Alzheimer's disease (AD) is associated with neurodegeneration in vulnerable limbic and heteromodal regions of the cerebral cortex, detectable in vivo using magnetic resonance imaging. It is not clear whether abnormalities of cortical anatomy in AD can be reliably measured across different subject samples, how closely they track symptoms, and whether they are detectable prior to symptoms. An exploratory map of cortical thinning in mild AD was used to define regions of interest that were applied in a hypothesis-driven fashion to other subject samples. Results demonstrate a reliably quantifiable in vivo signature of abnormal cortical anatomy in AD, which parallels known regional vulnerability to AD neuropathology. Thinning in vulnerable cortical regions relates to symptom severity even in the earliest stages of clinical symptoms. Furthermore, subtle thinning is present in asymptomatic older controls with brain amyloid binding as detected with amyloid imaging. The reliability and clinical validity of AD-related cortical thinning suggests potential utility as an imaging biomarker. This “disease signature” approach to cortical morphometry, in which disease effects are mapped across the cortical mantle and then used to define ROIs for hypothesis-driven analyses, may provide a powerful methodological framework for studies of neuropsychiatric diseases.

Recent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies.

It is believed that choice behavior reveals the underlying value of goods. The subjective values of stimuli can be changed through reward-based learning mechanisms as well as by modifying the description of the decision problem, but it has yet to be shown that preferences can be manipulated by perturbing intrinsic values of individual items. Here we show that the value of food items can be modulated by the concurrent presentation of an irrelevant auditory cue to which subjects must make a simple motor response (i.e. cue-approach training). Follow-up tests show that the effects of this pairing on choice lasted at least two months after prolonged training. Eye-tracking during choice confirmed that cue-approach training increased attention to the cued items. Neuroimaging revealed the neural signature of a value change in the form of amplified preference-related activity in ventromedial prefrontal cortex.

Objective:We previously used exploratory analyses across the entire cortex to determine that mild Alzheimer disease (AD) is reliably associated with a cortical signature of thinning in specific limbic and association regions. Here we investigated whether the cortical signature of AD-related thinning is present in individuals with questionable AD dementia (QAD) and whether a greater degree of regional cortical thinning predicts mild AD dementia. Methods: Results:Longitudinal clinical follow-up revealed that 20 participants converted to mild AD dementia (progressors) while 29 remained stable (nonprogressors) approximately 2.5 years after scanning. At baseline, QAD participants showed a milder degree of cortical thinning than typically seen in mild AD, and CDR Sum-of-Boxes correlated with thickness in temporal and parietal ROIs. Compared to nonprogressors, progressors showed temporal and parietal thinning. Using receiver operating characteristic curves, the thickness of an aggregate measure of these regions predicted progression to mild AD with 83% sensitivity and 65% specificity.Conclusions: Thinning in specific cortical areas known to be affected by Alzheimer disease (AD) is detectable in individuals with questionable AD dementia (QAD) and predicts conversion to mild AD dementia. This method could be useful for identifying individuals at relatively high risk for imminent progression from QAD to mild AD dementia, which may be of value in clinical trials. CDR-SB ϭ CDR Sum-of-Boxes; eTIV ϭ estimated total intracranial volume; EV ϭ entorhinal volume; HV ϭ hippocampal volume; MCI ϭ mild cognitive impairment; MCT ϭ mean cortical thickness; MMSE ϭ Mini-Mental State Examination; MTL ϭ medial temporal lobe; MTLT ϭ medial temporal lobe thickness; OC ϭ older controls; QAD ϭ questionable AD dementia; ROC ϭ receiver operating characteristic; ROI ϭ region of interest; WBV ϭ whole brain volume.Anatomic abnormalities of brain regions known to be early sites of Alzheimer disease (AD) pathology, such as medial temporal lobe (MTL) regions including the entorhinal cortex and hippocampal formation, can be detected in prodromal AD prior to dementia. 1-3 Although it is well known that early in its clinical course AD affects non-MTL neocortical association regions, 4,5 there has been little investigation of neocortical anatomy in prodromal AD prior to dementia. The few investigations of cortical anatomic abnormalities in mild cognitive impairment (MCI) 6 or prodromal AD 7-9 have used techniques that involve exploratory mapping of

Coherent fluctuations of spontaneous brain activity are present in distinct functional-anatomic brain systems during undirected wakefulness. However, the behavioral significance of this spontaneous activity has only begun to be investigated. Our previous studies have demonstrated that successful memory formation requires coordinated neural activity in a distributed memory network including the hippocampus and posteromedial cortices, specifically the precuneus and posterior cingulate (PPC), thought to be integral nodes of the default network. In this study, we examined whether intrinsic connectivity during the resting state between the hippocampus and PPC can predict individual differences in the performance of an associative memory task among cognitively intact older individuals. The intrinsic connectivity, between regions within the hippocampus and PPC that were maximally engaged during a subsequent memory fMRI task, was measured during a period of rest prior to the performance of the memory paradigm. Stronger connectivity between the hippocampal and posteromedial regions during rest predicted better performance on the memory task. Furthermore, hippocampal-PPC intrinsic connectivity was also significantly correlated with episodic memory measures on neuropsychological tests, but not with performance in non-memory domains. Whole brain exploratory analyses further confirmed the spatial specificity of the relationship between hippocampal-default network posteromedial cortical connectivity and memory performance in older subjects. Our findings provide support for the hypothesis that one of the functions of this large-scale brain network is to subserve episodic memory processes. Research is ongoing to determine if impaired connectivity between these regions may serve as a predictor of memory decline related to early Alzheimer's disease.Correspondence: Reisa A. Sperling M.

Advances in magnetic resonance imaging (MRI) have contributed greatly to the study of neurodegenerative processes, psychiatric disorders, and normal human development, but the effect of such improvements on the reliability of downstream morphometric measures has not been extensively studied. We examined how MRI-derived neurostructural measures are affected by three technological advancements: parallel acceleration, increased spatial resolution, and the use of a high bandwidth multiecho sequence. Test-retest data were collected from 11 healthy participants during 2 imaging sessions occurring approximately 2 weeks apart. We acquired 4 T1-weighted MP-RAGE sequences during each session: a non-accelerated anisotropic sequence (MPR), a non-accelerated isotropic sequence (ISO), an accelerated isotropic sequence (ISH), and an accelerated isotropic high bandwidth multiecho sequence (MEM). Cortical thickness and volumetric measures were computed for each sequence to assess test-retest reliability and measurement bias. Reliability was extremely high for most measures and similar across imaging parameters. Significant measurement bias was observed, however, between MPR and all isotropic sequences for all cortical regions and some subcortical structures. These results suggest that these improvements in MRI acquisition technology do not compromise data reproducibility, but that consistency should be maintained in choosing imaging parameters for structural MRI studies.

Although both normal aging and Alzheimer's disease (AD) are associated with regional cortical atrophy, few studies have directly compared the spatial patterns and magnitude of effects of these two processes. The extant literature has not addressed two important questions: 1) Is the pattern of age-related cortical atrophy different if cognitively intact elderly individuals with silent AD pathology are excluded? and 2) Does the age- or AD-related atrophy relate to cognitive function? Here we studied 142 young controls, 87 older controls, and 28 mild AD patients. In addition, we studied 35 older controls with neuroimaging data indicating the absence of brain amyloid. Whole-cortex analyses identified regions of interest (ROIs) of cortical atrophy in aging and in AD. Results showed that some regions are predominantly affected by age with relatively little additional atrophy in patients with AD, e.g., calcarine cortex; other regions are predominantly affected by AD with much less of an effect of age, e.g., medial temporal cortex. Finally, other regions are affected by both aging and AD, e.g., dorsolateral prefrontal cortex and inferior parietal lobule. Thus, the processes of aging and AD have both differential and partially overlapping effects on specific regions of the cerebral cortex. In particular, some frontoparietal regions are affected by both processes, most temporal lobe regions are affected much more prominently by AD than aging, while sensorimotor and some prefrontal regions are affected specifically by aging and minimally more by AD. Within normal older adults, atrophy in aging-specific cortical regions relates to cognitive performance, while in AD patients atrophy in AD-specific regions relates to cognitive performance. Further work is warranted to investigate the behavioral and clinical relevance of these findings in additional detail, as well as their histological basis; ROIs generated from the present study could be used strategically in such investigations.

Cue-approach training has been shown to effectively shift choices for snack food items by associating a cued button-press motor response to particular food items. Furthermore, attention was biased toward previously cued items, even when the cued item is not chosen for real consumption during a choice phase. However, the exact mechanism by which preferences shift during cue-approach training is not entirely clear. In three experiments, we shed light on the possible underlying mechanisms at play during this novel paradigm: (1) Uncued, wholly predictable motor responses paired with particular food items were not sufficient to elicit a preference shift; (2) Cueing motor responses early – concurrently with food item onset – and thus eliminating the need for heightened top–down attention to the food stimulus in preparation for a motor response also eliminated the shift in food preferences. This finding reinforces our hypothesis that heightened attention at behaviorally relevant points in time is key to changing choice behavior in the cue-approach task; (3) Crucially, indicating choice using eye movements rather than manual button presses preserves the effect, thus demonstrating that the shift in preferences is not governed by a learned motor response but more likely via modulation of subjective value in higher associative regions, consistent with previous neuroimaging results. Cue-approach training drives attention at behaviorally relevant points in time to modulate the subjective value of individual items, providing a mechanism for behavior change that does not rely on external reinforcement and that holds great promise for developing real world behavioral interventions.