Clustering Home Activity Distributions for Automatic Detection of Mild Cognitive Impairment in Older Adults

The public health implications of growing numbers of older adults at risk for dementia places pressure on identifying dementia at its earliest stages so as to develop proactive management plans. The prodromal dementia phase commonly identified as mild cognitive impairment is an important target for this early detection of impending dementia amenable to treatment. In this paper, we propose a method for home-based automatic detection of mild cognitive impairment in older adults through continuous monitoring via unobtrusive sensing technologies. Our method is composed of two main stages: a training stage and a test stage. For training, room activity distributions are estimated for each subject using a time frame of ω weeks, and then affinity propagation is employed to cluster the activity distributions and to extract exemplars to represent the different emerging clusters. For testing, room activity distributions belonging to a test subject with unknown cognitive status are compared to the extracted exemplars and get assigned the labels of the exemplars that result in the smallest normalized Kullbak-Leibler divergence. The labels of the activity distributions are then used to determine the cognitive status of the test subject. Using the sensor and clinical data pertaining to 85 homes with single occupants, we were able to automatically detect mild cognitive impairment in older adults with an F_0.5 score of 0.856. Also, we were able to detect the non-amnestic sub-type of mild cognitive impairment in older adults with an F_0.5 score of 0.958.

Gray and White Matter Degenerations in Subjective Memory Impairment: Comparisons with Normal Controls and Mild Cognitive Impairment

Subjective memory impairment (SMI) is now increasingly recognized as a risk factor of progression to dementia. This study investigated gray and white matter changes in the brains of SMI patients compared with normal controls and mild cognitive impairment (MCI) patients. We recruited 28 normal controls, 28 subjects with SMI, and 29 patients with MCI aged 60 or older. We analyzed gray and white matter changes using a voxel-based morphometry (VBM), hippocampal volumetry and regions of interest in diffusion tensor imaging (DTI). DTI parameters of corpus callosum and cingulum in SMI showed more white matter changes compared with those in normal controls, they were similar to those in MCI except in the hippocampus, which showed more degenerations in MCI. In VBM, SMI showed atrophy in the frontal, temporal, and parietal lobes compared with normal controls although it was not as extensive as that in MCI. Patients with SMI showed gray and white matter degenerations, the changes were distinct in white matter structures. SMI might be the first presenting symptom within the Alzheimer's disease continuum when combined with additional risk factors and neurodegenerative changes.

IMPROVING THE CLINICAL DETECTION OF LEWY BODY DEMENTIA WITH THE LEWY BODY COMPOSITE RISK SCORE

INTRODUCTION

Dementia with Lewy bodies (DLB) is a challenge to diagnose, particularly outside of expert centers with long delays in diagnosis leading to significant burden to patients and caregivers. While consensus criteria have excellent specificity, there is no standardized way to assess symptoms reducing sensitivity. We developed the Lewy Body Composite Risk Score (LBCRS) from autopsy-verified cases to improve the ability to detect DLB in clinic and research populations.

METHODS

The LBCRS was tested in a consecutive series of 256 patients compared with the Clinical Dementia Rating and gold standard measures of cognition, motor symptoms, function, and behavior. Psychometric properties including floor and ceiling effects; concurrent, construct, and known-groups validity, and internal consistency of the LBCRS were determined. Receiver operator characteristic (ROC) curves assessed the ability of LBCRS to differentiate: (a) DLB from Alzheimer's disease (AD); (b) DLB from all dementia, and (c) Mild cognitive impairment (MCI) due to DLB from MCI due to AD. The LBCRS was completed independent of the clinical evaluation.

RESULTS

Mean LBCRS scores were significantly different between DLB and AD (6.1±2.0 vs. 2.4±1.3, p<.001) and between MCI-DLB vs MCI-AD (3.2±0.9 vs. 1.0±0.8, p<.001). The LBCRS was able to discriminate DLB from other causes of dementia. Using a cut-off score of 3, areas under ROC for DLB vs. AD = 0.93 (0.89-0.98), and for MCI-DLB vs. MCI-AD = 0.96 (0.91-1.0).

DISCUSSION

The LBCRS increases diagnostic probability that Lewy body pathology is contributing to the dementia syndrome and should improve clinical detection and enrollment for clinical trials.

Mild Cognitive Impairment Subtypes in Older People With Depressive Symptoms: Relationship With Clinical Variables and Hippocampal Change

AIMS

To examine the rates and clinical characteristics of mild cognitive impairment (MCI) in older people with depressive symptoms and to determine the relative contribution of hippocampal volume and MCI to memory change.

METHOD

One hundred and fifty-two participants with lifetime Major Depression and remitted or mild symptoms and 28 healthy controls underwent psychiatric and neuropsychological assessments. Magnetic resonance imaging was also conducted in a subset of the patients (n = 81) and healthy controls (n = 18).

RESULTS

MCI was diagnosed in 75.7% of the patients and was associated with increasing age, medical burden, vascular risk factors, later age of depression onset and smaller hippocampi. Multiple regression showed that both hippocampal volume and MCI diagnosis mediate memory performance in depression.

CONCLUSIONS

MCI occurs in older adults with a history of depression and is not simply due to symptom severity. Memory change is linked to underlying hippocampal atrophy in this patient group.

A multicenter study of the early detection of synaptic dysfunction in Mild Cognitive Impairment using Magnetoencephalography-derived functional connectivity

Synaptic disruption is an early pathological sign of the neurodegeneration of Dementia of the Alzheimer's type (DAT). The changes in network synchronization are evident in patients with Mild Cognitive Impairment (MCI) at the group level, but there are very few Magnetoencephalography (MEG) studies regarding discrimination at the individual level. In an international multicenter study, we used MEG and functional connectivity metrics to discriminate MCI from normal aging at the individual person level. A labeled sample of features (links) that distinguished MCI patients from controls in a training dataset was used to classify MCI subjects in two testing datasets from four other MEG centers. We identified a pattern of neuronal hypersynchronization in MCI, in which the features that best discriminated MCI were fronto-parietal and interhemispheric links. The hypersynchronization pattern found in the MCI patients was stable across the five different centers, and may be considered an early sign of synaptic disruption and a possible preclinical biomarker for MCI/DAT.

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Across centers reliable abnormalities in the neuronal network organization of MCI patients

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These findings are consistent with the view that AD may, in its earliest stages, represent a disconnection syndrome.

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A high rate of classification accuracy in a blind study, especially for individuals who were cognitively normal

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All these suggest that MEG may be a useful marker of preclinical synaptic disruption.

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The hypersynchronization found in MCI patients may represent a compensatory response.

Nicotinic ligands as multifunctional agents for the treatment of neuropsychiatric disorders

The challenges associated with developing more effective treatments for neurologic and psychiatric illness such as Alzheimer's disease and schizophrenia are considerable. Both the symptoms and the pathophysiology of these conditions are complex and poorly understood and the clinical presentations across different patients can be very heterogeneous. Moreover, it has become apparent that the reductionist approach to drug discovery for these illnesses that has dominated the field for decades (i.e., the development of highly selective compounds or other treatment modalities focused on a very specific pathophysiologic target) has not been widely successful. Accordingly, a variety of new strategies have emerged including the development of "multitarget-directed ligands" (MTDLs), the development and/or identification of compounds that exhibit "multifunctional" activity (e.g., pro-cognitive plus neuroprotective, pro-cognitive plus antipsychotic activity), "repurposing" strategies for existing compounds that have other clinical indications, and novel "adjunctive" treatment strategies that might enhance the efficacy of the currently available treatments. Interestingly, a variety of ligands at nicotinic acetylcholine receptors (nAChRs) appear to have the potential to fulfill one or more of these desirable properties (i.e., multifunctional, repurposing, or adjunctive treatment potential). The purpose of this review (while not all-inclusive) is to provide an overview of a variety of nAChR ligands that demonstrate potential in these categories, particularly, "multifunctional" properties. Due to their densities in the mammalian brain and the amount of literature available, the review will focus on ligands of the high affinity α4β2 nAChR and the low affinity α7 nAChR.

"Are we ready for robots that care for us?" Attitudes and opinions of older adults toward socially assistive robots

Socially Assistive Robots (SAR) may help improve care delivery at home for older adults with cognitive impairment and reduce the burden of informal caregivers. Examining the views of these stakeholders on SAR is fundamental in order to conceive acceptable and useful SAR for dementia care. This study investigated SAR acceptance among three groups of older adults living in the community: persons with Mild Cognitive Impairment, informal caregivers of persons with dementia, and healthy older adults. Different technology acceptance questions related to the robot and user characteristics, potential applications, feelings about technology, ethical issues, and barriers and facilitators for SAR adoption, were addressed in a mixed-method study. Participants (n = 25) completed a survey and took part in a focus group (n = 7). A functional robot prototype, a multimedia presentation, and some use-case scenarios provided a base for the discussion. Content analysis was carried out based on recorded material from focus groups. Results indicated that an accurate insight of influential factors for SAR acceptance could be gained by combining quantitative and qualitative methods. Participants acknowledged the potential benefits of SAR for supporting care at home for individuals with cognitive impairment. In all the three groups, intention to use SAR was found to be lower for the present time than that anticipated for the future. However, caregivers and persons with MCI had a higher perceived usefulness and intention to use SAR, at the present time, than healthy older adults, confirming that current needs are strongly related to technology acceptance and should influence SAR design. A key theme that emerged in this study was the importance of customizing SAR appearance, services, and social capabilities. Mismatch between needs and solutions offered by the robot, usability factors, and lack of experience with technology, were seen as the most important barriers for SAR adoption.

Brain structural, functional, and cognitive correlates of recent versus remote autobiographical memories in amnestic Mild Cognitive Impairment

Deficits in autobiographical memory appear earlier for recent than for remote life periods over the course of Alzheimer's disease (AD). The present study aims to further our understanding of this graded effect by investigating the cognitive and neural substrates of recent versus remote autobiographical memories in patients with amnestic Mild Cognitive Impairment (aMCI) thanks to an autobiographical fluency task. 20 aMCI patients and 25 Healthy elderly Controls (HC) underwent neuropsychological tests assessing remote (20-to-30 years old) and recent (the ten last years) autobiographical memory as well as episodic and semantic memory, executive function and global cognition. All patients also had a structural MRI and an FDG-PET scan. Correlations were assessed between each autobiographical memory score and the other tests as well as grey matter volume and metabolism. Within the aMCI, performances for the remote period correlated with personal semantic memory and episodic memory retrieval whereas performances for the recent period only correlated with episodic memory retrieval. Neuroimaging analyses revealed significant correlations between performances for the remote period and temporal pole and temporo-parietal cortex volumes and anterior cingulate gyrus metabolism, while performances for the recent period correlated with hippocampal volume and posterior cingulate, medial prefrontal and hippocampus metabolism. The brain regions related with the retrieval of events from the recent period showed greater atrophy/hypometabolism in aMCI patients compared to HC than those involved in remote memories. Recall of recent memories essentially relies on episodic memory processes and brain network while remote memories also involve other processes such as semantic memory. This is consistent with the semanticization of memories with time and may explain the better resistance of remote memory in AD.

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We studied cognitive correlates of recent and remote autobiographical memories in aMCI.

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We evaluated brain structural and functional correlates of each period of life.

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Recent memories rely on episodic memory processes and brain network.

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Remote memories also involve other processes such as semantic memory.

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These findings contribute to explain the better resistance of remote memory in aMCI.

Scaling Cognitive Domains of the Montreal Cognitive Assessment: An Analysis Using the Partial Credit Model

The psychometric properties of the Montreal Cognitive Assessment (MoCA) were examined by using the Partial Credit Model. The study sample included 897 participants who were distributed into two main subgroups: (I) the clinical group (90 patients with Mild Cognitive Impairment, 90 patients with Alzheimer's disease, 33 patients with Frontotemporal Dementia, and 34 patients with Vascular dementia, whose diagnoses were previously established according to a consensus that was reached by a multidisciplinary team, based on the international criteria) and (II) the healthy group (composed of 650 cognitively healthy community dwellers). The results show (i) an overall good fit for both the items and the persons' values, (ii) high variability for the cognitive performance level of the cognitive domains (ranging between 1.90 and -3.35, where "Short-term Memory" was the most difficult item and "Spatial Orientation" was the easiest item) and between the subjects on the scale, (iii) high reliability for the estimation of the persons' values, (iv) good discriminant validity and high diagnostic utility, and (v) a minimal differential item functioning effect related to of pathology, gender, age, and educational level. MoCA and its cognitive domains are suitable measures to use for screening the cognitive status of cognitively healthy subjects and patients with cognitive impairment.

Boosting Classification Accuracy of Diffusion MRI Derived Brain Networks for the Subtypes of Mild Cognitive Impairment Using Higher Order Singular Value Decomposition

Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD), and around 10-15% of people with MCI develop AD each year. More recently, MCI has been further subdivided into early and late stages, and there is interest in identifying sensitive brain imaging biomarkers that help to differentiate stages of MCI. Here, we focused on anatomical brain networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying early versus late MCI.

Translating cognitive and everyday activity deficits into cognitive interventions in mild dementia and mild cognitive impairment

OBJECTIVE

Mild dementia is marked by deficits in cognition and everyday activities. However, few studies have translated findings from both areas of functioning into effective cognitive rehabilitation. The purpose of this review was to critically evaluate the existing literature on the type and success of interventions and on their extent of use of cognitive theory. Given the limited evidence base in this population, further insights were obtained from studies on mild cognitive impairment (MCI), which involves fewer cognitive and everyday functioning problems than dementia.

METHODS

From the literature searches, 11 studies on mild dementia and three studies on MCI were obtained. Studies were only included if the interventions either targeted instrumental activities of daily living or activities of daily living directly or as an outcome measure or if the interventions focused on real-life aspects not captured in the standardised daily activities. For inclusion, patients needed a diagnosis of dementia or MCI, and Mini-Mental State Examination scores had to be above 17 for mild dementia.

RESULTS

The majority of interventions indicated improved everyday activity performance in early dementia and MCI. Focusing on individual, as opposed to global, daily activities appeared to be an important determinant of intervention success in mild dementia but not in MCI. However, few attempts had been made to develop interventions grounded in evidence-based models.

CONCLUSIONS

This review highlights the need for further translation of the understanding of cognitive and everyday activity deficits into successful interventions for daily activities in MCI and early dementia. Hence, research is first required to link individual activities with cognitive domains.

Brain metabolic maps in Mild Cognitive Impairment predict heterogeneity of progression to dementia

[¹⁸F]FDG-PET imaging has been recognized as a crucial diagnostic marker in Mild Cognitive Impairment (MCI), supporting the presence or the exclusion of Alzheimer's Disease (AD) pathology. A clinical heterogeneity, however, underlies MCI definition. In this study, we aimed to evaluate the predictive role of single-subject voxel-based maps of [¹⁸F]FDG distribution generated through statistical parametric mapping (SPM) in the progression to different dementia subtypes in a sample of 45 MCI. Their scans were compared to a large normal reference dataset developed and validated for comparison at single-subject level. Additionally, Aβ42 and Tau CSF values were available in 34 MCI subjects. Clinical follow-up (mean 28.5 ± 7.8 months) assessed subsequent progression to AD or non-AD dementias. The SPM analysis showed: 1) normal brain metabolism in 14 MCI cases, none of them progressing to dementia; 2) the typical temporo-parietal pattern suggestive for prodromal AD in 15 cases, 11 of them progressing to AD; 3) brain hypometabolism suggestive of frontotemporal lobar degeneration (FTLD) subtypes in 7 and dementia with Lewy bodies (DLB) in 2 subjects (all fulfilled FTLD or DLB clinical criteria at follow-up); and 4) 7 MCI cases showed a selective unilateral or bilateral temporo-medial hypometabolism without the typical AD pattern, and they all remained stable. In our sample, objective voxel-based analysis of [¹⁸F]FDG-PET scans showed high predictive prognostic value, by identifying either normal brain metabolism or hypometabolic patterns suggestive of different underlying pathologies, as confirmed by progression at follow-up. These data support the potential usefulness of this SPM [¹⁸F]FDG PET analysis in the early dementia diagnosis and for improving subject selection in clinical trials based on MCI definition.

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We used an optimized voxel-based single-subject [¹⁸F]FDG-PET analysis

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We showed different hypometabolic patterns (AD and non-AD) underlying MCI condition

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Heterogeneous PET profiles predicted progression into specific dementia subtypes.

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Statistical analyses showed high positive and negative post-test probability values.

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CSF findings agreed with [¹⁸F]FDG-PET imaging in single cases.

Coronary artery disease and plasma apolipoprotein E4 in mild cognitive impairment

BACKGROUND

Atherosclerosis and apolipoprotein E4 (APOE4) are known risks for Dementia. We sought to evaluate the relationship between coronary atherosclerosis and APOE4 with mild cognitive impairment (MCI).

METHODS

In a case-control study, subjects with age more than 60 years and recent coronary angiography were evaluated by mini-mental state examination and neuropsychiatry unit cognitive assessment tool (NUCOG) to find the patients with MCI (n = 40) and the controls with normal cognition (n = 40). Coronary angiography records were re-assessed to find the severity of coronary artery disease by the Gensini scores. Plasma levels of APOE4 were measured.

RESULTS

There were no-significant difference between the 2 groups regarding the plasma APOE4 levels (P = 0.706) and the Gensini scores (P = 0.236). Associations between the Gensini scores and the NUCOG scores in the MCI group (r = -0.196, P = 0.225) and the control group (r = 0.189, P = 0.243) were not significant. However, the interaction effect between the Gensini and the NUCOG scores based on allocation to the control or the patient groups showed statistically significant difference (F(1,67) = 4.84, P = 0.031).

CONCLUSION

Although atherosclerosis has been considered as known risk factor for dementia and MCI, this study could not reveal that coronary atherosclerosis-related to declining in cognitive functioning. There was no significant association between plasma APOE4 levels and MCI.

Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis

For the last decade, it has been shown that neuroimaging can be a potential tool for the diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), and also fusion of different modalities can further provide the complementary information to enhance diagnostic accuracy. Here, we focus on the problems of both feature representation and fusion of multimodal information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). To our best knowledge, the previous methods in the literature mostly used hand-crafted features such as cortical thickness, gray matter densities from MRI, or voxel intensities from PET, and then combined these multimodal features by simply concatenating into a long vector or transforming into a higher-dimensional kernel space. In this paper, we propose a novel method for a high-level latent and shared feature representation from neuroimaging modalities via deep learning. Specifically, we use Deep Boltzmann Machine (DBM)(2), a deep network with a restricted Boltzmann machine as a building block, to find a latent hierarchical feature representation from a 3D patch, and then devise a systematic method for a joint feature representation from the paired patches of MRI and PET with a multimodal DBM. To validate the effectiveness of the proposed method, we performed experiments on ADNI dataset and compared with the state-of-the-art methods. In three binary classification problems of AD vs. healthy Normal Control (NC), MCI vs. NC, and MCI converter vs. MCI non-converter, we obtained the maximal accuracies of 95.35%, 85.67%, and 74.58%, respectively, outperforming the competing methods. By visual inspection of the trained model, we observed that the proposed method could hierarchically discover the complex latent patterns inherent in both MRI and PET.

Development of a psychometrically equivalent short form of the Face-Name Associative Memory Exam for use along the early Alzheimer's disease trajectory

Neuropsychologists are developing more challenging and specific tests to detect early and subtle changes in cognition related to preclinical Alzheimer's disease (AD). The 16-item Face-Name Associative Memory Exam (FNAME-16) is a challenging paired associative memory test able to detect subtle memory changes associated with biomarker evidence of preclinical AD. However, as individuals progress along the AD trajectory, measures that are sensitive at the preclinical stage may become too challenging by the stage of Mild Cognitive Impairment (MCI). Our goal was to develop a modified version of the face-name and face-occupation paired associative memory task (FNAME-12) with fewer stimuli and additional learning trials suitable for use in MCI. We administered the FNAME-12A, an alternate version FNAME 12B, the original FNAME-16, and a series of other neuropsychological measures to 65 clinically normal (CN) older adults (aged 65 to 85) and a subsample characterized by MCI (n = 18). The FNAME-12 exhibited psychometric equivalence with the FNAME-16 (r = .77, p < .001) and was correlated with other measures of episodic and semantic memory. The alternate form, FNAME-12B, was highly correlated with FNAME-12A (r = .76, p < .001). Mean performance on the FNAME 12A, stratified by education, was generated. The task could be completed by our MCI group yet remained challenging in the CN group, providing evidence for its utility along the AD trajectory.

[Awareness disorders in Alzheimer's disease and in mild cognitive impairment]

INTRODUCTION

Awareness disorders in Alzheimer's disease still remains unclear despite much research regarding this phenomenon. Papers report various and contrasted results with varying frequency from one study to another. Hence, the interest in awareness in Alzheimer's disease remains limited. Nevertheless, this symptom is closely associated with caregivers' burden and increases the patient's dependency, since the patient is unable to avoid dangers, requiring some care services or institutionalization The purpose of this current review is to recall the main neuro-anatomical and theoretical basis of awareness disorders, and to highlight the recent findings in Alzheimer's disease and in its pre-clinical stages.

METHOD

With this in mind, we have conducted a non-exhaustive search using the pubmed online database to collect the most important reviews and the most recent findings regarding awareness disorders in Mild Cognitive Impairment (MCI) and/or in Alzheimer's disease.

LITERATURE FINDINGS

In Alzheimer's disease, the links between awareness disorders and other variables, such as severity of dementia or depression, change from one study to the other and do not permit one to understand whether unawareness is an intrinsic or extrinsic reaction to the pathological process itself. Recent results suggest executive, cognitive and behavioral correlates more than psychopathological correlates, although the latter cannot be excluded. In Mild Cognitive Impairment, studies show varied results. Some studies report that patients suffering from Mild Cognitive Impairment can be compared to healthy control subjects and both groups have better awareness than patients with Alzheimer's disease. However, other studies show contrary results and awareness disorders might be a predictor of conversion from Mild Cognitive Impairment to dementia, as with apathy, in which the ability to cope with difficulties represents one of the main features.

DISCUSSION

These controversial results are due to the heterogeneity of Alzheimer patients and in particular of MCI patients, but also to various conceptions of awareness disorders in Alzheimer's disease; none of them, however, taking into account all its diversity and complexity. Thus, neurological approaches underline neuropsychological dysfunctions linked to right frontal and/or hemispheric damage but are based on brain injury or strokes, which are events that differ greatly from a neurodegenerative disease involving progressive cognitive, emotional and social disturbances. Psychiatric approaches have taken into account the various aspects of insight, which before were often forbidden and reduced to a categorical point of view, and so could contribute to a better understanding of awareness disorders in Alzheimer's disease. However, these aspects have been conceptualized for psychiatric patients, suffering from positive symptoms, where compliance in treatment is the central key. Insight in neurological diseases is more focused on negative symptoms and generally concerns a basic perception of impairments in mainly cognitive domains. Moreover, modeling has often opposed neurological and psychological mechanisms, so awareness disorders are out of scope of a primary and secondary symptomatology. Although some authors have proposed to take into account these two mechanisms (unawareness and denial), clinical practice has shown that it was impossible to distinguish them both. Finally, some social cognitive approaches are able to demonstrate that there is no correlation between severity of dementia and awareness disorders. Nevertheless, the Self-concept, underlying this point of view, does not permit distinguishing neuropsychological from psycho-social factors. Moreover, only one evaluation tool based on Self-modeling in Alzheimer's disease exists, and to conceptualize Self in a specific pathology does not permit the comparison of this pathology to others or to healthy control subjects. So, the authors present the multidimensional model proposed by Clare et al., and some perspectives to stimulate future research, and perform potential meta-analyses.

Communication Difficulty and Relevant Interventions in Mild Cognitive Impairment: Implications for Neuroplasticity

Mild Cognitive Impairment (MCI) represents a critical point for controlling cognitive decline. Patterns of communication difficulty have been observed in patients with MCI and warrant examination and management. The present systematic review examined (1) characteristics of communication difficulty in MCI by focusing on two domains: expressive and receptive communication, and (2) cognitive interventions that addressed communication difficulties in individuals with MCI. Of the 28 observational studies we reviewed, expressive and receptive communications were generally impaired in individuals with MCI, compared to their healthy counterparts. However, only one of seven interventions effectively improved communication related outcomes. We finished the paper with a discussion about how neuroplasticity influences communication abilities in individuals with MCI to inform the future development of interventions for communication difficulty.

Patient and carer views on participating in clinical trials for prodromal Alzheimer's disease and mild cognitive impairment

OBJECTIVE

There is great interest in conducting clinical trials of disease-modifying therapies in the prodromal (early, pre-dementia), asymptomatic stages of Alzheimer's disease. Diagnostic biomarker tests offer a means of identifying prodromal patients, but it is unclear how potential participants feel about their use. Deciding whether to take part in a clinical trial is a complex process in which eligible participants must balance risks and discomforts against uncertain benefits. We sought to explore the views of potential participants through qualitative research methods.

METHODS

Focus groups with people with early memory problems, current and former family carers explored attitudes towards participating in clinical trials in the prodromal stages of the disease, using an example of anti-amyloid antibody-therapy (immunotherapy), which are currently in development.

RESULTS

Despite the complexities involved, almost all participants had a clear idea about whether they, personally, would like to take part. Many were highly motivated to obtain an unambiguous diagnosis, regardless of their desire to participate in a clinical trial. Participants expressed minimal concern regarding the risk of adverse events associated with immunotherapy, whereas certain tests and trial procedures provoked greater anxiety. People with memory problems were found to assess the study demands in relation to their own priorities and circumstances.

CONCLUSIONS

The priorities of patients might be different to clinicians and those who design and regulate clinical trials. Patient views can be used to inform the ethical debate around the disclosure of biomarker status, the design of clinical trials and the content of trial information.

Staging dementia from symptom profiles on a care partner website

BACKGROUND

The World Wide Web allows access to patient/care partner perspectives on the lived experience of dementia. We were interested in how symptoms that care partners target for tracking relate to dementia stage, and whether dementia could be staged using only these online profiles of targeted symptoms.

OBJECTIVES

To use clinical data where the dementia stage is known to develop a model that classifies an individual's stage of dementia based on their symptom profile and to apply this model to classify dementia stages for subjects from a Web-based dataset.

METHODS

An Artificial Neural Network (ANN) was used to identify the relationships between the dementia stages and individualized profiles of people with dementia obtained from the 60-item SymptomGuide (SG). The clinic-based training dataset (n=320), with known dementia stages, was used to create an ANN model for classifying stages in Web-based users (n=1930).

RESULTS

The ANN model was trained in 66% of the 320 Memory Clinic patients, with the remaining 34% used to test its accuracy in classification. Training and testing staging distributions were not significantly different. In the 1930 Web-based profiles, 309 people (16%) were classified as having mild cognitive impairment, 36% as mild dementia, 29% as moderate, and 19% as severe. In both the clinical and Web-based symptom profiles, most symptoms became more common as the stage of dementia worsened (eg, mean 5.6 SD 5.9 symptoms in the MCI group versus 11.9 SD 11.3 in the severe). Overall, Web profiles recorded more symptoms (mean 7.1 SD 8.0) than did clinic ones (mean 5.5 SD 1.8). Even so, symptom profiles were relatively similar between the Web-based and clinical datasets.

CONCLUSION

Symptoms targeted for online tracking by care partners of people with dementia can be used to stage dementia. Even so, caution is needed to assure the validity of data collected online as the current staging algorithm should be seen as an initial step.

Oral trail making task as a discriminative tool for different levels of cognitive impairment and normal aging

The Trail Making Test (TMT) is a useful measure of executive dysfunction in elderly subjects. This study aims to investigate the discriminative validity of the oral version of the TMT (OTMT), which can be administered to subjects with visual or motor disabilities, in elderly patients with Mild Cognitive Impairment (MCI; n = 30), Alzheimer's disease (AD; n = 30), and healthy controls (HCs; n = 25). The WAIS-R Digit Span Backwards Subscale, written form of the Trail Making Task, the Clock Drawing Test, the AD Assessment Scale-Cognitive Subscale, and the OTMT were also administered to all participants in order to examine the concurrent validity of the OTMT. The OTMT part B discriminated between patients with MCI, AD, and HC correctly. The OTMT completion time was not correlated with age, but was negatively correlated with education. In conclusion, the OTMT (mostly part B) is a valid and practical measurement tool for different levels of cognitive impairment, especially for patients with visual or motor disabilities for whom the classical written form is not feasible.

Octodon degus: a model for the cognitive impairment associated with Alzheimer's disease

Octodon degus (O. degus) is a diurnal rodent that spontaneously develops several physiopathological conditions, analogous in many cases to those experienced by humans. In light of this, O. degus has recently been identified as a very valuable animal model for research in several medical fields, especially those concerned with neurodegenerative diseases in which risk is associated with aging. Octodon degus spontaneously develops β-amyloid deposits analogous to those observed in some cases of Alzheimer's disease (AD). Moreover, these deposits are thought to be the key feature for AD diagnosis, and one of the suggested causes of cell loss and cognitive deficit. This review aims to bring together information to support O. degus as a valuable model for the study of AD.

The impact of early dementia diagnosis and intervention on informal caregivers

In the absence of disease modifying therapies for dementia, the question rises what the benefits are of an early dementia diagnosis for patients and their caregivers. This paper reviews the caregiver perspective in dementia and addresses the question what the consequences are of promoting earlier dementia diagnosis. An early diagnosis offers caregivers the opportunity to advance the process of adaptation to the caregiver role. Caregivers that are better able to adapt to the changes that characterize dementia, feel more competent to care and experience less psychological problems. However, drawbacks of an early diagnosis may outweigh the benefits if people are left with a diagnosis but little support. There is convincing evidence that multicomponent caregiver interventions in the mild to moderate dementia stages are effective to improve caregiver well-being and delay institutionalization. However, there still exist a gap between the improved possibilities to diagnose people in the predementia stage versus the scarce knowledge on intervention effects in this very early stage. This stresses the urgent need for more research on early caregiver interventions that enhance role adaptation and that include long-term follow-up and cost-effectiveness evaluation. Early interventions may help caregivers in anticipating and accepting the future care role and transitions, with the increased possibility that caregivers can still involve the patient in the decision making process. As levels of stress and burden are still low in the predementia stage it provides excellent opportunities to empower the resources of caregivers.

A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI)

Alzheimer's disease (AD) is the most common cause of dementia in older adults. By the time an individual has been diagnosed with AD, it may be too late for potential disease modifying therapy to strongly influence outcome. Therefore, it is critical to develop better diagnostic tools that can recognize AD at early symptomatic and especially pre-symptomatic stages. Mild cognitive impairment (MCI), introduced to describe a prodromal stage of AD, is presently classified into early and late stages (E-MCI, L-MCI) based on severity. Using a graph-based semi-supervised learning (SSL) method to integrate multimodal brain imaging data and select valid imaging-based predictors for optimizing prediction accuracy, we developed a model to differentiate E-MCI from healthy controls (HC) for early detection of AD. Multimodal brain imaging scans (MRI and PET) of 174 E-MCI and 98 HC participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were used in this analysis. Mean targeted region-of-interest (ROI) values extracted from structural MRI (voxel-based morphometry (VBM) and FreeSurfer V5) and PET (FDG and Florbetapir) scans were used as features. Our results show that the graph-based SSL classifiers outperformed support vector machines for this task and the best performance was obtained with 66.8% cross-validated AUC (area under the ROC curve) when FDG and FreeSurfer datasets were integrated. Valid imaging-based phenotypes selected from our approach included ROI values extracted from temporal lobe, hippocampus, and amygdala. Employing a graph-based SSL approach with multimodal brain imaging data appears to have substantial potential for detecting E-MCI for early detection of prodromal AD warranting further investigation.

Judgment in Mild Cognitive Impairment and Alzheimer's disease

Judgment is the capacity to make decisions after considering available information, contextual factors, possible solutions and probable outcomes. Our aim was to investigate previous research studies regarding assessment of judgment in older adults with different degrees of cognitive impairment. To this end, a search of Pubmed and Lilacs electronic databases for studies published from January 1990 until August 2011 in English, Spanish and Portuguese was carried out. The terms used were "judgment" combined with the terms "dementia" or "Mild Cognitive Impairment" (MCI) or "Alzheimer's disease" (AD). Some studies showed that MCI and AD patients had impaired judgment. There is a lack of specific methods to measure judgment capacity, and data on judgment abilities in older adults with MCI and dementia are scarce. No studies with specific measures of judgment capacity in other dementias were found.

Using functional Magnetic Resonance Imaging to differentiate between healthy aging subjects, Mild Cognitive Impairment, and Alzheimer's patients

BACKGROUND

Alzheimer's disease is the most common form of dementia which is still difficult to be differentiated from other types of brain disorders. Moreover, Mild Cognitive Impairment refers to the presence of cognitive impairments that is not severe enough to meet the criteria of Alzheimer's, and its diagnosis in early stages is so critical. There is currently no distinct method available for diagnosing Alzheimer's or Mild Cognitive Impairment, and their diagnosis needs a combination of different methods and assessments.

METHODS

The aim of this study was to evaluate the effectiveness of functional Magnetic Resonance Imaging (fMRI) in differentiating between Alzheimer's, Mild Cognitive Impairment (MCI) and healthy aging. To prove fMRI's ability, resting-state brain activation patterns between these three groups of subjects were compared using Independent Component Analysis (ICA) algorithm. Forty age- and sex-matched subjects, 15 elderly, 11 MCI and 14 Alzheimer's subjects were examined.

RESULTS

The results showed that during a certain resting-state session, healthy aging brain benefits from larger area and greater intensity of activation (compared with MCI and Alzheimer's group) in Posterior Cingulate Cortex (PCC) region of the brain, as part of Default Mode Network.

CONCLUSIONS

This difference in activation pattern can be used as a diagnostic criterion in using fMRI for differentiating between Alzheimer's Disease (AD), MCI and healthy aging.

S-TOFHLA in mild Alzheimer's disease and Mild Cognitive Impairment patients as a measure of functional literacy: Preliminary study

The greatest difficulty in diagnosing cognitive loss in our population is the diversity of its education which has a broad spectrum ranging from illiteracy, functional illiteracy and different degrees of literacy, even in those with the same level of schooling.

Cognitive training in older adults with Mild Cognitive Impairment: Impact on cognitive and functional performance

Aging is associated with cognitive decline, yet this does not prevent older adults from finding ways to compensate for age-related deficits. Earlier studies have shown that cognitively unimpaired older adults can benefit from training programs. The efficacy of cognitive interventions among older adults without dementia but with cognitive decline (mild cognitive impairment, MCI) has not yet been widely tested.

Comparison of performance in neuropsychological tests in amnestic Mild Cognitive Impairment and Alzheimer's disease patients

Mild Cognitive Impairment (MCI) can be an intermediate state between normality and dementia in some patients. An early diagnosis, through neuropsychological assessment, could identify individuals at risk of developing dementia.

Objective

To verify differences in performance on neuropsychological tests among controls, amnestic MCI (aMCI) and Alzheimer's disease (AD) patients.

Methods

Sixty-eight AD patients (mean age 73.77±7.24; mean schooling 9.04±4.83; 40 women and 28 men), 34 aMCI patients (mean age 74.44±7.05; mean schooling 12.35±4.01; 20 women) and 60 controls (mean age 68.90±7.48; mean schooling 10.72±4.74; 42 women) were submitted to a neuropsychological assessment composed of tasks assessing executive functions, language, constructive abilities, reasoning and memory.

Results

There were statistically significant differences in performance across all tests among control, aMCI and AD groups, and also between only controls and AD patients. On comparing control and aMCI groups, we found statistically significant differences in memory tasks, except for immediate recall of Visual Reproduction. There were also statistically significant differences between aMCI and AD groups on tasks of constructive and visuoperceptual abilities, attention, language and memory, except for delayed recall of Visual Reproduction.

Conclusions

Neuropsychological assessment was able to discriminate aMCI from AD patients in almost all tests except for delayed recall of Visual Reproduction, visual organization (Hooper) and executive functions (WCST); and discriminate controls from AD patients in all tests, and controls from aMCI patients in all memory tests except for immediate recall of Visual Reproduction.

Differential patterns of hypoperfusion in subtypes of mild cognitive impairment

In this study the regional cerebral blood flow (rCBF) pattern of three Mild Cognitive Impairment (MCI) subtypes was measured with SPECT in 60 patients (nineteen with an amnestic deficit, sixteen with disexecutive deficits, and twenty five with mild multidomain deficits) and compared with that of 15 healthy matched older adults. The amnestic MCI subgroup showed significant hypoperfusion in the left hippocampus, parahippocampal gyrus and fronto-parieto-temporal areas. The disexecutive subgroup had significant hypoperfusion of the left superior, medial frontal and cingulate cortex. The multidomain subgroup had similar perfusion deficits to the amnestic subgroup, with an additional deficit in the left posterior cingulate gyrus. This study found differential patterns of hypoperfusion in MCI subtypes. Since all patients who progressed to dementia converted to probable Alzheimer's disease, the different rCBF patterns most likely reflect the neuropathological heterogeneity at onset and differences in disease stage.