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Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter‐dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health. [ABSTRACT FROM AUTHOR]

Early stages of Alzheimer's disease (AD) are associated with volume reductions in specific subregions of the medial temporal lobe (MTL). Using a manual segmentation method—the Olsen–Amaral–Palombo (OAP) protocol—previous work in healthy older adults showed that reductions in grey matter volumes in MTL subregions were associated with lower scores on the Montreal Cognitive Assessment (MoCA), suggesting atrophy may occur prior to diagnosis of mild cognitive impairment, a condition that often progresses to AD. However, current "gold standard" manual segmentation methods are labour intensive and time consuming. Here, we examined the utility of Automatic Segmentation of Hippocampal Subfields (ASHS) to detect volumetric differences in MTL subregions of healthy older adults who varied in cognitive status as determined by the MoCA. We trained ASHS on the OAP protocol to create the ASHS‐OAP atlas and then examined how well automated segmentation replicated manual segmentation. Volumetric measures obtained from the ASHS‐OAP atlas were also contrasted against those from the ASHS‐PMC atlas, a widely used atlas provided by the ASHS team. The pattern of volumetric results was similar between the ASHS‐OAP atlas and manual segmentation for anterolateral entorhinal cortex and perirhinal cortex, suggesting that ASHS‐OAP is a viable alternative to current manual segmentation methods for detecting group differences based on cognitive status. Although ASHS‐OAP and ASHS‐PMC produced varying volumes for most regions of interest, they both identified early signs of neurodegeneration in CA2/CA3/DG and identified marginal differences in entorhinal cortex. Our findings highlight the utility of automated segmentation methods but still underscore the need for a unified and harmonized MTL segmentation atlas. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Mnemonic Similarity Task (MST) is a popular memory task designed to assess hippocampal integrity. We assessed whether analyzing MST performance using a multinomial processing tree (MPT) cognitive model could detect individuals with elevated Alzheimer's disease (AD) biomarker status prior to cognitive decline. METHOD: We analyzed MST data from >200 individuals (young, cognitively healthy older adults and individuals with mild cognitive impairment [MCI]), a subset of which also had existing cerebrospinal fluid (CSF) amyloid beta (Aβ) and phosphorylated tau (pTau) data using both traditional and model‐derived approaches. We assessed how well each could predict age group, memory ability, MCI status, Aβ, and pTau status using receiver operating characteristic analyses. RESULTS: Both approaches predicted age group membership equally, but MPT‐derived metrics exceeded traditional metrics in all other comparisons. DISCUSSION: A MPT model of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for screening and monitoring older adults during the asymptomatic phase of AD. Highlights: The MST, along with cognitive modeling, identifies individuals with memory deficits and cognitive impairment.Cognitive modeling of the MST identifies individuals with increased AD biomarkers prior to changes in cognitive function.The MST is a digital biomarker that identifies individuals at high risk of AD. [ABSTRACT FROM AUTHOR]

BACKGROUND: Digital cognitive assessments, particularly those that can be done at home, present as low‐burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline. METHODS: We analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aβ)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline. RESULTS: Performance on the digital cognitive assessment was superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation. DISCUSSION: Digital assessments are effective at identifying at‐risk individuals, supporting their utility as low‐burden tools for early AD detection and monitoring. Highlights: Performance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau.Deficits in mnemonic discrimination are indicative of future cognitive decline.Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau. [ABSTRACT FROM AUTHOR]

Introduction: The Mnemonic Similarity Task (MST) is a widely used measure of individual tendency to discern small differences between remembered and presently presented stimuli. Significant work has established this measure as a reliable index of neurological and cognitive dysfunction and decline. However, questions remain about the neural and psychological mechanisms that support performance in the task. Methods: Here, we provide new insights into these questions by fitting seven previously-collected MST datasets (total N = 519), adapting a three-choice evidence accumulation model (the Linear Ballistic Accumulator). The model decomposes choices into automatic and deliberative components. Results: We show that these decomposed processes both contribute to the standard measure of behavior in this task, as well as capturing individual variation in this measure across the lifespan. We also exploit a delayed test/re-test manipulation in one of the experiments to show that model parameters exhibit improved stability, relative to the standard metric, across a 1 week delay. Finally, we apply the model to a resting-state fMRI dataset, finding that only the deliberative component corresponds to off-task co-activation in networks associated with long-term, episodic memory. Discussion: Taken together, these findings establish a novel mechanistic decomposition of MST behavior and help to constrain theories about the cognitive processes that support performance in the task. [ABSTRACT FROM AUTHOR]

Successful cognitive aging is often thought to result from resistance to the accumulation of pathology, resilience to the effects of pathological accumulation, or some combination of the two. While evidence for resilience has been found in typical aging populations, the oldest-old provide us with a unique window into the role of pathological accumulation in impacting cognition. Here, we aimed to assess group differences in measures of amyloid and tau across older age groups using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI age: 60–89) and The 90+ Study (age: 90–101). Additionally, using the ADNI dataset, we performed exploratory analyses of regional cingulate AV-45 SUVRs to assess if amyloid load in particular areas was associated with Top Cognitive Performance (TCP). Consistent with the literature, results showed no group differences in amyloid SUVRs both regionally and in the whole cortex. For tau with AV-1451, we also observed no differences in Braak composite SUVRs. Interestingly, these relationships persisted in the oldest-old. This indicates that Top Cognitive Performance throughout aging does not reflect resistance to amyloid and tau burden, but that other mechanisms may be associated with protection against amyloid and tau related neurodegeneration. [ABSTRACT FROM AUTHOR]

Aging dogs serve as a valuable preclinical model for Alzheimer's disease (AD) due to their natural age-related development of β-amyloid (Aβ) plaques, human-like metabolism, and large brains that are ideal for studying structural brain aging trajectories from serial neuroimaging. Here we examined the effects of chronic treatment with the calcineurin inhibitor (CNI) tacrolimus or the nuclear factor of activated T cells (NFAT)-inhibiting compound Q134R on age-related canine brain atrophy from a longitudinal study in middle-aged beagles (36 females, 7 males) undergoing behavioral enrichment. Annual MRI was analyzed using modern, automated techniques for region-of-interest-based and voxel-based volumetric assessments. We found that the frontal lobe showed accelerated atrophy with age, while the caudate nucleus remained relatively stable. Remarkably, the hippocampus increased in volume in all dogs. None of these changes were influenced by tacrolimus or Q134R treatment. Our results suggest that behavioral enrichment can prevent atrophy and increase the volume of the hippocampus but does not prevent aging-associated prefrontal cortex atrophy. [ABSTRACT FROM AUTHOR]

In some tasks (e.g., assigning meanings to ambiguous words) humans produce multiple distinct alternatives in response to a particular stimulus, apparently mirroring the environmental probabilities associated with each alternative. For this purpose, a network architecture is needed that can produce a distribution of outcomes, and a learning algorithm is needed that can lead to the discovery of ensembles of connection weights that reproduce the environmentally specified probabilities. Stochastic symmetric networks such as Boltzmann machines and networks that use graded activations perturbed with Gaussian noise can exhibit such distributions at equilibrium, and they can be trained to match environmentally specified probabilities using Contrastive Hebbian Leaning, the generalized form of the Boltzmann Learning algorithm. Learning distributions exacts a considerable computational cost as processing time is used both in settling to equilibrium and in sampling equilibrium statistics. The work presented here examines the extent of this cost and how it may be minimized, and produces speedups of roughly a factor of 5 compared to previously published results.

Objectives: Ample evidence suggests exercise is beneficial for hippocampal function. Furthermore, a single session of aerobic exercise provides immediate benefits to mnemonic discrimination performance, a highly hippocampal-specific memory process, in healthy younger adults. However, it is unknown if a single session of aerobic exercise alters mnemonic discrimination in older adults, who generally exhibit greater hippocampal deterioration and deficits in mnemonic discrimination performance. Methods: We conducted a within subject acute exercise study in 30 cognitively healthy and physically active older adults who underwent baseline testing and then completed two experimental visits in which they performed a mnemonic discrimination task before and after either 30 min of cycling exercise or 30 min of seated rest. Linear mixed-effects analyses were conducted in which condition order and age were controlled, time (pre vs. post) and condition (exercise vs. rest) were modeled as fixed effects, and subject as a random effect. Results: No significant time by condition interaction effect was found for object recognition (p  = .254, η2=.01), while a significant reduction in interference was found for mnemonic discrimination performance following the exercise condition (p  = .012, η2=.07). A post-intervention only analysis indicated that there was no difference between condition for object recognition (p  = .186, η2=.06), but that participants had better mnemonic discrimination performance (p  < .001, η2=.22) following the exercise. Conclusions: Our results suggest a single session of moderate-intensity aerobic exercise may reduce interference and elicit better mnemonic discrimination performance in healthy older adults, suggesting benefits for hippocampal-specific memory function. [ABSTRACT FROM AUTHOR]

The goal of the present study was to elucidate the role of the human striatum in learning via reward and punishment during an associative learning task. Previous studies have identified the striatum as a critical component in the neural circuitry of reward-related learning. It remains unclear, however, under what task conditions, and to what extent, the striatum is modulated by punishment during an instrumental learning task. Using high-resolution functional magnetic resonance imaging (fMRI) during a reward- and punishment-based probabilistic associative learning task, we observed activity in the ventral putamen for stimuli learned via reward regardless of whether participants were correct or incorrect (i.e., outcome). In contrast, activity in the dorsal caudate was modulated by trials that received feedback--either correct reward or incorrect punishment trials. We also identified an anterior/posterior dissociation reflecting reward and punishment prediction error estimates. Additionally, differences in patterns of activity that correlated with the amount of training were identified along the anterior/posterior axis of the striatum. We suggest that unique subregions of the striatum--separated along both a dorsal/ventral and anterior/posterior axis--differentially participate in the learning of associations through reward and punishment.

Many current theories of false memories propose that, when we retrieve a memory, we are not reactivating a veridical, fixed representation of a past event, but are rather reactivating incomplete fragments that may be accurate or distorted and may have arisen from other events. By presenting the two phases of the misinformation paradigm in different modalities, we could observe sensory reactivation of the auditory and visual cortex during the retrieval phase. Overall, true and false memories showed similar brain activation, but could be distinguished by this reactivation. This was true only in the early regions of the sensory cortex.

Rodent studies have suggested that "pattern separation," the ability to distinguish among similar experiences, is diminished in a subset of aged rats. We extended these findings to the human using a task designed to assess spatial pattern separation behavior (determining at time of test whether pairs of pictures shown during the study were in the same spatial locations). Using a standardized test of word recall to divide healthy aged adults into impaired and unimpaired groups relative to young performance, we demonstrate that aged impaired adults are biased away from pattern separation and toward pattern completion, consistent with the rodent studies.

False memories are often demonstrated using the misinformation paradigm, in which a person's recollection of a witnessed event is altered after exposure to misinformation about the event. The neural basis of this phenomenon, however, remains unknown. The authors used fMRI to investigate encoding processes during the viewing of an event and misinformation to see whether neural activity during either encoding phase could predict what would be remembered. fMRI data were collected as participants studied eight vignettes (Original Event phase). Shortly afterward, participants studied the same vignettes during scanning, but with changes to several details, serving as the misinformation (Misinformation phase). Two days later, their memories for the Original Event were assessed. Activity that subsequently led to true and false memories was examined during both encoding phases. Two interaction patterns between encoding phase (Original Event and Misinformation) and type of memory (true and false) were observed in MTL and PFC regions. In the left hippocampus tail and perirhinal cortex, a predictive item-encoding pattern was observed. During the Original Event phase, activity was greater for true than false memories, whereas during the Misinformation phase, activity was greater for false than true memories. In other regions, a pattern suggestive of source encoding was observed, in which activity for false memories was greater during the Original Event phase than the Misinformation phase. Together, these results suggest that encoding processes play a critical role in determining true and false memory outcome in misinformation paradigms. (Contains 4 figures and 2 tables.)