Neuropsychiatric symptoms: Risk factor or disease marker? A study of structural imaging biomarkers of Alzheimer's disease and incident cognitive decline.

Neuropsychiatric symptoms (NPS) are risk factors for Alzheimer's disease (AD) but can also manifest secondary to AD pathology. Mild behavioral impairment (MBI) refers to later-life emergent and persistent NPS that may mark early-stage AD. To distinguish MBI from NPS that are transient or which represent psychiatric conditions (non-MBI NPS), we investigated the effect of applying MBI criteria on NPS associations with AD structural imaging biomarkers and incident cognitive decline. Data for participants (n = 1273) with normal cognition (NC) or mild cognitive impairment (MCI) in the National Alzheimer's Coordinating Center Uniform Data Set were analyzed. NPS status (MBI, non-MBI NPS) was derived from the Neuropsychiatric Inventory Questionnaire and psychiatric history. Normalized measures of bilateral hippocampal (HPC) and entorhinal cortex (EC) volume, and AD meta-region of interest (ROI) mean cortical thickness were acquired from T1-weighted magnetic resonance imaging scans. Multivariable linear and Cox regressions examined NPS associations with imaging biomarkers and incident cognitive decline, respectively. MBI was associated with lower volume and cortical thickness in all ROIs in both NC and MCI, except for EC volume in NC. Non-MBI NPS were only associated with lower HPC volume in NC. Although both of the NPS groups showed higher hazards for MCI/dementia than No NPS, MBI participants showed more rapid decline. Although both types of NPS were linked to HPC atrophy, only NPS that emerged and persisted in later-life, consistent with MBI criteria, were related to AD neurodegenerative patterns beyond the HPC. Moreover, MBI predicted faster progression to dementia than non-MBI NPS.

Path Integration Detects Prodromal Alzheimer's Disease and Predicts Cognitive Decline.

Background: The entorhinal cortex is the very earliest involvement of Alzheimer's disease (AD). Grid cells in the medial entorhinal cortex form part of the spatial navigation system. Objective: We aimed to determine whether path integration performance can be used to detect patients with mild cognitive impairment (MCI) at high risk of developing AD, and whether it can predict cognitive decline. Methods: Path integration performance was assessed in 71 patients with early MCI (EMCI) and late MCI (LMCI) using a recently developed 3D virtual reality navigation task. Patients with LMCI were further divided into those displaying characteristic brain imaging features of AD, including medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single-photon emission tomography (LMCI+), and those not displaying such features (LMCI-). Results: Path integration performance was significantly lower in patients with LMCI+than in those with EMCI and LMCI-. A significantly lower performance was observed in patients who showed progression of MCI during 12 months, than in those with stable MCI. Path integration performance distinguished patients with progressive MCI from those with stable MCI, with a high classification accuracy (a sensitivity of 0.88 and a specificity of 0.70). Conclusions: Our results suggest that the 3D virtual reality navigation task detects prodromal AD patients and predicts cognitive decline after 12 months. Our navigation task, which is simple, short (12-15 minutes), noninvasive, and inexpensive, may be a screening tool for therapeutic choice of disease-modifiers in individuals with prodromal AD.

Lower entorhinal cortex thickness is associated with greater financial exploitation vulnerability in cognitively unimpaired older adults.

Research suggests that increased financial exploitation vulnerability due to declining decision making may be an early behavioral manifestation of brain changes occurring in preclinical Alzheimer's disease. One of the earliest documented brain changes during the preclinical phase is neurodegeneration in the entorhinal cortex. The objective of the current study was to examine the association between a measure of financial exploitation vulnerability and thickness in the entorhinal cortex in 97 cognitively unimpaired older adults. We also investigated financial exploitation vulnerability associations with frontal regions typically associated with decision making (e.g. dorsolateral and ventromedial prefrontal cortices), and additionally examined the interactive effect of age and cortical thickness on financial exploitation vulnerability. Results showed that greater financial exploitation vulnerability was associated with significantly lower entorhinal cortex thickness. There was a significant interaction between age and entorhinal cortex thickness on financial exploitation vulnerability, whereby lower entorhinal cortex thickness was associated with greater financial exploitation vulnerability in older participants. When the group was divided by age using a median split (70+ and <70 years old), lower entorhinal cortex thickness was associated with greater vulnerability only in the older group. Collectively, these findings suggest that financial exploitation vulnerability may serve as a behavioral manifestation of entorhinal cortex thinning, a phenomenon observed in suboptimal brain aging and preclinical Alzheimer's disease.

Replay-triggered brain-wide activation in humans.

The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay.

Estimating individual trajectories of structural and cognitive decline in mild cognitive impairment for early prediction of progression to dementia of the Alzheimer's type.

Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer's Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions-episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.

Sleep Quality Moderates the Associations between Cardiorespiratory Fitness and Hippocampal and Entorhinal Volume in Middle-Aged and Older Adults.

INTRODUCTION/PURPOSE: As individuals age, the entorhinal cortex (ERC) and hippocampus-crucial structures for memory-tend to atrophy, with related cognitive decline. Simultaneously, lifestyle factors that can be modified, such as exercise and sleep, have been separately linked to slowing of brain atrophy and functional decline. However, the synergistic impact of fitness and sleep on susceptible brain structures in aging adults remains uncertain. METHODS: We examined both independent and interactive associations of fitness and subjective sleep quality with regard to ERC thickness and hippocampal volume in 598 middle-aged and older adults from the Human Connectome Lifespan Aging Project. Cardiorespiratory fitness was assessed using the 2-min walk test, whereas subjective sleep quality was measured with the continuous Pittsburgh Sleep Quality Index global score. High-resolution structural magnetic resonance imaging was used to examine mean ERC thickness and bilateral hippocampal volume. Through multiple linear regression analyses, we investigated the moderating effects of subjective sleep quality on the association between fitness and brain structure, accounting for age, sex, education, body mass index, gait speed, and subjective physical activity. RESULTS: We found that greater cardiorespiratory fitness, but not subjective sleep quality, was positively associated with bilateral hippocampal volume and ERC thickness. Notably, significant interaction effects suggest that poor subjective sleep quality was associated with a weaker association between fitness and both hippocampal volume and ERC thickness. CONCLUSIONS: Findings suggest the potential importance of both cardiorespiratory fitness and subjective sleep quality in preserving critical, age-vulnerable brain structures. Interventions targeting brain health should consider potential combined effects of sleep and fitness on brain health.

Evidence for grid-cell-like activity in the time domain.

The relation between the processing of space and time in the brain has been an enduring cross-disciplinary question. Grid cells have been recognized as a hallmark of the mammalian navigation system, with recent studies attesting to their involvement in the organization of conceptual knowledge in humans. To determine whether grid-cell-like representations support temporal processing, we asked subjects to mentally simulate changes in age and time-of-day, each constituting "trajectory" in an age-day space, while undergoing fMRI. We found that grid-cell-like representations supported trajecting across this age-day space. Furthermore, brain regions concurrently coding past-to-future orientation positively modulated the magnitude of grid-cell-like representation in the left entorhinal cortex. Finally, our findings suggest that temporal processing may be supported by spatially modulated systems, and that innate regularities of abstract domains may interface and alter grid-cell-like representations, similarly to spatial geometry.

Circulating PACAP levels are associated with altered imaging measures of entorhinal cortex neurite density in posttraumatic stress disorder.

Introduction: Pituitary adenylate cyclase-activating polypeptide (PACAP) regulates plasticity in brain systems underlying arousal and memory and is associated with posttraumatic stress disorder (PTSD). Research in animal models suggests that PACAP modulates entorhinal cortex (EC) input to the hippocampus, contributing to impaired contextual fear conditioning. In PTSD, PACAP is associated with higher activity of the amygdala to threat stimuli and lower functional connectivity of the amygdala and hippocampus. However, PACAP-affiliated structural alterations of these regions have not been investigated in PTSD. Here, we examined whether peripheral PACAP levels were associated with neuronal morphology of the amygdala and hippocampus (primary analyses), and EC (secondary) using Neurite Orientation Dispersion and Density Imaging.Methods: Sixty-four (44 female) adults (19 to 54 years old) with DSM-5 Criterion A trauma exposure completed the Clinician-Administered PTSD Scale (CAPS-5), a blood draw, and magnetic resonance imaging. PACAP38 radioimmunoassay was performed and T1-weighted and multi-shell diffusion-weighted images were acquired. Neurite Density Index (NDI) and Orientation Dispersion Index (ODI) were quantified in the amygdala, hippocampus, and EC. CAPS-5 total score and anxious arousal score were used to test for clinical associations with brain structure.Results: Higher PACAP levels were associated with greater EC NDI (ß = 0.0099, q = 0.032) and lower EC ODI (ß = -0.0073, q = 0.047), and not hippocampal or amygdala measures. Neither EC NDI nor ODI was associated with clinical measures.Conclusions: Circulating PACAP levels were associated with altered neuronal density of the EC but not the hippocampus or amygdala. These findings strengthen evidence that PACAP may impact arousal-associated memory circuits in PTSD.

PACAP was associated with altered entorhinal cortex neurite density in PTSD.PACAP was not associated with altered neurite density in amygdala or hippocampus.PACAP may impact arousal-associated memory circuits.

Degeneration in Nucleus basalis of Meynert signals earliest stage of Alzheimer's disease progression.

Nucleus Basalis of Meynert (NbM), a crucial source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), has shown sensitivity to neurofibrillary degeneration in the early stages of Alzheimer's Disease. Using deformation-based morphometry (DBM) on up-sampled MRI scans from 1447 Alzheimer's Disease Neuroimaging Initiative participants, we aimed to quantify NbM degeneration along the disease trajectory. Results from cross-sectional analysis revealed significant differences of NbM volume between cognitively normal and early mild cognitive impairment cohorts, confirming recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. Longitudinal linear mixed-effect models were then used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results indicated the earliest deviations in NbM volumes from the cognitively healthy trajectory, challenging the prevailing idea that Alzheimer's originates in the EC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.

Altered grid-like coding in early blind people.

Cognitive maps in the hippocampal-entorhinal system are central for the representation of both spatial and non-spatial relationships. Although this system, especially in humans, heavily relies on vision, the role of visual experience in shaping the development of cognitive maps remains largely unknown. Here, we test sighted and early blind individuals in both imagined navigation in fMRI and real-world navigation. During imagined navigation, the Human Navigation Network, constituted by frontal, medial temporal, and parietal cortices, is reliably activated in both groups, showing resilience to visual deprivation. However, neural geometry analyses highlight crucial differences between groups. A 60° rotational symmetry, characteristic of a hexagonal grid-like coding, emerges in the entorhinal cortex of sighted but not blind people, who instead show a 90° (4-fold) symmetry, indicative of a square grid. Moreover, higher parietal cortex activity during navigation in blind people correlates with the magnitude of 4-fold symmetry. In sum, early blindness can alter the geometry of entorhinal cognitive maps, possibly as a consequence of higher reliance on parietal egocentric coding during navigation.

Grid-like entorhinal representation of an abstract value space during prospective decision making.

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making.

Sex significantly predicts medial temporal volume when controlling for the influence of ApoE4 biomarker and demographic variables: A cross-ethnic comparison.

OBJECTIVE: To explore the relationship between age, education, sex, and ApoE4 (+) status to brain volume among a cohort with amnestic mild cognitive impairment (aMCI). METHOD: One hundred and twenty-three participants were stratified into Hispanic (n = 75) and White non-Hispanic (WNH, N = 48). Multiple linear regression analyses were conducted with age, education, sex, and ApoE4 status as predictor variables and left and right combined MRI volumes of the hippocampus, parahippocampus, and entorhinal cortex as dependent variables. Variations in head sizes were corrected by normalization with a total intracranial volume measurement. RESULTS: Bonferroni-corrected results indicated that when controlling for ApoE4 status, education, and age, sex was a significant predictor of hippocampal volume among the Hispanic group (ß = .000464, R2 = .196, p < .01) and the WNH group (ß = .000455, R2 = .195, p < .05). Education (ß = .000028, R2 = .168, p < .01) and sex (ß = .000261, R2 = .168, p < .01) were significant predictors of parahippocampal volume among the Hispanic MCI group when controlling for the effects of ApoE4 status and age. One-way ANCOVAs comparing hippocampal and parahippocampal volume between males and females within groups revealed that females had significantly larger hippocampal volumes (p < .05). Hispanic females had significantly larger hippocampal (p < .001) and parahippocampal (p < .05) volume compared to males. No sex differences in parahippocampal volume were noted among WNHs. CONCLUSIONS: Biological sex, rather than ApoE4 status, was a greater predictor of hippocampal volume among Hispanic and WNH females. These findings add to the mixed literature on sex differences in dementia research and highlight continued emphasis on ethnic populations to elucidate on neurodegenerative disparities.

Associations between white matter hyperintensities, lacunes, entorhinal cortex thickness, declarative memory and leisure activity in cognitively healthy older adults: A 7-year study.

INTRODUCTION: Cerebral small vessel disease (cSVD) is a growing epidemic that affects brain health and cognition. Therefore, a more profound understanding of the interplay between cSVD, brain atrophy, and cognition in healthy aging is of great importance. In this study, we examined the association between white matter hyperintensities (WMH) volume, number of lacunes, entorhinal cortex (EC) thickness, and declarative memory in cognitively healthy older adults over a seven-year period, controlling for possible confounding factors. Because there is no cure for cSVD to date, the neuroprotective potential of an active lifestyle has been suggested. Supporting evidence, however, is scarce. Therefore, a second objective of this study is to examine the relationship between leisure activities, cSVD, EC thickness, and declarative memory. METHODS: We used a longitudinal dataset, which consisted of five measurement time points of structural MRI and psychometric cognitive ability and survey data, collected from a sample of healthy older adults (baseline N = 231, age range: 64-87 years, age M = 70.8 years), to investigate associations between cSVD MRI markers, EC thickness and verbal and figural memory performance. Further, we computed physical, social, and cognitive leisure activity scores from survey-based assessments and examined their associations with brain structure and declarative memory. To provide more accurate estimates of the trajectories and cross-domain correlations, we applied latent growth curve models controlling for potential confounders. RESULTS: Less age-related thinning of the right (ß = 0.92, p<.05) and left EC (ß = 0.82, p<.05) was related to less declarative memory decline; and a thicker EC at baseline predicted less declarative memory loss (ß = 0.54, p<.05). Higher baseline levels of physical (ß = 0.24, p<.05), and social leisure activity (ß = 0.27, p<.01) predicted less thinning of right EC. No relation was found between WMH or lacunes and declarative memory or between leisure activity and declarative memory. Higher education was initially related to more physical activity (ß = 0.16, p<.05) and better declarative memory (ß = 0.23, p<.001), which, however, declined steeper in participants with higher education (ß = -.35, p<.05). Obese participants were less physically (ß = -.18, p<.01) and socially active (ß = -.13, p<.05) and had thinner left EC (ß = -.14, p<.05) at baseline. Antihypertensive medication use (ß = -.26, p<.05), and light-to-moderate alcohol consumption (ß = -.40, p<.001) were associated with a smaller increase in the number of lacunes whereas a larger increase in the number of lacunes was observed in current smokers (ß = 0.30, p<.05). CONCLUSIONS: Our results suggest complex relationships between cSVD MRI markers (total WMH, number of lacunes, right and left EC thickness), declarative memory, and confounding factors such as antihypertensive medication, obesity, and leisure activitiy. Thus, leisure activities and having good cognitive reserve counteracting this neurodegeneration. Several confounding factors seem to contribute to the extent or progression/decline of cSVD, which needs further investigation in the future. Since there is still no cure for cSVD, modifiable confounding factors should be studied more intensively in the future to maintain or promote brain health and thus cognitive abilities in older adults.

Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease.

The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland-Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.

Asymmetry of brain development in adolescent rats studied by 3.0 T magnetic resonance imaging.

To study the developmental patterns of brain structure in adolescent rats based on the registration with the SIGMA template by 3.0T MRI. Forty male Sprague-Dawley rats (180-220 g) were randomly divided into four groups. Rats in the four groups underwent 3.0 T MRI head scans at 7, 11, 15, and 19 weeks of age, respectively. The voxel-based morphological analysis of the rat brain was performed by coregistration with the SIGMA rat brain template. 3.0 T MRI can be used to study the anatomical structure of the rat brain by registration with the SIGMA template The gray matter volume of the bilateral hippocampus and bilateral entorhinal cortex increased significantly in the development of the rat from 7 to 19 weeks of age. In this period, the subtle structure of the rat brain is asymmetrically developed. The rat aged 7-19 weeks has asymmetrical gray matter volume development in the bilateral entorhinal cortex and hippocampus.

An Optimized Deep Learning Model for Predicting Mild Cognitive Impairment Using Structural MRI.

Early diagnosis of mild cognitive impairment (MCI) with magnetic resonance imaging (MRI) has been shown to positively affect patients' lives. To save time and costs associated with clinical investigation, deep learning approaches have been used widely to predict MCI. This study proposes optimized deep learning models for differentiating between MCI and normal control samples. In previous studies, the hippocampus region located in the brain is used extensively to diagnose MCI. The entorhinal cortex is a promising area for diagnosing MCI since severe atrophy is observed when diagnosing the disease before the shrinkage of the hippocampus. Due to the small size of the entorhinal cortex area relative to the hippocampus, limited research has been conducted on the entorhinal cortex brain region for predicting MCI. This study involves the construction of a dataset containing only the entorhinal cortex area to implement the classification system. To extract the features of the entorhinal cortex area, three different neural network architectures are optimized independently: VGG16, Inception-V3, and ResNet50. The best outcomes were achieved utilizing the convolution neural network classifier and the Inception-V3 architecture for feature extraction, with accuracy, sensitivity, specificity, and area under the curve scores of 70%, 90%, 54%, and 69%, respectively. Furthermore, the model has an acceptable balance between precision and recall, achieving an F1 score of 73%. The results of this study validate the effectiveness of our approach in predicting MCI and may contribute to diagnosing MCI through MRI.

Dissociating distinct cortical networks associated with subregions of the human medial temporal lobe using precision neuroimaging.

Tract-tracing studies in primates indicate that different subregions of the medial temporal lobe (MTL) are connected with multiple brain regions. However, no clear framework defining the distributed anatomy associated with the human MTL exists. This gap in knowledge originates in notoriously low MRI data quality in the anterior human MTL and in group-level blurring of idiosyncratic anatomy between adjacent brain regions, such as entorhinal and perirhinal cortices, and parahippocampal areas TH/TF. Using MRI, we intensively scanned four human individuals and collected whole-brain data with unprecedented MTL signal quality. Following detailed exploration of cortical networks associated with MTL subregions within each individual, we discovered three biologically meaningful networks associated with the entorhinal cortex, perirhinal cortex, and parahippocampal area TH, respectively. Our findings define the anatomical constraints within which human mnemonic functions must operate and are insightful for examining the evolutionary trajectory of the MTL connectivity across species.

Medial Temporal Lobe Atrophy in Predementia Alzheimer's Disease: A Longitudinal Multi-Site Study Comparing Staging and A/T/N in a Clinical Research Cohort.

BACKGROUND: Atrophy of the medial temporal lobe (MTL) is a biological characteristic of Alzheimer's disease (AD) and can be measured by segmentation of magnetic resonance images (MRI). OBJECTIVE: To assess the clinical utility of automated volumetry in a cognitively well-defined and biomarker-classified multi-center longitudinal predementia cohort. METHODS: We used Automatic Segmentation of Hippocampal Subfields (ASHS) to determine MTL morphometry from MRI. We harmonized scanner effects using the recently developed longitudinal ComBat. Subjects were classified according to the A/T/N system, and as normal controls (NC), subjective cognitive decline (SCD), or mild cognitive impairment (MCI). Positive or negative values of A, T, and N were determined by cerebrospinal fluid measurements of the Aß42/40 ratio, phosphorylated and total tau. From 406 included subjects, longitudinal data was available for 206 subjects by stage, and 212 subjects by A/T/N. RESULTS: Compared to A-/T-/N- at baseline, the entorhinal cortex, anterior and posterior hippocampus were smaller in A+/T+orN+. Compared to NC A- at baseline, these subregions were also smaller in MCI A+. Longitudinally, SCD A+ and MCI A+, and A+/T-/N- and A+/T+orN+, had significantly greater atrophy compared to controls in both anterior and posterior hippocampus. In the entorhinal and parahippocampal cortices, longitudinal atrophy was observed only in MCI A+ compared to NC A-, and in A+/T-/N- and A+/T+orN+ compared to A-/T-/N-. CONCLUSION: We found MTL neurodegeneration largely consistent with existing models, suggesting that harmonized MRI volumetry may be used under conditions that are common in clinical multi-center cohorts.

Differential Laminar Activation Dissociates Encoding and Retrieval in the Human Medial and Lateral Entorhinal Cortex.

The hierarchically organized structures of the medial temporal lobe are critically important for episodic memory function. Accumulating evidence suggests dissociable information processing pathways are maintained throughout these structures including in the medial and lateral entorhinal cortex. Cortical layers provide an additional dimension of dissociation as the primary input to the hippocampus derives from layer 2 neurons in the entorhinal cortex, whereas the deeper layers primarily receive output from the hippocampus. Here, novel high-resolution T2-prepared functional MRI methods were successfully used to mitigate susceptibility artifacts typically affecting MRI signals in this region providing uniform sensitivity across the medial and lateral entorhinal cortex. During the performance of a memory task, healthy human subjects (age 25-33 years, mean age 28.2 ± 3.3 years, 4 female) showed differential functional activation in the superficial and deep layers of the entorhinal cortex associated with task-related encoding and retrieval conditions, respectively. The methods provided here offer an approach to probe layer-specific activation in normal cognition and conditions contributing to memory impairment.SIGNIFICANCE STATEMENT This study provides new evidence for differential neuronal activation in the superficial versus deep layers of the entorhinal cortex associated with encoding and retrieval memory processes, respectively, in cognitively normal adults. The study further shows that this dissociation can be observed in both the medial and the lateral entorhinal cortex. The study was achieved by using a novel functional MRI method allowing us to measure robust functional MRI signals in both the medial and lateral entorhinal cortex that was not possible in previous studies. The methodology established here in healthy human subjects lays a solid foundation for subsequent studies investigating layer-specific and region-specific changes in the entorhinal cortex associated with memory impairment in various conditions such as Alzheimer's disease.

Single voxel autocorrelation uncovers gradients of temporal dynamics in the hippocampus and entorhinal cortex during rest and navigation.

During navigation, information at multiple scales needs to be integrated. Single-unit recordings in rodents suggest that gradients of temporal dynamics in the hippocampus and entorhinal cortex support this integration. In humans, gradients of representation are observed, such that granularity of information represented increases along the long axis of the hippocampus. The neural underpinnings of this gradient in humans, however, are still unknown. Current research is limited by coarse fMRI analysis techniques that obscure the activity of individual voxels, preventing investigation of how moment-to-moment changes in brain signal are organized and how they are related to behavior. Here, we measured the signal stability of single voxels over time to uncover previously unappreciated gradients of temporal dynamics in the hippocampus and entorhinal cortex. Using our novel, single voxel autocorrelation technique, we show a medial-lateral hippocampal gradient, as well as a continuous autocorrelation gradient along the anterolateral-posteromedial entorhinal extent. Importantly, we show that autocorrelation in the anterior-medial hippocampus was modulated by navigational difficulty, providing the first evidence that changes in signal stability in single voxels are relevant for behavior. This work opens the door for future research on how temporal gradients within these structures support the integration of information for goal-directed behavior.