Social capabilities in Alzheimer's patients

Patients with stage-I (very mild and mild) Alzheimer's disease were asked to participate in a Dictator Game, a type of game in which a subject has to decide how to allocate a certain amount of money between himself and another person. The game enables the experimenter to examine the influence of social norms and social preferences on the decision-making process. When the results of treatments involving Alzheimer's disease patients were compared with those of identical treatments involving patients with mild cognitive impairment or healthy control subjects, with similar ages and social backgrounds, no statistically significant difference was found. This finding suggests that stage-I Alzheimer's disease patients may be as capable of making decisions involving social norms and preferences as other individuals of their age. Whatever brain structures are affected by the disease, they do not appear to influence, at this early stage, the neural basis for cooperation-enhancing social interactions.

Social capabilities in Alzheimer’s patients

Patients with stage-I (very mild and mild) Alzheimer s disease were asked to participatein a Dictator Game, a type of game in which a subject has to decide how to allocate acertain amount of money between himself and another person. The game enables theexperimenter to examine the influence of social norms and social preferences on thedecision-making process. When the results of treatments involving Alzheimer s diseasepatients were compared with those of identical treatments involving patients with mildcognitive impairment or healthy control subjects, with similar ages and socialbackgrounds, no statistically significant difference was found. This finding suggests thatstage-I Alzheimer s disease patients may be as capable of making decisions involvingsocial norms and preferences as other individuals of their age. Whatever brain structuresare affected by the disease, they do not appear to influence, at this early stage, the neuralbasis for cooperation-enhancing social interactions.

Improving the Quality of EEG Data in Patients With Alzheimers Disease Using ICA

Does Independent Component Analysis (ICA) denature EEG signals? We applied ICA to two groups of subjects (mild Alzheimer patients and control subjects). The aim of this study was to examine whether or not the ICA method can reduce both group di®erences and within-subject variability. We found that ICA diminished Leave-One- Out root mean square error (RMSE) of validation (from 0.32 to 0.28), indicative of the reduction of group di®erence. More interestingly, ICA reduced the inter-subject variability within each group (¾ = 2:54 in the ± range before ICA, ¾ = 1:56 after, Bartlett p = 0.046 after Bonfer- roni correction). Additionally, we present a method to limit the impact of human error (' 13:8%, with 75.6% inter-cleaner agreement) during ICA cleaning, and reduce human bias. These ¯ndings suggests the novel usefulness of ICA in clinical EEG in Alzheimer's disease for reduction of subject variability.

MemoryCon : Una aplicació d'Android per a potenciar la memòria dels malalts d'Alzheimer

This Degree Project is the development of an application for mobile devices with Android operating system. It is based on a generic manual with exercises for Alzheimer patients. The aim of the manual -and therefore, of the video game- is simply to be helpful in stimulating cognitive abilities of patients, ie players.

Calbindin D-28K and parvalbumin immunoreactivity in the frontal cortex in patients with frontal lobe dementia of non-Alzheimer type associated with amyotrophic lateral sclerosis

The morphology and distribution of local-circuit neurons (interneurons) were examined, by calbindin D-28k and parvalbumin immunocytochemistry, in the frontal cortex (area 8) in two patients with frontal lobe dementia of non-Alzheimer type associated with classical amyotrophic lateral sclerosis (ALS), and in seven normal cases. The density of calbindin D-28k immunoreactive cells was dramatically reduced in ALS patients, but the density of parvalbumin-immunoreactive neurons was preserved. Decreased density of calbindin D-28k-immunoreactive neurons, which are mainly located in the upper cortical layers, may interfere with the normal processing of cortico-cortical connections, whereas integrity of parvalbumin-immunoreactive cells may be associated with the preservation of the major inhibitory intracortical circuits in patients with frontal lobe dementia.

Involvement of Dab1 in APP processing and [beta]-amyloid deposition in sporadic Creutzfeldt-Jakob patients.

Alzheimer"s disease and prion pathologies (e.g., Creutzfeldt-Jakob disease) display profound neural lesions associated with aberrant protein processing and extracellular amyloid deposits. For APP processing, emerging data suggest that the adaptor protein Dab1 plays a relevant role in regulating its intracellular trafficking and secretase-mediated proteolysis. Although some data have been presented, a putative relationship between human prion diseases and Dab1/APP interactions is lacking. Therefore, we have studied the putative relation between Dab1, APP processing and Aβ deposition, targets in sCJD cases. Our biochemical results categorized two groups of sCJD cases, which also correlated with PrPsc types 1 and 2 respectively. One group, with PrPsc type 1 showed increased Dab1 phosphorylation, and lower βCTF production with an absence of Aβ deposition. The second sCJD group, which carried PrPsc type 2, showed lower levels of Dab1 phosphorylation and βCTF production, similar to control cases. Relevant Aβ deposition in the second sCJD group was measured. Thus, a direct correlation between Dab1 phosphorylation, Aβ deposition and PrPsc type in human sCJD is presented for the first time.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

APP processing and b-amyloid deposition in sporadic Creutzfeldt-Jakob patients is dependent on Dab1.

Alzheimer"s disease and prion pathologies (e.g., Creutzfeldt-Jakob disease (CJD)) display profound neural lesions associated with aberrant protein processing and extracellular amyloid deposits. Dab1 has been implicated in the regulation of Amyloid Precursor Protein (APP), but a direct link between human prion diseases and Dab1/APP interactions has not been published. Here we examined this putative relationship in seventeen cases of sporadic CJD (sCJD) post mortem. Biochemical analyses of brain tissue revealed two groups, which also correlated with PrPsc types 1 and 2. One group, with PrPsc type 1 showed increased Dab1 phosphorylation, and lower CTF production with an absence of A deposition. The second sCJD group, which carried PrPsc type 2, showed lower levels of Dab1 phosphorylation and CTF production, and A deposition. Thus, the present observations suggest a correlation between Dab1-phosphorylation, A deposition and PrPsc type in sCJD.

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.

Dendritic Spine Abnormalities in Hippocampal CA1 Pyramidal Neurons Underlying Memory Deficits in the SAMP8 Mouse Model of Alzheimer's Disease

SAMP8 is a strain of mice with accelerated senescence. These mice have recently been the focus of attention as they show several alterations that have also been described in Alzheimer"s disease (AD) patients. The number of dendritic spines, spine plasticity, and morphology are basic to memory formation. In AD, the density of dendritic spines is severely decreased. We studied memory alterations using the object recognition test. We measured levels of synaptophysin as a marker of neurotransmission and used Golgi staining to quantify and characterize the number and morphology of dendritic spines in SAMP8 mice and in SAMR1 as control animals. While there were no memory differences at 3 months of age, the memory of both 6- and 9-month-old SAMP8 mice was impaired in comparison with age-matched SAMR1 mice or young SAMP8 mice. In addition, synaptophysin levels were not altered in young SAMP8 animals, but SAMP8 aged 6 and 9 months had less synaptophysin than SAMR1 controls and also less than 3-month-old SAMP8 mice. Moreover, while spine density remained stable with age in SAMR1 mice, the number of spines started to decrease in SAMP8 animals at 6 months, only to get worse at 9 months. Our results show that from 6 months onwards SAMP8 mice show impaired memory. This age coincides with that at which the levels of synaptophysin and spine density decrease. Thus, we conclude that together with other studies that describe several alterations at similar ages, SAMP8 mice are a very suitable model for studying AD.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Successful therapies for Alzheimer's disease: why so many in animal models and none in humans?

Peering into the field of Alzheimer's disease (AD), the outsider realizes that many of the therapeutic strategies tested (in animal models) have been successful. One also may notice that there is a deficit in translational research, i.e., to take a successful drug in mice and translate it to the patient. Efforts are still focused on novel projects to expand the therapeutic arsenal to 'cure mice.' Scientific reasons behind so many successful strategies are not obvious. This article aims to review the current approaches to combat AD and to open a debate on common mechanisms of cognitive enhancement and neuroprotection. In short, either the rodent models are not good and should be discontinued, or we should extract the most useful information from those models. An example of a question that may be debated for the advancement in AD therapy is: In addition to reducing amyloid and tau pathologies, would it be necessary to boost synaptic strength and cognition? The debate could provide clues to turn around the current negative output in generating effective drugs for patients. Furthermore, discovery of biomarkers in human body fluids, and a clear distinction between cognitive enhancers and disease modifying strategies, should be instrumental for advancing in anti-AD drug discovery.

Hipertensión arterial y enfermedad de Alzheimer

Hypertension (HT) is the most prevalent cardiovascular risk factor associated with dementia and Alzheimer disease (AD). The evidence about the association within hight blood pressure (BP) level in the middle age and dementia and Alzheimer’s disease incidence in the advanced age has increased. Longitudinal studies show that in the previous years of onset AD, BP is similar or lower in the patients who develop AD with regard to those who not develop. When patients has developed AD the case is the same that the previous one. Most studies show that BP reduction is beneficious to prevent cognitive impairment, dementia and AD. Is spite of some discordant studies, health authorities recommend to treat isolated systolic HT with an ‘A’ evidence degree, level 1, to prevent AD. Animal experimentation prove different ways to act of antihypertensive drugs in the AD prevention and has established the pathophysiological bases in this relation, until now only showed through various clinical studies