Lexical retrieval in discourse: an early indicator of Alzheimer's dementia

Language abnormalities in Alzheimer's disease indicate reduced informativeness

OBJECTIVE

This study aims to elucidate the cognitive underpinnings of language abnormalities in Alzheimer's Disease (AD) using a computational cross-linguistic approach and ultimately enhance the understanding and diagnostic accuracy of the disease.

METHODS

Computational analyses were conducted on language samples of 156 English and 50 Persian speakers, comprising both AD patients and healthy controls, to extract language indicators of AD. Furthermore, we introduced a machine learning-based metric, Language Informativeness Index (LII), to quantify empty speech.

RESULTS

Despite considerable disparities in surface structures between the two languages, we observed consistency across language indicators of AD in both English and Persian. Notably, indicators of AD in English resulted in a classification accuracy of 90% in classifying AD in Persian. The substantial degree of transferability suggests that the language abnormalities of AD do not tightly link to the surface structures specific to English. Subsequently, we posited that these abnormalities stem from impairments in a more universal aspect of language production: the ability to generate informative messages independent of the language spoken. Consistent with this hypothesis, we found significant correlations between language indicators of AD and empty speech in both English and Persian.

INTERPRETATION

The findings of this study suggest that language impairments in AD arise from a deficit in a universal aspect of message formation rather than from the breakdown of language-specific morphosyntactic structures. Beyond enhancing our understanding of the psycholinguistic deficits of AD, our approach fosters the development of diagnostic tools across various languages, enhancing health equity and biocultural diversity.

Variability in Vowel Space in Parkinson's Disease: Associations With Cognitive and Motor Impairment

PURPOSE

People with Parkinson's disease (PwP) typically experience impairments in vowel articulation; however, less is known about how this measure varies with speech task type and clinical characteristics such as cognitive impairment. We characterized vowel space in PwP with and without mild cognitive impairment (MCI) comparing performance across phonation, reading, and picture description tasks. We evaluated associations between vowel space and cognitive impairment, as well as motor symptom severity to elucidate the factors contributing to variability in this acoustic measure.

METHOD

PwP (n = 48) and age-matched controls (n = 15) performed sustained phonation of corner vowels, a reading passage, and a picture description task (Cookie Theft picture). PwP participants were classified as with normal cognition (PD-NC) or MCI (PD-MCI), and motor symptoms were assessed using the Movement Disorders Society Unified Parkingson's Disease Rating Scale Part III (MDS-UPDRS Part III). Vowel articulation index (VAI) for each task and mean difference in VAI between tasks was compared between the groups using linear mixed models adjusted for age, sex, and education. The impact of motor severity was assessed by additionally adjusting the model for MDS-UPDRS Part III score.

RESULTS

In the adjusted mixed model, mean VAI was significantly lower in the PD-MCI group compared to the PD-NC group for all tasks. Within participants, adjusted mean differences demonstrated that all groups declined in VAI when sustained phonation was compared to either reading or picture description tasks. Adjustment for MDS-UPDRS Part III did not alter the results, suggesting no major association of motor impairment with vowel space variability within or between individuals or groups.

CONCLUSIONS

Variability in vowel space is impacted by cognitive impairment and speech task in PwP. These findings are relevant to the further development of speech markers in PwP and other neurogenerative diseases that impact both cognitive and motor functions.

Machine Learning Classification of Patients with Amnestic Mild Cognitive Impairment and Non-Amnestic Mild Cognitive Impairment from Written Picture Description Tasks

Individuals with Mild Cognitive Impairment (MCI), a transitional stage between cognitively healthy aging and dementia, are characterized by subtle neurocognitive changes. Clinically, they can be grouped into two main variants, namely patients with amnestic MCI (aMCI) and non-amnestic MCI (naMCI). The distinction of the two variants is known to be clinically significant as they exhibit different progression rates to dementia. However, it has been particularly challenging to classify the two variants robustly. Recent research indicates that linguistic changes may manifest as one of the early indicators of pathology. Therefore, we focused on MCI's discourse-level writing samples in this study. We hypothesized that a written picture description task can provide information that can be used as an ecological, cost-effective classification system between the two variants. We included one hundred sixty-nine individuals diagnosed with either aMCI or naMCI who received neurophysiological evaluations in addition to a short, written picture description task. Natural Language Processing (NLP) and a BERT pre-trained language model were utilized to analyze the writing samples. We showed that the written picture description task provided 90% overall classification accuracy for the best classification models, which performed better than cognitive measures. Written discourses analyzed by AI models can automatically assess individuals with aMCI and naMCI and facilitate diagnosis, prognosis, therapy planning, and evaluation.

Language Abnormalities in Alzheimer's Disease Arise from Reduced Informativeness: A Cross-Linguistic Study in English and Persian

INTRODUCTION

This research investigates the psycholinguistic origins of language impairments in Alzheimer's Disease (AD), questioning if these impairments result from language-specific structural disruptions or from a universal deficit in generating meaningful content.

METHODS

Cross-linguistic analysis was conducted on language samples from 184 English and 52 Persian speakers, comprising both AD patients and healthy controls, to extract various language features. Furthermore, we introduced a machine learning-based metric, Language Informativeness Index (LII), to quantify informativeness.

RESULTS

Indicators of AD in English were found to be highly predictive of AD in Persian, with a 92.3% classification accuracy. Additionally, we found robust correlations between the typical linguistic abnormalities of AD and language emptiness (low LII) across both languages.

DISCUSSION

Findings suggest AD linguistics impairments are attributed to a core universal difficulty in generating informative messages. Our approach underscores the importance of incorporating biocultural diversity into research, fostering the development of inclusive diagnostic tools.

Exploring Spoken Discourse and Its Neural Correlates in Women With Alzheimer's Disease With Low Levels of Education and Socioeconomic Status

PURPOSE

Early impairments in spoken discourse abilities have been identified in Alzheimer's disease (AD). However, the impact of AD on spoken discourse and the associated neuroanatomical correlates have mainly been studied in populations with higher levels of education, although preliminary evidence seems to indicate that socioeconomic status (SES) and level of education have an impact on spoken discourse. The purpose of this study was to analyze microstructural variables in spoken discourse in people with AD with low-to-middle SES and low level of education and to study their association with gray matter (GM) density.

METHOD

Nine women with AD and 10 matched (age, SES, and education) women without brain injury (WWBI) underwent a neuropsychological assessment, which included two spoken discourse tasks, and structural magnetic resonance imaging. Microstructural variables were extracted from the discourse samples using NILC-Metrix software. Brain density, measured by voxel-based morphometry, was compared between groups and then correlated with the differentiating microstructural variables.

RESULTS

The AD group produced a lower diversity of verbal time moods and fewer words and sentences than WWBI but a greater diversity of pronouns, prepositions, and lexical richness. At the neural level, the AD group presented a lower GM density bilaterally in the hippocampus, the inferior temporal gyrus, and the anterior cingulate gyrus. Number of words and sentences produced were associated with GM density in the left parahippocampal gyrus, whereas the diversity of verbal moods was associated with the basal ganglia and the anterior cingulate gyrus bilaterally.

CONCLUSIONS

The present findings are mainly consistent with previous studies conducted in groups with higher levels of SES and education, but they suggest that atrophy in the left inferior temporal gyrus could be critical in AD in populations with lower levels of SES and education. This research provides evidence on the importance of pursuing further studies including people with various SES and education levels.

WHAT IS ALREADY KNOWN ON THIS SUBJECT

Spoken discourse has been shown to be affected in Alzheimer disease, but most studies have been conducted on individuals with middle-to-high SES and high educational levels.

WHAT THIS STUDY ADDS

The study reports on microstructural measures of spoken discourse in groups of women in the early stage of AD and healthy women, with low-to-middle SES and lower levels of education.

CLINICAL IMPLICATIONS OF THIS STUDY

This study highlights the importance of taking into consideration the SES and education level in spoken discourse analysis and in investigating the neural correlates of AD.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24905046.

Language and communication rehabilitation in patients with schizophrenia: A narrative review

Language impairments often appear in patients with schizophrenia and are potential targets for rehabilitation. Clinical practice and research should be intimately connected. The aim was to perform a narrative review of the assessment and intervention tools that have been used for the rehabilitation of schizophrenia patients with language and communication impairments. Two types of tools, general and specific, were developed for both purposes. General tools include the Positive and Negative Syndrome Scale for assessment, and the Integrated Psychological Therapy for intervention. The specific tools used to evaluate language and communication impairments include the Scale for the Assessment of Thought, Language and Communication, the Formal Thought Disorder scales (for caregivers and patients), and the Thought and Language Disorder scale. The most recent language-specific intervention tools include the Cognitive Pragmatic Treatment, Conecta-2, Let's talk! Multimodal Speech-Gesture training, Speech Therapy Intervention Group, and PragmaCom. These tools primarily involve psychopathology/psychiatry, psychology, linguistics, speech and language therapy, and nursing. In conclusion, a wide range of assessment and intervention tools are available for the rehabilitation of language and communication impairments associated with schizophrenia. An integrative and interdisciplinary approach should always be considered for rehabilitation of language and communication in patients with schizophrenia throughout their lifetime.

Written discourse in diagnosis for acquired neurogenic communication disorders: current evidence and future directions

Purpose

We aimed to perform the first review of research focusing on written discourse performance in people with acquired neurogenic communication disorders. In studies from 2000 onward, we specifically sought to determine: (1) the differences between patient populations and control groups, (2) the differences between different patient populations, (3) longitudinal differences between patient populations, and (4) modality differences between spoken and written discourse performance.

Methods

We completed a thorough search on MEDLINE, Embase, Cochrane, APAPsycinfo, Web of Science, and Scopus databases. We identified studies that focus on written discourse performance in people with aphasia, primary progressive aphasia, mild cognitive impairment, and Alzheimer's disease.

Results

Nineteen studies were identified from the review of literature, some of which addressed more than one of our review questions. Fifteen studies included a comparison between clinical populations and controls. Six studies compared different characteristics of patient populations. Three studies reported changes over time in progressive disorders. Six studies targeted different modalities of discourse.

Conclusion

Differences in linguistic features by patient populations are not yet clear due to the limited number of studies and different measures and tasks used across the studies. Nevertheless, there is substantial evidence of numerous linguistic features in acquired neurogenic communication disorders that depart from those of healthy controls. Compared to the controls, people with aphasia tend to produce fewer words, and syntactically simpler utterances compared to the controls. People with Alzheimer's disease produce less information content, and this feature increases over time, as reported in longitudinal studies. Our review imparts additional information that written and spoken discourse provide unique insights into the cognitive and linguistic deficits experienced by people with aphasia, Alzheimer's disease, mild cognitive impairment and primary progressive aphasia and provide targets for treatment to improve written communication in these groups.

AI-based assessments of speech and language impairments in dementia

Recent advancements in the artificial intelligence (AI) domain have revolutionized the early detection of cognitive impairments associated with dementia. This has motivated clinicians to use AI-powered dementia detection systems, particularly systems developed based on individuals' and patients' speech and language, for a quick and accurate identification of patients with dementia. This paper reviews articles about developing assessment tools using machine learning and deep learning algorithms trained by vocal and textual datasets.

A comparison of techniques for deriving clustering and switching scores from verbal fluency word lists

Objective

To compare techniques for computing clustering and switching scores in terms of agreement, correlation, and empirical value as predictors of incident cognitive impairment (ICI).

Methods

We transcribed animal and letter F fluency recordings on 640 cases of ICI and matched controls from a national epidemiological study, amending each transcription with word timings. We then calculated clustering and switching scores, as well as scores indexing speed of responses, using techniques described in the literature. We evaluated agreement among the techniques with Cohen’s κ and calculated correlations among the scores. After fitting a base model with raw scores, repetitions, and intrusions, we fit a series of Bayesian logistic regression models adding either clustering and switching scores or speed scores, comparing the models in terms of several metrics. We partitioned the ICI cases into acute and progressive cases and repeated the regression analysis for each group.

Results

For animal fluency, we found that models with speed scores derived using the slope difference algorithm achieved the best values of the Watanabe–Akaike Information Criterion (WAIC), but with good net reclassification improvement (NRI) only for the progressive group (8.2%). For letter fluency, different models excelled for prediction of acute and progressive cases. For acute cases, NRI was best for speed scores derived from a network model (3.4%), while for progressive cases, the best model used clustering and switching scores derived from the same network model (5.1%). Combining variables from the best animal and letter F models led to marginal improvements in model fit and NRI only for the all-cases and acute-cases analyses.

Conclusion

Speed scores improve a base model for predicting progressive cognitive impairment from animal fluency. Letter fluency scores may provide complementary information.

GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models

Deep learning (DL) techniques involving fine-tuning large numbers of model parameters have delivered impressive performance on the task of discriminating between language produced by cognitively healthy individuals, and those with Alzheimer's disease (AD). However, questions remain about their ability to generalize beyond the small reference sets that are publicly available for research. As an alternative to fitting model parameters directly, we propose a novel method by which a Transformer DL model (GPT-2) pre-trained on general English text is paired with an artificially degraded version of itself (GPT-D), to compute the ratio between these two models' perplexities on language from cognitively healthy and impaired individuals. This technique approaches state-of-the-art performance on text data from a widely used "Cookie Theft" picture description task, and unlike established alternatives also generalizes well to spontaneous conversations. Furthermore, GPT-D generates text with characteristics known to be associated with AD, demonstrating the induction of dementia-related linguistic anomalies. Our study is a step toward better understanding of the relationships between the inner workings of generative neural language models, the language that they produce, and the deleterious effects of dementia on human speech and language characteristics.

Spatio-Semantic Graphs From Picture Description: Applications to Detection of Cognitive Impairment

Clinical assessments often use complex picture description tasks to elicit natural speech patterns and magnify changes occurring in brain regions implicated in Alzheimer's disease and dementia. As The Cookie Theft picture description task is used in the largest Alzheimer's disease and dementia cohort studies available, we aimed to create algorithms that could characterize the visual narrative path a participant takes in describing what is happening in this image. We proposed spatio-semantic graphs, models based on graph theory that transform the participants' narratives into graphs that retain semantic order and encode the visuospatial information between content units in the image. The resulting graphs differ between Cognitively Impaired and Unimpaired participants in several important ways. Cognitively Impaired participants consistently scored higher on features that are heavily associated with symptoms of cognitive decline, including repetition, evidence of short-term memory lapses, and generally disorganized narrative descriptions, while Cognitively Unimpaired participants produced more efficient narrative paths. These results provide evidence that spatio-semantic graph analysis of these tasks can generate important insights into a participant's cognitive performance that cannot be generated from semantic analysis alone.

A Systematic Review of Expressive and Receptive Prosody in People With Dementia

Purpose This review was designed to provide a systematic overview of prosody in people with a primary diagnosis of dementia (PwD) and evaluate the potential use of prosodic features for diagnosis of dementia. Method A systematic search of five databases was conducted using Medical Subject Headings and keywords. Studies included in the review were evaluated for their methodological quality using the modified Joanna Briggs Institute checklist. Results A total of 14 articles were identified as being relevant for this review. Among the 14 articles, the methodological quality ranged, with eight rated as weak, four rated as moderate, and two rated as strong. Ten of the 14 articles had people with Alzheimer's disease (AD) as participants, and the remaining four had people with frontotemporal dementia as participants. Four articles focused on receptive prosody, another six focused on expressive prosody, and the remaining four articles were investigations into both. The 14 articles presented inconsistent findings, and various tasks were used to measure prosodic features in PwD in the articles. Prosody was studied as a diagnostic tool for dementia in four of the articles, all of which were based on expressive prosody in individuals with AD. Among the four articles, three proposed the use of automatic speech analysis for diagnosis of AD. Conclusions This review demonstrates that prosody in PwD is an underinvestigated area. In particular, it was concerning that most articles were of weak methodological quality. Nevertheless, it was found that prosody may be a potential diagnostic tool for assessing dementia. More studies that replicate the existing studies and those with stronger methodology are needed to confirm that receptive and/or expressive prosody can be used for dementia diagnosis.

Coreferential processing in elderly with and without Alzheimer's disease

PURPOSE

To compare coreferential processing in elderly people with and without Alzheimer's disease in Brazilian Portuguese.

METHODS

Twelve elderly people without Alzheimer's (EA) and six elderly people with Alzheimer's disease (EWA) participated in the study. The Mini-Mental State Examination was used for cognitive screening of participants. Two experiments were performed using the self-monitored reading technique to analyze coreference processing. Each contained eight experimental phrases and 24 distracting phrases, one of them using repeated pronouns and names and the other using hyponyms and hypernyms. After reading, questions were asked related to the content of the sentences. The main variable of interest was reading time, measured after the presentation of anaphoric resuming.

RESULTS

In the first experiment, there were statistically significant results. The EA group processed the pronouns more quickly than repeated names. The volunteers of the EWA group were quicker in resuming repeated names. In the second experiment, the results show that the EA group showed preference for hypernyms in anaphoric resumption, whereas the EWA group did not present significant differences between conditions.

CONCLUSION

Elderly people without pathology processed pronouns and hypernyms more quickly compared to retrievals with repeated names and hyponyms, respectively, due to the smaller amount of semantic traits necessary to identify the antecedents in those conditions, as well as syntactic and discursive prominence. Elderly people with AD read names more readily than pronouns. There was no difference in anaphoric processing involving hyponyms and hypernyms, which may result from impaired working memory.

Lexical access in a bilingual speaker with dementia: Changes over time

In this article, we explore the naming skills of a bilingual English-Norwegian speaker diagnosed with Primary Progressive Aphasia, in each of his languages across three different speech contexts: confrontation naming, semi-spontaneous narrative (picture description), and conversation, and at two points in time: 12 and 30 months post diagnosis, respectively. The results are discussed in light of two main theories of lexical retrieval in healthy, elderly speakers: the Transmission Deficit Hypothesis and the Inhibitory Deficit Theory. Our data show that, consistent with the participant's premorbid use of and proficiency in the two languages, his performance in his L2 is lower than in his L1, but this difference diminishes as the disease progresses. This is the case across the three speech contexts; however, the difference is smaller in the narrative task, where his performance is very low in both languages already at the first measurement point. Despite his word finding problems, he is able to take active part in conversation, particularly in his L1 and more so at the first measurement point. In addition to the task effect, we find effects of word class, frequency, and cognateness on his naming skills. His performance seems to support the Transmission Deficit Hypothesis. By combining different tools and methods of analysis, we get a more comprehensive picture of the impact of the dementia on the speaker's languages from an intra-individual as well as an inter-individual perspective, which may be useful in research as well as in clinical practice.

Sentence comprehension in Slovak-speaking patients with Alzheimer's disease

BACKGROUND

According to some studies, sentence comprehension is diminished in Alzheimer's disease (AD) patients, but they differ on what underlies the sentence comprehension impairment. Sentence comprehension in AD patients has been studied mainly in the English language. It is less clear how patients with AD speaking a morphologically rich language with grammatical morphemes indicating case and through it even thematic roles process reversible sentences.

AIMS

To compare the comprehension of various syntactic constructions in Slovak-speaking AD patients and cognitively intact elderly people. We were concerned with the influence of the following aspects on sentence comprehension: its length, the order of thematic roles and the presence of a morphological cue placed on the first noun (or at the beginning of a sentence).

METHODS & PROCEDURES

We used our own Slovak test of sentence comprehension based on matching pictures to spoken sentences. These sentences contain transitive verbs and two nouns (person/animal), one functioning as a subject and the other as an object, which both can perform the action expressed by the verb. We assessed 62 healthy elderly people and two groups of AD patients. The first group consisted of 34 participants with a mild degree of AD and the other group of 43 participants with a moderate degree of AD.

OUTCOME & RESULTS

Statistical comparisons showed that the elderly controls were significantly better in the comprehension of simple active OVS (object-verb-subject word order) sentences and complex EO sentences (a centre-embedded relative clause with a relative pronoun substituting for an object) than patients with a mild degree of AD. In patients with a moderate degree of AD, comprehension of all tested sentence types was worse than in healthy elderly people. The results also indicated that even mild AD patients have more serious problems with processing sentences with non-canonical order of thematic roles regardless of a morphological cue at the beginning of a sentence.

CONCLUSION & IMPLICATIONS

The results point to diminished sentence comprehension in patients with AD. In the group of mild AD patients, the order of thematic roles played a significant role in their sentence comprehension. Even though the grammatical morphemes clearly code the functions of words in the Slovak language, mild AD patients do not process them in sentences with a non-canonical order of thematic roles at the same level as the healthy controls. Patients with moderate AD have significant problems even with the comprehension of sentences with a canonical order of thematic roles. These difficulties seem to be a consequence of insufficient resources for language processing.

Neural Correlates of Verbal Episodic Memory and Lexical Retrieval in Logopenic Variant Primary Progressive Aphasia

Objective: Logopenic variant primary progressive aphasia (lvPPA) is commonly associated with Alzheimer's disease (AD) pathology. But lvPPA patients display different cognitive and anatomical profile from the common clinical AD patients, whose verbal episodic memory is primarily affected. Reports of verbal episodic memory difficulty in lvPPA are inconsistent, and we hypothesized that their lexical retrieval impairment contributes to verbal episodic memory performance and is associated with left middle temporal gyrus atrophy.

Methods: We evaluated patients with lvPPA (n = 12) displaying prominent word-finding and repetition difficulties, and a demographically-matched cohort of clinical Alzheimer's disease (AD, n = 26), and healthy seniors (n = 16). We assessed lexical retrieval with confrontation naming and verbal episodic memory with delayed free recall. Whole-brain regressions related naming and delayed free recall to gray matter atrophy. Medial temporal lobe (MTL) subfields were examined using high in-plane resolution imaging.

Results: lvPPA patients had naming and delayed free recall impairments, but intact recognition memory. In lvPPA, delayed free recall was related to naming; both were associated with left middle temporal gyrus atrophy but not MTL atrophy. Despite cerebrospinal fluid evidence consistent with AD pathology, examination of MTL subfields revealed no atrophy in lvPPA. While AD patients displayed impaired delayed free recall, this deficit did not correlate with naming. Regression analyses related delayed free recall deficits in clinical AD patients to MTL subfield atrophy, and naming to left middle temporal gyrus atrophy.

Conclusion: Unlike amnestic AD patients, MTL subfields were not affected in lvPPA patients. Verbal episodic memory deficit observed in lvPPA was unlikely to be due to a hippocampal-mediated mechanism but appeared to be due to poor lexical retrieval. Relative sparing of MTL volume and intact recognition memory are consistent with previous reports of hippocampal-sparing variant cases of AD pathology, where neurofibrillary tangles are disproportionately distributed in cortical areas with relative sparing of the hippocampus. This suggests that AD neuropathology in lvPPA may originate in neuronal networks outside of the MTL, which deviates from the typical Braak staging pattern of spreading pathology in clinical AD.

Predicting probable Alzheimer's disease using linguistic deficits and biomarkers

BACKGROUND

The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this purpose, we developed different Machine Learning models on the DementiaBank language transcript clinical dataset, consisting of 99 patients with probable AD and 99 healthy controls.

RESULTS

Our models learned several syntactic, lexical, and n-gram linguistic biomarkers to distinguish the probable AD group from the healthy group. In contrast to the healthy group, we found that the probable AD patients had significantly less usage of syntactic components and significantly higher usage of lexical components in their language. Also, we observed a significant difference in the use of n-grams as the healthy group were able to identify and make sense of more objects in their n-grams than the probable AD group. As such, our best diagnostic model significantly distinguished the probable AD group from the healthy elderly group with a better Area Under the Receiving Operating Characteristics Curve (AUC) using the Support Vector Machines (SVM).

CONCLUSIONS

Experimental and statistical evaluations suggest that using ML algorithms for learning linguistic biomarkers from the verbal utterances of elderly individuals could help the clinical diagnosis of probable AD. We emphasise that the best ML model for predicting the disease group combines significant syntactic, lexical and top n-gram features. However, there is a need to train the diagnostic models on larger datasets, which could lead to a better AUC and clinical diagnosis of probable AD.

Word retrieval in picture descriptions produced by individuals with Alzheimer's disease

What can tests of single-word production tell us about word retrieval in connected speech? We examined this question in 20 people with Alzheimer's disease (AD) and in 20 cognitively intact individuals. All participants completed tasks of picture naming and semantic fluency and provided connected speech through picture descriptions. Picture descriptions were analyzed for total word output, percentages of content words, percentages of nouns, and percentages of pronouns out of all words, type-token ratio of all words and type-token ratio of nouns alone, mean frequency of all words and mean frequency of nouns alone, and mean word length. Individuals with AD performed worse than did cognitively intact individuals on the picture naming and semantic fluency tasks. They also produced a lower proportion of content words overall, a lower proportion of nouns, and a higher proportion of pronouns, as well as more frequent and shorter words on picture descriptions. Group differences in total word output and type-token ratios did not reach significance. Correlations between scores on tasks of single-word retrieval and measures of retrieval in picture descriptions emerged in the AD group but not in the control group. Scores on a picture naming task were associated with difficulties in word retrieval in connected speech in AD, while scores on a task of semantic verbal fluency were less useful in predicting measures of retrieval in context in this population.

Neuroanatomical foundations of naming impairments across different neurologic conditions

The ability to name objects or abstract entities is an essential feature of speech and language, being commonly considered a central component of normal neurologic function. For this reason, the bedside testing of naming performance is part of the neurologic examination, especially since naming impairments can signify the early onset of a progressive disease or the occurrence of a more established problem. Modern neuroscience research suggests that naming relies on specific and distributed networks that operate in concert to support various processing stages, spanning from object recognition to spoken words. Likewise, studies evaluating the types of naming impairments in patients with neurologic conditions have contributed to the understanding of acquired forms of naming impairments and the underlying stages during normal language processing. In this article, we review the neurobiological mechanisms supporting naming, with a focus on the clinical application of these concepts. We provide an overview of the stages of cognitive processing that are hypothesized to support naming. For each stage, we explore the evidence revealing its neural basis, drawing parallels to clinical syndromes that commonly disrupt each stage. We review the patterns of naming impairment across various neurologic conditions, including classic language disorders, such as poststroke aphasia or primary progressive aphasia, as well as other diseases where language impairments may be subtle but helpful for the appropriate diagnosis. In this context, we provide a structured and practical guide for the bedside naming assessments rooted in modern neuroscience, aimed at supporting the evaluation and diagnosis of neurologic conditions that affect language.

Changes in communication of Deaf people with dementia: A thematic interview with a close family member

BACKGROUND AND AIM

Learning about changes in communication of Deaf with dementia (DWD) is important in order to improve services and support DWD and their families. We explored family members' views on the changes in communication DWD have and the ways communication was adapted due to progression of dementia.

METHODS

A qualitative content analysis of thematic interviews that were conducted with eight close family members of DWD.

RESULTS

With decreasing vocabulary and increasing sign-finding difficulties, conversations became poorer, and DWD tended to diverge from the topic. Nonverbal communication became more important as the verbal communication abilities of DWD deteriorated, and the adult children took a more active role by taking initiative and guiding conversations.

CONCLUSION

DWD seem to go through similar changes in communication as hearing people with dementia. Adult children of DWD need to get used to interpreting and assisting their parent's communication through different phases of dementia.