Semantic Feature Analysis: Further Examination of Outcomes

Semantic Feature Analysis (SFA) has received considerable study over the past two decades as a word-retrieval treatment for aphasia (Boyle & Coelho, 1995; Lowell, Beeson, & Holland, 1995; Boyle, 2010; Wambaugh, Mauszycki, Cameron, Wright, & Nessler, 2013). SFA has been shown to have consistently positive acquisition effects (i.e., improvement of trained items), with generally positive but less predictable generalization effects (i.e., improvement in untrained items). SFA was originally designed as a cognitive treatment for children and adolescents sustaining traumatic brain injury (TBI) (Haarbauer-Krupa, Moser, Smith, Sullivan & Szekeres, 1985). The therapy was designed as an “organizing process for thinking and verbal expression” (p.303). Massaro and Tompkins (1994) operationalized SFA in a study with two participants with TBI. In keeping with the intentions of the original developers, Massaro and Tompkins measured SFA’s treatment effects in terms of increased production of semantically relevant content. In the treatment of aphasia, the focus of SFA relative to outcomes has been naming accuracy. That is, SFA has been used as a means of systematically stimulating semantic networks to facilitate naming. Additionally, SFA has been considered to potentially serve as a mediating strategy for self-cuing accurate naming and/or a compensatory strategy for circumventing word-retrieval difficulties. The current study was designed to elucidate the effects of SFA in aphasia treatment beyond naming accuracy. Given SFA was designed to improve verbal expression in general and may serve as a compensatory strategy, increased production of relevant content was of interest (after Tompkins & Massaro, 1994). In light of inconsistent generalization effects associated with SFA, the study was designed to explore its generalization effects relative to aspects of untreated items. Specifically, untreated items were controlled in terms of semantic relatedness, exposure in probing, and knowledge of phonological form

Computer-based cognitive intervention for aphasia: Behavioural and neurobiological outcomes

Aphasia, an acquired impairment of language that commonly occurs after stroke, can have significant consequences on all aspects of functioning of affected individuals. Some have proposed that the language deficits observed in aphasia are due to underlying limitations in cognitive processes that support language1-3. This ‘cognitive’ theory of aphasia is gaining increased attention in the research literature4, and is the impetus for the study of treatments for aphasia that target these underlying cognitive processes5-8. Indeed, studies of cognitive interventions in healthy populations have reported positive outcomes in behavioural (i.e. language and overall cognitive functioning9, 10) as well as neurobiological (i.e., brain function and/or structure11-13) domains, offering promise for the application of these types of interventions to aphasia. Recently, computer-based ‘brain training’ programs have become increasingly prevalent. BrainFitness (BF) is one such commercially available program; it has been used to show improvement in auditory processing speed, attention and working memory in typically aging adults14, 15. This program has the potential to be a useful intervention for individuals with aphasia, but questions regarding the clinical utility of the program and neural correlates of training-related behavioural changes remain. The purpose of this study was to investigate the effect of BF training in people with aphasia using behavioural and neurobiological outcome measures

Acquisition and generalization responses in aphasia treatment: Evidence from sentence-production treatment

Treatment of Underlying Forms (TUF) promotes not only acquisition of treated sentence types but also generalization to related but untreated sentences (e.g., Thompson, Shapiro, Kiran & Sobecks, 2003). In a meta-analysis examining TUF treatment outcomes, Dickey and Yoo (2010) found evidence that the factors governing TUF acquisition and generalization may be different. They found that general auditory comprehension ability but not overall aphasia severity or sentence-comprehension impairment predicted participants’ acquisition of treated sentences. In contrast, none of these factors were related to participants’ generalization to related but untreated sentences. Interestingly, Meinzer and colleagues (2010) found similar results for naming treatment: brain areas that were positively related to acquiring treated items were not associated with generalization to untreated words. These findings suggest that the mechanisms responsible for acquisition and generalization responses to aphasia treatment may be distinct. The current study examined this question further by testing the dose-response relationships for TUF, for both acquisition and generalization. It analyzed existing TUF treatment studies by using multilevel generalized linear regression to model changes in probe accuracy over the course of treatment. One model estimated the slope and intercept of acquisition and generalization curves in response to increasing amounts of treatment. A second set of models tested whether these dose-response relationships were moderated by aphasia severity (viz. Dickey & Yoo, 2010). Determining whether acquisition and generalization curves exhibit similar slopes and intercepts, and whether they are moderated by the same factors, will help establish how similar the two treatment responses are. Comparing the slopes and intercepts of these curves can also shed light on whether similar amounts of treatment are needed to promote acquisition and generalization

Localizing unique and overlapping lesion locations in apraxia of speech and aphasia

Since Darley’s original description of apraxia of speech (AOS; 1968), controversy has centered around its diagnosis, treatment, and lesion location. Behaviors common to AOS are often shared among other communication disorders, complicating clinical management. The current study sought to identify crucial brain damage that causes apraxic speech, as well as errors common in both AOS and aphasia. Results revealed that damage to premotor and supplementary motor areas is unique to AOS, while involvement of temporal lobe areas predicts behaviors attributable to aphasia. These findings contribute to research regarding the neuroanatomical mechanism of AOS, and may ultimately improve differential diagnostic procedures

Sound Production Treatment: Synthesis and Quantification of Outcomes

Treatment for acquired apraxia of speech (AOS) has taken numerous forms, with positive outcomes reported for most treatments. Following a critical evaluation and synthesis of the AOS treatment literature, AOS treatment guideline developers concluded that “taken as a whole, the AOS treatment literature indicates that individuals with AOS may be expected to make improvements in speech production as a result of treatment, even when AOS is chronic….and the strongest evidence for this conclusion exists for treatments designed to improve articulatory kinematic aspects of speech production” (Wambaugh, Duffy, McNeil, Robin, & Rogers, 2006; p.lxii ). This conclusion was based upon general criteria concerning the overall quantity and quality of the evidence-base. Strom (2008) subsequently confirmed the positive effects of articulatory-kinematic AOS treatment approaches using meta-analysis. The AOS guidelines developers grouped treatment studies by general focus (e.g., articulatory-kinematic, rate/rhythm, intersystemic reorganization, and alternative/augmentative); at the time of the guidelines report, no one treatment had a sufficient database to warrant individual consideration (Wambaugh et al., 2006). Over the past decade, additional AOS treatment evidence has accumulated with investigations moving toward comparisons of treatment approaches (Wambaugh, Mauszycki, & Ballard, 2013). Sound Production Treatment (SPT; Wambaugh, Kalinyak-Fliszar, West, & Doyle, 1998) is an articulatory-kinematic AOS treatment that has received relatively systematic study over the past 15 years. There are now sufficient reports of SPT to support its evaluation as a specific approach rather than as part of the general category of articulatory-kinematic approaches. A synthesis and quantification of the effects of SPT is needed to permit comparison to other treatments, to allow evaluation of different applications of SPT, and to facilitate examination of generalization effects of treatment. The purpose of the current investigation was to quantify the effects of SPT in terms of the magnitude of change (i.e., effect size) associated with treatment and follow-up phases of efficacy studies

Nonverbal Working Memory as a Predictor of Anomia Treatment Success: Preliminary Data

It has been well established that individuals with aphasia tend to have difficulty with nonverbal working memory (Lang & Quitz, 2012; Maher & Murray, 2012; Wright & Fergadiotis, 2012) that can influence linguistic and nonlinguistic processing. The extent to which these working memory deficits impact recovery from aphasia is still under investigation. From a clinical standpoint, the relationship between nonverbal working memory and response to aphasia treatment may hold prognostic value in predicting those individuals who will respond best to a particular type of treatment. To obtain this clinical goal, it will be necessary to assess the reliability of working memory tasks in individuals with aphasia (Mayer & Murray, 2012) because of high variability in performance across sessions in this population. The purpose of the study was threefold; (1) to identify the extent to which nonverbal working memory performance, as measured by the spatial span (SS) task (Wechsler, 1997), was reliable across multiple testing sessions in individuals with aphasia, (2) to determine if Cued Picture Naming Treatment (CPNT) impacted performance on the SS task, and (3) to determine the degree to which nonverbal working memory, as measured by the SS task, predicted response to anomia treatment in individuals with chronic aphasia

Judging Communicative Competence: Investigating Age-Related Stereotypes in Speech-Language Pathology Students

The proportion of the US population over age 65 is projected to reach almost 80 million by the year 2040, doubling the numbers from 2000 (Administration on Aging, 2012). With the aging of the population, the incidence of age-related diseases and disorders like stroke and dementia is expected to increase, adding to the caseloads of speech-language pathologists (SLPs). Most SLPs, by contrast, are younger adults; over a quarter of SLPs in the US are under age 35 (ASHA, 2012). Thus, as the elderly population grows, more intergenerational communication encounters will occur between SLPs and their aging clients, increasing demands for cultural competence, specifically with regard to ageism. However, the field of speech-language pathology has seen little research into the impact of age-related stereotypes on service delivery (Armstrong & McKechnie, 2003). One’s interactions with people are implicitly shaped by stereotypes, widely held unconscious representations of groups of people (Devine, 1989). According to the Age Stereotypes in Interaction model (Hummert, 2012), there are three main factors that trigger stereotypes: the perceiver’s self-system, the context of the interaction, and physical traits. ‘Self-system’ refers to one’s beliefs and attitudes, which are themselves determined by one’s age, cognitive complexity, and past experiences (Hummert, 2012; Ryan, 2007). Stereotypes can be reinforced by the context in which intergenerational encounters occur. To illustrate, Hummert and colleagues (1998) found that younger adults used different language when speaking to older adults in the hospital vs an apartment. Aspects of physical appearance (e.g. grey hair, stooped posture) create an immediate impression of the older individual (Adams et al., 2012). Using photographs, Hummert and colleagues (1997) found that adults perceived to be older were stereotyped more negatively than younger-looking adults. Negative stereotypes may, in turn, affect older adult’s responses, resulting in a cycle of reinforced stereotypes and negative interactions (Ryan, 2007). Williams and colleagues (2009) found that nurses who used ‘elderspeak’ met with more resistance to care in their patients with dementia. To prevent such negative interactions, SLPs must become aware of the potential impact of implicit age-related stereotypes. The purpose of this study was to determine whether SLP students are influenced by age-related stereotypes when judging the communication of older adults

Statistical Learning in Aphasia: Preliminary Results from an Artificial Grammar Learning Task

Statistical learning, i.e., the discovery of structure based on statistical properties of stimuli, is considered an implicit process that plays an important role in nonlinguistic and linguistic tasks, including speech segmentation and grammar learning (Aslin & Newport, 2012; Saffran, 2002; Saffran et al., 1996). Moreover, individual differences in statistical learning ability have been shown to be associated with natural language processing (Misyak & Christiansen, 2012; Misyak et al., 2010). Yet little is known about this type of learning in individuals with aphasia, who must relearn linguistic skills after brain damage. To date, studies of implicit learning processes in aphasia have provided mixed results, including evidence of limited or absent implicit learning for a visual artificial grammar (Christiansen et al., 2010; Zimmerer et al., 2014), as well as evidence of relatively intact implicit learning in Serial Reaction Time tasks (Goschke et al., 2001; Schuchard & Thompson, 2013). The purpose of the present study was to test statistical learning and overnight consolidation of an artificial phrase structure grammar under implicit conditions in individuals with agrammatic aphasia and healthy age-matched adults

Transcranial Direct Current Stimulation and Aphasia Treatment: A Pilot Study of Anodal, Cathodal and Sham Stimulation

Transcranial direct current stimulation (tDCS) may potentially enhance language therapy outcomes in aphasia. We report behavioral results for twelve participants with chronic aphasia matched for severity and randomized to receive anodal, cathodal or sham stimulation to the left hemisphere, concurrent with intensive speech-language therapy. Importantly, tDCS (1mA for 13 minutes) given 5 days a week over a prolonged period of time (6 weeks) was found to be safe. There was an advantage of both anodal and cathodal stimulation over sham stimulation. Cathodal stimulation to the left hemisphere may be a viable option and should not be overlooked in future research

How do persons with aphasia describe concrete objects?

Feature-based models of semantic processing are predicated on the notion that object concepts are constructed through the co-activation of semantic feature knowledge (e.g., Gainotti, 2006; Tyler et al., 2000; Warrington & Shallice, 1984). For example, for the concept DOG, semantic features include visual-perceptual (has fur, has wet nose), motor/action (walks, wags), and functional (guides the blind) information, along with knowledge of superordinate category membership (animal, mammal, canine), encyclopedic information (Lassie was a famous one, cats are afraid of them), and personal associations/opinions (Dogs are my favorite animal.). In fact, accessing such information is thought to activate retrieval of lexical knowledge for naming and learning the particular patterns of feature co-occurrence among different concepts allows us to categorize similar concepts using shared features (e.g., dogs, cats, mice: all breathe, eat, grow → are animals) distinguish similar concepts using distinctive features (dogs wag their tails, mice do not wag) and recognize concepts that are semantically unrelated (e.g., pencils are utensils used for writing and erasing, which are not activities frequently engaged in by dogs). As yet unresolved is whether different types of ‘core’ semantic features may be more salient to identification and differentiation of different concept domains. Is it, as ‘sensory/function’ or sensorimotor-based hypotheses suggest, that disproportionate deficit to living concepts results from deficient processing of visual-perceptual features (e.g., apple: red, round), considered most salient for their differentiation; whereas disproportionate impairment to nonliving concepts results from deficient processing of functional or action features (pencil: used to write and erase) (e.g., Gainotti, 2006; Warrington and Shallice, 1984)? Or is it the interaction among shared and distinctive features across types that results in disproportionately deficient processing between domains, with shared form-function relations being more robust for living concepts, whereas for nonliving concepts it is more distinctive form-function associations (e.g., Tyler et al., 2000)? Debate is ongoing. That said, a number of treatments for individuals with lexical retrieval impairment consequent to stroke-aphasia have been developed to take advantage of the relationship between access to semantic feature knowledge and activation of object names (see Boyle, 2010 and Kiran, 2007 for review). The purpose of this report is to add to the relatively small body of evidence regarding the types of semantic feature knowledge most accessible to those with aphasia and how that knowledge is accessed domains (i.e., living vs. nonliving)