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Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type a
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Hura Behforuzi , D. Brandon Burtis , John B. Williamson , Jennifer J. Stamps & Kenneth M. Heilman
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Department of Neurology, The Center for Neuropsychological Studies, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA b
Malcom Randall Veterans’ Affairs Medical Center, Geriatric Research, Education & Clinical Center, Gainesville, FL, USA c
Department of Neuroscience, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA Published online: 19 Nov 2013.
To cite this article: Hura Behforuzi, D. Brandon Burtis, John B. Williamson, Jennifer J. Stamps & Kenneth M. Heilman (2013) Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type, Cognitive Neuroscience, 4:3-4, 163-170, DOI: 10.1080/17588928.2013.854200 To link to this article: http://dx.doi.org/10.1080/17588928.2013.854200
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COGNITIVE NEUROSCIENCE, 2013 Vol. 4, Nos. 3–4, 163–170, http://dx.doi.org/10.1080/17588928.2013.854200
Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type
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Hura Behforuzi1, D. Brandon Burtis1,2, John B. Williamson1,2, Jennifer J. Stamps3, and Kenneth M. Heilman1,2 1
Department of Neurology, The Center for Neuropsychological Studies, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA 2 Malcom Randall Veterans’ Affairs Medical Center, Geriatric Research, Education & Clinical Center, Gainesville, FL, USA 3 Department of Neuroscience, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA Objectives: Early detection of Alzheimer disease (AD) is important. With AD, the loss of connectivity should first induce dysfunction in those representational networks with the weakest connectivity. Less frequently used networks have weaker connectivity. Given the letter “A” has more phonemes than the letters “F” and “S”, fewer words would begin with each of these “A” phonemes than with the “F” or “S” phonemes. We wanted to learn if patients with AD would produce fewer words starting with “A”. Methods: Patients with AD, mild cognitive impairment (MCI), and normal participants, were assessed with the Controlled Oral Word Association (COWA) test. Results: Compared to controls and MCI patients, AD patients produced relatively fewer words beginning with “A” than with “F” and “S”. Conclusions These results support the postulate that the less frequently used, and thus more weakly connected, phonetic-lexical networks are more sensitive to the degradation induced by AD.
Keywords: Alzheimer’s disease; Letter fluency; Vowel; Consonant.
The development of clinical instruments that enable the early detection of Alzheimer’s disease (AD) versus normal aging and other dementias remains a major objective of many studies. Patients with AD often have word finding difficulties, as assessed by naming to confrontation (e.g., Boston Naming Test) and word generation tests such as the Controlled Oral Word Association Test (COWA) (Benton, 1968), where participants are asked to generate words beginning with specified letters (e.g., F, A, and S)
in one minute, excluding proper names or numbers. When assessed with the COWA, patients with AD are often impaired (Henry, Crawford, & Phillips, 2004). In the semantic fluency test, participants are asked to produce words belonging to a given semantic category, such as animals, in 1 minute. Patients with AD are often more impaired on semantic fluency than phonemic fluency tasks (Henry et al., 2004). According to a revised Kussmaul’s model (Heilman, 2006; Kussmaul, 1877), there is a sequence of
Correspondence should be addressed to: Hura Behforuzi, Department of Neurology, Room L3-100, McKnight Brain Institute, 1149 Newell Drive, Gainesville, FL 32611, USA. E-mail: [email protected]fl.edu The study was supported by The State of Florida Memory Disorder Clinics.
The work of Brandon Burtis, DO, John B. Williamson, PhD and Kenneth M. Heilman, MD was authored as part of their official duties as Employees of the United States Government and the State of Florida and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. Hura Behforuzi MD and Jennifer Stamps BA, waive their right to assert copyright but not their right to be named as a co-authors.
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Figure 1. Diagrammatic model of the modular language processing network. In this diagrammatic model, speech comprehension is mediated by the 1-A-2-B-3 modular processing network, and in early Alzheimer’s disease (AD), comprehension is usually intact. Repetition, mediated by the 1-A-2-C-4-D-5-E-6 modular processing network, including the input and output phonological lexicons, is also usually intact in early AD. In contrast, naming is often impaired in early AD. The observation that most patients with early AD who have naming impairment can often recognize the pictures they are viewing would suggest that the visual recognition units have access to a relatively intact semantic-conceptual field (8-F-3). Thus, these patients’ naming impairment is probably related to a deficit in their ability to access the phonological output lexicon, which could be a deficit in either the 8-G-4 network or the 8-F-3-H-4 network. However, since most patients are also impaired at word finding during spontaneous speech, it is the latter network that is impaired. And since people can comprehend pictures they viewed, it is probably the connectivity between the semantic conceptual field and the output lexicon that is impaired (3-H-4). This postulate is supported by the observation that performance on the category-word fluency test, which is probably dependent on this same network (3-H-4), correlated with performance on the naming test. The impaired performance in letter-word fluency was not directly related to these patients impaired naming, suggesting that there is dysfunction in another network. Since most people use a phonetic search strategy, the 7-J-5-I-4 network may be used to activate the phonological output lexicon and the 4-D-5-E-6 network is used to produce these words. Since repetition is normal in patients with early AD, this latter production network (4-D-5-E-6) should be intact. Thus, these patients’ reduced ability to produce words that begin with the letter “A” is probably related to weakened connectivity in the 5-I-4 network.
processing stages in spontaneous speech production or naming which includes the development of the concepts with the activation of the semantic representations that are to be communicated (see Figure 1). Spoken words are combinations of sounds (phonemes) that are symbols of concepts. These sound symbols of concepts are stored in a phonological lexical (word sound) network. Thus, the next step is the selection of the phonological sequences (words) that are used to denote these concepts. Since these lexical-phonological sound representations of words need to be spoken, they are transformed into phonetic programs that control the position and movements of the articulatory apparatus. These action-movement programs allow people to produce the phoneme sequences that comprise spoken words. The naming disorder associated with AD has been attributed to
semantic-conceptual deficits as well as deficits of lexical access. Support of the lexical access deficit hypothesis comes from the study (Yoon et al., 2010) that used the Korean version of the Boston Naming Test in patients with early and moderate AD. Upon failure to name an item, either a semantic or phonemic cue was provided. These patients were significantly facilitated by phonemic cues, suggesting that the naming disorder associated with mild and moderate AD, is related to a deficit in lexical access. This hypothesis was also supported by Balthazar et al. who found that after phonemic cuing, there was no difference between the normal, MCI, and AD participants (Balthazar, Cendes, & Damasceno, 2008). When performing the COWA, people will often search their phonological lexicon for words that begin with the phoneme(s) (speech sounds) that this
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letter denotes. In English the initial letter “A” can represent one of the eight different first sounds including: “eɪ” (acorn), “æ” (apple), “ə” (about), “eə” (air), “ɑː” (arm), “ɔː” (authorize), “aɪ” (aisle), and “e” (aesthetic). In contrast, the consonant “F” at the beginning of words has only one phoneme and the consonant “S” has two phonemes (“s” (say) and “ʃ” (sure)). In the Oxford American Dictionary of Current English (Abate, 1999), there are approximately (~) 1960 words listed that begin with the letter “A” (~ 40 word/page and 49 pages), ~ 1730 words with the letter “F” (~ 40 words/page and 43 pages), and ~ 4680 with the letter “S” (~ 40 words/page and 117 pages). Assuming an equal number of words begin with each of the eight phonemes associated with the letter “A”, ~ 250 words would begin with each of these phonemes. In contrast, ~ 2340 words would begin with each of the two “S” phonemes and ~ 1730 with the single “F” phoneme. This would suggest that the phonemes associated with the letters “F” and “S” would be used more than six times as frequently as any one of the eight phonemes associated with the letter “A”. The individual sounds of a word are sequenced together to produce syllables. In languages such as English and Dutch, only 5% of the entire syllable inventory are needed to produce 80–85% of words (Levelt, Roelofs, & Meyer, 1999). Rather than assembling syllables, the so-called “mental syllabary” provides ready-made, phonological syllable units during phonetic encoding and words consisting of high frequency syllables are produced faster than words with low frequency syllables (Cholin, Levelt, & Schiller, 2006). This syllable frequency effect is most robust at the initial position of the word (Cholin et al., 2006) and it has been demonstrated that there are fewer “tip of the tongue” experiences for target words containing high-frequency first syllables relative to low-frequency syllables (Farrell & Abrams, 2011). The Hebbian hypothesis states, “neurons that fire together wire together” (Hebb, 1949). A corollary postulate is that less frequently used networks have weaker connectivity than more frequently used networks. The strength of connectivity should be reflected in the performance of normal subjects. Tombaugh et al. (1999) recruited a large group of normal participants (895) with a wide range of ages and years of education and found that the number of words produced in the COWA were significantly fewer with the letter “A” than the letters “F” and “S”. With the loss of neuronal connectivity found in AD (Terry et al., 1991), patients should first reveal more severe dysfunction in those representational
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networks with the weakest connectivity. According to this Hebbian concept, since the “F” and “S” phonemes would be more frequently used, the connectivity between the “F” and “S” phonetic representations and the words stored in the lexicon beginning with these letters would be stronger than the connectivity between the “A” phonetic representations and the words beginning with the eight different phonemes of “A”. Thus, the purpose of this study was to test the hypothesis that patients with AD, when compared to participants with MCI, as well as normal controls (NC), would be relatively more impaired in generating words beginning with the letter “A” versus words beginning with the letters “F” and “S”.
METHODS Participants 12 patients with probable AD, 11 with MCI and 22 NCs, all native English speakers, participated. AD and MCI subjects were evaluated by behavioral neurologists, and had neuropsychological testing as well as imaging and laboratory studies to rule out any treatable causes of cognitive decline. All of the AD participants met the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association for probable Alzheimer’s disease (McKhann et al., 1984). All MCI participants were diagnosed based on the National Institute on Aging and the Alzheimer’s Association recommendations (Albert et al., 2011). The NC participants were recruited prospectively and had no history of neurological or psychiatric disorders, head injury, substance abuse, or organ failure. This study was approved by the local IRB and the participants signed an informed consent. The AD patients (eight women and four men) had an age range of 54–83 (M = 72.42, SD = 8.17) with an average of 15.08 (SD = 3.02) years of education. The MCI patients (seven women and four men) had an age range of 50–85 (M = 68.18, SD = 10.75) with an average of 15.45 (SD = 3.11) years of education. The NC participants (11 women and 11 men) had an age range of 47– 86 (M = 72.91, SD = 8.15) with an average of 16.80 (SD = 3.51) years of education. Analysis of age and level of education revealed no significant differences between these three groups (age: F(2, 42) = 1.11, p = .33; education: F(2, 40) = 1.20, p = .31). One participant with MCI and two NC participants were left handed. All others were right handed. The mean
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significant difference across three groups (“F” fluency F(2, 42) = 13.85, p < .001, d = .62, “A” fluency F(2, 42) = 14.40, p < .001, d = .63, “S” fluency F(2, 42) = 11.58, p < .001, d = .58). However, Tukey post-hoc comparisons revealed significant differences between the participants with AD and MCI as well as between the participants with AD and normal controls. There was, however, no significant difference between patients with MCI and NCs (see Table 2). To learn if the patients with AD had a relatively greater impairment than the patients with MCI and the NC participants in producing words with the letter “A” compared to the letter “F”, we computed an F/A ratio and performed an ANOVA. This analysis revealed that the F/A ratio differed significantly between these groups, F(2, 42) = 4.28, p = .02, d = .40. Tukey posthoc comparisons of the three groups indicated that AD group (M = 2.39, 95% CI [.93, 3.85]) had a significantly higher F/A ratio than the MCIs (M = 1.02, 95% CI [.85, 1.19]), p = .02, and the NCs (M = 1.32, 95% CI [1.14, 1.50]), p = .04. A comparison between MCI group and NC group was not statistically significant (p > .05). We also performed a similar analysis using S/ A word production ratio and this also had a significant between-group difference, F(2, 42) = 5.97, p = .005, d = .47. Tukey post-hoc comparisons show that the AD group (M = 1.99, 95% CI [1.25, 2.72]) has a significantly higher S/A ratio than the MCIs (M = 1.06, 95% CI [.82, 1.30]), p = .005, and NCs (M = 1.37, 95% CI [1.22, 1.53]), p = .03. The MCI group was not different from the NC group (p > .05). Finally, the F/S ratio was examined (in AD patients with an average of 1.10 (SD = .65), in MCI group with an average of 1.08 (SD = .56) and in normal controls with an average of .98 (SD = .28)). This F/S ratio does not differ significantly between the groups, F(2, 42) = .29, p = .74. In summary, these results indicate that patients with AD have decreased fluency when performing the COWA with the letters “F”, “A”, and “S”. In addition, when attempting to generate words that
Mini Mental Status Examination (MMSE) score of the participants with AD was 20.50 (SD = 6.17, range: 10–29) and for the participants with MCI was 27.09 (SD = 2.30, range: 23–30).
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Apparatus and Procedures The participants were instructed to generate as many different words as possible in one minute that begin with the letter “F” without using proper names, numbers, or derivatives of the words they had previously used. After the trial with the letter “F”, they were tested in the same manner with the letter “A” and then the letter “S”. The examiner recorded the words generated by the participants verbatim. The scores for each phonemic fluency task were obtained excluding derivatives, proper names, and number errors, as well as words that were repeated. Output from the three letter trials were added together to obtain the total words produced. For the patients who were diagnosed with AD and MCI, the MMSE, the COWA test, Hopkins Verbal Learning Test (HVLT), Boston Naming Test (BNT), and category (animal) fluency test were performed as part of their routine clinical evaluation.
RESULTS The means and standard deviations for the letters “F”, “A”, and “S” for the participants with AD, MCI, and normal participants can be found in Table 1. Figure 2 demonstrates the relative performance of ADs, MCIs, and NCs on each fluency task. To learn if these three groups of participants (AD, MCI, NC) performed differently in the “F”, “A”, and “S” letter-word fluency tests, an analysis of variance (ANOVA) was used with the dependent variable being the number of correct words produced for each of these letters. This ANOVA for each letter fluency task showed a
TABLE 1 Means, standard deviations, and one-way ANOVA results for F/A ratio, S/A ratio, “F”, “A”, and “S” letter fluency scores in Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal controls (NC) – all native English speakers Groups Variable F/A ratio S/A ratio F A S
AD (M, SD) 2.39, 1.99, 7.33, 4.58, 7.67,
2.30 1.15 2.93 2.71 3.86
*p < .05; **p < .01; ***p < .001.
MCI (M, SD) 1.02, 1.06, 12.45, 12.73, 13.18,
.25 .36 3.32 4.14 4.42
NC (M, SD) 1.32, 1.37, 15.05, 12.09, 15.95,
.39 .34 4.85 4.95 5.37
ANOVA F(2, 42) 4.28* 5.97** 13.85*** 14.40*** 11.58***
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Figure 2.
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Relative performance of ADs, MCIs, and Normal Control English speakers on F, A, and S phonemic fluency tests.
TABLE 2 Post-hoc comparisons of “F”, “A”, and “S” phonemic fluency scores in AD, MCI, and normal controls – all native English speakers 95% Confidence interval Variable
Comparisons
Mean difference
Standard error
Lower bound
Upper bound
F
AD vs. MCI AD vs. NC MCI vs. NC AD vs. MCI AD vs. NC MCI vs. NC AD vs. MCI AD vs. NC MCI vs. NC
−5.12* −7.71** −2.59 −8.14** −7.50** .63 −5.51* −8.28** −2.77
1.70 1.46 1.50 1.78 1.53 1.58 2.00 1.72 1.77
−9.26 −11.27 −6.25 −12.48 −11.24 −3.20 −10.38 −12.47 −7.08
−.98 −4.15 1.07 −3.80 −3.78 4.48 −.65 −4.10 1.53
A
S
*p < .05; **p < .001.
begin with the letter “A” versus the letters “F” and “S”, the patients with AD were relatively more impaired. Some patients with MCI will go on to develop AD and although the MCI group’s performance was not different than that of the control group, we wanted to learn if there were some patients with MCI that were impaired with letter fluency. We found, however, that none of the MCI patients had a F/A or S/A ratio that was one and one half standard deviations above the means for normal subjects, suggesting that this is not a meaningful, distinguishing characteristic of people with MCI and healthy controls. Pearson correlation coefficients were computed to assess the relationships between fluency with the letters F, A, S, as well as the F/A ratio with other cognitive measures such as the MMSE, components of the HVLT (trials 1, 2, 3, recall and discrimination index), BNT, and category fluency scores (see Table 3) in the patients with AD and MCI. Significant positive correlations exist between the letter “A” score and the scores on the
MMSE, HVLT trials, BNT, and category fluency. In addition, these correlations were higher than the corresponding relations seen with the letters “F” and “S” scores. The F/A ratio correlated negatively with MMSE, two HVLT trials, and the category fluency scores, with the category fluency score having the strongest correlation (r = .6, p = .002). A significant correlation also exists between the BNT and category fluency scores (r = .6, p = .002).
GENERAL DISCUSSION Whereas several studies have examined letter fluency in patients with different forms of dementia, these studies did not examine the differences between vowels such as the letter “A” and consonants, such as the letters “F” and “S”. The results of the present study demonstrate that patients with AD are more impaired in generating words that begin with the letter “A” than words that begin with the letters “F” and “S”. Although
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TABLE 3 Pearson Correlations of “F”, “A”, “S” and F/A ratio letter fluency measures and Mini Mental Status Examination (MMSE), Hopkins Verbal Learning Test (HVLT) three trials, Boston Naming Test (BNT), and Category Fluency (CF) scores in AD, MCI, and normal English speakers Variable
MMSE (r)
HVLT1 (r)
HVLT2 (r)
HVLT3 (r)
BNT (r)
CF (r)
F A S F/A ratio
.59** .73*** .70*** −.52*
.56** .73*** .61** −.49*
.54** .63** .49* −.37
.50* .64** .53** −.46*
.54** .56** .46* −.37
.63** .80*** .74*** −.60**
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*p < .05; **p < .01; ***p < .001.
NCs also show the same relative decrement, the difference between vowel and consonant fluency is significantly greater in patients with AD. In accordance with Terry et al.’s (1991) anatomic demonstration of the loss of connectivity in patients with AD, Bell et al. studied patients who had AD and demonstrated an impairment of spreading activation (Bell, Chenery, & Ingram, 2001). In regard to the spread of activation, the naming disorders associated with AD may be related to a reduced ability of their conceptual-semantic system to correctly select words from their phonological output lexicon, as mentioned in Kussmaul’s model recently modified by Heilman (see Figure 1). The BNT partially assesses these functional systems and while the ability of our participants with AD to perform this picture-naming test was impaired, no correlation was detected between these participants’ performance on the BNT and the F/A ratio. This suggests that the AD participants’ relatively greater impairment in producing words beginning with the letter “A” may not be solely related to these patients’ impairment in having their conceptualsemantic networks access their phonological lexicon. In contrast to letter fluency, semantic fluency was highly correlated with the BNT, and this correlation suggests that the semantic fluency test may better assess the functional interactions between this conceptual-semantic network and the phonological-lexical network than does the letter fluency test. Lichtheim posited that the center for motor programming of word sounds, or Broca’s area, has access to the areas of auditory word representations, or what is now termed the phonological lexicon (Lichtheim, 1885). Letter fluency relies on searching the phonological output lexicon and one means of searching this lexicon may be to produce the phoneme or the phonemes associated with the initial letter. Thus, the production of phonemes or the phonetic process may engage, at least in part, the left inferior frontal lobe, namely, Broca’s area. Support for this postulate comes from Birn et al. who performed fMRI studies with normal subjects during a letter fluency task and
showed that relative to the category fluency task, the letter fluency task was associated with increased activation in the left premotor/inferior frontal gyrus (Birn et al., 2010). These findings are consistent with the postulate that letter versus category fluency may, at least in part, use a different network when retrieving words, and that when searching for words during a letter fluency task, normal people produce the sound or sounds associated with the letter being tested. The speech-language, information processing model presented in Figure 1 does illustrate the major modules and their connections, but does not address the means by which these modules might interact. Roth et al. (2006) proposed a parallel-distributed processing model that specifies how representations in these modules are stored as well as how this stored information is processed by the links between these modules. A critical characteristic of this model is that knowledge is stored in these networks as neuronal patterns of connectivity and that these connectivity patterns are both within and between modules. During the acquisition of language and speech, the strength of this connectivity is altered so that the pattern of activity in one module influences the activity in the other modules. The density of connections between the phonological lexicon and phonetic networks that represent syllables beginning with a specific letter are stronger and greater in number with higher frequency first syllables than with lower frequency first syllables. The ability to access words that start with a specific letter sound may be contained in a pattern associator network that connects the phonetic-articulatory module to the module that contains the phonological word representations stored in the output lexicon. In AD, with the loss of dendritic and axonal connectivity, the least frequently used networks which are the weakest, should be the first to become dysfunctional and the earliest behavioral impairments should be those that are supported by these networks. The most common syllables in English are the consonant vowel (CV) combination and not those that start with
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the letter “A”. Thus, the more frequently used CV syllables that start with consonants such as “F” and “S” may have stronger synaptic connections with the units in the phonological lexicon that start with these letters than those that start with the letter “A”. In addition, whereas the letter “A” can represent eight different phonemes, there are fewer words that begin with each of the phonemes represented by the letter “A” than words that start with the phonemes associated with the consonants “F” and “S”. Since there are fewer words beginning with each of the eight phonemes associated with the letter “A”, it is possible that when attempting to find words that begin with the letter “A” the subjects will have to more frequently alter their phonemic search strategy and patients with dementia may also have problems with disengaging from a strategy. For example, Takeda et al., (2010) used the Wisconsin Card Sorting Test to investigate patients with early dementia and found that they were impaired in shifting set. Whereas none of our participants with MCI had a significant impairment in their relative productivity of words beginning with the letter “A”, four of the 11 MCI subjects had lower scores producing words that began with an “A” than with an “F” or “S”. Perhaps if repeatedly tested over time, a relative decrement in “A” fluency may be an early sign of developing AD. Future studies will have to test this possibility as well as determine if this deficit is specific for AD patients versus patients with other forms of dementia. Finally, some brief cognitive assessments, such as the Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005) test patients’ ability to perform “F” fluency. If instead the letter “A” is used, it may increase this assessment’s sensitivity.
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Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., & Hill, R. (1991). Physical basis of cognitive alterations in Alzheimer’s disease: Synapse loss is the major correlate of cognitive impairment. Annals of Neurology, 30(4), 572– 580. doi: 10.1002/ana.410300410 Tombaugh, T. N., Kozak, J., & Rees, L. (1999). Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Archives of
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Cognitive Neuroscience Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/pcns20
Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type a
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Hura Behforuzi , D. Brandon Burtis , John B. Williamson , Jennifer J. Stamps & Kenneth M. Heilman
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Department of Neurology, The Center for Neuropsychological Studies, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA b
Malcom Randall Veterans’ Affairs Medical Center, Geriatric Research, Education & Clinical Center, Gainesville, FL, USA c
Department of Neuroscience, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA Published online: 19 Nov 2013.
To cite this article: Hura Behforuzi, D. Brandon Burtis, John B. Williamson, Jennifer J. Stamps & Kenneth M. Heilman (2013) Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type, Cognitive Neuroscience, 4:3-4, 163-170, DOI: 10.1080/17588928.2013.854200 To link to this article: http://dx.doi.org/10.1080/17588928.2013.854200
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COGNITIVE NEUROSCIENCE, 2013 Vol. 4, Nos. 3–4, 163–170, http://dx.doi.org/10.1080/17588928.2013.854200
Impaired initial vowel versus consonant letter-word fluency in dementia of the Alzheimer type
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Hura Behforuzi1, D. Brandon Burtis1,2, John B. Williamson1,2, Jennifer J. Stamps3, and Kenneth M. Heilman1,2 1
Department of Neurology, The Center for Neuropsychological Studies, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA 2 Malcom Randall Veterans’ Affairs Medical Center, Geriatric Research, Education & Clinical Center, Gainesville, FL, USA 3 Department of Neuroscience, College of Medicine, McKnight Brain Institute, University of Florida, Gainesville, FL, USA Objectives: Early detection of Alzheimer disease (AD) is important. With AD, the loss of connectivity should first induce dysfunction in those representational networks with the weakest connectivity. Less frequently used networks have weaker connectivity. Given the letter “A” has more phonemes than the letters “F” and “S”, fewer words would begin with each of these “A” phonemes than with the “F” or “S” phonemes. We wanted to learn if patients with AD would produce fewer words starting with “A”. Methods: Patients with AD, mild cognitive impairment (MCI), and normal participants, were assessed with the Controlled Oral Word Association (COWA) test. Results: Compared to controls and MCI patients, AD patients produced relatively fewer words beginning with “A” than with “F” and “S”. Conclusions These results support the postulate that the less frequently used, and thus more weakly connected, phonetic-lexical networks are more sensitive to the degradation induced by AD.
Keywords: Alzheimer’s disease; Letter fluency; Vowel; Consonant.
The development of clinical instruments that enable the early detection of Alzheimer’s disease (AD) versus normal aging and other dementias remains a major objective of many studies. Patients with AD often have word finding difficulties, as assessed by naming to confrontation (e.g., Boston Naming Test) and word generation tests such as the Controlled Oral Word Association Test (COWA) (Benton, 1968), where participants are asked to generate words beginning with specified letters (e.g., F, A, and S)
in one minute, excluding proper names or numbers. When assessed with the COWA, patients with AD are often impaired (Henry, Crawford, & Phillips, 2004). In the semantic fluency test, participants are asked to produce words belonging to a given semantic category, such as animals, in 1 minute. Patients with AD are often more impaired on semantic fluency than phonemic fluency tasks (Henry et al., 2004). According to a revised Kussmaul’s model (Heilman, 2006; Kussmaul, 1877), there is a sequence of
Correspondence should be addressed to: Hura Behforuzi, Department of Neurology, Room L3-100, McKnight Brain Institute, 1149 Newell Drive, Gainesville, FL 32611, USA. E-mail: [email protected]fl.edu The study was supported by The State of Florida Memory Disorder Clinics.
The work of Brandon Burtis, DO, John B. Williamson, PhD and Kenneth M. Heilman, MD was authored as part of their official duties as Employees of the United States Government and the State of Florida and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. Hura Behforuzi MD and Jennifer Stamps BA, waive their right to assert copyright but not their right to be named as a co-authors.
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Figure 1. Diagrammatic model of the modular language processing network. In this diagrammatic model, speech comprehension is mediated by the 1-A-2-B-3 modular processing network, and in early Alzheimer’s disease (AD), comprehension is usually intact. Repetition, mediated by the 1-A-2-C-4-D-5-E-6 modular processing network, including the input and output phonological lexicons, is also usually intact in early AD. In contrast, naming is often impaired in early AD. The observation that most patients with early AD who have naming impairment can often recognize the pictures they are viewing would suggest that the visual recognition units have access to a relatively intact semantic-conceptual field (8-F-3). Thus, these patients’ naming impairment is probably related to a deficit in their ability to access the phonological output lexicon, which could be a deficit in either the 8-G-4 network or the 8-F-3-H-4 network. However, since most patients are also impaired at word finding during spontaneous speech, it is the latter network that is impaired. And since people can comprehend pictures they viewed, it is probably the connectivity between the semantic conceptual field and the output lexicon that is impaired (3-H-4). This postulate is supported by the observation that performance on the category-word fluency test, which is probably dependent on this same network (3-H-4), correlated with performance on the naming test. The impaired performance in letter-word fluency was not directly related to these patients impaired naming, suggesting that there is dysfunction in another network. Since most people use a phonetic search strategy, the 7-J-5-I-4 network may be used to activate the phonological output lexicon and the 4-D-5-E-6 network is used to produce these words. Since repetition is normal in patients with early AD, this latter production network (4-D-5-E-6) should be intact. Thus, these patients’ reduced ability to produce words that begin with the letter “A” is probably related to weakened connectivity in the 5-I-4 network.
processing stages in spontaneous speech production or naming which includes the development of the concepts with the activation of the semantic representations that are to be communicated (see Figure 1). Spoken words are combinations of sounds (phonemes) that are symbols of concepts. These sound symbols of concepts are stored in a phonological lexical (word sound) network. Thus, the next step is the selection of the phonological sequences (words) that are used to denote these concepts. Since these lexical-phonological sound representations of words need to be spoken, they are transformed into phonetic programs that control the position and movements of the articulatory apparatus. These action-movement programs allow people to produce the phoneme sequences that comprise spoken words. The naming disorder associated with AD has been attributed to
semantic-conceptual deficits as well as deficits of lexical access. Support of the lexical access deficit hypothesis comes from the study (Yoon et al., 2010) that used the Korean version of the Boston Naming Test in patients with early and moderate AD. Upon failure to name an item, either a semantic or phonemic cue was provided. These patients were significantly facilitated by phonemic cues, suggesting that the naming disorder associated with mild and moderate AD, is related to a deficit in lexical access. This hypothesis was also supported by Balthazar et al. who found that after phonemic cuing, there was no difference between the normal, MCI, and AD participants (Balthazar, Cendes, & Damasceno, 2008). When performing the COWA, people will often search their phonological lexicon for words that begin with the phoneme(s) (speech sounds) that this
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IMPAIRED INITIAL VOWEL LETTER-WORD FLUENCY IN ALZHEIMER’S
letter denotes. In English the initial letter “A” can represent one of the eight different first sounds including: “eɪ” (acorn), “æ” (apple), “ə” (about), “eə” (air), “ɑː” (arm), “ɔː” (authorize), “aɪ” (aisle), and “e” (aesthetic). In contrast, the consonant “F” at the beginning of words has only one phoneme and the consonant “S” has two phonemes (“s” (say) and “ʃ” (sure)). In the Oxford American Dictionary of Current English (Abate, 1999), there are approximately (~) 1960 words listed that begin with the letter “A” (~ 40 word/page and 49 pages), ~ 1730 words with the letter “F” (~ 40 words/page and 43 pages), and ~ 4680 with the letter “S” (~ 40 words/page and 117 pages). Assuming an equal number of words begin with each of the eight phonemes associated with the letter “A”, ~ 250 words would begin with each of these phonemes. In contrast, ~ 2340 words would begin with each of the two “S” phonemes and ~ 1730 with the single “F” phoneme. This would suggest that the phonemes associated with the letters “F” and “S” would be used more than six times as frequently as any one of the eight phonemes associated with the letter “A”. The individual sounds of a word are sequenced together to produce syllables. In languages such as English and Dutch, only 5% of the entire syllable inventory are needed to produce 80–85% of words (Levelt, Roelofs, & Meyer, 1999). Rather than assembling syllables, the so-called “mental syllabary” provides ready-made, phonological syllable units during phonetic encoding and words consisting of high frequency syllables are produced faster than words with low frequency syllables (Cholin, Levelt, & Schiller, 2006). This syllable frequency effect is most robust at the initial position of the word (Cholin et al., 2006) and it has been demonstrated that there are fewer “tip of the tongue” experiences for target words containing high-frequency first syllables relative to low-frequency syllables (Farrell & Abrams, 2011). The Hebbian hypothesis states, “neurons that fire together wire together” (Hebb, 1949). A corollary postulate is that less frequently used networks have weaker connectivity than more frequently used networks. The strength of connectivity should be reflected in the performance of normal subjects. Tombaugh et al. (1999) recruited a large group of normal participants (895) with a wide range of ages and years of education and found that the number of words produced in the COWA were significantly fewer with the letter “A” than the letters “F” and “S”. With the loss of neuronal connectivity found in AD (Terry et al., 1991), patients should first reveal more severe dysfunction in those representational
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networks with the weakest connectivity. According to this Hebbian concept, since the “F” and “S” phonemes would be more frequently used, the connectivity between the “F” and “S” phonetic representations and the words stored in the lexicon beginning with these letters would be stronger than the connectivity between the “A” phonetic representations and the words beginning with the eight different phonemes of “A”. Thus, the purpose of this study was to test the hypothesis that patients with AD, when compared to participants with MCI, as well as normal controls (NC), would be relatively more impaired in generating words beginning with the letter “A” versus words beginning with the letters “F” and “S”.
METHODS Participants 12 patients with probable AD, 11 with MCI and 22 NCs, all native English speakers, participated. AD and MCI subjects were evaluated by behavioral neurologists, and had neuropsychological testing as well as imaging and laboratory studies to rule out any treatable causes of cognitive decline. All of the AD participants met the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association for probable Alzheimer’s disease (McKhann et al., 1984). All MCI participants were diagnosed based on the National Institute on Aging and the Alzheimer’s Association recommendations (Albert et al., 2011). The NC participants were recruited prospectively and had no history of neurological or psychiatric disorders, head injury, substance abuse, or organ failure. This study was approved by the local IRB and the participants signed an informed consent. The AD patients (eight women and four men) had an age range of 54–83 (M = 72.42, SD = 8.17) with an average of 15.08 (SD = 3.02) years of education. The MCI patients (seven women and four men) had an age range of 50–85 (M = 68.18, SD = 10.75) with an average of 15.45 (SD = 3.11) years of education. The NC participants (11 women and 11 men) had an age range of 47– 86 (M = 72.91, SD = 8.15) with an average of 16.80 (SD = 3.51) years of education. Analysis of age and level of education revealed no significant differences between these three groups (age: F(2, 42) = 1.11, p = .33; education: F(2, 40) = 1.20, p = .31). One participant with MCI and two NC participants were left handed. All others were right handed. The mean
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significant difference across three groups (“F” fluency F(2, 42) = 13.85, p < .001, d = .62, “A” fluency F(2, 42) = 14.40, p < .001, d = .63, “S” fluency F(2, 42) = 11.58, p < .001, d = .58). However, Tukey post-hoc comparisons revealed significant differences between the participants with AD and MCI as well as between the participants with AD and normal controls. There was, however, no significant difference between patients with MCI and NCs (see Table 2). To learn if the patients with AD had a relatively greater impairment than the patients with MCI and the NC participants in producing words with the letter “A” compared to the letter “F”, we computed an F/A ratio and performed an ANOVA. This analysis revealed that the F/A ratio differed significantly between these groups, F(2, 42) = 4.28, p = .02, d = .40. Tukey posthoc comparisons of the three groups indicated that AD group (M = 2.39, 95% CI [.93, 3.85]) had a significantly higher F/A ratio than the MCIs (M = 1.02, 95% CI [.85, 1.19]), p = .02, and the NCs (M = 1.32, 95% CI [1.14, 1.50]), p = .04. A comparison between MCI group and NC group was not statistically significant (p > .05). We also performed a similar analysis using S/ A word production ratio and this also had a significant between-group difference, F(2, 42) = 5.97, p = .005, d = .47. Tukey post-hoc comparisons show that the AD group (M = 1.99, 95% CI [1.25, 2.72]) has a significantly higher S/A ratio than the MCIs (M = 1.06, 95% CI [.82, 1.30]), p = .005, and NCs (M = 1.37, 95% CI [1.22, 1.53]), p = .03. The MCI group was not different from the NC group (p > .05). Finally, the F/S ratio was examined (in AD patients with an average of 1.10 (SD = .65), in MCI group with an average of 1.08 (SD = .56) and in normal controls with an average of .98 (SD = .28)). This F/S ratio does not differ significantly between the groups, F(2, 42) = .29, p = .74. In summary, these results indicate that patients with AD have decreased fluency when performing the COWA with the letters “F”, “A”, and “S”. In addition, when attempting to generate words that
Mini Mental Status Examination (MMSE) score of the participants with AD was 20.50 (SD = 6.17, range: 10–29) and for the participants with MCI was 27.09 (SD = 2.30, range: 23–30).
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Apparatus and Procedures The participants were instructed to generate as many different words as possible in one minute that begin with the letter “F” without using proper names, numbers, or derivatives of the words they had previously used. After the trial with the letter “F”, they were tested in the same manner with the letter “A” and then the letter “S”. The examiner recorded the words generated by the participants verbatim. The scores for each phonemic fluency task were obtained excluding derivatives, proper names, and number errors, as well as words that were repeated. Output from the three letter trials were added together to obtain the total words produced. For the patients who were diagnosed with AD and MCI, the MMSE, the COWA test, Hopkins Verbal Learning Test (HVLT), Boston Naming Test (BNT), and category (animal) fluency test were performed as part of their routine clinical evaluation.
RESULTS The means and standard deviations for the letters “F”, “A”, and “S” for the participants with AD, MCI, and normal participants can be found in Table 1. Figure 2 demonstrates the relative performance of ADs, MCIs, and NCs on each fluency task. To learn if these three groups of participants (AD, MCI, NC) performed differently in the “F”, “A”, and “S” letter-word fluency tests, an analysis of variance (ANOVA) was used with the dependent variable being the number of correct words produced for each of these letters. This ANOVA for each letter fluency task showed a
TABLE 1 Means, standard deviations, and one-way ANOVA results for F/A ratio, S/A ratio, “F”, “A”, and “S” letter fluency scores in Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal controls (NC) – all native English speakers Groups Variable F/A ratio S/A ratio F A S
AD (M, SD) 2.39, 1.99, 7.33, 4.58, 7.67,
2.30 1.15 2.93 2.71 3.86
*p < .05; **p < .01; ***p < .001.
MCI (M, SD) 1.02, 1.06, 12.45, 12.73, 13.18,
.25 .36 3.32 4.14 4.42
NC (M, SD) 1.32, 1.37, 15.05, 12.09, 15.95,
.39 .34 4.85 4.95 5.37
ANOVA F(2, 42) 4.28* 5.97** 13.85*** 14.40*** 11.58***
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Figure 2.
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Relative performance of ADs, MCIs, and Normal Control English speakers on F, A, and S phonemic fluency tests.
TABLE 2 Post-hoc comparisons of “F”, “A”, and “S” phonemic fluency scores in AD, MCI, and normal controls – all native English speakers 95% Confidence interval Variable
Comparisons
Mean difference
Standard error
Lower bound
Upper bound
F
AD vs. MCI AD vs. NC MCI vs. NC AD vs. MCI AD vs. NC MCI vs. NC AD vs. MCI AD vs. NC MCI vs. NC
−5.12* −7.71** −2.59 −8.14** −7.50** .63 −5.51* −8.28** −2.77
1.70 1.46 1.50 1.78 1.53 1.58 2.00 1.72 1.77
−9.26 −11.27 −6.25 −12.48 −11.24 −3.20 −10.38 −12.47 −7.08
−.98 −4.15 1.07 −3.80 −3.78 4.48 −.65 −4.10 1.53
A
S
*p < .05; **p < .001.
begin with the letter “A” versus the letters “F” and “S”, the patients with AD were relatively more impaired. Some patients with MCI will go on to develop AD and although the MCI group’s performance was not different than that of the control group, we wanted to learn if there were some patients with MCI that were impaired with letter fluency. We found, however, that none of the MCI patients had a F/A or S/A ratio that was one and one half standard deviations above the means for normal subjects, suggesting that this is not a meaningful, distinguishing characteristic of people with MCI and healthy controls. Pearson correlation coefficients were computed to assess the relationships between fluency with the letters F, A, S, as well as the F/A ratio with other cognitive measures such as the MMSE, components of the HVLT (trials 1, 2, 3, recall and discrimination index), BNT, and category fluency scores (see Table 3) in the patients with AD and MCI. Significant positive correlations exist between the letter “A” score and the scores on the
MMSE, HVLT trials, BNT, and category fluency. In addition, these correlations were higher than the corresponding relations seen with the letters “F” and “S” scores. The F/A ratio correlated negatively with MMSE, two HVLT trials, and the category fluency scores, with the category fluency score having the strongest correlation (r = .6, p = .002). A significant correlation also exists between the BNT and category fluency scores (r = .6, p = .002).
GENERAL DISCUSSION Whereas several studies have examined letter fluency in patients with different forms of dementia, these studies did not examine the differences between vowels such as the letter “A” and consonants, such as the letters “F” and “S”. The results of the present study demonstrate that patients with AD are more impaired in generating words that begin with the letter “A” than words that begin with the letters “F” and “S”. Although
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TABLE 3 Pearson Correlations of “F”, “A”, “S” and F/A ratio letter fluency measures and Mini Mental Status Examination (MMSE), Hopkins Verbal Learning Test (HVLT) three trials, Boston Naming Test (BNT), and Category Fluency (CF) scores in AD, MCI, and normal English speakers Variable
MMSE (r)
HVLT1 (r)
HVLT2 (r)
HVLT3 (r)
BNT (r)
CF (r)
F A S F/A ratio
.59** .73*** .70*** −.52*
.56** .73*** .61** −.49*
.54** .63** .49* −.37
.50* .64** .53** −.46*
.54** .56** .46* −.37
.63** .80*** .74*** −.60**
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*p < .05; **p < .01; ***p < .001.
NCs also show the same relative decrement, the difference between vowel and consonant fluency is significantly greater in patients with AD. In accordance with Terry et al.’s (1991) anatomic demonstration of the loss of connectivity in patients with AD, Bell et al. studied patients who had AD and demonstrated an impairment of spreading activation (Bell, Chenery, & Ingram, 2001). In regard to the spread of activation, the naming disorders associated with AD may be related to a reduced ability of their conceptual-semantic system to correctly select words from their phonological output lexicon, as mentioned in Kussmaul’s model recently modified by Heilman (see Figure 1). The BNT partially assesses these functional systems and while the ability of our participants with AD to perform this picture-naming test was impaired, no correlation was detected between these participants’ performance on the BNT and the F/A ratio. This suggests that the AD participants’ relatively greater impairment in producing words beginning with the letter “A” may not be solely related to these patients’ impairment in having their conceptualsemantic networks access their phonological lexicon. In contrast to letter fluency, semantic fluency was highly correlated with the BNT, and this correlation suggests that the semantic fluency test may better assess the functional interactions between this conceptual-semantic network and the phonological-lexical network than does the letter fluency test. Lichtheim posited that the center for motor programming of word sounds, or Broca’s area, has access to the areas of auditory word representations, or what is now termed the phonological lexicon (Lichtheim, 1885). Letter fluency relies on searching the phonological output lexicon and one means of searching this lexicon may be to produce the phoneme or the phonemes associated with the initial letter. Thus, the production of phonemes or the phonetic process may engage, at least in part, the left inferior frontal lobe, namely, Broca’s area. Support for this postulate comes from Birn et al. who performed fMRI studies with normal subjects during a letter fluency task and
showed that relative to the category fluency task, the letter fluency task was associated with increased activation in the left premotor/inferior frontal gyrus (Birn et al., 2010). These findings are consistent with the postulate that letter versus category fluency may, at least in part, use a different network when retrieving words, and that when searching for words during a letter fluency task, normal people produce the sound or sounds associated with the letter being tested. The speech-language, information processing model presented in Figure 1 does illustrate the major modules and their connections, but does not address the means by which these modules might interact. Roth et al. (2006) proposed a parallel-distributed processing model that specifies how representations in these modules are stored as well as how this stored information is processed by the links between these modules. A critical characteristic of this model is that knowledge is stored in these networks as neuronal patterns of connectivity and that these connectivity patterns are both within and between modules. During the acquisition of language and speech, the strength of this connectivity is altered so that the pattern of activity in one module influences the activity in the other modules. The density of connections between the phonological lexicon and phonetic networks that represent syllables beginning with a specific letter are stronger and greater in number with higher frequency first syllables than with lower frequency first syllables. The ability to access words that start with a specific letter sound may be contained in a pattern associator network that connects the phonetic-articulatory module to the module that contains the phonological word representations stored in the output lexicon. In AD, with the loss of dendritic and axonal connectivity, the least frequently used networks which are the weakest, should be the first to become dysfunctional and the earliest behavioral impairments should be those that are supported by these networks. The most common syllables in English are the consonant vowel (CV) combination and not those that start with
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IMPAIRED INITIAL VOWEL LETTER-WORD FLUENCY IN ALZHEIMER’S
the letter “A”. Thus, the more frequently used CV syllables that start with consonants such as “F” and “S” may have stronger synaptic connections with the units in the phonological lexicon that start with these letters than those that start with the letter “A”. In addition, whereas the letter “A” can represent eight different phonemes, there are fewer words that begin with each of the phonemes represented by the letter “A” than words that start with the phonemes associated with the consonants “F” and “S”. Since there are fewer words beginning with each of the eight phonemes associated with the letter “A”, it is possible that when attempting to find words that begin with the letter “A” the subjects will have to more frequently alter their phonemic search strategy and patients with dementia may also have problems with disengaging from a strategy. For example, Takeda et al., (2010) used the Wisconsin Card Sorting Test to investigate patients with early dementia and found that they were impaired in shifting set. Whereas none of our participants with MCI had a significant impairment in their relative productivity of words beginning with the letter “A”, four of the 11 MCI subjects had lower scores producing words that began with an “A” than with an “F” or “S”. Perhaps if repeatedly tested over time, a relative decrement in “A” fluency may be an early sign of developing AD. Future studies will have to test this possibility as well as determine if this deficit is specific for AD patients versus patients with other forms of dementia. Finally, some brief cognitive assessments, such as the Montreal Cognitive Assessment (MoCA) (Nasreddine et al., 2005) test patients’ ability to perform “F” fluency. If instead the letter “A” is used, it may increase this assessment’s sensitivity.
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