Although reading skill remains relatively stable with advancing age in humans, neurophysiological measures suggest potential reductions in efficiency of lexical information processing. It is unclear whether these age-related changes are secondary to decreases in regional cortical thickness and/or microstructure of fiber tracts essential to language. Magnetoencephalography, volumetric MRI, and diffusion tensor imaging were performed in 10 young (18–33 years) and 10 middle-aged (42–64 years) human individuals to evaluate the spatiotemporal dynamics and structural correlates of age-related changes in lexical-semantic processing. Increasing age was associated with reduced activity in left temporal lobe regions from 250–350ms and in left inferior prefrontal cortex from 350–450ms (i.e., N400). Hierarchical regression indicated that age no longer predicted left inferior prefrontal activity after cortical thickness and fractional anisotropy (FA) of the uncinate fasciculus (UF) were considered. Interestingly, FA of the UF was a stronger predictor of the N400 response than cortical thickness. Age-related reductions in left-lateralization of language responses were observed between 250–350ms, and were associated with left temporal thinning and frontotemporal FA reductions. N400 reductions were not associated with poorer task performance. Rather, increasing age was associated with reduction in the left prefrontal N400, which in turn was also associated with slower response time. These results reveal that changes in the neurophysiology of language occur by middle age and appear to be partially mediated by structural brain loss. These neurophysiological changes may reflect an adaptive process that ensues as communication between left perisylvian regions declines.

The number of elderly patients seeking clinical treatment for memory problems will rise sharply in coming years as our population ages. These patients present a challenge for diagnosis and prognosis since cognitive problems in older patients can arise from many etiologies, some of which are curable. With the development of clinically available biomarkers for detecting Alzheimer’s disease pathology in living patients, evaluation of cognitively impaired elderly patients is about to undergo a major paradigm shift. This article describes the two classes of biomarkers available for assessing Alzheimer’s disease risk: those that indicate presence of amyloid pathology and those that provide evidence of neuronal injury and neurodegeneration. We argue that, currently, incorporation of biomarkers of neurodegeneration can help in patient prognosis whereas tests for amyloid, if used in isolation, have potential for harm. Amyloid tests are clinically useful only when evidence suggests progressive cognitive decline or neurodegeneration.

We investigated the relationship between regional atrophy rates and 2-year cognitive decline in a large cohort of patients with mild cognitive impairment (MCI; N=103) and healthy controls (N=90). Longitudinal MRIs were analyzed using high-throughput image analysis procedures. Atrophy rates were derived by calculating percent cortical volume loss between baseline and 24-month scans. Step-wise regressions were performed to investigate the contribution of atrophy rates to language, memory, and executive functioning decline, controlling for age, gender, baseline performances, and disease progression. In MCI, left temporal lobe atrophy rates were associated with naming decline, whereas bilateral temporal, left frontal, and left anterior cingulate atrophy rates were associated with semantic fluency decline. Left entorhinal atrophy rate was associated with memory decline and bilateral frontal atrophy rates were associated with executive function decline. These data provide evidence that regional atrophy rates in MCI contribute to domain-specific cognitive decline, which appears to be partially independent of disease progression. MRI measures of regional atrophy can provide valuable information for understanding the neural basis of cognitive impairment in MCI.

The relationship between neurodegeneration and the two hallmark proteins of Alzheimer's disease, amyloid-β (Aβ) and tau, is still unclear. Here, we examined 286 non-demented participants (107 cognitively normal older adults and 179 memory impaired individuals) who underwent longitudinal MR imaging and lumbar puncture. Using mixed effects models, we investigated the relationship between longitudinal entorhinal cortex atrophy, CSF p-tau181p and CSF Aβ1-42. We found a significant relationship between elevated entorhinal cortex atrophy and decreased CSF Aβ1-42 only with elevated CSF p-tau181p. Our findings indicate that Aβ-associated volume loss occurs only in the presence of phospho-tauin humans at risk for dementia.

Objective

To investigate a possible link between cardiovascular risk factors and age-related cognitive decline, the association of the 1998 Framingham Cardiac Risk Score (FCRS) with the trajectory of cognitive function test (CFT) performance over 18 years was examined in adults 50 years and older without clinical heart disease at baseline.

Methods

Participants were 985 men and women who had assessments of cognitive function at three to four year intervals. The association of FCRS category with CFT score trajectory was examined using mixed effect models stratified by sex and controlling for age, education, and number of repeat cognitive assessments.

Results

At baseline, median FCRS corresponded to a 14% risk of a CHD event within 10 years for men and a 8% risk for women; 31% of men and 6% of women were at high (>20%) risk. In longitudinal analyses, women with FCRS risk >7% had a higher rate of decline on tests of verbal fluency (p’s <.05) and long term recall (p’s <.01) compared to low risk women; modest, but significant (p’s <.05), differences in the trajectory of MMSE and Trails B scores were also apparent. FCRS category was not related to the rate of decline in CFT performance in men.

Conclusions

For older women, very low levels of CHD risk were associated with preservation of cognitive function over 10 years, suggesting that maintenance of cardiovascular health may slow cognitive decline. The minimal association in men, who were at higher baseline risk, may be due to selective attrition of men with greater cognitive decline.

Objective

To elucidate the relationship between the two hallmark proteins of Alzheimer's disease (AD), amyloid-β (Aβ) and tau, and clinical decline over time among cognitively normal older individuals.

Design

A longitudinal cohort of clinically and cognitively normal older individuals assessed with baseline lumbar puncture and longitudinal clinical assessments.

Setting

Research centers across the United States and Canada.

Patients

We examined one hundred seven participants with a Clinical Dementia Rating (CDR) of 0 at baseline examination.

Main Outcome Measures

Using linear mixed effects models, we investigated the relationship between CSF p-tau181p, CSF Aβ1-42 and clinical decline as assessed using longitudinal change in global CDR, CDR-Sum of Boxes (CDR-SB), and the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog).

Results

We found a significant relationship between decreased CSF Aβ1-42 and longitudinal change in global CDR, CDR-SB, and ADAS-cog in individuals with elevated CSF p-tau181p. In the absence of CSF p-tau181p, the effect of CSF Aβ1-42 on longitudinal clinical decline was not significantly different from zero.

Conclusions

In cognitively normal older individuals, Aβ-associated clinical decline over a mean of three years may occur only in the presence of ongoing, “downstream” neurodegeneration.

Age is the strongest risk factor for sporadic Alzheimer disease (AD), yet the effects of age on rates of clinical decline and brain atrophy in AD have been largely unexplored. Here, we examined longitudinal rates of change as a function of baseline age for measures of clinical decline and structural MRI-based regional brain atrophy, in cohorts of AD, mild cognitive impairment (MCI), and cognitively healthy (HC) individuals aged 65 to 90 years (total n = 723). The effect of age was modeled using mixed effects linear regression. There was pronounced reduction in rates of clinical decline and atrophy with age for AD and MCI individuals, whereas HCs showed increased rates of clinical decline and atrophy with age. This resulted in convergence in rates of change for HCs and patients with advancing age for several measures. Baseline cerebrospinal fluid densities of AD-relevant proteins, Aβ1–42, tau, and phospho-tau181p (ptau), showed a similar pattern of convergence with advanced age across cohorts, particularly for ptau. In contrast, baseline clinical measures did not differ by age, indicating uniformity of clinical severity at baseline. These results imply that the phenotypic expression of AD is relatively mild in individuals older than approximately 85 years, and this may affect the ability to distinguish AD from normal aging in the very old. Our findings show that inclusion of older individuals in clinical trials will substantially reduce the power to detect disease-modifying therapeutic effects, leading to dramatic increases in required clinical trial sample sizes with age of study sample.

Objective

An automated cognitive neurophysiological test is presented that characterizes how an individual was affected by a drug or treatment. The test calculates sub-scores for working memory task performance, cortical activation, and alertness, and combines the sub-scores into an overall score.

Methods

The test was applied in a double-blind, placebo-controlled study of alcohol, caffeine, diphenhydramine, and sleep deprivation in 16 healthy adults.

Results

The between- and within-day variability of the sub-scores and overall scores for placebo were all near zero, suggesting that the scores are stable. All treatments affected the overall score, while differential effects on sub-scores highlighted the added value of EEG measures.

Conclusions

The test is sensitive to relatively mild alterations in cognitive function. Its automation makes it suitable for use in large-scale clinical trials.

Significance

By combining task performance with EEG brain function measures, the test may prove to have better sensitivity and specificity in detecting changes due to drugs or other treatments than comparable neuropsychological test batteries that do not directly measure brain function signals.

Background

The development of better treatments for brain diseases of the elderly will necessitate more sensitive and efficient means of repeatedly assessing an individual's neurocognitive status.

Aim

To illustrate the development of an assessment combining episodic memory and working memory tasks with simultaneous electroencephalography and evoked potential (EP) brain function measures.

Methods

Data from matched groups of elderly subjects with mildly impaired episodic verbal memory on neuropsychological tests and those with no objective signs of impairment were used for scale development. An exploratory multivariate divergence analysis selected task performance and neurophysiological variables that best recognized impairment. Discriminant validity was then initially assessed on separate impaired and unimpaired groups.

Results

Decreased response accuracy and parietal late positive component EP amplitude in the episodic memory task best characterized impaired subjects. Sensitivity in recognizing impairment in the validation analysis was 89% with 79% specificity (area under the curve = 0.94). Retest reliability was 0.89 for the unimpaired and 0.74 for the impaired validation groups.

Conclusion

These promising initial results suggest that with further refinement and testing, an assessment combining cognitive task performance with simultaneous neurofunctional measures could eventually provide an important benefit for clinicians and researchers.

Alzheimer’s disease (AD) is a common progressive neurodegenerative disorder that is not currently diagnosed until a patient reaches the stage of dementia. There is a pressing need to identify AD at an earlier stage, so that treatment, when available, can begin early. Quantitative structural MRI is sensitive to the neurodegeneration that occurs in mild and preclinical AD, and is predictive of decline to dementia in individuals with mild cognitive impairment. Objective evidence of ongoing brain atrophy will be critical for risk/benefit decisions once potentially aggressive, disease-modifying treatments become available. Recent advances have paved the way for the use of quantitative structural MRI in clinical practice, and initial clinical use has been promising. However, further experience with these measures in the relatively unselected patient populations seen in clinical practice is needed to complete translation of the recent enormous advances in scientific knowledge of AD into the clinical realm.

Reduced levels of β-amyloid1-42 (Aβ1-42) and increased levels of tau proteins in the cerebrospinal fluid (CSF) are found in Alzheimer’s disease (AD), likely reflecting Aβ deposition in plaques and neuronal and axonal damage. It is not known whether these biomarkers are associated with brain atrophy also in healthy aging. We tested the relationship between CSF levels of Aβ1-42 and tau (total tau and tau phosphorylated at threonine 181) proteins and 1-year brain atrophy in 71 cognitively normal elderly individuals. Results showed that under a certain threshold value, levels of Aβ1-42 correlated highly with 1-year change in a wide range of brain areas. The strongest relationships were not found in the regions most vulnerable early in AD. Above the threshold level, Aβ1-42 was not related to brain changes, but significant volume reductions as well as ventricular expansion were still seen. It is concluded that Aβ1-42 correlates with brain atrophy and ventricular expansion in a subgroup of cognitively normal elderly individuals but that reductions independent of CSF levels of Aβ1-42 is common. Further research and follow-up examinations over several years are needed to test whether degenerative pathology will eventually develop in the group of cognitively normal elderly individuals with low levels of Aβ1-42.

This study aims to investigate the relationship between executive function and verbal memory and to explore the underlying neuroanatomical correlates in 358 individuals with amnestic mild cognitive impairment (MCI) and 222 healthy controls (HCs). The MCI participants were divided into 2 groups (high vs. low) based on executive function task performance. Results demonstrated that although both MCI groups were impaired on all memory measures relative to HCs, MCI individuals with higher executive function (HEF) demonstrated better verbal memory performance than those with lower executive function (LEF), particularly on measures of learning. The 2 MCI groups did not differ in mesial temporal morphometric measures, but the MCI LEF group showed significant thinning in dorsolateral prefrontal and posterior cingulate cortices bilaterally compared with the MCI HEF and HCs. Further, thickness in numerous regions of frontal cortex, and bilateral posterior cingulate, was significantly associated with memory performance in all MCI participants above and beyond the contribution of the mesial temporal regions known to be associated with episodic memory. Overall, these results demonstrate the importance of evaluating executive function in individuals with MCI to predict involvement of brain areas beyond the mesial temporal lobe.

Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimerâs disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c) examining their underlying brain morphometric correlates. A total of 607 participants were assigned to three MCI groups (high learning-low retention; low learning-high retention; low learning-low retention) and one control group (high learning-high retention) based on scores above or below a 1.5 SD cutoff on learning and retention indices of the Rey Auditory Verbal Learning Test. Our results demonstrated that MCI individuals with predominantly a learning deficit showed a widespread pattern of gray matter loss at baseline, whereas individuals with a retention deficit showed more focal gray matter loss. Moreover, either learning or retention measures provided good predictive value for longitudinal clinical outcome over two years, although impaired learning had modestly better predictive power than impaired retention. As expected, impairments in both measures provided the best predictive power. Thus, the conventional practice of relying solely on the use of delayed recall or retention measures in studies of amnestic MCI misses an important subset of older adults at risk of developing AD. Overall, our results highlight the importance of including learning measures in addition to retention measures when making a diagnosis of MCI and for predicting clinical outcome.

Attentional set-shifting ability, commonly assessed with the Trail Making Test (TMT), decreases with increasing age in adults. Since set-shifting performance relies on activity in widespread brain regions, deterioration of the white matter tracts that connect these regions may underlie the age-related decrease in performance. We used an automated fiber tracking method to investigate the relationship between white matter integrity in several cortical association tracts and TMT performance in a sample of 24 healthy adults, 21 – 80 years. Diffusion tensor images were used to compute average fractional anisotropy (FA) for five cortical association tracts, the corpus callosum (CC), and the corticospinal tract (CST), which served as a control. Results showed that advancing age was associated with declines in set-shifting performance and with decreased FA in the CC and in association tracts that connect frontal cortex to more posterior brain regions, including the inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF), and superior longitudinal fasciculus (SLF). Declines in average FA in these tracts, and in average FA of the right inferior longitudinal fasciculus (ILF), were associated with increased time to completion on the set-shifting subtask of the TMT but not with the simple sequencing subtask. FA values in these tracts were strong mediators of the effect of age on set-shifting performance. Automated tractography methods can enhance our understanding of the fiber systems involved in performance of specific cognitive tasks and of the functional consequences of age-related changes in those systems.

Noninvasive MRI biomarkers for Alzheimer's disease (AD) may enable earlier clinical diagnosis and the monitoring of therapeutic effectiveness. To assess potential neuroimaging biomarkers, the Alzheimer's Disease Neuroimaging Initiative is following normal controls (NC) and individuals with mild cognitive impairment (MCI) or AD. We applied high-throughput image analyses procedures to these data to demonstrate the feasibility of detecting subtle structural changes in prodromal AD. Raw DICOM scans (139 NC, 175 MCI, and 84 AD) were downloaded for analysis. Volumetric segmentation and cortical surface reconstruction produced continuous cortical surface maps and region-of-interest (ROI) measures. The MCI cohort was subdivided into single- (SMCI) and multiple-domain MCI (MMCI) based on neuropsychological performance. Repeated measures analyses of covariance were used to examine group and hemispheric effects while controlling for age, sex, and, for volumetric measures, intracranial vault. ROI analyses showed group differences for ventricular, temporal, posterior and rostral anterior cingulate, posterior parietal, and frontal regions. SMCI and NC differed within temporal, rostral posterior cingulate, inferior parietal, precuneus, and caudal midfrontal regions. With MMCI and AD, greater differences were evident in these regions and additional frontal and retrosplenial cortices; evidence for non-AD pathology in MMCI also was suggested. Mesial temporal right-dominant asymmetries were evident and did not interact with diagnosis. Our findings demonstrate that high-throughput methods provide numerous measures to detect subtle effects of prodromal AD, suggesting early and later stages of the preclinical state in this cross-sectional sample. These methods will enable a more complete longitudinal characterization and allow us to identify changes that are predictive of conversion to AD.

Brain atrophy and altered CSF-levels of amyloid beta (Aβ42) and the microtubule-associated protein tau are potent biomarkers of Alzheimer's Disease (AD) related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions: (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change (CDR sum of boxes [CDR-sb])? 370 participants (105 NC/ 175 MCI/ 90 AD) from the Alzheimer's Disease Neuroimaging Initiative were studied, of whom 309 were followed for one and 176 for two years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest (ROIs). Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Aβ42 comparable to controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes, and that the two types of biomarkers yield complementary information.

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years) were followed with repeated MRI, and were compared to 122 patients with mild to moderate Alzheimer's disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest (ROIs). Cortical reductions in the healthy elderly were extensive after only one year, especially evident in temporal and prefrontal cortex where annual decline was about 0.5%. All subcortical and ventricular regions except caudate nucleus and the 4th ventricle changed significantly over one year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.

Current research supports the strong potential of structural MRI profiles, even within cross-sectional designs, as a promising method for the discrimination of Alzheimer’s Disease (AD) from normal controls and for the prediction of Mild Cognitive Impairment (MCI) progression and conversion to AD. Findings suggest that measures of structural change in mesial and lateral temporal, cingulate, parietal and midfrontal areas may facilitate the assessment of a treatment’s ability to halt the progressive structural loss that accompanies clinical decline in MCI. The performance of prediction is likely to continue to improve with the incorporation of measures from other neuroimaging modalities, clinical assessments, and neuromedical biomarkers, as the regional profile of individuals at risk for progression is refined.

Identifying a preclinical phase of Alzheimer’s Disease (PCAD) that is distinct from cognitive changes in healthy aging continues to be a major research focus. Combining neuropsychological and neuroimaging methodologies should improve our ability to differentiate healthy from pathological aging, although studies that utilize both methods often result in equivocal findings, possibly due to variability in cognitive test performance that may be capturing distinct phenotypes. One method of capturing this cognitive variability is to utilize contrasting neuropsychological tests to identify subgroups representative of distinct cognitive phenotypes, and determine whether differences in brain morphometry support these classifications. We review several approaches to defining cognitive subgroups, and we consider the possibility that cognitive asymmetry might provide one means of identifying both functional and structural changes associated with aging and dementia.

Inappropriate response tendencies may be stopped via a specific fronto/basal-ganglia/primary-motor-cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from sub-dural electrodes in four patients while they performed a stop signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band (∼16 Hz) for successful vs. unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100 - 250 ms after the stop signal – a time range consistent with a putative inhibitory control process, rather than stop signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta-band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased gamma-aminobutyric acid inhibition in M1. Taken together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta-frequency band in a right IFG/basal-ganglia network, with downstream effects on M1.

Study Objectives

This study examined how sleep loss affects neurophysiologic signals related to attention and working memory.

Design

Subjective sleepiness, resting-state electroencephalogram, and behavior and electroencephalogram during performance of working-memory tasks were recorded in a within-subject, repeated-measures design.

Setting

Data collection occurred in a computerized laboratory setting.

Participants

Sixteen healthy adults (mean age, 26 years; 8 female)

Interventions

Data from alert daytime baseline tests were compared with data from tests during a late-night, extended-wakefulness session that spanned up to 21 hours of sleep deprivation.

Measurements and Results

Alertness measured both subjectively and electrophysiologically decreased monotonically with increasing sleep deprivation. A lack of alertness-related changes in electroencephalographic measures of the overall mental effort exerted during task execution indicated that participants attempted to maintain high levels of performance throughout the late-night tests. Despite such continued effort, responses became slower, more variable, and more error prone within 1 hour after participants' normal time of sleep onset. This behavior failure was accompanied by significant degradation of event-related brain potentials related to the transient focusing of attention.

Conclusions

Moderate sleep loss compromises the function of neural circuits critical to subsecond attention allocation during working-memory tasks, even when an effort is made to maintain wakefulness and performance. Multivariate analyses indicate that combinations of working-memory-related behavior and neurophysiologic measures can be sensitive enough to permit reliable detection of such effects of sleep loss in individuals. Similar methods might prove useful for assessment of functional alertness in patients with sleep disorders.

The tau and amyloid pathobiological processes underlying Alzheimer disease (AD) progresses slowly over periods of decades before clinical manifestation as mild cognitive impairment (MCI), then more rapidly to dementia, and eventually to end-stage organ failure. The failure of clinical trials of candidate disease modifying therapies to slow disease progression in patients already diagnosed with early AD has led to increased interest in exploring the possibility of early intervention and prevention trials, targeting MCI and cognitively healthy (HC) populations. Here, we stratify MCI individuals based on cerebrospinal fluid (CSF) biomarkers and structural atrophy risk factors for the disease. We also stratify HC individuals into risk groups on the basis of CSF biomarkers for the two hallmark AD pathologies. Results show that the broad category of MCI can be decomposed into subsets of individuals with significantly different average regional atrophy rates. By thus selectively identifying individuals, combinations of these biomarkers and risk factors could enable significant reductions in sample size requirements for clinical trials of investigational AD-modifying therapies, and provide stratification mechanisms to more finely assess response to therapy. Power is sufficiently high that detecting efficacy in MCI cohorts should not be a limiting factor in AD therapeutics research. In contrast, we show that sample size estimates for clinical trials aimed at the preclinical stage of the disorder (HCs with evidence of AD pathology) are prohibitively large. Longer natural history studies are needed to inform design of trials aimed at the presymptomatic stage.