKGROUND AND PURPOSE: Semantic deficits, deficits in word meaning, have a large impact on aphasic patients' verbal communication. We investigated the effects of semantic treatment on verbal communication in a randomized controlled trial. METHODS: Fifty-eight patients with a combined semantic and phonological deficit were randomized to receive either semantic treatment or the control treatment focused on word sound (phonology). Fifty-five patients completed pretreatment and posttreatment assessment of verbal communication (Amsterdam Nijmegen Everyday Language Test [ANELT]). In an on-treatment analysis (n=46), treatment-specific effects on semantic and phonological measures were explored. RESULTS: Both groups improved on the ANELT, with no difference between groups in overall score (difference, -1.1; 95% confidence interval [CI], -5.3 to 3.1). After semantic treatment, patients improved on a semantic measure (mean improvement, 2.9; 95% CI, 1.2 to 4.6), whereas after phonological treatment, patients improved on phonological measures (mean improvement, 3.0; 95% CI, 1.4 to 4.7, and 3.0; 95% CI, 1.2 to 4.7). CONCLUSIONS: No differences in primary outcome were noted between the 2 treatments. Our findings challenge the current notion that semantic treatment is more effective than phonological treatment for patients with a combined semantic and phonological deficit. The selective gains on the semantic and phonological measures suggest that improved verbal communication was achieved in a different way for each treatment group.