Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau

Objective: New diagnostic criteria for mild cognitive impairment (MCI) due to Alzheimer's disease (AD) have been developed using biomarkers aiming to establish whether the clinical syndrome is likely due to underlying AD. We investigated the utility of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers in predicting progression from amnesic MCI to dementia, testing the hypotheses that (1) markers of amyloid and neurodegeneration provide distinct and complementary prognostic information over different time intervals, and that (2) evidence of neurodegeneration in amyloid-negative MCI individuals would be useful prognostically. Methods: Data were obtained from the ADNI-1 (Alzheimer's Disease Neuroimaging Initiative Phase 1) database on all individuals with a baseline diagnosis of MCI, baseline MRI and CSF data, and at least one follow-up visit. MRI data were processed using a published set of a priori regions of interest to derive a measure known as the ``AD signature,'' as well as hippocampal volume. The CSF biomarkers amyloid-β, total tau, and phospho tau were also examined. We performed logistic regression analyses to identify the best baseline biomarker predictors of progression to dementia over 1 or 3 years, and Cox regression models to test the utility of these markers for predicting time-to-dementia. Results: For prediction of dementia in MCI, the AD signature cortical thickness biomarker performed better than hippocampal volume. Although CSF tau measures were better than CSF amyloid-β at predicting dementia within 1 year, the AD signature was better than all CSF measures at prediction over this relatively short-term interval. CSF amyloid-β was superior to tau and AD signature at predicting dementia over 3 years. When CSF amyloid-β was dichotomized using previously published cutoff values and treated as a categorical variable, a multivariate stepwise Cox regression model indicated that both the AD signature MRI marker and the categorical CSF amyloid-β marker were useful in predicting time-to-event diagnosis of AD dementia. Conclusion: In amnesic MCI, short-term (1 year) prognosis of progression to dementia relates strongly to baseline markers of neurodegeneration, with the AD signature MRI biomarker of cortical thickness performing the best among MRI and CSF markers studied here. Longer-term (3 year) prognosis in these individuals was better predicted by a marker indicative of brain amyloid. Prediction of time-to-event in a survival model was predicted by the combination of these biomarkers. These results provide further support for emerging models of the temporal relationship of pathophysiologic events in AD and demonstrate the utility of these biomarkers at the prodromal stage of the illness

Improved Proper Name Recall in Aging after Electrical Stimulation of the Anterior Temporal Lobes

Evidence from neuroimaging and neuropsychology suggests that portions of the anterior temporal lobes (ATLs) play a critical role in proper name retrieval. We previously found that anodal transcranial direct current stimulation (tDCS) to the ATLs improved retrieval of proper names in young adults (Ross et al., 2010). Here we extend that finding to older adults who tend to experience greater proper-naming deficits than young adults. The task was to look at pictures of famous faces or landmarks and verbally recall the associated proper name. Our results show a numerical improvement in face naming after left or right ATL stimulation, but a statistically significant effect only after left-lateralized stimulation. The magnitude of the enhancing effect was similar in older and younger adults but the lateralization of the effect differed depending on age. The implications of these findings for the use of tDCS as tool for rehabilitation of age-related loss of name recall are discussed

Recognition memory in amnestic-mild cognitive impairment: insights from event-related potentials

Episodic memory loss is the hallmark cognitive dysfunction associated with Alzheimer’s disease (AD). Amnestic mild cognitive impairment (a-MCI) frequently represents a transitional stage between normal aging and early AD. A better understanding of the qualitative features of memory loss in a-MCI may have important implications for predicting those most likely to harbor AD-related pathology and for disease monitoring. Dual process models of memory argue that recognition memory is subserved by the dissociable processes of recollection and familiarity. Work studying recognition memory in a-MCI from this perspective has been controversial, particularly with regard to the integrity of familiarity. Event-related potentials (ERPs) offer an alternative means for assessing these functions without the associated assumptions of behavioral estimation methods. ERPs were recorded while a-MCI patients and cognitively normal (CN) age-matched adults performed a recognition memory task. When retrieval success was measured (hits versus correct rejections) in which performance was matched by group, a-MCI patients displayed similar neural correlates to that of the CN group, including modulation of the FN400 and the late positive complex (LPC) which are thought to index familiarity and recollection, respectively. Alternatively, when the integrity of these components was measured based on retrieval attempts (studied versus unstudied items), a-MCI patients displayed a reduced FN400 and LPC. Furthermore, modulation of the FN400 correlated with a behavioral estimate of familiarity and the LPC with a behavioral estimate of recollection obtained in a separate experiment in the same individuals, consistent with the proposed mappings of these indices. These results support a global decline of recognition memory in a-MCI, which suggests that the memory loss of prodromal AD may be qualitatively distinct from normal aging

Stable Coronal X-Ray Emission Over Twenty Years of XZ Tau

XZ Tau AB is a frequently observed binary YSO in the Taurus Molecular Cloud; XZ Tau B has been classified as an EXOr object. We present new Chandra/HETG-ACIS-S observations of XZ Tau AB, complemented with variability monitoring of the system with XMM-Newton, to constrain the variability of this system and identify high-resolution line diagnostics to better understand the underlying mechanisms that produce the X-rays. We observe two flares with XMM-Newton, but find that outside of these flares the coronal X-ray spectrum of XZ Tau AB is consistent over twenty years of observations. We compare the ensemble of XZ Tau X-ray observations over time with the scatter across stars observed in point-in-time observations of the Orion Nebula Cluster and find that both overlap in terms of plasma properties, i.e., some of the scatter observed in the X-ray properties of stellar ensembles stems from intrinsic source variability.Comment: Accepted for publication in the Astronomical Journal. 19 pages, 11 figure

Temporally distinct neural coding of perceptual similarity and prototype bias

Psychological models suggest that perceptual similarity can be divided into geometric effects, such as metric distance in stimulus space, and non-geometric effects, such as stimulus-specific biases. We investigated the neural and temporal separability of these effects in a carry-over, event-related potential (ERP) study of facial similarity. By testing this dual effects model against a temporal framework of visual evoked components, we demonstrate that the behavioral distinction between geometric and non-geometric similarity effects is consistent with dissociable neural responses across the time course of face perception. We find an ERP component between the “face-selective” N170 and N250 responses (the “P200”) that is modulated by transitions of face appearance, consistent with neural adaptation to the geometric similarity of face transitions. In contrast, the N170 and N250 reflect non-geometric stimulus bias, with different degrees of neural adaptation dependent upon the direction of transition within the stimulus space. These results suggest that the neural coding of perceptual similarity, in terms of both geometric and non-geometric representations, occurs rapidly and from relatively early in the perceptual processing stream

Cognitive status impacts age-related changes in attention to novel and target events in normal adults.

In this study, the authors investigated the relationship between the cognitive status of normal adults and age-related changes in attention to novel and target events. Old, middle-age, and young subjects, divided into cognitively high and cognitively average performing groups, viewed repetitive standard stimuli, infrequent target stimuli, and unique novel visual stimuli. Subjects controlled viewing duration by a button press that led to the onset of the next stimulus. They also responded to targets by pressing a foot pedal. The amount of time spent looking at different kinds of stimuli served as a measure of visual attention and exploratory activity. Cognitively high performers spent more time viewing novel stimuli than cognitively average performers. The magnitude of the difference between cognitively high and cognitively average performing groups was largest among old subjects. Cognitively average performers had slower and less accurate responses to targets than cognitively high performers. The results provide strong evidence that the link between engagement by novelty and higher cognitive performance increases with age. Moreover, the results support the notion of there being different patterns of normal cognitive aging and the need to identify the factors that influence them

Regional Deep Atrophy: a Self-Supervised Learning Method to Automatically Identify Regions Associated With Alzheimer's Disease Progression From Longitudinal MRI

Longitudinal assessment of brain atrophy, particularly in the hippocampus, is a well-studied biomarker for neurodegenerative diseases, such as Alzheimer's disease (AD). In clinical trials, estimation of brain progressive rates can be applied to track therapeutic efficacy of disease modifying treatments. However, most state-of-the-art measurements calculate changes directly by segmentation and/or deformable registration of MRI images, and may misreport head motion or MRI artifacts as neurodegeneration, impacting their accuracy. In our previous study, we developed a deep learning method DeepAtrophy that uses a convolutional neural network to quantify differences between longitudinal MRI scan pairs that are associated with time. DeepAtrophy has high accuracy in inferring temporal information from longitudinal MRI scans, such as temporal order or relative inter-scan interval. DeepAtrophy also provides an overall atrophy score that was shown to perform well as a potential biomarker of disease progression and treatment efficacy. However, DeepAtrophy is not interpretable, and it is unclear what changes in the MRI contribute to progression measurements. In this paper, we propose Regional Deep Atrophy (RDA), which combines the temporal inference approach from DeepAtrophy with a deformable registration neural network and attention mechanism that highlights regions in the MRI image where longitudinal changes are contributing to temporal inference. RDA has similar prediction accuracy as DeepAtrophy, but its additional interpretability makes it more acceptable for use in clinical settings, and may lead to more sensitive biomarkers for disease monitoring in clinical trials of early AD.Comment: Submitted to NeuroImage for revie

Increased Responsiveness to Novelty is Associated with Successful Cognitive Aging

The animal literature suggests that exposure to more complex, novel environments promotes neurogenesis and cognitive performance in older animals. Studies in humans indicate that participation in intellectually stimulating activities may serve as a buffer against mental decline and help to sustain cognitive abilities. Here, we show that across old adults, increased responsiveness to novel events (as measured by viewing duration and the size of the P3 event-related potential) is strongly linked to better performance on neuropsychological tests, especially those involving attention/executive functions. Cognitively high performing old adults generate a larger P3 response to visual stimuli than cognitively average performing adults. These results suggest that cognitively high performing adults successfully manage the task by appropriating more resources and that the increased size of their P3 component represents a beneficial compensatory mechanism rather than less efficient processing