The Rapid Naming Test: Development and initial validation in typically aging adults

The MINT Sprint 2.0: A picture naming test for detection of naming impairments in Alzheimer's disease and in preclinical AD

INTRODUCTION

Evidence on the onset of naming deficits in Alzheimer's disease (AD) is mixed. Some studies showed an early decline, but others did not. The present study introduces evidence from a novel naming test.

METHODS

Cognitively normal (n = 138), mild cognitive impairment (MCI; n = 21), and Alzheimer's disease (AD; n = 31) groups completed an expanded Multilingual Naming Test with a time-pressured administration procedure (MINT Sprint 2.0). Cerebrospinal fluid biomarkers classified participants as true controls (n = 61) or preclinical AD (n = 26).

RESULTS

Total correct MINT Sprint 2.0 scores exhibited good sensitivity and specificity (>0.85) for discriminating true controls from cognitively impaired (MCI/AD) groups and showed significant differences between true controls and preclinical AD groups. Time measurement did not improve classification, but percent resolved scores exhibited promise as an independent AD marker.

DISCUSSION

Naming deficits can be detected in the earliest stages of AD with tests and procedures designed for this purpose.

The MINT Sprint: Exploring a Fast Administration Procedure with an Expanded Multilingual Naming Test

OBJECTIVES

The present study examined if time-pressured administration of an expanded Multilingual Naming Test (MINT) would improve or compromise assessment of bilingual language proficiency and language dominance.

METHODS

Eighty Spanish-English bilinguals viewed a grid with 80 MINT-Sprint pictures and were asked to name as many pictures as possible in 3 min in each language in counterbalanced order. An Oral Proficiency Interview rated by four native Spanish-English bilinguals provided independent assessment of proficiency level. Bilinguals also self-rated their proficiency, completed two subtests of the Woodcock-Muñoz, and a speeded translation recognition test. We compared scores after 2 min, a first-pass through all the pictures, and a second-pass in which bilinguals were prompted to try to name skipped items.

RESULTS

The MINT Sprint and a subset score including original MINT items were highly correlated with Oral Proficiency Interview scores for predicting the degree of language dominance - matching or outperforming all other measures. Self-ratings provided weaker measures (especially of degree of balance - i.e., bilingual index scores) and did not explain any unique variance in measuring the degree of language dominance when considered together with second-pass naming scores. The 2-min scoring procedure did not improve and appeared not to hamper assessment of absolute proficiency level but prompting to try to name skipped items improved assessment of language dominance and naming scores, especially in the nondominant language.

CONCLUSIONS

Time-pressured rapid naming saves time without significantly compromising assessment of proficiency level. However, breadth of vocabulary knowledge may be as important as retrieval speed for maximizing the accuracy in proficiency assessment.

Neurocognitive health of older adults experiencing homelessness in Oakland, California

Background and objectives

The homeless population in the US is aging. Cognitive impairment is prevalent in this population, yet little is known about the neurologic etiologies of such impairment. Addressing this gap in knowledge is important because homeless older adults with cognitive impairment due to neurodegenerative disease may need lifelong tailored support to obtain and maintain housing. In this study, we characterized the neurocognitive health of a sample of adults who experienced homelessness for the first time after age 50 using gold standard behavioral neurology examination practices.

Methods

We conducted a descriptive cross-sectional study of older adults who first experienced homelessness after age 50. We recruited our sample purposively from an ongoing longitudinal cohort study of adults who were aged 50 and over and homeless when they entered the cohort. For this sub study, we enrolled a convenience sample from those who reported their first episode of homelessness after age 50. We did not exclude individuals based on history of substance use. Neurologists conducted a structured neurocognitive history intake, neurological examination, neuropsychological evaluation, and functional assessment between November 2020 and February 2021. We screened all participants for neurocognitive disorders using gold standard clinical research diagnostic criteria.

Results

We evaluated 25 participants, most were men (76%) and Black (84%), with a median age of 61 years. The most common neurocognitive complaints included deficits in recent episodic memory (n = 15, 60%), executive functions (n = 13, 52%), and behavior/mood, with apathy being the most common complaint (n = 20, 80%). Neuropsychological testing revealed a high prevalence of socioemotional deficits (n = 20, 80%). Common neurological examination deficits included difficulties with coordination, such as impaired Luria task (n = 16, 64%), signs of distal peripheral neuropathy (n = 8, 32%), anosmia/hyposmia (n = 4, 21%), and signs of mild Parkinsonism (n = 5, 20%). The most common diagnoses were MCI (n = 7, 28%), bvFTD (n = 4, 16%), AD (n = 4, 16%), and DLB (n = 2, 8%).

Discussion

Our findings suggest that neurocognitive concerns and examination deficits are common among older homeless adults. Specific neurocognitive disorders may be overrepresented in this population, particularly frontotemporal disorders. Longitudinal studies involving brain biomarkers are needed to characterize the neurocognitive health of this vulnerable population more precisely.

Examining Effectiveness of Rapid Automatized Naming and Reading Skills in Identifying Gifted Students

The aim of this study was to determine the effectiveness of Rapid Automatized Naming (RAN) and reading skills in distinguishing gifted students from their non-gifted peers. A total of 260 third grade students participated in the study. Of these students, 144 were gifted, while the others were not. As the data collection tools, personal information form, reading text, and the RAN test were used. The RAN test scores (time for naming shapes, colors, numbers, and letters), reading speed, and rate of accuracy in reading were the main variables of the research. In the research, correlational research was used as the method, logistic regression and MANOVA were used for the data analysis. The results of the study showed that all predictive variables (reading rate, reading accuracy, time for naming shapes and time for naming numbers) are significant predictors of giftedness, except for variables related to time for naming letters and colors, and that there was a statistically significant difference between gifted and non-gifted students in terms of the RAN scores regarding all sub-tests and reading variables. According to the research findings, it can be suggested that evidence on time for naming numbers and shapes, reading rate, and accuracy skills can be used as additional supporting components in distinguising gifted students from their non-gifted peers.

Norms for pictures of proper names: contrasting famous people and well-known places in younger and older adults

Proper names comprise a class of labels that arbitrarily nominate specific entities, such as people and places. Compared to common nouns, retrieving proper names is more challenging. Thus, they constitute good alternative semantic categories for psycholinguistic and neurocognitive research and intervention. The ability to retrieve proper names is known to decrease with aging. Likewise, their retrieval may differ across their different categories (e.g., people and places) given their specific associated knowledge. Therefore, proper names' stimuli require careful selection due to their high dependence on prior experiences. Notably, normative datasets for pictures of proper names are scarce and hardly have considered the influence of aging and categories. The current study established culturally adapted norms for proper names' pictures (N = 80) from an adult sample (N = 107), in psycholinguistic measures (naming and categorization scores) and evaluative dimensions (fame, familiarity, distinctiveness, arousal, and representational quality). These norms were contrasted across different categories (famous people and well-known places) and age groups (younger and older adults). Additionally, the correlations between all variables were examined. Proper names' pictures were named and categorized above chance and overall rated as familiar, famous, distinctive, and of high representational quality. Age effects were observed across all variables, except familiarity. Category effects were occasionally observed. Finally, the correlations between the psycholinguistic measures and all rated dimensions suggest the relevance of controlling for these dimensions when assessing naming abilities. The current norms provide a relevant aging-adapted dataset that is publicly available for research and intervention purposes.

Identification of the main components of spontaneous speech in primary progressive aphasia and their neural underpinnings using multimodal MRI and FDG-PET imaging

BACKGROUND

Primary progressive aphasia (PPA) is a clinical syndrome characterized by gradual loss of language skills. This study aimed to evaluate the diagnostic capacity of a connected speech task for the diagnosis of PPA and its variants, to determine the main components of spontaneous speech, and to examine their neural correlates.

METHODS

A total of 118 participants (31 patients with nfvPPA, 11 with svPPA, 45 with lvPPA, and 31 healthy controls) were evaluated with the Cookie Theft picture description task and a comprehensive language assessment protocol. Patients also underwent ¹⁸F-fluorodeoxyglucose positron emission tomography and magnetic resonance imaging studies. Principal component analysis and machine learning were used to evaluate the main components of connected speech and the accuracy of connected speech parameters for diagnosing PPA. Voxel-based analyses were conducted to evaluate the correlation between spontaneous speech components and brain metabolism, brain volumes, and white matter microstructure.

RESULTS

Discrimination between patients with PPA and controls was 91.67%, with 77.78% discrimination between PPA variants. Parameters related to speech rate and lexical variables were the most discriminative for classification. Three main components were identified: lexical features, fluency, and syntax. The lexical component was associated with ventrolateral frontal regions, while the fluency component was associated with the medial superior prefrontal cortex. Number of pauses was more related with the left parietotemporal region, while pauses duration with the bilateral frontal lobe. The lexical component was correlated with several tracts in the language network (left frontal aslant tract, left superior longitudinal fasciculus I, II, and III, left arcuate fasciculus, and left uncinate fasciculus), and fluency was linked to the frontal aslant tract.

CONCLUSION

Spontaneous speech assessment is a useful, brief approach for the diagnosis of PPA and its variants. Neuroimaging correlates suggested a subspecialization within the left frontal lobe, with ventrolateral regions being more associated with lexical production and the medial superior prefrontal cortex with speech rate.

Application of Machine Learning to Electroencephalography for the Diagnosis of Primary Progressive Aphasia: A Pilot Study

Background. Primary progressive aphasia (PPA) is a neurodegenerative syndrome in which diagnosis is usually challenging. Biomarkers are needed for diagnosis and monitoring. In this study, we aimed to evaluate Electroencephalography (EEG) as a biomarker for the diagnosis of PPA. Methods. We conducted a cross-sectional study with 40 PPA patients categorized as non-fluent, semantic, and logopenic variants, and 20 controls. Resting-state EEG with 32 channels was acquired and preprocessed using several procedures (quantitative EEG, wavelet transformation, autoencoders, and graph theory analysis). Seven machine learning algorithms were evaluated (Decision Tree, Elastic Net, Support Vector Machines, Random Forest, K-Nearest Neighbors, Gaussian Naive Bayes, and Multinomial Naive Bayes). Results. Diagnostic capacity to distinguish between PPA and controls was high (accuracy 75%, F1-score 83% for kNN algorithm). The most important features in the classification were derived from network analysis based on graph theory. Conversely, discrimination between PPA variants was lower (Accuracy 58% and F1-score 60% for kNN). Conclusions. The application of ML to resting-state EEG may have a role in the diagnosis of PPA, especially in the differentiation from controls. Future studies with high-density EEG should explore the capacity to distinguish between PPA variants.