Deficient acquisition and consolidation: intertrial free recall performance in Alzheimer's disease and mild cognitive impairment

Previous research demonstrates that dementia of the Alzheimer type (DAT) is characterised by deficits of episodic memory, especially in the acquisition of new material. As well as this deficit in acquisition, some researchers have also argued for a deficit in consolidation in DAT. We examined acquisition and consolidation by measuring the intertrial gained and lost access in DAT, Mild Cognitive Impairment (MCI) and controls. We report findings from a study of clinical data based on assessment of patients using three free recall trials of a word list. We found that both DAT and MCI groups showed a deficit in acquisition and consolidation of items between trials relative to controls. Moreover, the DAT group was significantly impaired relative to the MCI group for both acquisition and consolidation. Correlations within each group showed that there were strong relationships between intertrial measures and standard measures of memory function. Importantly in no group was there a significant correlation between our measures of acquisition and consolidation: we argue that these measures reflect different underlying processes, and the failure to consolidate in DAT and MCI is not related to the deficit in acquisition. Finally, we showed strong correlations between our measure and dementia severity, suggesting that acquisition and consolidation both get worse as the dementia progresses.

Neural correlates of true and false memory in mild cognitive impairment

The goal of this research was to investigate the changes in neural processing in mild cognitive impairment. We measured phase synchrony, amplitudes, and event-related potentials in veridical and false memory to determine whether these differed in participants with mild cognitive impairment compared with typical, age-matched controls. Empirical mode decomposition phase locking analysis was used to assess synchrony, which is the first time this analysis technique has been applied in a complex cognitive task such as memory processing. The technique allowed assessment of changes in frontal and parietal cortex connectivity over time during a memory task, without a priori selection of frequency ranges, which has been shown previously to influence synchrony detection. Phase synchrony differed significantly in its timing and degree between participant groups in the theta and alpha frequency ranges. Timing differences suggested greater dependence on gist memory in the presence of mild cognitive impairment. The group with mild cognitive impairment had significantly more frontal theta phase locking than the controls in the absence of a significant behavioural difference in the task, providing new evidence for compensatory processing in the former group. Both groups showed greater frontal phase locking during false than true memory, suggesting increased searching when no actual memory trace was found. Significant inter-group differences in frontal alpha phase locking provided support for a role for lower and upper alpha oscillations in memory processing. Finally, fronto-parietal interaction was significantly reduced in the group with mild cognitive impairment, supporting the notion that mild cognitive impairment could represent an early stage in Alzheimer’s disease, which has been described as a ‘disconnection syndrome’.

Enhancing prospective memory in mild cognitive impairment: the role of enactment

Prospective memory (PM) is a fundamental requirement for independent living which might be prematurely compromised in the neurodegenerative process, namely in mild cognitive impairment (MCI), a typical prodromal Alzheimer's disease (AD) phase. Most encoding manipulations that typically enhance learning in healthy adults are of minimal benefit to AD patients. However, there is some indication that these can display a recall advantage when encoding is accompanied by the physical enactment of the material. The aim of this study was to explore the potential benefits of enactment at encoding and cue-action relatedness on memory for intentions in MCI patients and healthy controls using a behavioral PM experimental paradigm. Method: We report findings examining the influence of enactment at encoding for PM performance in MCI patients and education-matched controls using a laboratory-based PM task with a factorial independent design. Results: PM performance was consistently superior when physical enactment was used at encoding and when target-action pairs were strongly associated. Importantly, these beneficial effects were cumulative and observable across both a healthy and a cognitively impaired lifespan as well as evident in the perceived subjective difficulty in performing the task. Conclusions: The identified beneficial effects of enacted encoding and semantic relatedness have unveiled the potential contribution of this encoding technique to optimize attentional demands through an adaptive allocation of resources strategies. We discuss our findings with respect to their potential impact on developing strategies to improve PM in AD sufferers.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Dementia and cancer: a review of the literature and current practice

Age is a risk factor for dementia, and also for most cancers. Surprisingly, rates of cancer appear to be lower in individuals with dementia and vice versa. Genetic mechanisms could underpin this inverse relationship and are outlined, but underdiagnosis must also be taken into account. Individuals with cancer and dementia pose unique challenges to healthcare professionals owing to the potential for impaired decision-making capacity, poor communication and difficulties following medication regimes. Mild cognitive impairment and ‘chemo brain’ should be differentiated from progressive neurodegeneration.

Advanced feature selection methods in multinominal dementia classification from structural MRI data

Recent studies showed that features extracted from brain MRIs can well discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study provides an algorithm that sequentially applies advanced feature selection methods for findings the best subset of features in terms of binary classification accuracy. The classifiers that provided the highest accuracies, have been then used for solving a multi-class problem by the one-versus-one strategy. Although several approaches based on Regions of Interest (ROIs) extraction exist, the prediction power of features has not yet investigated by comparing filter and wrapper techniques. The findings of this work suggest that (i) the IntraCranial Volume (ICV) normalization can lead to overfitting and worst the accuracy prediction of test set and (ii) the combined use of a Random Forest-based filter with a Support Vector Machines-based wrapper, improves accuracy of binary classification.

Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data

We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

Fruits, vegetables, 100% juice, and cognitive function

Although reviews of the association between polyphenol intake and cognition exist, research examining the cognitive effects of fruit, vegetable, and juice consumption across epidemiological and intervention studies has not been previously examined. Critical inclusion criteria were human participants, a measure of fruit, vegetable, or 100% juice consumption, an objective measure of cognitive function, and a clinical diagnosis of neuropsychological disease. Studies were excluded if consumption of fruit, vegetables, or juice was not assessed in isolation from other foods groups, or if there was no statistical control for education or IQ. Seventeen of 19 epidemiological studies and 3 of 6 intervention studies reported significant benefits of fruit, vegetable, or juice consumption for cognitive performance. The data suggest that chronic consumption of fruits, vegetables, and juices is beneficial for cognition in healthy older adults. The limited data from acute interventions indicate that consumption of fruit juices can have immediate benefits for memory function in adults with mild cognitive impairment; however, as of yet, acute benefits have not been observed in healthy adults. Conclusions regarding an optimum dietary intake for fruits, vegetables, and juices are difficult to quantify because of substantial heterogeneity in the categorization of consumption of these foods.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Chronic consumption of flavanone-rich orange juice is associated with cognitive benefits: an 8-wk randomised, double-blind, placebo-controlled trial in healthy older adults

Background: Research indicates that chronic consumption of flavonoids is associated with cognitive benefits in adults with mild cognitive impairment and neurodegenerative disease, although, there has been no such studies in healthy older adults. Furthermore, the effects of commonly consumed orange juice flavanones on cognitive function remain unexplored. Objective: To investigate whether eight weeks of daily flavanone-rich orange juice consumption was beneficial for cognitive function in healthy older adults. Design: High flavanone (HF: 305mg) 100% orange juice and equicaloric low flavanone (LF: 37mg) orange flavored cordial (500ml) were consumed daily for eight weeks by thirty seven healthy older adults (mean age 67 years) according to a crossover, double blind, randomized design separated by a four week washout. Cognitive function, mood and blood pressure were assessed at baseline and follow up with standardized validated tests. Results: Global cognitive function was significantly better following eight week consumption of flavanone-rich juice relative to eight week consumption of the low flavanone control. No significant effects on mood or blood pressure were observed. Conclusions: Chronic daily consumption of flavanone-rich 100% orange juice over eight weeks is beneficial for cognitive function in healthy older adults. The potential for flavanone-rich foods and drinks to attenuate cognitive decline in ageing and the mechanisms which underlie these effects should be investigated.

Concord Grape Juice, cognitive function and driving performance: a 12 week, placebo controlled, randomised, crossover trial in mothers of pre-teen children

Background: Daily consumption of Concord grape juice (CGJ) over three to four months has been shown to improve memory function in adults with mild cognitive impairment, and reduce blood pressure in hypertensive adults. These benefits are likely due to the high concentration of polyphenols in CGJ. Increased stress can impair cognitive function and elevate blood pressure. Thus we examined the potential beneficial effect of CGJ in individuals experiencing somewhat stressful demanding lifestyles. Objective: To examine the effects of twelve weeks’ daily consumption of CGJ on cognitive function, driving performance, and blood pressure in healthy, middle-aged working mothers. Design: Twenty five healthy mothers of pre-teen children, aged 40-50 years, who were employed for > 30 hours/week consumed 12oz (355ml) CGJ (containing 777mg total polyphenols) or an energy, taste and appearance matched placebo daily for twelve weeks according to a randomised, crossover design with a four week washout. Verbal and spatial memory, executive function, attention, blood pressure and mood were assessed at baseline, six weeks and twelve weeks. Immediately following the cognitive battery, a subsample of seventeen females completed a driving performance assessment in the University of Leeds Driving Simulator. The twenty five minute driving task required participants to match the speed and direction of a lead vehicle. Results: Significant improvements in immediate spatial memory and driving performance were observed following CGJ relative to placebo. There was evidence of an enduring effect of CGJ such that participants who received CGJ in arm 1 maintained better performance in the placebo arm. Conclusions: Cognitive benefits associated with chronic consumption of flavonoid-rich grape juice are not exclusive to adults with mild cognitive impairment. Moreover, these cognitive benefits are apparent in complex everyday tasks such as driving. Effects may persist beyond cessation of flavonoid consumption and future studies should carefully consider the length of washout within crossover designs.

Small time two-sided LIL behavior for Lévy processes at zero

We wish to characterize when a Lévy process X t crosses boundaries b(t), in a two-sided sense, for small times t, where b(t) satisfies very mild conditions. An integral test is furnished for computing the value of sup t→0|X t |/b(t) = c. In some cases, we also specify a function b(t) in terms of the Lévy triplet, such that sup t→0 |X t |/b(t) = 1.

Asymptotic behavior at infinity of solutions of multidimensional second kind integral equations

We consider second kind integral equations of the form x(s) - (abbreviated x - K x = y ), in which Ω is some unbounded subset of Rn. Let Xp denote the weighted space of functions x continuous on Ω and satisfying x (s) = O(|s|-p ),s → ∞We show that if the kernel k(s,t) decays like |s — t|-q as |s — t| → ∞ for some sufficiently large q (and some other mild conditions on k are satisfied), then K ∈ B(XP) (the set of bounded linear operators on Xp), for 0 ≤ p ≤ q. If also (I - K)-1 ∈ B(X0) then (I - K)-1 ∈ B(XP) for 0 < p < q, and (I- K)-1∈ B(Xq) if further conditions on k hold. Thus, if k(s, t) = O(|s — t|-q). |s — t| → ∞, and y(s)=O(|s|-p), s → ∞, the asymptotic behaviour of the solution x may be estimated as x (s) = O(|s|-r), |s| → ∞, r := min(p, q). The case when k(s,t) = к(s — t), so that the equation is of Wiener-Hopf type, receives especial attention. Conditions, in terms of the symbol of I — K, for I — K to be invertible or Fredholm on Xp are established for certain cases (Ω a half-space or cone). A boundary integral equation, which models three-dimensional acoustic propaga-tion above flat ground, absorbing apart from an infinite rigid strip, illustrates the practical application and sharpness of the above results. This integral equation mod-els, in particular, road traffic noise propagation along an infinite road surface sur-rounded by absorbing ground. We prove that the sound propagating along the rigid road surface eventually decays with distance at the same rate as sound propagating above the absorbing ground.