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

Subjective rating scale for discourse: Evidence from the efficacy of subjective rating scale in amnestic mild cognitive impairments

In clinical settings, the language ability of patients with neurologic communication disorders have been measured by quantitative parameters such as the total number of words in dialogue and picture description tasks. However, this quantitative analysis requires a long period of time in order to analyze the quantitative parameters, and results can differ according to discourse tasks. The purposes of this study are to explore whether SR-D may predict the quantitative measures of discourse tasks. Forty patients with amnestic MCI and 40 normal elderly participated in the study. We gathered responses to 10 items regarding SR-D and analyzed the quantitative measures of narrative discourse through 3 discourse tasks (i.e, picture description, dialogue, procedural discourse). We found significant differences in MLTW, CIU, and SR-D scores between the 2 groups. In particular, 4 items were significantly correlated with the performance of MLTW and CIU. Sensitivity and specificity of these 4 items were 100% and 75%, respectively. In terms of economic opportunity costs, objective measures cannot be evaluated to be practical, since it is used in research rather than clinical diagnosis in general. Therefore, evaluation of discourse using a few items proven in its sensitivity and specificity could allow a wide use of such measure in not only research but also in clinical diagnosis. These findings suggest that subjective measures of narrative discourse may be valid with objective language tests to predict individual discourse performance.

Identification of Mild Cognitive Impairment From Speech in Swedish Using Deep Sequential Neural Networks

While people with mild cognitive impairment (MCI) portray noticeably incipient memory difficulty in remembering events and situations along with problems in decision making, planning, and finding their way in familiar environments, detailed neuropsychological assessments also indicate deficits in language performance. To this day, there is no cure for dementia but early-stage treatment can delay the progression of MCI; thus, the development of valid tools for identifying early cognitive changes is of great importance. In this study, we provide an automated machine learning method, using Deep Neural Network Architectures, that aims to identify MCI. Speech materials were obtained using a reading task during evaluation sessions, as part of the Gothenburg MCI research study. Measures of vowel duration, vowel formants (F1 to F5), and fundamental frequency were calculated from speech signals. To learn the acoustic characteristics associated with MCI vs. healthy controls, we have trained and evaluated ten Deep Neural Network Architectures and measured how accurately they can diagnose participants that are unknown to the model. We evaluated the models using two evaluation tasks: a 5-fold crossvalidation and by splitting the data into 90% training and 10% evaluation set. The findings suggest first, that the acoustic features provide significant information for the identification of MCI; second, the best Deep Neural Network Architectures can classify MCI and healthy controls with high classification accuracy (M = 83%); and third, the model has the potential to offer higher accuracy than 84% if trained with more data (cf., SD≈15%). The Deep Neural Network Architecture proposed here constitutes a method that contributes to the early diagnosis of cognitive decline, quantify the progression of the condition, and enable suitable therapeutics.

Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Background: The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals.

Methods: We enrolled 96 participants (age range 50–75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features.

Results: Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI.

Conclusions: Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption.

Connected speech and language in mild cognitive impairment and Alzheimer's disease: A review of picture description tasks

INTRODUCTION

The neuropsychological profile of people with mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia includes a history of decline in memory and other cognitive domains, including language. While language impairments have been well described in AD dementia, language features of MCI are less well understood. Connected speech and language analysis is the study of an individual's spoken discourse, usually elicited by a target stimulus, the results of which can facilitate understanding of how language deficits typical of MCI and AD dementia manifest in everyday communication. Among discourse genres, picture description is a constrained task that relies less on episodic memory and more on semantic knowledge and retrieval, within the cognitive demands of a communication context. Understanding the breadth of evidence across the continuum of cognitive decline will help to elucidate the areas of strength and need in terms of using this method as an evaluative tool for both cognitive changes and everyday functional communication.

METHOD

We performed an extensive literature search of peer-reviewed journal articles that focused on the use of picture description tasks for evaluating language in persons with MCI or AD dementia. We selected articles based on inclusion and exclusion criteria and described the measures assessed, the psychometric properties that were reported, the findings, and the limitations of the included studies.

RESULTS

36 studies were selected and reviewed. Across all 36 studies, there were 1, 127 patients with AD dementia and 274 with MCI or early cognitive decline. Multiple measures were examined, including those describing semantic content, syntactic complexity, speech fluency, vocal parameters, and pragmatic language. Discriminant validity widely reported and distinct differences in language were observable between adults with dementia and controls; fewer studies were able to distinguish language differences between typically aging adults and those with MCI.

DISCUSSION

Our review shows that picture description tasks are useful tools for detecting differences in a wide variety of language and communicative measures. Future research should expand knowledge about subtle changes to language in preclinical AD and Mild Cognitive Impairment (MCI) which may improve the utility of this method as a clinically meaningful screening tool.

Quanti-qualitative components of the semantic verbal fluency test in cognitively healthy controls, mild cognitive impairment, and dementia subtypes

This study is aimed to evaluating the underlying cognitive strategies used during Semantic Verbal Fluency (SVF) performance and comparing the differences between cognitively healthy controls (CHC), amnestic and amnestic-multiple domain mild cognitive impairment (a-MCI and a-md-MCI), Alzheimer's disease (AD), Lewy body dementia (LBD), and behavioral variant frontotemporal dementia (bvFTD). The cross-sectional study comprised 236 participants involving 78 CHC individuals, 33 a-MCI and 48 a-md-MCI, 39 AD, 22 LBD, and 16 bvFTD patients. Scores differed significantly when comparing CHC with dementia groups, showing medium to large variances. The best components in distinguishing between CHC and the dementia groups were the SVF-Total score and SVF-Cluster Size variables. CHC showed different performance in the SVF-Cluster Size variable compared with a-md-MCI, AD, and bvFTD; whereas, in the SVF-Mean Cluster Size, CHC differed from MCI's, AD, and LBD. The switching component displayed smaller capacity to differentiate between the clinical groups. The effect size was large comparing AD with bvFTD (1.267) and medium comparing AD with LBD (0.689) using the SVF-Cluster Size variable, but small using the other variables for the comparisons between dementia groups. Quanti-qualitative examination of the SVF may provide a valuable clue in distinguishing CHC from MCI and different dementia subtypes.

Diagnostic Value of Time-Constrained Naming Test in Mild Cognitive Impairment

BACKGROUND

Naming difficulties have recently garnered more interest in elderly individuals with mild cognitive impairment (MCI). We anticipate that naming tests with the consideration of response time can provide more informative and distinct neuropsychological profiles of individuals with MCI.

METHODS

Naming tests were administered to 76 elderly individuals with MCI and 149 healthy elderly (HE). We analyzed the impact of MCI on naming performance and occurrence of "delayed" response. We also validated the predictive power of naming tests with a time-constrained scoring system.

RESULTS

MCI participants performed poorer on the noun naming test than HE participants (p = 0.014). MCI was significantly associated with the occurrence of "delayed" response on the noun (odds ratio [OR] = 3.57; 95% confidence interval [CI] = 1.78-7.17) and verb naming tests (OR = 4.66; 95% CI = 2.07-10.46). The time-constrained naming scores were significantly better able to distinguish the MCI from the HE group than the conventional spontaneous naming score on both the noun (p < 0.001) and verb (p = 0.002) naming tests.

CONCLUSIONS

Our findings broaden the knowledge related to the naming ability in individuals with MCI, with respect to the response time. We also confirmed the validity of the naming tests by applying the "delayed" responses as supplementary assessments in the diagnosis of MCI.

Beneficial Effect of Multidomain Cognitive Training on the Neuropsychological Performance of Patients with Early-Stage Alzheimer's Disease

Background and Purpose

There is an increasing interest in the effect of nonpharmacological interventions on the course of patients with Alzheimer's disease (AD). The objective of the present study is to determine the benefits of a structured, multidomain, mostly computer-based, cognitive training (MCT) οn the cognitive performance of patients with early-stage AD.

Method

Fifty patients with early-stage AD participated in the study. Patients were randomly allocated either to the training program group (n = 25) or to a wait list control group (n = 25). The training program group received computer-assisted MCT and linguistic exercises utilizing pen and paper supplemented by cognitive-linguistic exercises for homework. The duration of the MCT intervention program was 15 weeks, and it was administered twice a week. Each session lasted for approximately one hour. Objective measures of episodic memory, delayed memory, word recognition, attention, executive function, processing speed, semantic fluency, and naming were assessed at baseline and after the completion of the program in both groups.

Results

Analysis showed that in controls, delayed memory and executive function had deteriorated over the observation period of 15 weeks, while the training group improved their performance in word recognition, Boston Naming Test (BNT), semantic fluency (SF), clock-drawing test (CDT), digit span forward (DSF), digit span backward (DSB), trail-making test A (TMT A), and trail-making test B (TMT B). Comparison between the training group and the controls showed that MCT had a significant beneficial effect in delayed memory, naming, semantic fluency, visuospatial ability, executive functions, attention, and processing speed.

Conclusions

The study provides evidence of a beneficial effect of MCT with an emphasis on cognitive-language performance of patients with early-stage AD. Considering the limited efficacy of current pharmacological therapies in AD, concurrent computer-based MCT may represent an additional enhancing treatment option in early-stage AD patients.

Diagnostic and prognostic role of semantic processing in preclinical Alzheimer's disease

Relatively spared during most of the timeline of normal aging, semantic memory shows a subtle yet measurable decline even during the pre-clinical stage of Alzheimer's disease. This decline is thought to reflect early neurofibrillary changes and impairment is detectable using tests of language relying on lexical-semantic abilities. A promising approach is the characterization of semantic parameters such as typicality and age of acquisition of words, and propositional density from verbal output. Seminal research like the Nun Study or the analysis of the linguistic decline of famous writers and politicians later diagnosed with Alzheimer's disease supports the early diagnostic value of semantic processing and semantic memory. Moreover, measures of these skills may play an important role for the prognosis of patients with mild cognitive impairment.

Episodic memory and delayed recall are significantly more impaired in younger patients with deficit schizophrenia than in elderly patients with amnestic mild cognitive impairment

BACKGROUND

Both amnestic mild cognitive impairment (aMCI) and schizophrenia, in particular deficit schizophrenia, are accompanied by cognitive impairments. The aim of the present study was to examine the cognitive differences between aMCI and (non)deficit schizophrenia.

METHODS

Towards this end we recruited 60 participants with aMCI, 40 with deficit and 40 with nondeficit schizophrenia and 103 normal volunteers. Cognitive measures were assessed with the Consortium to Establish a Registry for Alzheimer's disease (CERAD) using the Verbal Fluency Test (VFT), Boston Naming Test (BNT), Mini-Mental State Examination (MMSE), Word list memory (WLM), Word list recall (WLRecall) and Word list recognition (WLRecognition). Data were analyzed using multivariate analyses and machine learning techniques.

RESULTS

BNT scores were significantly lower in aMCI as compared with nondeficit schizophrenia. Patients with deficit schizophrenia had significantly lower MMSE, WLM, WL True Recall and WL Recognition than aMCI patients, while WL False Recall was significantly higher in deficit schizophrenia than in aMCI. Neural network importance charts show that deficit and nondeficit schizophrenia are best separated from aMCI using total BNT score, while WLM and WL false Recall follow at a distance.

CONCLUSIONS

Patients with schizophrenia and aMCI have a significantly different neurocognitive profile. Memory impairments, especially in episodic memory, are significantly worse in younger patients with deficit schizophrenia as compared with elderly patients with aMCI, while the latter show more dysnomia than patients with schizophrenia.

Disruption of Semantic Network in Mild Alzheimer's Disease Revealed by Resting-State fMRI

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing.

Connected Language in Late Middle-Aged Adults at Risk for Alzheimer's Disease

Connected language is often impaired among people with Alzheimer's disease (AD), yet little is known about when language difficulties first emerge on the path to a clinical diagnosis. The objective of this study was to determine whether individuals with psychometric (preclinical) evidence of amnestic mild cognitive impairment (pMCI) showed deficits in connected language measures. Participants were 39 pMCI and 39 cognitively healthy (CH) adults drawn from the Wisconsin Registry for Alzheimer's Prevention, who were matched for age, literacy, and sex. Participants completed a connected language task in which they described the Cookie Theft picture from the Boston Diagnostic Aphasia Examination. Language samples were analyzed across three language domains: content, syntactic complexity, and speech fluency. Paired t-tests were used to compare CH and pMCI groups on all variables, and Cohen's d effect sizes were calculated for each comparison. The CH and pMCI groups differed significantly on measures of content (e.g., CH group produced more semantic units, more unique words and had larger idea density, on average, than the pMCI group). The picture description findings are consistent with previous retrospective studies showing semantic language differences in adults with autopsy-confirmed AD. Given that these comparisons are between cognitively healthy and pMCI individuals (before a clinical MCI diagnosis), these findings may represent subtle language difficulty in spontaneous speech, and may be predictive of larger language changes over time.

A Speech Recognition-based Solution for the Automatic Detection of Mild Cognitive Impairment from Spontaneous Speech

BACKGROUND

Even today the reliable diagnosis of the prodromal stages of Alzheimer's disease (AD) remains a great challenge. Our research focuses on the earliest detectable indicators of cognitive decline in mild cognitive impairment (MCI). Since the presence of language impairment has been reported even in the mild stage of AD, the aim of this study is to develop a sensitive neuropsychological screening method which is based on the analysis of spontaneous speech production during performing a memory task. In the future, this can form the basis of an Internet-based interactive screening software for the recognition of MCI.

METHODS

Participants were 38 healthy controls and 48 clinically diagnosed MCI patients. The provoked spontaneous speech by asking the patients to recall the content of 2 short black and white films (one direct, one delayed), and by answering one question. Acoustic parameters (hesitation ratio, speech tempo, length and number of silent and filled pauses, length of utterance) were extracted from the recorded speech signals, first manually (using the Praat software), and then automatically, with an automatic speech recognition (ASR) based tool. First, the extracted parameters were statistically analyzed. Then we applied machine learning algorithms to see whether the MCI and the control group can be discriminated automatically based on the acoustic features.

RESULTS

The statistical analysis showed significant differences for most of the acoustic parameters (speech tempo, articulation rate, silent pause, hesitation ratio, length of utterance, pause-per-utterance ratio). The most significant differences between the two groups were found in the speech tempo in the delayed recall task, and in the number of pauses for the question-answering task. The fully automated version of the analysis process - that is, using the ASR-based features in combination with machine learning - was able to separate the two classes with an F1-score of 78.8%.

CONCLUSION

The temporal analysis of spontaneous speech can be exploited in implementing a new, automatic detection-based tool for screening MCI for the community.

Detection Test for Language Impairments in Adults and the Aged-A New Screening Test for Language Impairment Associated With Neurodegenerative Diseases: Validation and Normative Data

To date, there is no quick screening test that could be used during routine office visits to accurately assess language disorders in neurodegenerative diseases. To fill this important gap, we developed the Detection Test for Language impairments in Adults and the Aged (DTLA), a quick, sensitive, standardized screening test designed to assess language disorders in adults and the elderly individuals. In Study 1, we describe the development of the DTLA. In Study 2, we report data on the DTLA's validity and reliability. Finally, in Study 3, we establish normative data for the test. The DTLA has good convergent and discriminant validity as well as good internal consistency and test-retest reliability. Norms for the DTLA obtained from a sample of 545 healthy, community-dwelling, French-speaking adults from 4 French-speaking countries (Belgium, Canada (Quebec), France, and Switzerland) are provided. The development, validation, and standardization of the DTLA constitute a significant effort to meet the need for a language screening test adapted to neurodegenerative diseases.

A computerized test for the assessment of mild cognitive impairment subtypes in sentence processing

This study examines thesentence processing ability of mild cognitive impairment (MCI) subtypes. In addition to standard MCI neuropsychological tests, an experimental approach was applied to assess language. 133 people (93 MCI/40 controls) participated in novel computerized sentence processing tasks. Results presented statistically significant differences between MCI/controls andMCI subtypes (ANOVA):(a) duration F(2,92) = 19.259,p < .001) in sentence construction; (b) correct answers (F(2, 89) = 8.560,p < .001) and duration (F2,89) = 15.525,p < .001)in text comprehension; (c) correct answers (F(2, 92) = 8.975,p < .001) andduration (F(2, 92) = 4.360,p = .016) in metaphoric sentences comprehension; (d) correct answers (F(2, 92) = 12.836,p < .001) andduration (F(2, 92) = 10.974,p < .001) in verb form generation. Subtle changes in MCIsubtypes could affect sentence processing and provide useful information for cognitive decline risk estimation and screening purposes.

Detecting Dementia Through Interactive Computer Avatars

This paper proposes a new approach to automatically detect dementia. Even though some works have detected dementia from speech and language attributes, most have applied detection using picture descriptions, narratives, and cognitive tasks. In this paper, we propose a new computer avatar with spoken dialog functionalities that produces spoken queries based on the mini-mental state examination, the Wechsler memory scale-revised, and other related neuropsychological questions. We recorded the interactive data of spoken dialogues from 29 participants (14 dementia and 15 healthy controls) and extracted various audiovisual features. We tried to predict dementia using audiovisual features and two machine learning algorithms (support vector machines and logistic regression). Here, we show that the support vector machines outperformed logistic regression, and by using the extracted features they classified the participants into two groups with 0.93 detection performance, as measured by the areas under the receiver operating characteristic curve. We also newly identified some contributing features, e.g., gap before speaking, the variations of fundamental frequency, voice quality, and the ratio of smiling. We concluded that our system has the potential to detect dementia through spoken dialog systems and that the system can assist health care workers. In addition, these findings could help medical personnel detect signs of dementia.

Comparing the effects of clinician and caregiver-administered lexical retrieval training for progressive anomia

There is a growing body of literature indicating that lexical retrieval training can result in improved naming ability in individuals with neurodegenerative disease. Traditionally, treatment is administered by a speech-language pathologist, with little involvement of caregivers or carry-over of practice into the home. This study examined the effects of a lexical retrieval training programme that was implemented first by a clinician and, subsequently, by a trained caregiver. Two dyads, each consisting of one individual with anomia caused by neurodegenerative disease (one with mild cognitive impairment and one with logopenic primary progressive aphasia) and their caregiver, participated in the study. Results indicated medium and large effect sizes for both clinician- and caregiver-trained items, with generalisation to untrained stimuli. Participants reported improved confidence during communication as well as increased use of trained communication strategies after treatment. This study is the first to document that caregiver-administered speech and language intervention can have positive outcomes when paired with training by a clinician. Caregiver-administered treatment may be a viable means of increasing treatment dosage in the current climate of restricted reimbursement, particularly for patients with progressive conditions.

Predicting mild cognitive impairment from spontaneous spoken utterances

INTRODUCTION

Trials in Alzheimer's disease are increasingly focusing on prevention in asymptomatic individuals. We hypothesized that indicators of mild cognitive impairment (MCI) may be present in the content of spoken language in older adults and be useful in distinguishing those with MCI from those who are cognitively intact. To test this hypothesis, we performed linguistic analyses of spoken words in participants with MCI and those with intact cognition participating in a clinical trial.

METHODS

Data came from a randomized controlled behavioral clinical trial to examine the effect of unstructured conversation on cognitive function among older adults with either normal cognition or MCI (ClinicalTrials.gov: NCT01571427). Unstructured conversations (but with standardized preselected topics across subjects) were recorded between interviewers and interviewees during the intervention sessions of the trial from 14 MCI and 27 cognitively intact participants. From the transcription of interviewees recordings, we grouped spoken words using Linguistic Inquiry and Word Count (LIWC), a structured table of words, which categorizes 2500 words into 68 different word subcategories such as positive and negative words, fillers, and physical states. The number of words in each LIWC word subcategory constructed a vector of 68 dimensions representing the linguistic features of each subject. We used support vector machine and random forest classifiers to distinguish MCI from cognitively intact participants.

RESULTS

MCI participants were distinguished from those with intact cognition using linguistic features obtained by LIWC with 84% classification accuracy which is well above chance 60%.

DISCUSSION

Linguistic analyses of spoken language may be a powerful tool in distinguishing MCI subjects from those with intact cognition. Further studies to assess whether spoken language derived measures could detect changes in cognitive functions in clinical trials are warrented.

Is "Learning" episodic memory? Distinct cognitive and neuroanatomic correlates of immediate recall during learning trials in neurologically normal aging and neurodegenerative cohorts

Although commonly interpreted as a marker of episodic memory during neuropsychological exams, relatively little is known regarding the neurobehavior of "total learning" immediate recall scores. Medial temporal lobes are clearly associated with delayed recall performances, yet immediate recall may necessitate networks beyond traditional episodic memory. We aimed to operationalize cognitive and neuroanatomic correlates of total immediate recall in several aging syndromes. Demographically-matched neurologically normal adults (n=91), individuals with Alzheimer's disease (n=566), logopenic variant primary progressive aphasia (PPA) (n=34), behavioral variant frontotemporal dementia (n=97), semantic variant PPA (n=71), or nonfluent/agrammatic variant PPA (n=39) completed a neurocognitive battery, including the CVLT-Short Form trials 1-4 Total Immediate Recall; a majority subset also completed a brain MRI. Regressions covaried for age and sex, and MMSE in cognitive and total intracranial volume in neuroanatomic models. Neurologically normal adults demonstrated a heterogeneous pattern of cognitive associations with total immediate recall (executive, speed, delayed recall), such that no singular cognitive or neuroanatomic correlate uniquely predicted performance. Within the clinical cohorts, there were syndrome-specific cognitive and neural associations with total immediate recall; e.g., semantic processing was the strongest cognitive correlate in svPPA (partial r=0.41), while frontal volumes was the only meaningful neural correlate in bvFTD (partial r=0.20). Medial temporal lobes were not independently associated with total immediate recall in any group (ps>0.05). Multiple neurobehavioral systems are associated with "total learning" immediate recall scores that importantly differ across distinct clinical syndromes. Conventional memory networks may not be sufficient or even importantly contribute to total immediate recall in many syndromes. Interpreting learning scores as equivalent to episodic memory may be erroneous.

Connected Speech in Neurodegenerative Language Disorders: A Review

Language assessment has a crucial role in the clinical diagnosis of several neurodegenerative diseases. The analysis of extended speech production is a precious source of information encompassing the phonetic, phonological, lexico-semantic, morpho-syntactic, and pragmatic levels of language organization. The knowledge about the distinctive linguistic variables identifying language deficits associated to different neurodegenerative diseases has progressively improved in the last years. However, the heterogeneity of such variables and of the way they are measured and classified limits any generalization and makes the comparison among studies difficult. Here we present an exhaustive review of the studies focusing on the linguistic variables derived from the analysis of connected speech samples, with the aim of characterizing the language disorders of the most prevalent neurodegenerative diseases, including primary progressive aphasia, Alzheimer's disease, movement disorders, and amyotrophic lateral sclerosis. A total of 61 studies have been included, considering only those reporting group analysis and comparisons with a group of healthy persons. This review first analyzes the differences in the tasks used to elicit connected speech, namely picture description, story narration, and interview, considering the possible different contributions to the assessment of different linguistic domains. This is followed by an analysis of the terminologies and of the methods of measurements of the variables, indicating the need for harmonization and standardization. The final section reviews the linguistic domains affected by each different neurodegenerative disease, indicating the variables most consistently impaired at each level and suggesting the key variables helping in the differential diagnosis among diseases. While a large amount of valuable information is already available, the review highlights the need of further work, including the development of automated methods, to take advantage of the richness of connected speech analysis for both research and clinical purposes.

Mapping visual dominance in human sleep

Sleep is a universal behavior, essential for humans and animals alike to survive. Its importance to a person's physical and mental health cannot be overstated. Although lateralization of function is well established in the lesion, split-brain and task based neuroimaging literature, and more recently in functional imaging studies of spontaneous fluctuations of the fMRI BOLD signal during wakeful rest, it is unknown if these asymmetries are present during sleep. We investigated hemispheric asymmetries in the global brain signal during non-REM sleep. Here we show that increasing sleep depth is accompanied by an increasing rightward asymmetry of regions in visual cortex including primary bilaterally and in the right hemisphere along the lingual gyrus and middle temporal cortex. In addition, left hemisphere language regions largely maintained their leftward asymmetry during sleep. Right hemisphere attention related regions expressed a more complicated relation with some regions maintaining a rightward asymmetry while this was lost in others. These results suggest that asymmetries in the human brain are state dependent.

Natural products against Alzheimer's disease: Pharmaco-therapeutics and biotechnological interventions

Alzheimer's disease (AD) is a severe, chronic and progressive neurodegenerative disease associated with memory and cognition impairment ultimately leading to death. It is the commonest reason of dementia in elderly populations mostly affecting beyond the age of 65. The pathogenesis is indicated by accumulation of the amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFT) in brain tissues and hyperphosphorylation of tau protein in neurons. The main cause is considered to be the formation of reactive oxygen species (ROS) due to oxidative stress. The current treatment provides only symptomatic relief by offering temporary palliative therapy which declines the rate of cognitive impairment associated with AD. Inhibition of the enzyme acetylcholinesterase (AChE) is considered as one of the major therapeutic strategies offering only symptomatic relief and moderate disease-modifying effect. Other non-cholinergic therapeutic approaches include antioxidant and vitamin therapy, stem cell therapy, hormonal therapy, use of antihypertensive or lipid-lowering medications and selective phosphodiesterase (PDE) inhibitors, inhibition of β-secretase and γ-secretase and Aβ aggregation, inhibition of tau hyperphosphorylation and intracellular NFT, use of nonsteroidal anti-inflammatory drugs (NSAIDs), transition metal chelators, insulin resistance drugs, etanercept, brain-derived neurotrophic factor (BDNF) etc. Medicinal plants have been reported for possible anti-AD activity in a number of preclinical and clinical trials. Ethnobotany, being popular in China and in the Far East and possibly less emphasized in Europe, plays a substantial role in the discovery of anti-AD agents from botanicals. Chinese Material Medica (CMM) involving Chinese medicinal plants has been used traditionally in China in the treatment of AD. Ayurveda has already provided numerous lead compounds in drug discovery and many of these are also undergoing clinical investigations. A number of medicinal plants either in their crude forms or as isolated compounds have exhibited to reduce the pathological features associated with AD. In this present review, an attempt has been made to elucidate the molecular mode of action of various plant extracts, phytochemicals and traditional herbal formulations investigated against AD as reported in various preclinical and clinical tests. Herbal synergism often found in polyherbal formulations were found effective to combat disease heterogeneity as found in complex pathogenesis of AD. Finally a note has been added to describe biotechnological improvement, genetic and genomic resources and mathematical and statistical techniques for empirical model building associated with anti-AD plant secondary metabolites and their source botanicals.

Patients with Mild Alzheimer's Disease Fail When Using Their Working Memory: Evidence from the Eye Tracking Technique

Patients with Alzheimer's disease (AD) develop progressive language, visuoperceptual, attentional, and oculomotor changes that can have an impact on their reading comprehension. However, few studies have examined reading behavior in AD, and none have examined the contribution of predictive cueing in reading performance. For this purpose we analyzed the eye movement behavior of 35 healthy readers (Controls) and 35 patients with probable AD during reading of regular and high-predictable sentences. The cloze predictability of words N - 1, and N + 1 exerted an influence on the reader's gaze duration. The predictabilities of preceding words in high-predictable sentences served as task-appropriate cues that were used by Control readers. In contrast, these effects were not present in AD patients. In Controls, changes in predictability significantly affected fixation duration along the sentence; noteworthy, these changes did not affect fixation durations in AD patients. Hence, only in healthy readers did predictability of upcoming words influence fixation durations via memory retrieval. Our results suggest that Controls used stored information of familiar texts for enhancing their reading performance and imply that contextual-word predictability, whose processing is proposed to require memory retrieval, only affected reading behavior in healthy subjects. In AD patients, this loss reveals impairments in brain areas such as those corresponding to working memory and memory retrieval. These findings might be relevant for expanding the options for the early detection and monitoring in the early stages of AD. Furthermore, evaluation of eye movements during reading could provide a new tool for measuring drug impact on patients' behavior.

Linguistic Features Identify Alzheimer's Disease in Narrative Speech

BACKGROUND

Although memory impairment is the main symptom of Alzheimer's disease (AD), language impairment can be an important marker. Relatively few studies of language in AD quantify the impairments in connected speech using computational techniques.

OBJECTIVE

We aim to demonstrate state-of-the-art accuracy in automatically identifying Alzheimer's disease from short narrative samples elicited with a picture description task, and to uncover the salient linguistic factors with a statistical factor analysis.

METHODS

Data are derived from the DementiaBank corpus, from which 167 patients diagnosed with "possible" or "probable" AD provide 240 narrative samples, and 97 controls provide an additional 233. We compute a number of linguistic variables from the transcripts, and acoustic variables from the associated audio files, and use these variables to train a machine learning classifier to distinguish between participants with AD and healthy controls. To examine the degree of heterogeneity of linguistic impairments in AD, we follow an exploratory factor analysis on these measures of speech and language with an oblique promax rotation, and provide interpretation for the resulting factors.

RESULTS

We obtain state-of-the-art classification accuracies of over 81% in distinguishing individuals with AD from those without based on short samples of their language on a picture description task. Four clear factors emerge: semantic impairment, acoustic abnormality, syntactic impairment, and information impairment.

CONCLUSION

Modern machine learning and linguistic analysis will be increasingly useful in assessment and clustering of suspected AD.

Speech rhythm alterations in Spanish-speaking individuals with Alzheimer's disease

Rhythm is the speech property related to the temporal organization of sounds. Considerable evidence is now available for suggesting that dementia of Alzheimer's type is associated with impairments in speech rhythm. The aim of this study is to assess the use of an automatic computerized system for measuring speech rhythm characteristics in an oral reading task performed by 45 patients with Alzheimer's disease (AD) compared with those same characteristics among 82 healthy older adults without a diagnosis of dementia, and matched by age, sex and cultural background. Ranges of rhythmic-metric and clinical measurements were applied. The results show rhythmic differences between the groups, with higher variability of syllabic intervals in AD patients. Signal processing algorithms applied to oral reading recordings prove to be capable of differentiating between AD patients and older adults without dementia with an accuracy of 87% (specificity 81.7%, sensitivity 82.2%), based on the standard deviation of the duration of syllabic intervals. Experimental results show that the syllabic variability measurements extracted from the speech signal can be used to distinguish between older adults without a diagnosis of dementia and those with AD, and may be useful as a tool for the objective study and quantification of speech deficits in AD.

Accuracy of a Brief Neuropsychological Battery for the Diagnosis of Dementia and Mild Cognitive Impairment: An Analysis of the NEDICES Cohort

Early separation of mild cognitive impairment (MCI) from normal aging and mild cases of dementia remains a challenge, especially in the general population. We aimed to analyze the diagnostic accuracy of a brief neuropsychological battery (BNB) in dementia and MCI cases from the Neurological Disorders in Central Spain (NEDICES) population-based cohort study. We screened 3,891 participants into dementia and non-dementia groups using a two-phase procedure: screening (MMSE-37 and Pfeffer-11) and clinical diagnosis by specialists (DSM-IV criteria). We selected subsequently a subsample of dementia (n = 98), MCI (n = 71), and cognitively healthy (n = 123) participants matched in socio-demographic characteristics. The clinical validity of each test of the BNB was determined by the area under the ROC curve. We determined the best combination of tests to classify individuals into the diagnostic groups by logistic regression analyses. The results indicated that dementia and MCI groups could be best discriminated from the healthy control group on the basis of their scores on the semantic verbal fluency and delayed recall subtests of the BNB. As for discriminating the MCI group from the dementia group, immediate recall tasks (stories and pictures) yielded the highest level of accuracy. Probably the most interesting finding is that the verbal fluency task consistently allowed discrimination among the diagnostic groups. Overall, subtests of the BNB are more accurate in differentiating dementia patients than MCI patients from healthy controls. In this population-based sample, a more fine-grained discrimination that includes MCI patients should follow a systematic subtest-wise analysis and decision.

Vocabulary Size in Speech May Be an Early Indicator of Cognitive Impairment

Little is known about the relationship between mild cognitive impairment (MCI) and changes to language abilities. Here, we used the revised Hasegawa Dementia Scale (HDS-R) to identify suspected MCI in elderly individuals. We then analyzed written and spoken narratives to compare the language abilities between study participants with and without MCI in order to explore the relationship between cognitive and language abilities, and to identify a possible indicator for the early detection of MCI and dementia. We recruited 22 people aged 74 to 86 years (mean: 78.32 years; standard deviation: 3.36). The participants were requested to write and talk about one of the happiest events in their lives. Based on HDS-R scores, we divided the participants into 2 groups: the MCI Group comprised 8 participants with a score of 26 or lower, while the Healthy Group comprised 14 participants with a score of 27 or higher. The transcriptions of both written and spoken samples for each participant were used in the measurement of NLP-based language ability scores. Our analysis showed no significant differences in writing abilities between the 2 groups in any of the language ability scores. However, analysis of the spoken narrative showed that the MCI Group had a significantly larger vocabulary size. In addition, analysis of a metric that signified the gap in content between the spoken and written narratives also revealed a larger vocabulary size in the MCI Group. Individuals with early-stage MCI may be engaging in behavior to conceal their deteriorating cognition, thereby leading to a temporary increase in their active spoken vocabulary. These results indicate the possible detection of early stages of reduced cognition before dementia onset through the analysis of spoken narratives.

Risk for Mild Cognitive Impairment Is Associated With Semantic Integration Deficits in Sentence Processing and Memory

OBJECTIVES

We examined the degree to which online sentence processing and offline sentence memory differed among older adults who showed risk for amnestic and nonamnestic varieties of mild cognitive impairment (MCI), based on psychometric classification.

METHOD

Participants (N = 439) read a series of sentences in a self-paced word-by-word reading paradigm for subsequent recall and completed a standardized cognitive test battery. Participants were classified into 3 groups: unimpaired controls (N = 281), amnestic MCI (N = 94), or nonamnestic MCI (N = 64).

RESULTS

Relative to controls, both MCI groups had poorer sentence memory and showed reduced sentence wrap-up effects, indicating reduced allocation to semantic integration processes. Wrap-up effects predicted subsequent recall in the control and nonamnestic groups. The amnestic MCI group showed poorer recall than the nonamnestic MCI group, and only the amnestic MCI group showed no relationship between sentence wrap-up and recall.

DISCUSSION

Our findings suggest that psychometrically defined sub-types of MCI are associated with unique deficits in sentence processing and can differentiate between the engagement of attentional resources during reading and the effectiveness of engaging attentional resources in producing improved memory.

Association between the Cardio-Ankle Vascular Index and Executive Function in Community-Dwelling Elderly People

AIM

The aim of this study was to investigate the cross-sectional association between arterial stiffness (AS) measured with the cardio-ankle vascular index (CAVI) and executive function in community-dwelling elderly people.

METHODS

Subjects were 140 community-dwelling elderly people who participated in the study at Kobe, Japan during the period of August-September 2014, of which 126 (mean age±SD: 73.2±6.1, female: 67.5%) met the inclusion criteria and completed the study. Age, sex, body mass index, global cognition, existence of chronic disease, medication, smoking history, and years of education were assessed. The degree of AS was assessed using CAVI. Executive function was assessed using the Category Word Fluency Test (CWFT), Letter Word Fluency Test (LWFT), and Digit Symbol Substitution Test (DSST). We used a correlation analysis and multiple linear regression analysis to investigate whether higher CAVI was independently associated with lower executive function.

RESULTS

In the univariate analysis, higher mean CAVI correlated with lower CWFT (rho=－0.21, p=0.020), LWFT (rho=－0.32, p＜0.001), and DSST (rho=－0.31, p＜0.001). In the multivariate analysis, higher mean CAVI was associated with lower LWFT (β=－0.21, p=0.046) after adjusting for confounding factors, although there was no association with CWFT (β=－0.05, p=0.61) and DSST (β=－0.06, p=0.51).

CONCLUSIONS

We found that high CAVI was associated with lower LWFT. These results suggest that arterial stiffness is associated with lower performance in phonemic fluency.

Detection of mild Alzheimer's disease and mild cognitive impairment from elderly speech: Binary discrimination using logistic regression

In this research, we have developed a novel data-mining approach for detection of cognitive impairment, SPCIR (Speech Prosody-Based Cognitive Impairment Rating), which can discriminate between mild cognitive impairment and mild Alzheimer's disease from elderly using prosodic sign extracted from elderly speech during questionnaire test. This paper proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection using receiver operating characteristic (ROC) curve analysis, and reports the sensitivity and specificity of SPCIR for diagnosis (control; mild cognitive impairment/mild Alzheimer's disease).

Processing complex pseudo-words in mild cognitive impairment: The interaction of preserved morphological rule knowledge with compromised cognitive ability

Mild cognitive impairment (MCI) affects the cognitive performance of elderly adults. However, the level of severity is not high enough to be diagnosed with dementia. Previous research reports subtle language impairments in individuals with MCI specifically in domains related to lexical meaning. The present study used both off-line (grammaticality judgment) and on-line (lexical decision) tasks to examine aspects of lexical processing and how they are affected by MCI. 21 healthy older adults and 23 individuals with MCI saw complex pseudo-words that violated various principles of word formation in Slovenian and decided if each letter string was an actual word of their language. The pseudo-words ranged in their degree of violability. A task effect was found, with MCI performance to be similar to that of healthy controls in the off-line task but different in the on-line task. Overall, the MCI group responded slower than the elderly controls. No significant differences were observed in the off-line task, while the on-line task revealed a main effect of Violation type, a main effect of Group and a significant Violation × Group interaction reflecting a difficulty for the MCI group to process pseudo-words in real time. That is, while individuals with MCI seem to preserve morphological rule knowledge, they experience additional difficulties while processing complex pseudo-words. This was attributed to an executive dysfunction associated with MCI that delays the recognition of ungrammatical formations.

More Delusions May Be Observed in Low-Proficient Multilingual Alzheimer's Disease Patients

Background

Language impairment and behavioral symptoms are both common phenomena in dementia patients. In this study, we investigated the behavioral symptoms in dementia patients with different language backgrounds. Through this, we aimed to propose a possible connection between language and delusion.

Methods

We recruited 21 patients with Alzheimer’s disease (AD), according to the DSM-IV and NINCDS-ADRDA criteria, from the memory clinic of the Cardinal Tien Hospital in Taipei, Taiwan. They were classified into two groups: 11 multilinguals who could speak Japanese, Taiwanese and Mandarin Chinese, and 10 bilinguals who only spoke Taiwanese and Mandarin Chinese. There were no differences between age, education, disease duration, disease severity, environment and medical care between these two groups. Comprehensive neuropsychological examinations, including Clinical Dementia Rating (CDR), Mini-Mental Status Examination (MMSE), Cognitive Abilities Screening Instrument (CASI), Verbal fluency, Chinese version of the Boston naming test (BNT) and the Behavioral Pathology in Alzheimer’s Disease Rating Scale (BEHAVE-AD), were administered.

Results

The multilingual group showed worse results on the Boston naming test. Other neuropsychological tests, including the MMSE, CASI and Verbal fluency, were not significantly different. More delusions were noted in the multilingual group. Three pairs of subjects were identified for further examination of their differences. These three cases presented the typical scenario of how language misunderstanding may cause delusions in multilingual dementia patients. Consequently, more emotion and distorted ideas may be induced in the multilinguals compared with the MMSE-matched controls.

Conclusion

Inappropriate mixing of language or conflict between cognition and emotion may cause more delusions in these multilingual patients. This reminds us that delusion is not a pure biological outcome of brain degeneration. Although the cognitive performance was not significantly different between our groups, language may still affect their delusion.

Speaking in Alzheimer's Disease, is That an Early Sign? Importance of Changes in Language Abilities in Alzheimer's Disease

It is known that Alzheimer’s disease (AD) influences the temporal characteristics of spontaneous speech. These phonetical changes are present even in mild AD. Based on this, the question arises whether an examination based on language analysis could help the early diagnosis of AD and if so, which language and speech characteristics can identify AD in its early stage. The purpose of this article is to summarize the relation between prodromal and manifest AD and language functions and language domains. Based on our research, we are inclined to claim that AD can be more sensitively detected with the help of a linguistic analysis than with other cognitive examinations. The temporal characteristics of spontaneous speech, such as speech tempo, number of pauses in speech, and their length are sensitive detectors of the early stage of the disease, which enables an early simple linguistic screening for AD. However, knowledge about the unique features of the language problems associated with different dementia variants still has to be improved and refined.

Potentials and limits to enhance cognitive functions in healthy and pathological aging by tDCS

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that is increasingly used in research and clinical settings to enhance the effects of cognitive training. In our present review, we will first summarize studies using tDCS alone and in combination with cognitive training in older adults and patients with Alzheimer’s dementia (AD). We will also review one study (Meinzer et al., 2014c) that showed an improvement in cognitive performance during anodal tDCS over the left inferior frontal cortex in patients with mild cognitive impairment (MCI) which is regarded as a prodromal stage of AD. Although promising short-term results have been reported, evidence from randomized controlled trials (RCTs) with sufficient sample sizes is scarce. In addition, stimulation protocols (in terms of intensity, duration, and repetition of stimulation) that lead to sustained improvements in outcome measures relevant for daily life still remain to be established. Following, we will discuss modulating factors such as technical parameters as well as the question whether there are specific cognitive functions (e.g., learning, memory consolidation, executive control) which are more amenable to tDCS enhancement than others. Finally, we will highlight future directions and limitations in this field and emphasize the need to conduct RCTs to establish efficacy of interventions for activities of daily life for a given patient population.

Specific cognitive functions and depressive symptoms as predictors of activities of daily living in older adults with heterogeneous cognitive backgrounds

Cognitive functioning influences activities of daily living (ADL). However, studies reporting the association between ADL and neuropsychological performance show inconsistent results regarding what specific cognitive domains are related to each specific functional domains. Additionally, whether depressive symptoms are associated with a worse functional performance in older adults is still under explored. We investigated if specific cognitive domains and depressive symptoms would affect different aspects of ADL. Participants were 274 older adults (96 normal aging participants, 85 patients with mild cognitive impairment, and 93 patients probable with mild Alzheimer's disease dementia) with low formal education (∼4 years). Measures of ADL included three complexity levels: Self-care, Instrumental-Domestic, and Instrumental-Complex. The specific cognitive functions were evaluated through a factorial strategy resulting in four cognitive domains: Executive Functions, Language/Semantic Memory, Episodic Memory, and Visuospatial Abilities. The Geriatric Depression Scale measured depressive symptoms. Multiple linear regression analysis showed executive functions and episodic memory as significant predictors of Instrumental-Domestic ADL, and executive functions, episodic memory and language/semantic memory as predictors of Instrumental-Complex ADL (22 and 28% of explained variance, respectively). Ordinal regression analysis showed the influence of specific cognitive functions and depressive symptoms on each one of the instrumental ADL. We observed a heterogeneous pattern of association with explained variance ranging from 22 to 38%. Different instrumental ADL had specific cognitive predictors and depressive symptoms were predictive of ADL involving social contact. Our results suggest a specific pattern of influence depending on the specific instrumental daily living activity.

Deficits in narrative discourse elicited by visual stimuli are already present in patients with mild cognitive impairment

Language batteries used to assess the skills of elderly individuals, such as naming and semantic verbal fluency, present some limitations in differentiating healthy controls from patients with amnestic mild cognitive impairment (a-MCI). Deficits in narrative discourse occur early in dementia caused by Alzheimer's disease (AD), and the narrative discourse abilities of a-MCI patients are poorly documented. The present study sought to propose and evaluate parameters for investigating narrative discourse in these populations. After a pilot study of 30 healthy subjects who served as a preliminary investigation of macro- and micro-linguistic aspects, 77 individuals (patients with AD and a-MCI and a control group) were evaluated. The experimental task required the participants to narrate a story based on a sequence of actions visually presented. The Control and AD groups differed in all parameters except narrative time and the total number of words recalled. The a-MCI group displayed mild discursive difficulties that were characterized as an intermediate stage between the Control and AD groups' performances. The a-MCI and Control groups differed from the AD group with respect to global coherence, discourse type and referential cohesion. The a-MCI and AD groups were similar to one another but differed from the Control group with respect to the type of words recalled, the repetition of words in the same sentence, the narrative structure and the inclusion of irrelevant propositions in the narrative. The narrative parameter that best distinguished the three groups was the speech effectiveness index. The proposed task was able to reveal differences between healthy controls and groups with cognitive decline. According to our findings, patients with a-MCI already present narrative deficits that are characterized by mild discursive difficulties that are less severe than those found in patients with AD.

Review of information and communication technology devices for monitoring functional and cognitive decline in Alzheimer's disease clinical trials

Detecting and monitoring early cognitive impairment in Alzheimer's disease (AD) is a significant need in the field of AD therapeutics. Successful AD clinical trial designs have to overcome challenges related to the subtle nature of early cognitive changes. Continuous unobtrusive assessments using Information and Communication Technology (ICT) devices to capture markers of intra-individual change over time to assess cognitive and functional disability therefore offers significant benefits. We review the literature and provide an overview on randomized clinical trials in AD that use intelligent systems to monitor functional decline, as well as strengths, weaknesses, and future directions for the use of ICTs in a new generation of AD clinical trials.

Semantic profiles in mild cognitive impairment associated with Alzheimer's and Parkinson's diseases

The temporal and the prefrontal cortices have different roles in semantic information processing: the temporal lobe is where knowledge is stored (Graham and Hodges, 1997), whereas the prefrontal cortex is more specifically involved in executive aspects of semantic processing. Relatively little is known about the semantic profiles of mild cognitive impairment (MCI) in Alzheimer's disease (AD) and Parkinson's disease (PD). This observational study investigated naming and semantic questionnaire performances in three groups of subjects: 10 patients with the amnestic-type MCI prodrome of AD (aMCI), 10 patients with early-stage executive-type MCI in PD (MCI-PD), and 10 normal subjects. The MCI-PD subjects demonstrated inferior performances on a semantic questionnaire, whereas the aMCI group displayed modest difficulties in a naming task. These differences may be explained by topographical differences in pathological involvement. Since the frontal areas are more functionally impaired in PD, we hypothesize that the semantic deficit may be a consequence of a deficiency in control of semantic processing. On the other hand, the semantic deficit in aMCI may be related to a lexical-semantic storage dysfunction resulting from pathological involvement of the temporal lobe.

Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease

Background

To evaluate the interest of using automatic speech analyses for the assessment of mild cognitive impairment (MCI) and early-stage Alzheimer's disease (AD).

Methods

Healthy elderly control (HC) subjects and patients with MCI or AD were recorded while performing several short cognitive vocal tasks. The voice recordings were processed, and the first vocal markers were extracted using speech signal processing techniques. Second, the vocal markers were tested to assess their “power” to distinguish among HC, MCI, and AD. The second step included training automatic classifiers for detecting MCI and AD, using machine learning methods and testing the detection accuracy.

Results

The classification accuracy of automatic audio analyses were as follows: between HCs and those with MCI, 79% ± 5%; between HCs and those with AD, 87% ± 3%; and between those with MCI and those with AD, 80% ± 5%, demonstrating its assessment utility.

Conclusion

Automatic speech analyses could be an additional objective assessment tool for elderly with cognitive decline.

Impairment of homonymous processing in Alzheimer's disease

An important issue in research on language is how concepts are represented and associated with each other in the brain. Many investigations have focused on language ambiguity and the phenomenon of homonymy in which a single lexical item, presenting the same form, is related to different meanings. Our study aims to test the hypothesis that weak association of meaning characterizing homonyms may be especially prone to brain damage. To verify this hypothesis a test of attribution of the meaning of homonymous words, the Humpty Dumpty (HD) test, was applied to 50 patients with Alzheimer's disease (AD) and 50 healthy subjects. Results show that AD patients are impaired in the HD test in an early phase of disease and that performance correlates with naming ability and phonological fluency. The data are in keeping with a growing body of literature that supports dual impairment to the semantic system in AD, i.e., to semantic knowledge and active processing and access to the semantic field. The evaluation of the ability to resolve homonymous ambiguity, using the HD test, may provide a useful and quick clinical tool to detect the anomalies of the semantic network linked to either a loss of the core system where meaning of words is stored or an impairment of the access to an intact semantic representation.

Preparing a persian version of kimberley indigenous cognitive assessment for assessing the cognitive problems of illiterate geriatric patients

BACKGROUND

The rate of dementia is increasing rapidly. With the recognized high rate of illiteracy among geriatric patients, preparing an appropriate device for special screening among the low-educated elderly seems to be necessary. The aim of this study is to prepare and assess the psychometric properties of the Persian version of the Kimberley Indigenous Cognitive Assessment (KICA) in Iranian adults, in 2012.

MATERIALS AND METHODS

One hundred and eighty elders participated in this psychometric study. Ninety patients with dementia according to the Diagnostic and Statistical Manual of Mental Disorders, fourth Edition, Text Revision (DSM-IV-TR) criteria, who had been admitted to Geriatrics and Neurology in some of the private clinics in Esfahan, Iran, in 2012, were selected. The rest of the participants were normal persons with the same demographic characteristics as the dementia group, who were selected from the patients' acquaintances and from the Retired Personnel Organization. The statistical tools were the KICA scale, Mini-Mental State Examination (MMSE), and Modified Mini-Mental State Examination (3MSE).

RESULTS

The best clinical cutoff point of the test was 31, with a sensitivity of 92% and specificity of 88%. The Cronbach's alpha coefficient of KICA was 0.93. Among the KICA's subscales, the maximum Cronbach's alpha coefficient belonged to Praxis (α = 0.933) and the minimum one belonged to Delayed Recall (α = 0.927). The correlation coefficients of the KICA score with MMSE and 3MSE were 0.58 and 0.57, respectively.

CONCLUSION

The KICA test has been seen to be a reliable and valid tool to assess cognitive impairment in the aged people of Iran. The KICA test can be used as a cognitive assessment test for distinguishing patients with dementia, especially illiterate ones from other healthy people in Iran.