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Verbal Fluency in Aphasia and Right-Hemisphere Damage: Qualitative Analysis Yields Relationship to General Cognitive Factors. Mayer, J. F., Murray, L. L., Ikatu, T., kean, J. A., & Rey, O. Adult Language and Cognition Lab Indiana University. Introduction.
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Verbal Fluency in Aphasia and Right-Hemisphere Damage: Qualitative Analysis Yields Relationship to General Cognitive Factors Mayer, J. F., Murray, L. L., Ikatu, T., kean, J. A., & Rey, O. Adult Language and Cognition Lab Indiana University
Introduction It is well known that many adults with aphasia demonstrate concomitant, nonlinguistic cognitive deficits. This has led to resource or processing models of aphasia, by which language-specific deficits are generated or exacerbated by domain-general cognitive impairments (e.g., McNeil et al., 1991; Murray et al., 1997). Despite increasing clinical and empirical attention to general cognitive factors of aphasia, the nature of these deficits and their interaction with language skills remains elusive.
Introduction, cont. Why a Dual-task Paradigm? • Allows simultaneous exploration of cognitive and linguistic factors in task performance. • Should differentiate adults with and without aphasia given growing evidence that aphasia in part reflects deficient allocation of attentional resources (e.g., McNeil et al., 1991) Why Verbal Fluency? • A particularly challenging word retrieval situation, often used as a measure of “executive” function in patients with brain injury (Schwartz & Baldo, 2001) • Controlled, effortful attention and strategic search required for successful completion (Rosen & Engle, 1997) • These are processes with which individuals with aphasia are known to have particular difficulty (Murray et al., 1998)
Why Qualitative Analysis? Theoretical implications: • Capacity for controlled attention (I.e., WM) predicts verbal fluency in non-brain-damaged (NBD) subjects in single-task paradigms (Subjects with high WM span generate more items per category). • Does this relationship hold for subjects with aphasia? • In dual-task paradigms with (NBD) adults, high, but not low-span NBD subjects (per results of WM capacity tests) are adversely affected (Rosen & Engle, 1997). • This suggests qualitatively different retrieval processes, depending on resource capacity or allocation: i.e., effortful search, versus a less effective passive, associative strategy that is more resistant to load effects. • However, based on dual-task paradigms used with adults with aphasia (LBD), LBD adults’ word retrieval skills should be negatively (disproportionately) affected by increasing cognitive demands (e.g., Murray, 2000) • Contrary to predictions from resource theories of aphasia, LBD patients may be less affected by the increased demands of a dual task paradigm if they have capacity limitations and relatedly are using qualitatively different strategies than NBD adults. Clinical implications: • Strategies for word recall may be revealed and subsequently exploited in aphasia treatment (Sarno et al., 2005)
Purpose of this Study: Delineate more finely a resource model of aphasia by using a dual task paradigm to examine both quantitative and qualitative verbal fluency performance by adults with aphasia (LBD), compared to non-brain damaged (NBD) and right-hemisphere brain damaged (RBD) adults.
Methods • Subjects: • 25 NBD, 23 LBD, 13 RBD subjects • Matched for age and education; screened for adequate vision, hearing, and absence of limb apraxia • LBD subjects: Variety of aphasia types represented, mild to moderate impairment (Aphasia Diagnostic Profiles). • RBD subjects: mild to severe cognitive communicative impairment (Mini Inventory of Right Brain Injury) • Initial Test Battery: • Boston Naming Test (BNT), Working Memory Protocol (WM) (Tompkins et al., 1994),Test of Everyday Attention (TEA)
Dual task procedures Verbal fluency task completed under five attention conditions: • Isolation: No distraction • Focused Attention: Concurrent tone stimuli; subjects instructed to ignore tones during fluency task • Divided Attention #1: Subjects completed verbal fluency and tone discrimination tasks with priority given to fluency (75%, vs 25% tone task) • Divided Attention #2: Equal priority to fluency and tone tasks (50% and 50%) • Divided Attention #3: Priority given to tone task (75%, vs 25% fluency task)
Task Descriptions • Verbal Fluency: • Semantic categories: clothing, school items, grocery store items, beverages, sports • Order of categories randomized across experimental conditions • Two-minute time limit • Tone Discrimination: • Forty 500ms pure tones presented randomly at 500 or 2000 Hz
Data Analysis • Quantitative analyses: Number of items generated per condition and over time • 3x5 (group x condition) and 3x4x5 (group x time x condition) ANOVA • Correlative analyses: Relationship to scores on BNT, ADP, TEA, and WM • Qualitative analyses: Word frequency and category typicality • 3x5 (group x condition) and 3x4x5 (group x time x condition) ANOVAs • Frequency counts from Kucera & Francis (1967); Typicality values modified from procedure by Sailor et al. (2004)
Results: Accuracy • Significant main effects of: time (p =.00), condition (p =.00), group (p =.00), significant interaction: time x condition (p =.00) • NBD >> LBD = RBD • Non-significant NBD trends: Greater overall change in accuracy within and across conditions
Results: Accuracy (Correlation analysis) and Frequency • Fluency accuracy, but not word frequency, significantly related to scores on the BNT (r=.57), ADP (r=.76), TEA (r=.593), and WM (r=.74) • Frequency: No significant differences across or within groups. • Nonsignificant trends in word frequency: • LBD: Most variability in word frequency • RBD: Trend towards lower word frequency overall • NBD: Little change in frequency across conditions and over time
Results: Typicality Significant main effects of: Group (p = .00), Condition (p = .002). Significant interaction: Condition x Group (p = .048). Post-hoc testing (Tukey HSD), NBD << LBD = RBD
Typicality Over Time: Significant main effects of: Group (p = .00) , Condition (p = .00), Epoch (p = .00), Condition x Group (p = .04), Group x Epoch (p = .01). LBD: Most typical, and with the least variation across time & condition.
Discussion: More than just word retrieval • As predicted from previous research (e.g., Auma et al., 1997): • NBD subjects generated significantly more items during fluency tasks, across all attention conditions, than both LBD and RBD subjects • Fluency accuracy, but not frequency, correlated significantly with linguistic and cognitive-linguistic measures • Supports “executive” nature of fluency task, across all subjects. • Frequency may be less important for word structure/storage than for lexcial identification (Coney, 2005) • Qualitative analysis: Provides insight into why: Not just a matter of language-specific word retrieval skills • Typicality = An index of semantic complexity • Passive, associative strategy during verbal fluency yields highly typical category exemplars • Controlled, effortful search will yield less typical, more complex category exemplars • This strategic search for low dominance exemplars is required for successful fluency performance across time (Kane & Engle, 2000)
“Controlled Attention”: Time effects • NBD subjects were able to engage in controlled search for successful fluency performance across epochs • Note steep decrease in typicality from Time 1 to 2, reflecting a switch from initial automatic retrieval to controlled, systematic search • LBD and RBD subjects: Relied on more automatic, less controlled search (i.e., highly typical exemplars indicative of passive/associative strategy), leading to decreased accuracy overall • That LBD and RBD performance was essentially identical points to attentional mechanisms (i.e., linguistic performance) rather than structure of semantic categories (i.e., linguistic competence) to explain decreased accuracy. • Arguably, this study emphasized congitive factors in fluency due to: 1) longer retrieval periods (120 vs 60 sec), and 2) dual task demands (vs., e.g., Schwartz & Baldo, 2004)
“Limited Resources” : Dual task effects • Normal-to-aphasia continuum(e.g., McNeil et al., 1991) • Resource theory predicts NBD subjects will perform MORE like LBD adults given increased cognitive demands • Our results confirm this: NBD subjects with decreased accuracy and increased typicality as dual task demands increased • Likewise, LBD adults perform more like “low-span” NBD subjects (Rosen & Engle, 1997) • Accuracy-typicality trade-off • Resource theory predicts LBD subjects will be differentially affected by dual task demands • Does not take into account qualitative difference in retrieval strategies • Our results show LBD (and RBD) subjects were LESS affected by dual task demands due to less controlled or systematic (and less effective overall) search strategies. • Emphasizes importance of fine-grained analyses for interpretation of dual-task data. • Poor allocation of attentional resources in adults with aphasia may affect their ability to access efficiently relatively intact linguistic forms.
Clinical Implications • Clincial relevance of verbal fluency tasks often overlooked • Likely due in part to common failure to consider qualitative aspects of fluency performance (Sarno et al., 2005) • Measuring a “typicality” index in patient’s output will provide insight for clinicians into patient’s word-finding strategies • Clincians may be advised to train patients to engage in more systematic or controlled search of the lexicon by: • Generalized “attention” training (e.g., Helm-Estabrooks et al., 2000) • Semantic-based single-word treatments (e.g., Semantic Feature Analyses; Boyle & Coelho, 1995)
SelectedReferences Coney, J. (2005). Word frequency and lateralization of lexical processes. Neuropsychologia, 43, 142-148. Kane, M. J., & Engle, R. W. (2000). Working memory capacity, proactive interference, and divided attention: Limits on long-term memory retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 336-358. Mcneil, M. R., Odell, K., & Tseng, C. H. (1991). Toward the integration of resource allocation into a general theory of aphasia. Clinical Aphasiology, 20, 21-39. Murray, L. L., Holland, A. L., & Beeson, P. M. (1994). Audiotry processing in individuals with mild aphasia: A study of resource allocation. Journal of Speech, Language, and Hearing Research, 40, 792-808. Rosen, V. M., & Engle, R. W. (1997). The role of working memory capacity in retrieval. Journal of Experimental Psychology: General, 126, 211-227. Sailor, K., Antoine, M., Diaz, M., Kuslansky, G., & Kluger, G. (2004). The effects of Alzheimer’s Disease on item output in verbal fluency tasks. Neuropsychology, 18, 306-314. Sarno, M. T., Postman, W. A., Cho, Y. S., & Norman, R. G. (2005). Evolution of phonemic word fluency performance in post-stroke aphasia. Journal of Communication Disorders, 38, 83-107. Schwartz, S., & Baldo, J. (2001). Distinct patterns of word retrieval in right and left frontal lobe patients: A multidimensional perspective. Neuropsychologia, 39, 1209-1217.