For nearly a century, the primary method employed by psychologists to define and test the validity of constructs evaluated by assessment instruments has been shared-variance techniques such as intervariable correlations or factor analysis with large normative or mixed clinical samples. To illustrate the shortcomings of this approach, we conducted (1) correlational analyses of immediate- and delayed-memory measures separately in normal participants and in homogeneous samples of patients with either Alzheimer's disease or Huntington's disease; and (2) factor analysis of immediate and delayed-recall and recognition measures in a large, homogeneous sample of patients with Alzheimer's disease. The findings revealed that cognitive measures that share variance in the intact brain-thereby giving the facade of assessing a unitary construct-can dissociate and contribute to unique variance in the damaged brain, but only if the pathology occurs in brain regions known to disrupt vital cognitive processes tapped by those measures. The results illustrate that shared-variance procedures applied to normal or mixed clinical populations can mask some of the most vital cognitive constructs, such as the classic distinction between short- and long-term memory. Implications of these findings for research and clinical practice are discussed.

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In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18–40 (n = 129), 40–60 (n = 62) and 60–90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands’ power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

The importance of designating criteria for diagnosing dementia lies in its implications for clinical treatment, research, caregiving, and decision-making. Dementia diagnosis in Huntington's disease (HD) is often based on criteria developed for Alzheimer's disease requiring memory loss. However, it is likely that other cognitive deficits contribute to functional impairment in HD before memory declines. The goal is to identify cognitive deficits that contribute to functional impairment to support dementia criteria that reflect HD neuropathology. Eighty-four HD mutation-positive subjects completed neuropsychological tests and the Unified Huntington's Disease Rating Scale Functional Independence Scale (FIS). Functional impairment was defined as 80 or below on the FIS. Speed of processing, initiation, and attention measures accounted for 70.0% of the variance in FIS ratings (linear regression) and correctly classified 91.7% of subjects as functionally impaired or intact (logistic regression). Measures of memory, motor impairment except dysarthria, neuroleptic use, and depressed mood did not improve prediction. A definition of HD dementia that includes cognitive impairment in at least two areas of cognition but does not require a memory deficit, in the context of impaired functional abilities and a deteriorating course, more accurately reflects HD neuropathology and could lead to improved research methods and patient care.

Little is known about possible differences in the memory deficits that occur in Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). We compared 24 autopsy-confirmed DLB and 24 age-, education-, and MMSE-matched autopsy-confirmed AD patients on the California Verbal Learning Test (CVLT) and the Wechsler Memory Scale-Revised Logical Memory subtest. The DLB and AD groups were similarly impaired on CVLT Total Learning (Trials 15) and Long Delayed Free Recall, but the DLB group demonstrated relative improvement in Savings scores and on recognition testing compared to the AD group. Likewise, the patient groups were equally impaired on Logical Memory immediate and delayed recall, but the DLB group's Saving scores were significantly better than those of the AD patients. These results indicate that while both DLB and AD patients exhibit significant memory impairment, the ability to consolidate information may be less severely impaired in DLB patients than in AD patients.

Dementia with Lewy Bodies (DLB) is often characterized by pronounced impairment in visuospatial skills, attention, and executive functions. However, the strength of the phenotypic expression of DLB varies and may be weaker in patients with extensive concomitant Alzheimer’s disease (AD). To determine whether strength of the DLB clinical phenotype impacts cognitive decline, visuospatial and language tests were retrospectively used to predict two-year rate of global cognitive decline in 22 autopsy-confirmed DLB patients (21 with concomitant AD) and 44 autopsy-confirmed “pure” AD patients. Generalized Estimating Equations (GEE) revealed a significant interaction such that poor baseline performances on tests of visuospatial skills were strongly associated with a rapid rate of cognitive decline in DLB but not AD (p < .001). No effect of confrontation naming was found. DLB patients with poor visuospatial skills had fewer neurofibrillary tangles and were more likely to experience visual hallucinations than those with better visuospatial skills. These results suggest that the severity of visuospatial deficits in DLB may identify those facing a particularly malignant disease course and may designate individuals whose clinical syndrome is impacted more by Lewy body formation than AD pathology.

Memory tests that are in a recall format have almost universally measured accuracy in terms of the number of target items reported by the examinee. However, this traditional scoring method can, in certain cases, result in artificially inflated memory accuracy scores. That is, just as a "yes" response bias and high false-positive rate on recognition testing can artificially inflate a patient's hit rate, so, too, a liberal response bias and high intrusion rate on recall testing can artificially inflate a patient's level of target recall. Recognition tests correct for this problem by using a discriminability measure that provides a single score of hit rate relative to false-positive rate; however, recall tests rarely provide a single score of recall accuracy that corrects for intrusion rate. In the present study, we examined the utility of a new recall discriminability measure that analyzes target recall relative to intrusion rate. Patients with Alzheimer's disease (AD) or Huntington's disease (HD) were administered the CVLT-II, which provides both the traditional measure of target recall and a new measure of recall discriminability. The results indicate that the new recall discriminability measure was superior to the traditional level of target recall measure in distinguishing the recall performance of AD and HD patients. Implications of these results for clinical practice and theories of memory disorder in dementia are discussed.

The cortical pathology in Alzheimer's disease (AD) should lead to the loss of effective interaction between distinct neocortical areas. This study compared 2 conditions within a single sensory integration task that differed in the demands placed on effective cross-cortical interaction. AD patients were impaired in their ability to bind distinct visual features of a stimulus when this binding placed greater demands on cross-cortical interaction (i.e., motion and color) but were not impaired when this binding placed lesser demands on such interaction (i.e., motion and luminance). In contrast, neurologically intact individuals and patients with Huntington's disease were able to effectively bind features under both conditions. These results provide psychophysical support for the presence of functional disconnectivity in AD and demonstrate the utility of AD for investigating the neurocognitive substrates of sensory integration.