Language performance in Alzheimer's disease and mild cognitive impairment: a comparative review

Investigating sentence processing and working memory in patients with mild Alzheimer and elderly people

INTRODUCTION

Linguistic disorders are one of the common problems in Alzheimer's disease, which in recent years has been considered as one of the key parameters in the diagnosis of Alzheimer (AD). Given that changes in sentence processing and working memory and the relationship between these two activities may be a diagnostic parameter in the early and preclinical stages of AD, the present study examines the comprehension and production of sentences and working memory in AD patients and healthy aged people.

METHODS

Twenty-five people with mild Alzheimer's and 25 healthy elderly people participated in the study. In this study, we used the digit span to evaluate working memory. Syntactic priming and sentence completion tasks in canonical and non-canonical conditions were used for evaluating sentence production. We administered sentence picture matching and cross-modal naming tasks to assess sentence comprehension.

RESULTS

The results of the present study revealed that healthy elderly people and patients with mild Alzheimer's disease have a significant difference in comprehension of relative clause sentences (P <0.05). There was no significant difference between the two groups in comprehension of simple active, simple active with noun phrase and passive sentences (P> 0.05). They had a significant difference in auditory and visual reaction time (P <0.05). Also there was a significant difference between the two groups in syntactic priming and sentence completion tasks. However, in non-canonical condition of sentence completion, the difference between the two groups was not significant (P> 0.05).

CONCLUSION

The results of the present study showed that the mean scores related to comprehension, production and working memory in people with mild Alzheimer's were lower than healthy aged people, which indicate sentence processing problems at this level of the disease. People with Alzheimer have difficulty comprehending and producing complex syntactic structures and have poorer performance in tasks that required more memory demands. It seems that the processing problems of these people are due to both working memory and language problems, which are not separate from each other and both are involved in.

The Hong Kong Grocery Shopping Dialog Task (HK-GSDT): A Quick Screening Test for Neurocognitive Disorders

The Hong Kong Grocery Shopping Dialog Task (HK-GSDT) is a short and easy-to-administer cognitive test developed for quickly screening neurocognitive disorders (NCDs). In the test, participants are instructed to do a hypothetical instrumental activity of daily living task of purchasing ingredients for a dish from a grocery store and verbally describe the specific shopping procedures. The current study aimed to validate the test with a sample of 545 Hong Kong older adults (58.8% female; aged 73.4 ± 8.37 years), including 464 adults with normal cognitive function, 39 with mild NCD, and 42 with major NCD. Demographic characteristics (i.e., sex, age, education) and clinical diagnosis of cognitive states (i.e., major NCD, mild NCD, and normal aging) were collected. Cognitive functioning was measured using the HK-GSDT and several standardized NCD-screening tests. The results showed good reliability (i.e., internal consistency) and structural validity in the HK-GSDT. It discriminated among different cognitive conditions, particularly between major NCDs and the other conditions, as effectively as did the existing standardized neurocognitive tests (e.g., Montreal Cognitive Assessment, Hong Kong List Learning Test). Moreover, the HK-GSDT explained additional variance of cognitive condition on top of those standardized neurocognitive tests. These results indicate that the HK-GSDT can be used alone, or in combination with other tests, to screen for NCDs.

The functional connectivity of language network across the life span: Disentangling the effects of typical aging from Alzheimer's disease

Language is usually characterized as the most preserved cognitive function during typical aging. Several neuroimaging studies have shown that healthy aging is characterized by inter-network compensation which correlates with better language performance. On the contrary, language deficits occur early in the course of Alzheimer's disease (AD). Therefore, this study compares young participants, healthy older participants, and prodromal AD participants, to characterize functional connectivity changes in language due to healthy aging or prodromal AD. We first compared measures of integrated local correlations (ILCs) and fractional amplitude of low-frequency oscillations (fALFFs) in language areas. We showed that both groups of older adults had lower connectivity values within frontal language-related areas. In the healthy older group, higher integrated local correlation (ILC) and fALFF values in frontal areas were positively correlated with fluency and naming tasks. We then performed seed-based analyses for more precise discrimination between healthy aging and prodromal AD. Healthy older adults showed no functional alterations at a seed-based level when the seed area was not or only slightly impaired compared to the young adults [i.e., inferior frontal gyrus (IFG)], while prodromal AD participants also showed decreased connectivity at a seed-based level. On the contrary, when the seed area was similarly impaired in healthy older adults and prodromal AD participants on ILC and fALFF measures, their connectivity maps were also similar during seed-to-voxel analyses [i.e., superior frontal gyrus (SFG)]. Current results show that functional connectivity measures at a voxel level (ILC and fALFF) are already impacted in healthy aging. These findings imply that the functional compensations observed in healthy aging depend on the functional integrity of brain areas at a voxel level.

Predicting Scores on the Mini-Mental State Examination (MMSE) from Spontaneous Speech

The aim of this study was to examine the relationship between language components, such as lexical density, length, and content in terms of “Time, Space and Action”, with MMSE scores. For this reason, a group of 33 older participants, without a diagnosis of dementia, was examined, providing information regarding recent and future events. Participants with higher MMSE scores showed higher lexical density, speech length, as well as number of tokens related to Time, Place and Action in their speech. However, these differences only reach the statistical level for lexical density when participants were divided into two groups (MCI and healthy controls). Word frequency was lower for participants with MCI but this difference was not statistically significant. Lastly, lexical density was positively correlated with MMSE scores and predicted MMSE scores. These results could be of interest at the applied level in the screening of MCI.

Regression-Based Normative Data for Independent and Cognitively Active Spanish Older Adults: Verbal Fluency Tests and Boston Naming Test

An increased cognitive reserve is associated with changes in the pattern of cognitive decline during aging. Thus, normative data adapted to the characteristics of the target population are needed to reduce the possibility of false diagnoses. The aim of this work was to develop normative data for the Phonemic Verbal Fluency test, the Semantic Verbal Fluency test and the Boston Naming Test (BNT).

METHOD

Regression-based normative data were calculated from a sample of 118 non-depressed, cognitively active, independent community-dwelling adults aged 55 or older (64.4% women) from SABIEX (University for Seniors at the Universidad Miguel Hernández de Elche). Raw scores were regressed on age, sex, and education.

RESULTS

The effects of age and education varied across neuropsychological measures. No effect of sex was found in any of the tests assessed. Statistically significant differences were found in the proportion of low scores using SABIEX or population-based normative datasets. The level of agreement identifying individuals labeled as showing one or more low scores was only fair-to-good.

CONCLUSIONS

Normative data obtained from the general population might not be sensitive to identify low scores in cognitively active older adults, increasing the risk of misdiagnoses. A friendly calculator is available for neuropsychological assessment.

The therapeutic efficacy of transcranial magnetic stimulation in managing Alzheimer’s disease: A systemic review and meta-analysis

Background

Repetitive Transcranial Magnetic Stimulation (rTMS) is widely used to treat Alzheimer’s Disease. However, the effect of rTMS is still controversial. The purpose of the present study is to evaluate the effectiveness of rTMS on cognitive performance of AD patients.

Methods

We systematically searched relevant literatures in four major databases - PubMed, EMBASE, Web of Science, and the Cochrane Central Register of Controlled Trials [Central] before 28th April 2022. Both randomized controlled trials and cross-section studies that compared the therapeutic effect of rTMS with blank control or sham stimuli were included.

Results

A total of 14 studies involving 513 AD patients were finally included for meta-analysis. It was found that rTMS significantly improved global cognitive function (SMD = 0.24, 95%CI, 0.12 to 0.36, P = 0.0001) and daily living ability (IADL: SMD = 0.64, 95%CI, 0.21to 1.08, P = 0.004) in patients with AD, but did not show improvement in language, memory, executive ability, and mood. In further analyses, rTMS at 10 Hz, on a single target with 20 sessions of treatment was shown to produce a positive effect. In addition, improvement in cognitive functions lasted for at least 6 weeks (SMD = 0.67, 95%CI, 0.05 to 1.30,P = 0.04).

Conclusion

rTMS can improve the global cognition and daily living ability of AD patients. In addition, attention should be paid to the safety of rTMS in AD patients with seizures. Given the relatively small sample size, our results should be interpreted with caution.

Neuropsychological networks in cognitively healthy older adults and dementia patients

Neuropsychological tests have commonly been used to determine the organization of cognitive functions by identifying latent variables. In contrast, an approach which has seldom been employed is network analysis. We characterize the network structure of a set of representative neuropsychological test scores in cognitively healthy older adults and MCI and dementia patients using network analysis. We employed the neuropsychological battery from the National Alzheimer's Coordinating Center which included healthy controls (n = 7623), mild cognitive impairment patients (n = 5981) and dementia patients (n = 2040), defined according to the Clinical Dementia Rating. The results showed that, according to several network analysis measures, the most central cognitive function is executive function followed by attention, language, and memory. At the test level, the most central test was the Trail Making Test B, which measures cognitive flexibility. Importantly, these results and most other network measures, such as the community organization and graph representation, were similar across the three diagnostic groups. Therefore, network analysis can help to establish a ranking of cognitive functions and tests based on network centrality and suggests that this organization is preserved in dementia. Central nodes might be particularly relevant both from a theoretical and clinical point of view, as they are more associated with other nodes, and their disruption is likely to have a larger effect on the overall network than peripheral nodes. The present analysis may provide a proof of principle for the application of network analysis to cognitive data.

Identifying neurocognitive disorder using vector representation of free conversation

In recent years, studies on the use of natural language processing (NLP) approaches to identify dementia have been reported. Most of these studies used picture description tasks or other similar tasks to encourage spontaneous speech, but the use of free conversation without requiring a task might be easier to perform in a clinical setting. Moreover, free conversation is unlikely to induce a learning effect. Therefore, the purpose of this study was to develop a machine learning model to discriminate subjects with and without dementia by extracting features from unstructured free conversation data using NLP. We recruited patients who visited a specialized outpatient clinic for dementia and healthy volunteers. Participants’ conversation was transcribed and the text data was decomposed from natural sentences into morphemes by performing a morphological analysis using NLP, and then converted into real-valued vectors that were used as features for machine learning. A total of 432 datasets were used, and the resulting machine learning model classified the data for dementia and non-dementia subjects with an accuracy of 0.900, sensitivity of 0.881, and a specificity of 0.916. Using sentence vector information, it was possible to develop a machine-learning algorithm capable of discriminating dementia from non-dementia subjects with a high accuracy based on free conversation.

Cognitive Writing Process Characteristics in Alzheimer's Disease

In this article, we explore if the observation of writing behavior can assist in the screening and follow-up of mild cognitive impairment (MCI) and mild dementia due to Alzheimer's disease (AD). To this end, we examined the extent to which overall writing process measures and pausing behavior during writing differed between 15 cognitively impaired patients and 15 age- and gender-matched healthy controls. Participants completed two typed picture description tasks that were registered with Inputlog, a keystroke logging program that captures keyboard activity during text production. The following variables were analyzed with mixed-effects models: time on task; number of characters, pauses and Pause-bursts per minute; proportion of pause time; duration of Pause-bursts; and pause time between words. For pause time between words, also the effect of pauses preceding specific word categories was analyzed. Results showed a main effect of group on all variables. In addition, for pause time between words a main effect of part-of-speech was found as well. Results indicate that writing process analysis can possibly serve as a supplementary tool for the screening and follow-up of AD.

Picture-naming test for a linguistically diverse population with cognitive impairment and dementia

BACKGROUND

Picture-naming tests (PNTs) evaluate linguistic impairment in dementia due to semantic memory impairment, impaired lexical retrieval or perceptual deficits. They also assess the decline in naming impairment at various stages of dementia and mild cognitive impairment (MCI) that occurs due to progressive cognitive impairment. With the increasing numbers of people with dementia globally, it is necessary to have validated naming tests and norms that are culturally and linguistically appropriate.

AIMS

In this cross-sectional study we harmonized a set of 30 images applicable to the Indian context across five languages and investigated the picture-naming performance in patients with MCI and dementia.

METHODS & PROCEDURES

A multidisciplinary expert group formed by the Indian Council of Medical Research (ICMR) collaborated towards developing and adapting a picture naming test (PNT) known as the ICMR-PNT in five Indian languages: Hindi, Bengali, Telugu, Kannada and Malayalam. Based on cross-cultural adaptation guidelines and item-wise factor analysis and correlations established separately across five languages, the final version of the ICMR-PNT test was developed. A total of 368 controls, 123 dementia and 128 MCI patients were recruited for the study. Psychometric properties of the adapted version of the ICMR-PNT were examined, and sensitivity and specificity were examined.

OUTCOMES & RESULTS

The ICMR-PNT scores in all languages combined were higher in controls compared with patients with dementia and MCI (F_{2, 615} = 139.85; p < 0.001). Furthermore, PNT scores for MCI was higher in comparison with patients with dementia in all languages combined (p < 0.001). The area under the curve across the five languages ranged from 0.81 to 1.00 for detecting dementia. There was a negative correlation between Clinical Dementia Rating (CDR) and ICMR-PNT scores and a positive correlation between Addenbrooke's Cognitive Examination-III (ACE-III) and ICMR-PNT scores in control and patient groups.

CONCLUSIONS & IMPLICATIONS

The ICMR-PNT was developed by following cross-cultural adaptation guidelines and establishing correlations using item-wise factor analysis across five languages. This adapted PNT was found to be a reliable tool when assessing naming abilities effectively in mild to moderate dementia in a linguistically diverse context.

WHAT THIS PAPER ADDS

What is already known on this subject Picture-naming evaluates language impairment linked to naming difficulties due to semantic memory, lexical retrieval or perceptual disturbances. As a result, picture naming tests (PNTs) play an important role in the diagnosis of dementia. In a heterogeneous population such as India, there is a need for a common PNT that can be used across the wide range of languages. What this study adds to existing knowledge PNTs such as the Boston Naming Test (BNT) were developed for the educated, mostly English-speaking, Western populations and are not appropriate for use in an Indian context. To overcome this challenge, a PNT was harmonized in five Indian languages (Hindi, Bengali, Telugu, Kannada and Malayalam) and we report the patterns of naming difficulty in patients with MCI and dementia. The ICMR-PNT demonstrated good diagnostic accuracy when distinguishing patients with mild to moderate dementia from cognitively normal individuals. What are the potential or actual clinical implications of this work? With the growing number of persons suffering from Alzheimer's disease and other forms of dementia around the world, its critical to have culturally and linguistically relevant naming tests and diagnosis. This validated ICMR-PNT can be used widely as a clinical tool to diagnose dementia and harmonize research efforts across diverse populations.

ROCK and PDE-5 Inhibitors for the Treatment of Dementia: Literature Review and Meta-Analysis

Dementia is a disease in which memory, thought, and behavior-related disorders progress gradually due to brain damage caused by injury or disease. It is mainly caused by Alzheimer’s disease or vascular dementia and several other risk factors, including genetic factors. It is difficult to treat as its incidence continues to increase worldwide. Many studies have been performed concerning the treatment of this condition. Rho-associated kinase (ROCK) and phosphodiesterase-5 (PDE-5) are attracting attention as pharmacological treatments to improve the symptoms. This review discusses how ROCK and PDE-5 affect Alzheimer’s disease, vascular restructuring, and exacerbation of neuroinflammation, and how their inhibition helps improve cognitive function. In addition, the results of the animal behavior analysis experiments utilizing the Morris water maze were compared through meta-analysis to analyze the effects of ROCK inhibitors and PDE-5 inhibitors on cognitive function. According to the selection criteria, 997 publications on ROCK and 1772 publications on PDE-5 were screened, and conclusions were drawn through meta-analysis. Both inhibitors showed good improvement in cognitive function tests, and what is expected of the synergy effect of the two drugs was confirmed in this review.

Temporal speech parameters detect mild cognitive impairment in different languages: validation and comparison of the Speech-GAP Test® in English and Hungarian

BACKGROUND

The development of automatic speech recognition (ASR) technology allows the analysis of temporal (time-based) speech parameters characteristic of mild cognitive impairment (MCI). However, no information has been available on whether the analysis of spontaneous speech can be used with the same efficiency in different language environments.

OBJECTIVE

The main goal of this international pilot study is to address the question whether the Speech-Gap Test® (S-GAP Test®), previously tested in the Hungarian language, is appropriate for and applicable to the recognition of MCI in other languages such as English.

METHOD

After an initial screening of 88 individuals, English-speaking (n = 33) and Hungarian-speaking (n = 33) participants were classified as having MCI or as healthy controls (HC) based on Petersen's criteria. Speech of each participant was recorded via a spontaneous speech task. 15 temporal parameters were determined and calculated by means of ASR.

RESULTS

Seven temporal parameters in the English-speaking sample and 5 in the Hungarian-speaking sample showed significant differences between the MCI and the HC group. Receiver operating characteristics (ROC) analysis clearly distinguished the English-speaking MCI cases from the HC group based on speech tempo and articulation tempo with 100% sensitivity, and on three more temporal parameters with high sensitivity (85.7%). In the Hungarian-speaking sample, the ROC analysis showed similar sensitivity rates (92.3%).

CONCLUSION

The results of this study in different native-speaking populations suggest that changes in acoustic parameters detected by the S-GAP Test® might be present across different languages.

Hemispheric Cortical, Cerebellar and Caudate Atrophy Associated to Cognitive Impairment in Metropolitan Mexico City Young Adults Exposed to Fine Particulate Matter Air Pollution

Exposures to fine particulate matter PM_2.5 are associated with Alzheimer's, Parkinson's (AD, PD) and TDP-43 pathology in young Metropolitan Mexico City (MMC) residents. High-resolution structural T1-weighted brain MRI and/or Montreal Cognitive Assessment (MoCA) data were examined in 302 volunteers age 32.7 ± 6.0 years old. We used multivariate linear regressions to examine cortical surface area and thickness, subcortical and cerebellar volumes and MoCA in ≤30 vs. ≥31 years old. MMC residents were exposed to PM_2.5 ~ 30.9 µg/m³. Robust hemispheric differences in frontal and temporal lobes, caudate and cerebellar gray and white matter and strong associations between MoCA total and index scores and caudate bilateral volumes, frontotemporal and cerebellar volumetric changes were documented. MoCA LIS scores are affected early and low pollution controls ≥ 31 years old have higher MoCA vs. MMC counterparts (p ≤ 0.0001). Residency in MMC is associated with cognitive impairment and overlapping targeted patterns of brain atrophy described for AD, PD and Fronto-Temporal Dementia (FTD). MMC children and young adult longitudinal studies are urgently needed to define brain development impact, cognitive impairment and brain atrophy related to air pollution. Identification of early AD, PD and FTD biomarkers and reductions on PM2.5 emissions, including poorly regulated heavy-duty diesel vehicles, should be prioritized to protect 21.8 million highly exposed MMC urbanites.

Potential Mechanisms Underlying Resistance to Dementia in Non-Demented Individuals with Alzheimer's Disease Neuropathology

Alzheimer’s disease (AD) is the most common form of dementia and typically characterized by the accumulation of amyloid-β plaques and tau tangles. Intriguingly, there also exists a group of elderly which do not develop dementia during their life, despite the AD neuropathology, the so-called non-demented individuals with AD neuropathology (NDAN). In this review, we provide extensive background on AD pathology and normal aging and discuss potential mechanisms that enable these NDAN individuals to remain cognitively intact. Studies presented in this review show that NDAN subjects are generally higher educated and have a larger cognitive reserve. Furthermore, enhanced neural hypertrophy could compensate for hippocampal and cingulate neural atrophy in NDAN individuals. On a cellular level, these individuals show increased levels of neural stem cells and ‘von Economo neurons’. Furthermore, in NDAN brains, binding of Aβ oligomers to synapses is prevented, resulting in decreased glial activation and reduced neuroinflammation. Overall, the evidence stated here strengthens the idea that some individuals are more resistant to AD pathology, or at least show an elongation of the asymptomatic state of the disease compared to others. Insights into the mechanisms underlying this resistance could provide new insight in understanding normal aging and AD itself. Further research should focus on factors and mechanisms that govern the NDAN cognitive resilience in order to find clues on novel biomarkers, targets, and better treatments of AD.

Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network

Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis of AD mainly depends on the interviews between patients and doctors, which is slow, expensive, and subjective, so it is not a better solution to recognize AD using the currently available neuropsychological examinations and clinical diagnostic criteria. A recent study has indicated the potential of language analysis for AD diagnosis. In this study, we proposed a novel feature purification network that can improve the representation learning of transformer model further. Though transformer has made great progress in generating discriminative features because of its long-distance reasoning ability, there is still room for improvement. There exist many common features that are not indicative of any specific class, and we rule out the influence of common features from traditional features extracted by transformer encoder and can get more discriminative features for classification. We apply this method to improve transformer's performance on three public dementia datasets and get improved classification results markedly. Specifically, the method on Pitt datasets gets state-of-the-art (SOTA) result.

Evaluating Voice-Assistant Commands for Dementia Detection

Early detection of cognitive decline involved in Alzheimer's Disease and Related Dementias (ADRD) in older adults living alone is essential for developing, planning, and initiating interventions and support systems to improve users' everyday function and quality of life. In this paper, we explore the voice commands using a Voice-Assistant System (VAS), i.e., Amazon Alexa, from 40 older adults who were either Healthy Control (HC) participants or Mild Cognitive Impairment (MCI) participants, age 65 or older. We evaluated the data collected from voice commands, cognitive assessments, and interviews and surveys using a structured protocol. We extracted 163 unique command-relevant features from each participant's use of the VAS. We then built machine-learning models including 1-layer/2-layer neural networks, support vector machines, decision tree, and random forest, for classification and comparison with standard cognitive assessment scores, e.g., Montreal Cognitive Assessment (MoCA). Our classification models using fusion features achieved an accuracy of 68%, and our regression model resulted in a Root-Mean-Square Error (RMSE) score of 3.53. Our Decision Tree (DT) and Random Forest (RF) models using selected features achieved higher classification accuracy 80-90%. Finally, we analyzed the contribution of each feature set to the model output, thus revealing the commands and features most useful in inferring the participants' cognitive status. We found that features of overall performance, features of music-related commands, features of call-related commands, and features from Automatic Speech Recognition (ASR) were the top-four feature sets most impactful on inference accuracy. The results from this controlled study demonstrate the promise of future home-based cognitive assessments using Voice-Assistant Systems.

A simple counting of verbal fluency errors discriminates between normal cognition, mild cognitive impairment and Alzheimer's disease

For this observational cross-sectional study, different modalities of verbal fluency tasks (VFTs) were compared between 143 participants: 35 cognitively healthy controls (CHCs), 71 mild cognitive impairment (MCI) and 37 mild Alzheimer's disease (AD) patients. Binomial logistic regression models were defined to identify VFT variables associated with MCI and AD, with respect to CHC. The results showed that the best errors/repetitions variable associated with MCI and AD was the phonemic task, and with every error the odds of being in the MCI group increased 9.9 times and 12.2 times in AD group, accompanied by high accuracy values (MCI: AUC = 0.824, sensitivity = 0.676, specificity = 0.943; AD: AUC = 0.883, sensitivity = 0.784, specificity = 0.943). The results suggest that, in addition to solely register raw scores, a simple counting of errors and repetitions during VFT can offer valuable clues in detecting MCI and AD, especially in the phonemic task.

Self-reported word-finding complaints are associated with cerebrospinal fluid amyloid beta and atrophy in cognitively normal older adults

INTRODUCTION

Self-reported word-finding difficulties are among the most frequent complaints in cognitively normal (CN) older adults. However, the clinical significance is still debated.

METHODS

We selected 239 CN from the Alzheimer's Disease Neuroimaging Initiative database who had completed the Everyday Cognition (ECog) questionnaire, as well as a lumbar puncture for amyloid beta (Aβ) and magnetic resonance imaging.

RESULTS

Word-finding complaints, with a few other memory items, were significantly more severe compared to all other cognitive complaints. Ecog-Lang1 (Forgetting names of objects) severity significantly predicted Aβ levels in CN, even when controlling for general cognitive complaint, demographic, and psychological variables. Individuals with high Ecog-Lang1 complaints showed atrophy in the left fusiform gyrus and the left rolandic operculum compared to CN with low complaints.

DISCUSSION

Overall, our results support the fact that word-finding complaints should be taken seriously. They have the potential to identify CN at risk of AD and support the need to include other cognitive domains in the investigation of subjective cognitive decline.

Picture Description of the Western Aphasia Battery Picnic Scene: Reference Data for the French Canadian Population

PURPOSE

The main aim of this study is to provide French Canadian reference data for quantitative measures extracted from connected speech samples elicited by the Western Aphasia Battery-Revised picnic scene, a discourse task frequently used in clinical assessment of acquired language disorders.

METHOD

Our sample consisted of 62 healthy French Canadian adults divided in two age groups: a 50- to 69-year-old group and a 70- to 90-year-old group.

RESULTS

High interrater reliability scores were obtained for most of the variables. Most connected speech variables did not demonstrate an age effect. However, the 70- to 90-year-old group produced more repetitions than the 50- to 69-year-old group and displayed reduced communication efficiency (number of information content units per minute).

CONCLUSION

These findings contribute to building a reference data set to analyze descriptive discourse production in clinical settings.

Family history of FXTAS is associated with age-related cognitive-linguistic decline among mothers with the FMR1 premutation

BACKGROUND

Women who carry a premutation allele of the FMR1 gene are at increased vulnerability to an array of age-related symptoms and disorders, including age-related decline in select cognitive skills. However, the risk factors for age-related decline are poorly understood, including the potential role of family history and genetic factors. In other forms of pathological aging, early decline in syntactic complexity is observed and predicts the later onset of neurodegenerative disease. To shed light on the earliest signs of degeneration, the present study characterized longitudinal changes in the syntactic complexity of women with the FMR1 premutation across midlife, and associations with family history of fragile X-associated tremor/ataxia syndrome (FXTAS) and CGG repeat length.

METHODS

Forty-five women with the FMR1 premutation aged 35-64 years at study entry participated in 1-5 longitudinal assessments spaced approximately a year apart (130 observations total). All participants were mothers of children with confirmed fragile X syndrome. Language samples were analyzed for syntactic complexity and participants provided information on family history of FXTAS. CGG repeat length was determined via molecular genetic testing.

RESULTS

Hierarchical linear models indicated that women who reported a family history of FXTAS exhibited faster age-related decline in syntactic complexity than those without a family history, with that difference emerging as the women reached their mid-50 s. CGG repeat length was not a significant predictor of age-related change.

CONCLUSIONS

Results suggest that women with the FMR1 premutation who have a family history of FXTAS may be at increased risk for neurodegenerative disease, as indicated by age-related loss of syntactic complexity. Thus, family history of FXTAS may represent a personalized risk factor for age-related disease. Follow-up study is needed to determine whether syntactic decline is an early indicator of FXTAS specifically, as opposed to being a more general age-related cognitive decline associated with the FMR1 premutation.

The Diagnostic Value of Language Screening in Primary Progressive Aphasia: Validation and Application of the Sydney Language Battery

PURPOSE

The three variants of primary progressive aphasia (PPA) differ in clinical presentation, underlying brain pathology, and clinical course, which stresses the need for early differentiation. However, brief cognitive tests that validly distinguish between all PPA variants are lacking. The Sydney Language Battery (SYDBAT) is a promising screening instrument that can be used as a first step in a comprehensive neuropsychological assessment to distinguish PPA subtypes, but evidence on its validity and reliability is to date limited. In the current study, the validation and diagnostic value of the SYDBAT are described for discriminating PPA subtypes as well as distinguishing PPA from mild cognitive impairment (MCI) or Alzheimer's dementia (AD).

METHOD

Forty-five patients with PPA (13 with semantic PPA, 20 with logopenic PPA, and 12 with nonfluent/agrammatic PPA), 25 MCI patients, 13 AD patients, and 50 cognitively unimpaired controls were included in this study. Both patients and controls completed the SYDBAT-NL (Dutch version). Performance on and predictive ability of the four subtests (i.e., Naming, Word Comprehension, Repetition, and Semantic Association) were assessed. In addition, construct validity and internal consistency were examined.

RESULTS

Different SYDBAT performance patterns were found across PPA and non-PPA patient groups. While a discriminant function analysis based on SYDBAT subtest scores could predict PPA subtype with 78% accuracy, it was more difficult to disentangle PPA from non-PPA patients based on SYDBAT scores alone. For assisting in clinical interpretation, simple rules were set up and translated into a diagnostic decision tree for subtyping PPA, which was capable of diagnosing a large proportion of the cases. Satisfying validity and reliability measures were found.

CONCLUSIONS

The SYDBAT is an easy-to-use and promising screen for assessing single-word language processes, which may contribute to the differential diagnostic process of PPA and the assessment of language impairment in MCI and AD. It can be easily implemented for initial screening of patients in a memory clinic.

Rates of Cognitive and Functional Impairments in Older Adults Residing in a Continuing Care Senior Housing Community

OBJECTIVE

The current cross-sectional study examined cognition and performance-based functional abilities in a continuing care senior housing community (CCSHC) that is comparable to other CCSHCs in the US with respect to residents' demographic characteristics.

METHOD

Participants were 110 older adult residents of the independent living unit. We assessed sociodemographics, mental health, neurocognitive functioning, and functional capacity.

RESULTS

Compared to normative samples, participants performed at or above expectations in terms of premorbid functioning, attention span and working memory, processing speed, timed set-shifting, inhibitory control, and confrontation naming. They performed below expectation in verbal fluency and verbal and visual learning and memory, with impairment rates [31.4% (>1 SD below the mean) and 18.49% (>1.5 SD below the mean)] well above the general population (16% and 7%, respectively). Within the cognitive test battery, two tests of delayed memory were most predictive of a global deficit score. Most cognitive test scores correlated with performance-based functional capacity.

CONCLUSIONS

Overall, results suggest that a subset of older adults in the independent living sector of CCSHCs are cognitively and functionally impaired and are at risk for future dementia. Results also argue for the inclusion of memory tests in abbreviated screening batteries in this population. We suggest that CCSHCs implement regular cognitive screening procedures to identify and triage those older adults who could benefit from interventions and, potentially, a transition to a higher level of care.

Functional Neural Correlates of Semantic Fluency Task Performance in Mild Cognitive Impairment and Alzheimer's Disease: An FDG-PET Study

BACKGROUND

Total score (TS) of semantic verbal fluency test (SVFT) is generally used to interpret results, but it is ambiguous as to specific neural functions it reflects. Different SVFT strategy scores reflecting qualitative aspects are proposed to identify specific cognitive functions to overcome limitations of using the TS.

OBJECTIVE

Functional neural correlates of the TS as well as the other strategy scores in subjects with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia using Fluorine-18-Fluorodeoxyglucose positron emission tomography (FDG-PET).

METHODS

Correlations between various SVFT scores (i.e., TS, mean cluster size, switching (SW), hard switching, cluster switching (CSW)) and cerebral glucose metabolism were explored using voxelwise whole-brain approach. Subgroup analyses were also performed based on the diagnosis and investigated the effects of disease severity on the associations.

RESULTS

Significant positive correlation between TS and cerebral glucose metabolism was found in prefrontal, parietal, cingulate, temporal cortex, and subcortical regions. Significantly increased glucose metabolism associated with the SW were found in similar but smaller regions, mainly in the fronto-parieto-temporal regions. CSW was only correlated with the caudate. In the subgroup analysis conducted to assess different contribution of clinical severity, differential associations between the strategy scores and regional glucose metabolism were found.

CONCLUSION

SW and CSW may reflect specific language and executive functions better than the TS. The SVFT is influenced by brain dysfunction due to the progression of AD, as demonstrated by the SW with larger involvement of temporal lobe for the AD, and CSW with significant association only for the MCI.

A Comparison of Speech Features between Mild Cognitive Impairment and Healthy Aging Groups

Background and Purpose

Language dysfunction is a symptom common to patients with Alzheimer's disease (AD). Speech feature analysis may be a patient-friendly screening test for early-stage AD. We aimed to investigate the speech features of amnestic mild cognitive impairment (aMCI) compared to normal controls (NCs).

Methods

Spoken responses to test questions were recorded with a microphone placed 15 cm in front of each participant. Speech samples delivered in response to four spoken test prompts (free speech test, Mini-Mental State Examination [MMSE], picture description test, and sentence repetition test) were obtained from 98 patients with aMCI and 139 NCs. Each recording was transcribed, with speech features noted. The frequency of the ten speech features assessed was evaluated to compare speech abilities between the test groups.

Results

Among the ten speech features, the frequency of pauses (p=0.001) and mumbles (p=0.001) were significantly higher in patients with aMCI than in NCs. Moreover, MMSE score was found to negatively correlate with the frequency of pauses (r=−0.441, p<0.001) and mumbles (r=−0.341, p<0.001).

Conclusions

Frequent pauses and mumbles reflect cognitive decline in aMCI patients in episodic and semantic memory tests. Speech feature analysis may prove to be a speech-based biomarker for screening early-stage cognitive impairment.

Changes in Speech Range Profile Are Associated with Cognitive Impairment

Background and Purpose

The aim of this study was to describe the variations in the speech range profile (SRP) of patients affected by cognitive decline.

Methods

We collected the data of patients managed for suspected voice and speech disorders, and suspected cognitive impairment. Patients underwent an Ear Nose and Throat evaluation and Mini-Mental State Examination (MMSE). To obtain SRP, we asked the patients to read 18 sentences twice, at their most comfortable pitch and loudness as they would do in daily conversation, and recorded their voice on to computer software.

Results

The study included 61 patients. The relationship between the MMSE score and SRP parameters was established. Increased severity of the MMSE score resulted in a statistically significant reduction in the average values of the semitones to the phonetogram, and the medium and maximum sound pressure levels (p<0.001). The maximum predictivity of MMSE was based on the highly significant values of semitones (p<0.001) and the maximum sound pressure levels (p=0.010).

Conclusions

The differences in SRP between the various groups were analyzed. Specifically, the SRP value decreased with increasing severity of cognitive decline. SRP was useful in highlighting the relationship between all cognitive declines tested and speech.

Detecting impaired language processing in patients with mild cognitive impairment using around-the-ear cEEgrid electrodes

Mild cognitive impairment (MCI) is the term used to identify those individuals with subjective and objective cognitive decline but with preserved activities of daily living and an absence of dementia. Although MCI can impact functioning in different cognitive domains, most notably episodic memory, relatively little is known about the comprehension of language in MCI. In this study, we used around-the-ear electrodes (cEEGrids) to identify impairments during language comprehension in patients with MCI. In a group of 23 patients with MCI and 23 age-matched controls, language comprehension was tested in a two-word phrase paradigm. We examined the oscillatory changes following word onset as a function of lexico-semantic single-word retrieval (e.g., swrfeq vs. swift) and multiword binding processes (e.g., horse preceded by swift vs. preceded by swrfeq). Electrophysiological signatures (as measured by the cEEGrids) were significantly different between patients with MCI and controls. In controls, lexical retrieval was associated with a rebound in the alpha/beta range, and binding was associated with a post-word alpha/beta suppression. In contrast, both the single-word retrieval and multiword binding signatures were absent in the MCI group. The signatures observed using cEEGrids in controls were comparable with those signatures obtained with a full-cap EEG setup. Importantly, our findings suggest that patients with MCI have impaired electrophysiological signatures for comprehending single words and multiword phrases. Moreover, cEEGrid setups provide a noninvasive and sensitive clinical tool for detecting early impairments in language comprehension in MCI.

Language Decline Characterizes Amnestic Mild Cognitive Impairment Independent of Cognitive Decline

Purpose This research investigated the nature of cognitive decline in prodromal Alzheimer's disease (AD), particularly in mild cognitive impairment, amnestic type (aMCI). We assessed language in aMCI as compared with healthy aging (HA) and healthy young (HY) with new psycholinguistic assessment of complex sentences, and we tested the degree to which deficits on this language measure relate to performance in other general cognitive domains such as memory. Method Sixty-one individuals with aMCI were compared with 24 HA and 10 HY adults on a psycholinguistic measure of complex sentence production (relative clauses). In addition, HA, HY, and a subset of the aMCI participants (n = 22) were also tested on a multidomain cognitive screen, the Addenbrooke's Cognitive Examination-Revised (ACE-R), and on a verbal working memory Brown-Peterson (BP) test. General and generalized linear mixed models were used to test psycholinguistic results and to test whether ACE-R and BP performance predicted performance on the psycholinguistic test similarly in the aMCI and HA groups. Results On the psycholinguistic measure, sentence imitation was significantly deficited in aMCI in comparison with that in HA and HY. Experimental factorial designs revealed that individuals with aMCI had particular difficulty repeating sentences that especially challenged syntax-semantics integration. As expected, the aMCI group also performed significantly below the HY and HA groups on the ACE-R. Neither the ACE-R Memory subtest nor the BP total scores predicted performance on the psycholinguistic task for either the aMCI or the HA group. However, the ACE-R total score significantly predicted psycholinguistic task performance, with increased ACE-R performance predicting increased psycholinguistic task performance only for the HA group, not for the aMCI group. Conclusions Results suggest a selective deterioration in language in aMCI, specifically a weakening of syntax-semantics integration in complex sentence processing, and a general independence of this language deficit and memory decline. Results cohere with previous assessments of the nature of difficulty in complex sentence formation in aMCI. We argue that clinical screening for prodromal AD can be strengthened by supplementary testing of language, as well as memory, and extended evaluation of strength of their relation.

Tablet-Based Automatic Assessment for Early Detection of Alzheimer's Disease Using Speech Responses to Daily Life Questions

Health-monitoring technologies for automatically detecting the early signs of Alzheimer's disease (AD) have become increasingly important. Speech responses to neuropsychological tasks have been used for quantifying changes resulting from AD and differentiating AD and mild cognitive impairment (MCI) from cognitively normal (CN). However, whether and how other types of speech tasks with less burden on older adults could be used for detecting early signs of AD remains unexplored. In this study, we developed a tablet-based application and compared speech responses to daily life questions with those to neuropsychological tasks in terms of differentiating MCI from CN. We found that in daily life questions, around 80% of speech features showing significant differences between CN and MCI overlapped those showing significant differences in both our study and other studies using neuropsychological tasks, but the number of significantly different features as well as their effect sizes from life questions decreased compared with those from neuropsychological tasks. On the other hand, the results of classification models for detecting MCI by using the speech features showed that daily life questions could achieve high accuracy, i.e., 86.4%, comparable to neuropsychological tasks by using eight questions against all five neuropsychological tasks. Our results indicate that, while daily life questions may elicit weaker but statistically discernable differences in speech responses resulting from MCI than neuropsychological tasks, combining them could be useful for detecting MCI with comparable performance to using neuropsychological tasks, which could help develop health-monitoring technologies for early detection of AD in a less burdensome manner.

The Eyes Are More Eloquent Than Words: Anticipatory Looking as an Index of Event Memory in Alzheimer's Disease

Alzheimer's disease (AD) is a disorder in which individuals experience a difficulty in maintaining event memory for when, where, who, and what. However, verbal deficiency, one of the other symptoms of AD, may prevent a precise diagnosis of event memory because existing tests are based on verbal instructions by the tester and verbal response from patient. Therefore, non-verbal methods are essential to evaluate event memory in AD. The present study, using eye tracking, investigated whether AD patients deployed anticipatory looking to target acts related to future events based on previous experience when an identical video was presented to them twice. The results revealed the presence of anticipatory looking, although AD patients were unable to verbally report the content of the video. Our results illustrate that AD patients have a one-time event memory better than previously thought.

Connected Speech Characteristics of Bengali Speakers With Alzheimer's Disease: Evidence for Language-Specific Diagnostic Markers

Background and aim: Speech and language characteristics of connected speech provide a valuable tool for identifying, diagnosing and monitoring progression in Alzheimer's Disease (AD). Our knowledge of linguistic features of connected speech in AD is primarily derived from English speakers; very little is known regarding patterns of linguistic deficits in speakers of other languages, such as Bengali. Bengali is a highly inflected pro-drop language from the Indo-Aryan language family. It is the seventh most spoken language in the world, yet to date, no studies have investigated the profile of linguistic impairments in Bengali speakers with AD. The aim of this study was to characterize connected speech production and identify the linguistic features affected in Bengali speakers with AD. Methods: Participants were six Bengali speaking AD patients and eight matched controls from the urban metropolis, Kolkata, India. Narrative samples were elicited in Bengali using the Frog Story. Samples were analyzed using the Quantitative Production Analysis and the Correct Information Unit analyses to quantify six different aspects of speech production: speech rate, structural and syntactic measures, lexical measures, morphological and inflectional measures, semantic measures and measure of spontaneity and fluency disruptions. Results and conclusions: In line with the extant literature from English speakers, the Bengali AD participants demonstrated decreased speech rate, simplicity of sentence forms and structures, and reduced semantic content. Critically, differences with English speakers' literature emerged in the domains of Bengali specific linguistic features, such as the pro-drop nature of Bengali and its inflectional properties of nominal and verbal systems. Bengali AD participants produced fewer pronouns, which is in direct contrast with the overuse of pronouns by English AD participants. No obvious difficulty in producing nominal and verbal inflections was evident. However, differences in the type of noun inflections were evident; these were characterized by simpler inflectional features used by AD speakers. This study represents the first of its kind to characterize connected speech production in Bengali AD participants and is a significant step forward toward the development of language-specific clinical markers in AD. It also provides a framework for cross-linguistic comparisons across structurally distinct and under-explored languages.

Stress Is Associated With Neurocognitive Function in Hispanic/Latino Adults: Results From HCHS/SOL Socio-Cultural Ancillary Study

OBJECTIVES

The purpose of this study was to evaluate the hypothesis that chronic and acculturative stress would be negatively associated with neurocognitive function among middle aged to older Hispanics/Latinos.

METHOD

Our analytic sample consisted of 3,265 participants (mean age = 56.7 (±0.24)) from the Hispanic Community Health Study/Study of Latinos who participated in its Sociocultural Ancillary Study. During the baseline phase of this project, participants were assessed on multiple domains of neurocognitive function, and completed self-report measures of chronic and acculturative stress.

RESULTS

Each standard deviation increase in chronic stress was associated with lower performance in a verbal learning task (B = -.17, 95% CI [-.32, -.01]); this association was no longer significant after adjusting for mental and physical health symptoms, including depression and anxiety symptoms, and cardiovascular health. A standard deviation increase in acculturative stress was associated with poorer performance in all cognitive measures (Bs range = -.13 to -1.03). Associations of acculturation stress with psychomotor speed, verbal learning, and word fluency remained significant after adjusting for mental and physical health symptoms.

DISCUSSION

Our results suggest that mental and physical health may help explain some cross-sectional associations between stress and cognition and highlight the need to examine culture-specific psychosocial stressors to better understand the context of psychosocial risk factors for neurocognitive performance.

Using Automatic Assessment of Speech Production to Predict Current and Future Cognitive Function in Older Adults

Neurodegenerative conditions like Alzheimer disease affect millions and have no known cure, making early detection important. In addition to memory impairments, dementia causes substantial changes in speech production, particularly lexical-semantic characteristics. Existing clinical tools for detecting change often require considerable expertise or time, and efficient methods for identifying persons at risk are needed. This study examined whether early stages of cognitive decline can be identified using an automated calculation of lexical-semantic features of participants' spontaneous speech. Unimpaired or mildly impaired older adults (N = 39, mean 81 years old) produced several monologues (picture descriptions and expository descriptions) and completed a neuropsychological battery, including the Modified Mini-Mental State Exam. Most participants (N = 30) returned one year later for follow-up. Lexical-semantic features of participants' speech (particularly lexical frequency) were significantly correlated with cognitive status at the same visit and also with cognitive status one year in the future. Thus, automated analysis of speech production is closely associated with current and future cognitive test performance and could provide a novel, scalable method for longitudinal tracking of cognitive health.

Validity of the Montreal Cognitive Assessment (MoCA) Index Scores: a Comparison with the Cognitive Domain Scores of the Seoul Neuropsychological Screening Battery (SNSB)

Background and Purpose

A new approach was proposed to score the Montreal Cognitive Assessment (MoCA) index scores for 6 cognitive domains: orientation (OIS), attention (AIS), language (LIS), visuospatial function (VIS), memory (MIS), and executive function (EIS). This study investigated whether the MoCA index scores represent the functions of each cognitive domain by examining the correlations with the corresponding cognitive domain scores derived from conventional neuropsychological tests included in the Seoul Neuropsychological Screening Battery, 2nd Edition (SNSB-II).

Methods

The participants were 104 amnestic mild cognitive impairment (aMCI), 74 vascular mild cognitive impairment (VaMCI), 73 dementia of the Alzheimer's type (DAT), and 41 vascular dementia (VaD) patients. All participants were administered the Korean-MoCA and SNSB-II.

Results

Like the MoCA total score, the MoCA-OIS, MoCA-VIS, and MoCA-MIS showed differences between aMCI and AD groups and between VaMCI and VaD groups. The MoCA-AIS, MoCA-LIS, and MoCA-EIS showed significant differences between VaMCI and VaD groups, but no difference between aMCI and DAT groups. In the aMCI and VaMCI groups, all index scores of the MoCA showed significant correlations with the corresponding cognitive domain scores of the SNSB-II. Except for MoCA-MIS, the MoCA-AIS, MoCA-LIS, MoCA-VIS, and MoCA-EIS also showed significant correlations with the corresponding domain scores of the SNSB-II in the DAT and VaD groups.

Conclusions

These results indicate that all MoCA index scores, except for MoCA-MIS, which does not reflect the severity of memory impairment in dementia patients, provide highly valid information on the function of each cognitive domain in patients with mild cognitive impairment and dementia.

Inference comprehension from reading in individuals with mild cognitive impairment

Inference comprehension is a complex ability that recruits distinct cognitive domains, such as language, memory, attention, and executive functions. Therefore, it might be sensitive to identify early deficits in subjects with MCI. To compare the performance of subjects with mild cognitive impairment (MCI) in an inference reading comprehension task, and to analyze the correlations between inferential comprehension and other cognitive functions. We studied 100 individuals aged 60 and over, divided into MCI (50) [aMCI (35), naMCI (15)], and cognitively healthy individuals [controls (50)]. The Implicit Management Test (IMT) was used to assess inference in reading comprehension in five categories: explicit, logical, distractor, pragmatic, and "others". MCI group performed worse than controls in logical, pragmatic, distractor, and "others" questions (p < 0.01). The aMCI and naMCI subgroups presented a similar performance in all types of questions (p > 0.05). We observed significant correlations between the total IMT score and the TMT-A in the naMCI group (r = - 0.562, p = 0.036), and the Rey-Osterrieth Complex Figure and RAVLT tasks in the aMCI group (r = 0.474, p = 0.010 and r = 0.593, p = 0.0001, respectively). The MCI group as a whole performed worse than controls on the logical, pragmatic, other and distractor questions, and consequently on the total score. There were no differences in explicit questions, which impose lower inferential demands. The aMCI group suffered a significant impact from memory on inference comprehension, and difficulties in executive functions impacted naMCI performance. The IMT was useful to differentiate MCI patients from cognitively healthy individuals, but not MCI subgroups among themselves.

Current advances in digital cognitive assessment for preclinical Alzheimer's disease

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost-effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech-adoption increases, and external events (i.e., COVID-19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in-clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study-provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Preliminary assessment of connected speech and language as marker for cognitive change in late middle-aged Black/African American adults at risk for Alzheimer's disease

Background

Connected speech-language (CSL) has been a promising measure of assessing cognitive decline in populations at-risk for Alzheimer's disease and related dementias (ADRD) populations. A common way to obtain CSL is through using picture description tasks such as the most frequently used image Cookie Theft (CT). However, questions have been raised about using CT for diverse communities. Little is known about the CSL produced in response to this task in Black/African American (BAA) adults aged 48-74.

Goals

The present study's goals were to characterize CSL in BAA adults by sex and APOE-ε4 status from Milwaukee in the Wisconsin Registry for Alzheimer's Prevention (WRAP) study when presented with the CT picture description task and to identify differences in CSL output between BAAs and non-Hispanic Whites (NHW).

Methods and Procedures

We collected CSL samples from the CT picture from 48 BAA participants and 30 NHW participants from the WRAP participants in Milwaukee, WI group. CSL was analyzed using chi-square tests, T-tests, and ANCOVA. Linear mixed effect regression models were used to determine the association between cognitive status and longitudinal CSL in BAA participants with more than 1 timepoint.

Outcomes and Results

Declines in CSL of BAA participants were associated with subtle declines in cognition. Among BAA participants, we found no significant differences in speech measures in terms of sex and APOE-ε4 status. Our results showed no significant differences in speech measures between BAA and NHW groups.

Conclusions

CSL analysis provides an inexpensive way to evaluate preclinical changes in cognitive status that may not be as affected by other factors, such as ethnocultural background. Future studies with larger sample sizes and participants from other geographic locations can clarify these findings.

fMRI Investigation of Semantic Lexical Processing in Healthy Control and Alzheimer's Disease Subjects Using Naming Task: A Preliminary Study

For decades, scientists have been trying to solve the problem of dementia, with no cure currently available. Semantic-lexical impairment is well established as the early critical sign of dementia, although there are still gaps in knowledge that must be investigated. In this study, we used fMRI to observe the neural activity of 31 subjects, including 16 HC (Healthy Control) and 15 AD (Alzheimer's Disease), who participated in the naming task. The neuropsychology profile of HC (Healthy Control) and AD (Alzheimer's Disease) are discussed in this study. The involvement of FG (Fusiform Gyrus) and IFG (Inferior Frontal Gyrus) shows dominant activation in both of the groups. We observed a decrease in neural activity in the AD group, resulting in semantic deficit problems in this preliminary study. Furthermore, ROI analysis was performed and revealed both hyperactivation and hypoactivation in the AD group. The compensatory mechanism demonstrated during the task, due to the effort required to identify an animal's name, represents the character profile of AD.

Language Network Connectivity Increases in Early Alzheimer's Disease

Background:

Language production deficits occur early in the course of Alzheimer’s disease (AD); however, only a few studies have focused on language network’s functional connectivity in mild cognitive impairment (MCI) due to AD.

Objective:

The current study aims to uncover the extent of language alteration at the MCI stage, at a behavioral and neural level, using univariate and multivariate analyses of structural MRI and resting-state fMRI.

Methods:

Twenty-four MCI due to AD participants and 24 matched healthy controls underwent a comprehensive language evaluation, a structural T1-3D MRI, and resting-state fMRI. We performed seed-based analyses, using the left inferior frontal gyrus and left posterior temporal gyrus as seeds. Then, we analyzed connectivity between executive control networks and language network in each group. Finally, we used multivariate pattern analyses to test whether the two groups could be distinguished based on the pattern of atrophy within the language network; within the executive control networks, as well as the pattern of functional connectivity within the language network and within the executive control networks.

Results:

MCI due to AD participants had language impairment during standardized language tasks and connected-speech production. Regarding functional connectivity, univariate analyses were not able to discriminate participants, while multivariate pattern analyses could significantly predict participants’ group. Language network’s functional connectivity could discriminate MCI due to AD participants better than executive control networks. Most notably, they revealed an increased connectivity at the MCI stage, positively correlated with language performance.

Conclusion:

Multivariate analyses represent a useful tool for investigating the functional and structural (re-)organization of the neural bases of language.

Language Impairment in Alzheimer's Disease-Robust and Explainable Evidence for AD-Related Deterioration of Spontaneous Speech Through Multilingual Machine Learning

Alzheimer's disease (AD) is a pervasive neurodegenerative disease that affects millions worldwide and is most prominently associated with broad cognitive decline, including language impairment. Picture description tasks are routinely used to monitor language impairment in AD. Due to the high amount of manual resources needed for an in-depth analysis of thereby-produced spontaneous speech, advanced natural language processing (NLP) combined with machine learning (ML) represents a promising opportunity. In this applied research field though, NLP and ML methodology do not necessarily ensure robust clinically actionable insights into cognitive language impairment in AD and additional precautions must be taken to ensure clinical-validity and generalizability of results. In this study, we add generalizability through multilingual feature statistics to computational approaches for the detection of language impairment in AD. We include 154 participants (78 healthy subjects, 76 patients with AD) from two different languages (106 English speaking and 47 French speaking). Each participant completed a picture description task, in addition to a battery of neuropsychological tests. Each response was recorded and manually transcribed. From this, task-specific, semantic, syntactic and paralinguistic features are extracted using NLP resources. Using inferential statistics, we determined language features, excluding task specific features, that are significant in both languages and therefore represent "generalizable" signs for cognitive language impairment in AD. In a second step, we evaluated all features as well as the generalizable ones for English, French and both languages in a binary discrimination ML scenario (AD vs. healthy) using a variety of classifiers. The generalizable language feature set outperforms the all language feature set in English, French and the multilingual scenarios. Semantic features are the most generalizable while paralinguistic features show no overlap between languages. The multilingual model shows an equal distribution of error in both English and French. By leveraging multilingual statistics combined with a theory-driven approach, we identify AD-related language impairment that generalizes beyond a single corpus or language to model language impairment as a clinically-relevant cognitive symptom. We find a primary impairment in semantics in addition to mild syntactic impairment, possibly confounded by additional impaired cognitive functions.

Predicting Alzheimer's Disease from Spoken and Written Language Using Fusion-Based Stacked Generalization

The importance of automating the diagnosis of Alzheimer disease (AD) towards facilitating its early prediction has long been emphasized, hampered in part by lack of empirical support. Given the evident association of AD with age and the increasing aging population owing to the general well-being of individuals, there have been unprecedented estimated economic complications. Consequently, many recent studies have attempted to employ the language deficiency caused by cognitive decline in automating the diagnostic task via training machine learning (ML) algorithms with linguistic patterns and deficits. In this study, we aim to develop multiple heterogeneous stacked fusion models that harness the advantages of several base learning algorithms to improve the overall generalizability and robustness of AD diagnostic ML models, where we parallelly utilized two different written and spoken-based datasets to train our stacked fusion models. Further, we examined the effect of linking these two datasets to develop a hybrid stacked fusion model that can predict AD from written and spoken languages. Our feature spaces involved two widely used linguistic patterns: lexicosyntactics and character n-gram spaces. We firstly investigated lexicosyntactics of AD alongside healthy controls (HC), where we explored a few new lexicosyntactic features, then optimized the lexicosyntactic feature space by proposing a correlation feature selection technique that eliminates features based on their feature-feature inter-correlations and feature-target correlations according to a certain threshold. Our stacked fusion models establish benchmarks on both datasets with AUC of 98.1% and 99.47% for the spoken and written-based datasets, respectively, and corresponding accuracy and F1 score values around 95% on spoken-based dataset and around 97% on the written-based dataset. Likewise, the hybrid stacked fusion model on linked data presents an optimal performance with 99.2% AUC as well as accuracy and F1 score falling around 97%. In view of the achieved performance and enhanced generalizability of such fusion models over single classifiers, this study suggests replacing the initial traditional screening test with such models that can be embedded into an online format for a fully automated remote diagnosis.

Identification of Mild Cognitive Impairment Among Chinese Based on Multiple Spoken Tasks

BACKGROUND

Previous studies explored the use of noninvasive biomarkers of speech and language for the detection of mild cognitive impairment (MCI). Yet, most of them employed single task which might not have adequately captured all aspects of their cognitive functions.

OBJECTIVE

The present study aimed to achieve the state-of-the-art accuracy in detecting individuals with MCI using multiple spoken tasks and uncover task-specific contributions with a tentative interpretation of features.

METHODS

Fifty patients clinically diagnosed with MCI and 60 healthy controls completed three spoken tasks (picture description, semantic fluency, and sentence repetition), from which multidimensional features were extracted to train machine learning classifiers. With a late-fusion configuration, predictions from multiple tasks were combined and correlated with the participants' cognitive ability assessed using the Montreal Cognitive Assessment (MoCA). Statistical analyses on pre-defined features were carried out to explore their association with the diagnosis.

RESULTS

The late-fusion configuration could effectively boost the final classification result (SVM: F1 = 0.95; RF: F1 = 0.96; LR: F1 = 0.93), outperforming each individual task classifier. Besides, the probability estimates of MCI were strongly correlated with the MoCA scores (SVM: -0.74; RF: -0.71; LR: -0.72).

CONCLUSION

Each single task tapped more dominantly to distinct cognitive processes and have specific contributions to the prediction of MCI. Specifically, picture description task characterized communications at the discourse level, while semantic fluency task was more specific to the controlled lexical retrieval processes. With greater demands on working memory load, sentence repetition task uncovered memory deficits through modified speech patterns in the reproduced sentences.

Individuals With Mild Cognitive Impairment and Alzheimer's Disease Benefit From Audiovisual Speech Cues and Supportive Sentence Context

Purpose Speech perception in noise becomes difficult with age but can be facilitated by audiovisual (AV) speech cues and sentence context in healthy older adults. However, individuals with Alzheimer's disease (AD) may present with deficits in AV integration, potentially limiting the extent to which they can benefit from AV cues. This study investigated the benefit of these cues in individuals with mild cognitive impairment (MCI), individuals with AD, and healthy older adult controls. Method This study compared auditory-only and AV speech perception of sentences presented in noise. These sentences had one of two levels of context: high (e.g., "Stir your coffee with a spoon") and low (e.g., "Bob didn't think about the spoon"). Fourteen older controls (M _age = 72.71 years, SD = 9.39), 13 individuals with MCI (M _age = 79.92 years, SD = 5.52), and nine individuals with probable Alzheimer's-type dementia (M _age = 79.38 years, SD = 3.40) completed the speech perception task and were asked to repeat the terminal word of each sentence. Results All three groups benefited (i.e., identified more terminal words) from AV and sentence context. Individuals with MCI showed a smaller AV benefit compared to controls in low-context conditions, suggesting difficulties with AV integration. Individuals with AD showed a smaller benefit in high-context conditions compared to controls, indicating difficulties with AV integration and context use in AD. Conclusions Individuals with MCI and individuals with AD do benefit from AV speech and semantic context during speech perception in noise (albeit to a lower extent than healthy older adults). This suggests that engaging in face-to-face communication and providing ample context will likely foster more effective communication between patients and caregivers, professionals, and loved ones.

Verbal Fluency in Mild Alzheimer's Disease: Transcranial Direct Current Stimulation over the Dorsolateral Prefrontal Cortex

BACKGROUND

Recent studies showed that in healthy controls and in aphasic patients, inhibitory trains of repetitive transcranial magnetic stimulation (rTMS) over the right prefrontal cortex can improve phonemic fluency performance, while anodal transcranial direct current stimulation (tDCS) over the left prefrontal cortex can improve performance in naming and semantic fluency tasks.

OBJECTIVE

This study aimed at investigating the effects of cathodal tDCS over the left or the right dorsolateral prefrontal cortex (DLPFC) on verbal fluency tasks (VFT) in patients with mild Alzheimer's disease (AD).

METHODS

Forty mild AD patients participated in the study (mean age 73.17±5.61 years). All participants underwent cognitive baseline tasks and a VFT twice. Twenty patients randomly received cathodal tDCS to the left or the right DLPFC, and twenty patients were assigned to a control group in which only the two measures of VFT were taken, without the administration of the tDCS.

RESULTS

A significant improvement of performance on the VFT in AD patients was present after tDCS over the right DLPFC (p = 0.001). Instead, no difference was detected between the two VFTs sessions after tDCS over the left DLPFC (p = 0.42). Furthermore, these results cannot be related to task learning effects, since no significant difference was found between the two VFT sessions in the control group (p = 0.73).

CONCLUSION

These data suggest that tDCS over DLPFC can improve VFT performance in AD patients. A hypothesis is that tDCS enhances adaptive patterns of brain activity between functionally connected areas.