Exploring the Association between Amyloid-ß and Memory Markers for Alzheimer's Disease in Cognitively Unimpaired Older Adults.

BACKGROUND: Memory tests vary in their sensitivity for detection of pre-symptomatic Alzheimer's disease (AD). The Visual Short-Term Memory Binding Test (VSTMBT) identifies AD-related performance deficits in older adults who are otherwise cognitively unimpaired. OBJECTIVE: We investigated the association of this psychometric measure with brain amyloidosis and atrophy. DESIGN: Cross-sectional mixed and correlational. SETTING: Cognitive Reserve Study from Columbia University. PARTICIPANTS: a sample of 39 cognitively unimpaired older adults (Age: M=65.3, SD=3.07) was obtained from the above study. MEASUREMENTS: Extensive neuropsychological and neuroimaging (MRI and amyloid-ß PET) assessments were carried out. RESULTS: Performance on the VSTMBT allowed us to split the sample into Low Binding Cost (LBC, N=21) and High Binding Cost (HBC, N=18). Groups were matched according to age [p=0.702], years of education [0.071], and sex [p=0.291]. HBC's performance was comparable to that seen in symptomatic AD. Groups only differed in their amyloid-ß deposition on PET in regions of the right ventral stream linked to visual cognition and affected early in AD pathogenesis (lateral-occipital cortex, p = 0.008; fusiform gyrus, p = 0.017; and entorhinal cortex, p = 0.046). Other regions known to be linked to low-level visual integration function also revealed increased amyloid-ß deposition in HBC. CONCLUSIONS: VSTMB deficits are associated with neuropathogenesis (i.e., amyloid-ß deposition) in the earliest affected regions in pre-symptomatic AD. The VSTMB test holds potential for the identification of cognitively unimpaired older adults with very early AD pathogenesis and may thus be a useful tool for early intervention trials or other forms of clinical research.

Polygenic indices for cognition in healthy aging; the role of brain measures.

Background: Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging. Methods: We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH). Results: Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures. Conclusions: Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

Adjudicating Mild Cognitive Impairment Due to Alzheimer's Disease as a Novel Endpoint Event in the TOMMORROW Prevention Clinical Trial.

BACKGROUND: The onset of mild cognitive impairment (MCI) is an essential outcome in Alzheimer's disease (AD) prevention trials and a compelling milestone for clinically meaningful change. Determining MCI, however, may be variable and subject to disagreement. Adjudication procedures may improve the reliability of these determinations. We report the performance of an adjudication committee for an AD prevention trial. METHODS: The TOMMORROW prevention trial selected cognitively normal participants at increased genetic risk for AD and randomized them to low-dose pioglitazone or placebo treatment. When adjudication criteria were triggered, a participant's clinical information was randomly assigned to a three-member panel of a six-member independent adjudication committee. Determination of whether or not a participant reached MCI due to AD or AD dementia proceeded through up to three review stages - independent review, collaborative review, and full committee review - requiring a unanimous decision and ratification by the chair. RESULTS: Of 3494 participants randomized, the committee adjudicated on 648 cases from 386 participants, resulting in 96 primary endpoint events. Most participants had cases that were adjudicated once (n = 235, 60.9%); the rest had cases that were adjudicated multiple times. Cases were evenly distributed among the eight possible three-member panels. Most adjudicated cases (485/648, 74.8%) were decided within the independent review (stage 1); 14.0% required broader collaborative review (stage 2), and 11.1% needed full committee discussion (stage 3). The primary endpoint event decision rate was 39/485 (8.0%) for stage 1, 29/91 (31.9%) for stage 2, and 28/72 (38.9%) for stage 3. Agreement between the primary event outcomes supported by investigators' clinical diagnoses and the decisions of the adjudication committee increased from 50% to approximately 93% (after around 100 cases) before settling at 80-90% for the remainder of the study. CONCLUSIONS: The adjudication process was designed to provide independent, consistent determinations of the trial endpoints. These outcomes demonstrated the extent of uncertainty among trial investigators and agreement between adjudicators when the transition to MCI due to AD was prospectively assessed. These methods may inform clinical endpoint determination in future AD secondary prevention studies. Reliable, accurate assessment of clinical events is critical for prevention trials and may mean the difference between success and failure.

CoblationTM-assisted excision of suprastomal granulation tissue.

BACKGROUND: Suprastomal granulation tissue is a common complication of long-term tracheostomy. It may be associated with bleeding, aphonia, airway obstruction and delayed decannulation. METHODS: This study describes the experience of a tertiary paediatric medical centre with CoblationTM-assisted suprastomal granulation tissue excision. RESULTS: Thirteen children (mean age, 5.7 years) who underwent the procedure from 2013 to 2019 because of delayed decannulation or aphonia were included. Lumen obstruction ranged from 50 to 90 per cent, with a mean of 68.8 per cent. After the procedure, decannulation was successfully performed in 7 patients, and voice quality improved in 10 patients. There were no peri- or post-operative complications. CONCLUSION: This is the largest series to date that describes Coblation used for the treatment of suprastomal granuloma. Coblation has advantages of high precision, relatively low temperature (thereby avoiding thermal injury to adjacent tissue), haemostatic resection and feasibility for use for even large granulomas. The promising results should prompt further studies in larger samples.

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults.

BACKGROUND: Cognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e. alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies. METHOD: In a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54-88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50-80). Fifteen models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition). RESULTS: No moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education) and 16 composites (i.e. combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two-thirds of brain-cognition models: the composites of (1) occupational complexity and verbal intelligence, (2) education and verbal intelligence, and (3) education, occupational complexity, and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone. CONCLUSION: These results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.

Polygenic score for sleep duration. Association with cognition.

STUDY OBJECTIVES: Age-related changes in sleep include a reduction in total sleep time and a greater incidence of sleep disorders, and are also an integral part of neurodegenerations. In the present study, we aimed to: a) identify common genetic variants that may influence self-reported sleep duration, and b) examine the association between the identified genetic variants and performance in different cognitive domains. METHODS: A sample of 197 cognitively healthy participants, aged 20-80 years, mostly non-Hispanic Whites (69%), were selected from the Reference Abilities Neural Network and the Cognitive Reserve study. Each participant underwent an evaluation of sleep function and assessment of neuropsychological performance on global cognition and four different domains (memory, speed of processing, fluid reasoning, language). Published GWAS summary statistics from a Polygenic Score (PS) for sleep duration in a large European ancestry cohort (N = 30,251) were used to derive a PS in our study sample. Multivariate linear models were used to test the associations between the PS and sleep duration and cognitive performance. Age, sex, and education were used as covariates. Secondary analyses were conducted in three age-groups (young, middle, old). RESULTS: Higher PS was linked to longer sleep duration and was also associated with better performance in global cognition, fluid reasoning, speed of processing, and language, but not memory. Results especially for fluid reasoning, language, and global cognition were driven mostly by the young group. CONCLUSIONS: Our study replicated the previously reported association between sleep-PS and longer sleep duration. We additionally found a significant association between the sleep-PS and cognitive function. Our results suggest that common genetic variants may influence the link between sleep duration and cognitive health.

Dietary fatty acids and risk of Alzheimer's disease and related dementias: Observations from the Washington Heights-Hamilton Heights-Inwood Columbia Aging Project (WHICAP).

INTRODUCTION: High dietary intake of long chain, polyunsaturated fatty acids is associated with lower Alzheimer's disease (AD) risk. METHODS: Washington Heights-Hamilton Heights-Inwood Columbia Aging Project is a multiethnic, prospective observational study of aging and dementia among elderly (≥ 65 years). Dietary intake was measured using a food frequency questionnaire. Dietary short-, medium-, and long-chain fatty acid intakes were categorized by number of carbons and double bonds. Consensus AD diagnoses were made. Associations between AD risk and dietary fatty acid and cholesterol intakes were estimated using multivariable Cox proportional hazards regression models. RESULTS: Of 2612 multiethnic women (67%) and men (baseline age 76.3 [6.4] years), 380 developed AD over an average 4.5 years follow-up. Lower risk of AD was associated with increasing intakes of docosahexaenoic acid (DHA; hazard ratio [HR] = 0.73, 95% confidence interval [CI]: 0.57 to 0.95, P = 0.018) and eicosapentaenoic acid (EPA; HR = 0.74, 95% CI: 0.57 to 0.95, P = 0.021), and longer AD-free survival (P < 0.05). DISCUSSION: Higher intake of DHA and EPA are protective for AD.

Identifying a task-invariant cognitive reserve network using task potency.

Cognitive reserve (CR) is thought to protect against the consequence of age- or disease-related structural brain changes across multiple cognitive domains. The neural basis of CR may therefore comprise a functional network that is actively involved in many different cognitive processes. To investigate the existence of such a "task-invariant" CR network, we measured functional connectivity in a cognitively normal sample between 20 and 80 years old (N â€‹= â€‹265), both at rest and during the performance of 11 separate tasks that aim to capture four latent cognitive abilities (i.e. vocabulary, episodic memory, processing speed, and fluid reasoning). For each individual, we determined the change in functional connectivity from the resting state to each task state, which is referred to as "task potency" (Chauvin et al., 2018, 2019). Task potency was calculated for each pair among 264 nodes (Power et al., 2012) and then summarized across tasks reflecting the same cognitive ability. Subsequently, we established the correlation between task potency and IQ or education (i.e. CR factors). We identified a set of 57 pairs in which task potency showed significant correlations with IQ, but not education, across all four cognitive abilities. These pairs were included in a principal component analysis, from which we extracted the first component to obtain a latent variable reflecting task potency in this task-invariant CR network. This task potency variable was associated with better episodic memory (ߠ​= â€‹0.19, p â€‹< â€‹.01) and fluid reasoning performance (ߠ​= â€‹0.17, p â€‹< â€‹.01) above and beyond the effects of cortical thickness (range [absolute] ߠ​= â€‹0.28-0.32, p â€‹< â€‹.001). Our identification of this task-invariant network contributes to a better understanding of the mechanism underlying CR, which may facilitate the development of CR-enhancing treatments. Our work also offers a useful alternative operational measure of CR for future studies.

A Dopamine Receptor genetic variant enhances perceptual speed in cognitive healthy subjects.

Cognition is under strong genetic control, yet the specific genes are unknown. To investigate genetic influences on specific cognitive domains, 153 cognitive healthy subjects of European ancestry from the Reference Abilities Study (RANN) were genotyped for 1,160 variants within 446 neuropsychiatric genes. Adjusted linear regression models evaluated the association between the genetic variants and four reference abilities, which capture variance in age-related cognitive function (Vocabulary, Episodic Memory, Perceptual Speed, and Reasoning). 159 variants nominally significant in the RANN cohort were then re-evaluated in an independent cohort of 868 cognitive healthy subjects from the Religious Orders Study and Rush Memory Aging Project. Meta-analysis yielded a Bonferroni adjusted statistically significant association between perceptual speed and a variant located in the promoter of the dopamine receptor D4 gene, rs3756450 (ß=0.23, SE=0.05, P meta =2.3 × 10-5). Our data suggest that genetic variation in a dopamine pathway gene influences perceptual speed performance in cognitively healthy individuals.

Dataset on the associations between sleep quality/duration and cognitive performance in cognitively healthy older adults.

In the present data, we provide the details of the cross-sectional study examining the associations between sleep quality/sleep duration and cognitive performance. Data are from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD). A total of 1484 older adults (65 y.o. or older) took part in the study. Sleep measurements were drawn from the sleep scale of the Medical Outcomes Study (MOS). Cognition was used as a z-score drawn by different tests. The domains examined were: executive function, visuo-spatial ability, language, attention- speed of processing, as well as the composite z-score of all the cognitive domains (including memory). Linear regression models were conducted to investigate the associations between sleep quality and cognition, and sleep duration and cognition as well. We also conducted linear regression analyses for the associations between sleep quality/duration and cognitive domains/composite cognitive score based on the status of the Apolipoprotein E-ε4 (ApoE-ε4) genotype. Analyses were performed excluding both the demented and the Mild Cognitive Impairment (MCI) participants. Adjustments conducted for multiple covariates. For further analyses and enhanced discussion, see original article: "Sleep quality and duration in relation to memory in the elderly: initial results from the Hellenic Longitudinal Investigation of Aging and Diet" by Tsapanou et al. [1].

Sleep quality and duration in relation to memory in the elderly: Initial results from the Hellenic Longitudinal Investigation of Aging and Diet.

BACKGROUND: Sleep is crucial for cognition, particularly for memory, given its complex association with neurodegenerative processes. The aim of the present study was to examine the association between sleep quality as well as sleep duration and memory performance in a Greek elderly population. SETTING: Cross-sectional design in the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD), a population representative study of Greek elderly (65years or older). METHODS: Data from 1589 participants free of sleep medication were included. Sleep quality was estimated by using the Sleep Scale from the Medical Outcomes Study. An extensive neuropsychological assessment examining memory was administered to each participant. Linear regression analyses were used to examine whether sleep quality (higher score, poor quality) and/or sleep duration were associated with memory expressed in the form of a z-score. Age, sex, education, and body mass index were included as covariates. The main analyses were conducted first on the total sample, then with the exclusion of demented participants, and finally with the exclusion of both demented and participants with Mild Cognitive Impairment (MCI). We then conducted further analyses on the non-demented, non-MCI group, initially stratified by Apolipoprotein E-ε4 gene. We further examined the role of co-morbidities, as well as the association between sleep duration groups and memory. We also explored any interaction effect between sex and sleep quality/duration on memory. We then examined the associations between components of sleep measures and memory scores. Lastly, we examined the associations between sleep quality/duration and verbal/non-verbal memory separately. RESULTS: In the total sample, we noted significant associations between sleep duration and memory (B=-0.001, p≤0.0001), but not for sleep quality and memory (B=-0.038, p=0.121). After excluding the demented participants, the associations were significant for: sleep quality and memory (B=-0.054, p=0.023), and sleep duration and memory (B=-0.001, p≤0.0001). After excluding both the MCI and the demented subjects, the associations between sleep quality and memory (B=-0.065, p=0.006), and sleep duration and memory (B=-0.001, p=0.003) were still significant. The association between the sleep duration groups and memory function was also significant, such that poor memory performance was associated with the longer sleep duration group. The results remained significant even after controlling for the co-morbidities, as well as after adding in the model anxiety and depression as covariates. Associations between sleep quality and memory, and sleep duration and memory were present in the ApoE-ε4 non-carriers. The individual sleep questions that were probably shown to be driving the associations between sleep and memory were: time to fall asleep, sleep not quiet, getting enough sleep to feel rested upon waking in the morning, and getting the amount of sleep needed. Sleep duration was associated with both verbal and non-verbal memory, while sleep quality was only associated with verbal memory. CONCLUSION: Poor sleep quality and longer sleep duration were linked to low memory performance, independent of demographic and clinical factors, in a large sample of cognitively healthy older Greek adults. Other parameters than sleep and memory measurements could play an important role on the association. Levels of melatonin, or circadian rhythms dysregulation might play a crucial role in the above associations.

Diagnostic utility of brain activity flow patterns analysis in attention deficit hyperactivity disorder.

BACKGROUND: A previous small study suggested that Brain Network Activation (BNA), a novel ERP-based brain network analysis, may have diagnostic utility in attention deficit hyperactivity disorder (ADHD). In this study we examined the diagnostic capability of a new advanced version of the BNA methodology on a larger population of adults with and without ADHD. METHOD: Subjects were unmedicated right-handed 18- to 55-year-old adults of both sexes with and without a DSM-IV diagnosis of ADHD. We collected EEG while the subjects were performing a response inhibition task (Go/NoGo) and then applied a spatio-temporal Brain Network Activation (BNA) analysis of the EEG data. This analysis produced a display of qualitative measures of brain states (BNA scores) providing information on cortical connectivity. This complex set of scores was then fed into a machine learning algorithm. RESULTS: The BNA analysis of the EEG data recorded during the Go/NoGo task demonstrated a high discriminative capacity between ADHD patients and controls (AUC = 0.92, specificity = 0.95, sensitivity = 0.86 for the Go condition; AUC = 0.84, specificity = 0.91, sensitivity = 0.76 for the NoGo condition). CONCLUSIONS: BNA methodology can help differentiate between ADHD and healthy controls based on functional brain connectivity. The data support the utility of the tool to augment clinical examinations by objective evaluation of electrophysiological changes associated with ADHD. Results also support a network-based approach to the study of ADHD.

Cognitive Reserve and Brain Maintenance: Orthogonal Concepts in Theory and Practice.

Cognitive Reserve and Brain Maintenance have traditionally been understood as complementary concepts: Brain Maintenance captures the processes underlying the structural preservation of the brain with age, and might be assessed relative to age-matched peers. Cognitive Reserve, on the other hand, refers to how cognitive processing can be performed regardless of how well brain structure has been maintained. Thus, Brain Maintenance concerns the "hardware," whereas Cognitive Reserve concerns "software," that is, brain functioning explained by factors beyond mere brain structure. We used structural brain data from 368 community-dwelling adults, age 20-80, to derive measures of Brain Maintenance and Cognitive Reserve. We found that Brain Maintenance and Cognitive were uncorrelated such that values on one measure did not imply anything about the other measure. Further, both measures were positively correlated with verbal intelligence and education, hinting at formative influences of the latter to both measures. We performed extensive split-half simulations to check our derived measures' statistical robustness. Our approach enables the out-of-sample quantification of Brain Maintenance and Cognitive Reserve for single subjects on the basis of chronological age, neuropsychological performance and structural brain measures. Future work will investigate the prognostic power of these measures with regard to future cognitive status.

Why Is Later Age at Retirement Beneficial for Cognition? Results from a French Population-based Study.

OBJECTIVE: To determine whether and how age at retirement influences the risk of dementia. The association between the age at retirement, the number of working years and the risk of dementia was evaluated over 12 years of follow-up. DESIGN: A prospective population-based study. SETTING: Three-City cohort, a French population-based study of community-dwelling individuals aged 65 to 95. PARTICIPANTS: The sample consisted of 1,658 non-demented participants at baseline. MEASUREMENTS: All participants were evaluated at home at the initial visit and at two years interval for a period of 12 years. An active research of dementia was conducted at each follow-up; all suspected cases were analysed by an independent committee of neurologists. Information regarding retirement age and number of working years was collected at baseline using a structured questionnaire. RESULTS: The multivariate Cox model, including both the age at retirement and the number of working years and adjusted for potential confounders, revealed that the risk of dementia was independently associated with the age at retirement (p=0.022) but not with the number of working years (p=0.296). CONCLUSION: Although our results are in accordance with previous studies (i.e., older age at retirement is associated with decreased risk of dementia), it provides additional information regarding the possible explanation for such results. Given that a longer working life did not reduce the risk of dementia, the age at retirement cannot be considered as a new factor of cognitive reserve but rather seems to be a psycho-social vulnerability factor. Further evidence is necessary to identify work and retirement related factors that influence the association between the age at retirement and the risk of dementia.

The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the derivation of these networks, we also observed some brain-behavioral correlations, notably for the fluid-reasoning network whose network score correlated with performance on the memory and fluid-reasoning tasks. While age did not influence the expression of this RANN, the slope of the association between network score and fluid-reasoning performance was negatively associated with higher ages. These results provide support for the hypothesis that a set of specific, age-invariant neural networks underlies these four RAs, and that these networks maintain their cognitive specificity and level of intensity across age. Activation common to all 12 tasks was identified as another activation pattern resulting from a mean-contrast Partial-Least-Squares technique. This common pattern did show associations with age and some subject demographics for some of the reference domains, lending support to the overall conclusion that aspects of neural processing that are specific to any cognitive reference ability stay constant across age, while aspects that are common to all reference abilities differ across age.

A novel electroencephalography-based tool for objective assessment of network dynamics activated by nociceptive stimuli.

BACKGROUND: Pain perception is typically assessed using subjective measures; an objective measure of the response to pain would be valuable. In this study, Brain Network Activation (BNA), a novel multivariate pattern analysis and scoring algorithm, was applied to event-related potentials (ERPs) elicited by cortical responses to brief heat stimuli. Objectives of this study were to evaluate the utility of BNA as a quantitative and qualitative measure of cortical response to pain. METHODS: Contact Heat Evoked Potentials (CHEPs) data were collected from 17 healthy, right-handed volunteers (10 M, 7F) using 5 different temperatures (35, 41, 46, 49 and 52 °C). A set of spatio-temporal activity patterns common to all the subjects in the group (Reference Brain Network Model; RBNM) was generated using the BNA algorithm, based on evoked responses at 52 °C. RESULTS: Frame by frame 'unfolding' of the brain network across time showed qualitative differences between responses to painful and non-painful stimuli. Brain network activation scores were shown to be a better indicator of the individual's sensitivity to pain when compared to subjective pain ratings. Additionally, BNA scores correlated significantly with temperature, demonstrated good test-retest reliability, as well as a high degree of sensitivity, specificity and accuracy in correctly categorizing subjects who reported stimuli as painful. CONCLUSIONS: These results may provide evidence that the multivariate analysis performed with BNA may be useful as a quantitative, temporally sensitive tool for assessment of pain perception.

Stable closed-loop fiber-optic delay of arbitrary radio-frequency waveforms.

Thermal drifts in long fiber-optic delay lines are compensated based on chromatic dispersion. An arbitrary input radio-frequency (RF) waveform and a control RF sine wave modulate two different tunable laser sources and are coupled into the fiber delay line. The RF phase of the control tone at the output of the delay line is monitored and used to adjust the wavelengths of both sources, so that the effects of thermal drifts and dispersion cancel out. The input and control waveforms are separated in the optical domain, and no restrictions are imposed on their RF spectra. A figure of merit is proposed, in terms of the fiber delay, range of temperature changes that may be compensated for, and residual delay variations. An upper bound on performance is established in terms of the specifications of the tunable lasers. The principle is used in the stable distribution of sine waves and of broadband linear frequency-modulated (LFM) waveforms, which are commonly employed in radar systems. Lastly, the method is incorporated in stable interrogation of a localized hot-spot within a high-resolution, distributed Brillouin fiber sensing setup. The results demonstrate the applicability of the proposed protocol in the processing of arbitrary waveforms, as part of larger, more complex systems.

A Combined Measure of Cognition and Function for Clinical Trials: The Integrated Alzheimer's Disease Rating Scale (iADRS).

It is generally recognized that more sensitive instruments for the earliest stages of Alzheimer's disease (AD) are needed. The integrated Alzheimer's Disease Rating Scale (iADRS) combines scores from 2 widely accepted measures, the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) and the Alzheimer's Disease Cooperative Study - instrumental Activities of Daily Living (ADCS-iADL). Disease progression and treatment differences as measured by the iADRS were analyzed using data from solanezumab EXPEDITION, EXPEDITION2, and EXPEDITION-EXT Studies; semagacestat IDENTITY Study; and donepezil ADCS - mild cognitive impairment (ADCS-MCI) Study. Psychometric properties of the iADRS were established through principal component analysis (PCA) and estimation of contributions of subscores and individual item scores to the iADRS total score. The iADRS performed better than most composites and scales in detecting disease progression and comparably or better than individual scales in detecting treatment differences. PCA demonstrated the iADRS can be divided into two principal components primarily representing cognitive items and instrumental ADLs. Dynamic ranges of the subscales were similar across all studies, reflecting approximately equal contributions from both subscales to the iADRS total score. In item analyses, every item contributed to the total score, with varying strength of contributions by item and across data sets. The iADRS demonstrated acceptable psychometric properties and was effective in capturing disease progression from MCI through moderate AD and treatment effects across the early disease spectrum. These findings suggest the iADRS can be used in studies of mixed populations, ensuring sensitivity to treatment effects as subjects progress during studies of putative disease-modifying agents.

Clinical and Economic Characteristics of Milestones along the Continuum of Alzheimer's Disease: Transforming Functional Scores into Levels of Dependence.

BACKGROUND: Because Alzheimer's disease (AD) is characterized by a gradual decline, it can be difficult to identify distinct clinical milestones that signal disease advancement. Adapting a functional scale may be a useful way of staging disease progression that is more informative for healthcare systems. OBJECTIVES: To adapt functional scale scores into discrete levels of dependence as a way of staging disease progression that is more informative to care providers and stakeholders who rely on the functional impact of diseases to determine access to supportive services and interventions. DESIGN: Analysis of data from the GERAS study. SETTING: GERAS is an 18-month prospective, multicenter, naturalistic, observational cohort study reflecting the routine care of patients with AD in France, Germany, and the United Kingdom. PARTICIPANTS: Data were from baseline results of 1497 community-living patients, aged ≥55 years, diagnosed with probable AD and their caregivers. MEASUREMENTS: We used data from the Alzheimer's Disease Cooperative Study Activities of Daily Living Inventory (ADCS-ADL) and mapped items onto established categories of functional dependence, validated using clinical and economic measures. Cognitive function, behavioral symptoms, caregiver burden, and cost were assessed. Based on stages of functional dependence described by the Dependence Scale, individual ADCS-ADL items were used to approximate 6 dependence levels. RESULTS: There was a significant relationship between assigned level of dependence derived from the ADCS-ADL score and cognitive severity category. As the assigned level of dependence increased, the associated clinical and economic indicators demonstrated a pattern of greater disease severity. CONCLUSIONS: This mapping provides initial support for dependence levels as appropriate interim clinical milestones that characterize the functional deficits associated with AD.