Medial Temporal Lobe Subregions Research Articles

Encoding of Visual Objects in the Human Medial Temporal Lobe.

The human medial temporal lobe (MTL) plays a crucial role in recognizing visual objects, a key cognitive function that relies on the formation of semantic representations. Nonetheless, it remains unknown how visual information of general objects is translated into semantic representations in the MTL. Furthermore, the debate about whether the human MTL is involved in perception has endured for a long time. To address these questions, we investigated three distinct models of neural object coding-semantic coding, axis-based feature coding, and region-based feature coding-in each subregion of the human MTL, using high-resolution fMRI in two male and six female participants. Our findings revealed the presence of semantic coding throughout the MTL, with a higher prevalence observed in the parahippocampal cortex (PHC) and perirhinal cortex (PRC), while axis coding and region coding were primarily observed in the earlier regions of the MTL. Moreover, we demonstrated that voxels exhibiting axis coding supported the transition to region coding and contained information relevant to semantic coding. Together, by providing a detailed characterization of neural object coding schemes and offering a comprehensive summary of visual coding information for each MTL subregion, our results not only emphasize a clear role of the MTL in perceptual processing but also shed light on the translation of perception-driven representations of visual features into memory-driven representations of semantics along the MTL processing pathway.

Tau PET burden in Brodmann areas 35 and 36 is associated with individual differences in cognition in non-demented older adults.

The accumulation of neurofibrillary tau tangles, a neuropathological hallmark of Alzheimer's disease (AD), occurs in medial temporal lobe (MTL) regions early in the disease process, with some of the earliest deposits localized to subregions of the entorhinal cortex. Although functional specialization of entorhinal cortex subregions has been reported, few studies have considered functional associations with localized tau accumulation. In this study, stepwise linear regressions were used to examine the contributions of regional tau burden in specific MTL subregions, as measured by 18F-MK6240 PET, to individual variability in cognition. Dependent measures of interest included the Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini Mental State Examination (MMSE), and composite scores of delayed episodic memory and language. Other model variables included age, sex, education, APOE4 status, and global amyloid burden, indexed by 11C-PiB. Tau burden in right Brodmann area 35 (BA35), left and right Brodmann area 36 (BA36), and age each uniquely contributed to the proportion of explained variance in CDR-SB scores, while right BA36 and age were also significant predictors of MMSE scores, and right BA36 was significantly associated with delayed episodic memory performance. Tau burden in both left and right BA36, along with education, uniquely contributed to the proportion of explained variance in language composite scores. Importantly, the addition of more inclusive ROIs, encompassing less granular segmentation of the entorhinal cortex, did not significantly contribute to explained variance in cognition across any of the models. These findings suggest that the ability to quantify tau burden in more refined MTL subregions may better account for individual differences in cognition, which may improve the identification of non-demented older adults who are on a trajectory of decline due to AD.

Tau deposition patterns within the medial temporal lobe follow the connectivity of the entorhinal cortex – a combined post‐mortem and 7T fMRI study

AbstractBackgroundIn aging, tau pathology develops in the medial temporal lobe (MTL), but spreads extensively to the cortex in the presence of amyloid‐beta, driving neurodegeneration and Alzheimer’s disease (AD) dementia development. This suggests that earliest age‐related MTL tau is a pre‐requisite for cortical tau spreading and the development of AD. Using tau‐PET in AD, we found previously that functional connectivity routes the cortical expansion of tau, supporting the concept of trans‐neuronal tau spreading. However, it is unclear whether MTL tau accumulation follows within‐MTL connections, in particular those of the entorhinal (EC) and transentorhinal cortex (A35), i.e. the earliest sites of tau accumulation. To address this, we combined post‐mortem histopathological MTL tau assessments with high‐resolution 7T functional MRI to determine MTL subregional connectivity.MethodsWe included 3D post‐mortem quantitative histopathological tau assessments of 14 MTL subregions (Fig.1A) in 18 participants with overall low AD neuropathological change to capture earliest tau (Fig.1B), and 7T resting‐state fMRI from young and healthy controls (n = 29) to characterize MTL functional connectivity. Using post‐mortem data, we assessed the covariance of AT8‐stained tau among MTL subregions (Fig.1C) and assessed the correlation with functional connectivity among the same regions (Fig.1D). Further, we determined seed‐based connectivity to determine which MTL subregions connectivity pattern was the best predictor of MTL‐wide tau patterns.ResultsPost‐mortem tau levels were highest in the amygdala, followed by A35 and the EC (Fig.2A). As hypothesized, we found an association between MTL connectivity and covariance in MTL tau (r = 0.42, p<0.001, Fig.2B), where closely connected regions showed correlated tau. When assessing seed‐based connectivity as a predictor of MTL tau patterns, EC connectivity was the best predictor for MTL tau deposition patterns (Fig.2C).ConclusionsClosely connected MTL subregions show correlated histopathologically‐assessed tau load, suggesting connectivity to route earliest within MTL tau spreading. Despite highest tau in the amygdala, EC connectivity was the best predictor of MTL tau patterns, suggesting that the EC is a key source for within MTL tau spreading. This can be critical to assess EC connectivity as a potential treatment target to prevent cortical tau spreading and thus neurodegeneration and cognitive decline in AD.

Tau deposition patterns within the medial temporal lobe follow the connectivity of the entorhinal cortex – a combined post‐mortem and 7T fMRI study

AbstractBackgroundIn aging, tau pathology develops in the medial temporal lobe (MTL), but spreads extensively to the cortex in the presence of amyloid‐beta, driving neurodegeneration and Alzheimer’s disease (AD) dementia development. This suggests that earliest age‐related MTL tau is a pre‐requisite for cortical tau spreading and the development of AD. Using tau‐PET in AD, we found previously that functional connectivity routes the cortical expansion of tau, supporting the concept of trans‐neuronal tau spreading. However, it is unclear whether MTL tau accumulation follows within‐MTL connections, in particular those of the entorhinal (EC) and transentorhinal cortex (A35), i.e. the earliest sites of tau accumulation. To address this, we combined post‐mortem histopathological MTL tau assessments with high‐resolution 7T functional MRI to determine MTL subregional connectivity.MethodWe included 3D post‐mortem quantitative histopathological tau assessments of 14 MTL subregions (Fig.1A) in 18 participants with overall low AD neuropathological change to capture earliest tau (Fig.1B), and 7T resting‐state fMRI from young and healthy controls (n = 29) to characterize MTL functional connectivity. Using post‐mortem data, we assessed the covariance of AT8‐stained tau among MTL subregions (Fig.1C) and assessed the correlation with functional connectivity among the same regions (Fig.1D). Further, we determined seed‐based connectivity to determine which MTL subregions connectivity pattern was the best predictor of MTL‐wide tau patterns.ResultPost‐mortem tau levels were highest in the amygdala, followed by A35 and the EC (Fig.2A). As hypothesized, we found an association between MTL connectivity and covariance in MTL tau (r = 0.42, p<0.001, Fig.2B), where closely connected regions showed correlated tau. When assessing seed‐based connectivity as a predictor of MTL tau patterns, EC connectivity was the best predictor for MTL tau deposition patterns (Fig.2C).ConclusionClosely connected MTL subregions show correlated histopathologically‐assessed tau load, suggesting connectivity to route earliest within MTL tau spreading. Despite highest tau in the amygdala, EC connectivity was the best predictor of MTL tau patterns, suggesting that the EC is a key source for within MTL tau spreading. This can be critical to assess EC connectivity as a potential treatment target to prevent cortical tau spreading and thus neurodegeneration and cognitive decline in AD.

Comparison of histological delineation of the entorhinal, perirhinal, ectorhinal, and parahippocampal cortices by different neuroanatomy laboratories

AbstractBackgroundThe medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and a hotspot of neurodegenerative processes (e.g., accumulation of tau tangles or TDP‐43). Importantly, the MTL cortex comprises several subregions with distinct functional, cytoarchitectonic, and macro‐anatomical features (Fig. 1). In vivo imaging studies measuring atrophy or aggregates of pathologies in these subregions rely on various segmentation protocols. Comparability of these imaging studies is limited as segmentation protocols differ, which results from different macro‐anatomical parcellations and cytoarchitectonic definitions of MTL subregions. Thus, it must be clarified to which extent definitions of MTL subregions overlap between neuroanatomists, to establish a harmonized MTL magnetic resonance imaging (MRI) segmentation protocol. We give an overview of cytoarchitectonic definitions of MTL cortex subregions provided by four neuroanatomists from independent laboratories.MethodFour neuroanatomists performed annotations of the entorhinal cortex, Brodmann area (BA) 35, BA36, and the parahippocampal cortex on digital histology images. Nissl‐stained series were acquired in three specimens (Fig. 2). Slices (50µm thick) were prepared perpendicular to the anterior commissure‐posterior comimssure line spanning the entire longitudinal extent of the MTL cortex. Neuroanatomists annotated MTL cortex subdivisions on digitized (20X resolution) slices with 5mm spacing. Parcellations, terminology, and delineations were compared between neuroanatomists.ResultCytoarchitectonic features of the MTL cortex subregions are described in detail. Overall, we observed higher agreement in the definition of the entorhinal cortex and BA35, while definitions of BA36 and the parahippocampal cortex exhibited less overlap between neuroanatomists (Fig. 2). The degree of overlap of cytoarchitectonic definitions was reflected in the neuroanatomists’ agreement on the respective delineations. Lower agreement on annotations was observed for transitional zones where gradual changes from one subregion to another occur (Fig. 3). Due to the gradual transition of features from, for example, proisocortex to periallocortex, border placement is difficult to determine according to the neuroanatomists.ConclusionThe results highlight that definitions and parcellations of the MTL cortex are variable but increase understanding of why these differences arise. This sets a crucial foundation for a harmonized in vivo MRI segmentation protocol for cortical MTL subregions and the study of these regions in the context of dementia.

Aging and Alzheimer’s Disease Have Dissociable Effects on Local and Regional Medial Temporal Lobe Connectivity

AbstractBackgroundThe extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD.MethodIn this cross‐sectional study, we analyzed data from 179 individuals from the Aging Brain Cohort study of the Penn ADRC. Detailed information about participants is provided in Table 1. For intra‐MTL FC comparisons, the MTL subregions were segmented using the automated segmentation of hippocampal subfields‐T1 (ASHS‐T1) pipeline (Fig. 1a). When modeling the MTL’s interactions with the rest of the cortex, we employed four MTL ROIs (left/right × anterior/posterior) derived from an ex vivo atlas of tau accumulation in the MTL. Our functional datasets were preprocessed using a customized fMRIprep pipeline. Sparse network estimations and modularity‐based consensus clustering were used to reconstruct the AT and PM network systems (Fig. 1b). Age effect analyses and group comparisons along the AD continuum were performed using the General Linear Model within the network‐based statistical framework.ResultsThe preclinical stage of AD was characterized by increased FC between the perirhinal cortex and other regions of the MTL, as well as between the anterior MTL and its direct neighbors in the AT network (Fig. 1c‐d). This effect was not present in symptomatic AD. Instead, symptomatic patients displayed reduced hippocampal and intra‐PM connectivity. For normal aging, our results led to three main conclusions (for visuals, see Fig. 2). First, intra‐network connectivity of both the AT and PM networks decreases with age. Second, FC between the anterior and posterior segments of the MTL declines with age. Finally, within the MTL, we observed greater vulnerability of the posterior MTL subregions, particularly the parahippocampal cortex, to age‐associated FC decline.ConclusionTogether, the current results provide evidence for aberrant connectivity in the preclinical stage of AD that may have implications for early AD pathophysiology.

Aging and Alzheimer’s Disease Have Dissociable Effects on Local and Regional Medial Temporal Lobe Connectivity

AbstractBackgroundThe extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD.MethodIn this cross‐sectional study, we analyzed data from 179 individuals from the Aging Brain Cohort study of the Penn ADRC. Detailed information about participants is provided in Table 1. For intra‐MTL FC comparisons, the MTL subregions were segmented using the automated segmentation of hippocampal subfields‐T1 (ASHS‐T1) pipeline (Fig. 1a). When modeling the MTL’s interactions with the rest of the cortex, we employed four MTL ROIs (left/right × anterior/posterior) derived from an ex vivo atlas of tau accumulation in the MTL. Our functional datasets were preprocessed using a customized fMRIprep pipeline. Sparse network estimations and modularity‐based consensus clustering were used to reconstruct the AT and PM network systems (Fig. 1b). Age effect analyses and group comparisons along the AD continuum were performed using the General Linear Model within the network‐based statistical framework.ResultThe preclinical stage of AD was characterized by increased FC between the perirhinal cortex and other regions of the MTL, as well as between the anterior MTL and its direct neighbors in the AT network (Fig. 1c‐d). This effect was not present in symptomatic AD. Instead, symptomatic patients displayed reduced hippocampal and intra‐PM connectivity. For normal aging, our results led to three main conclusions (for visuals, see Fig. 2). First, intra‐network connectivity of both the AT and PM networks decreases with age. Second, FC between the anterior and posterior segments of the MTL declines with age. Finally, within the MTL, we observed greater vulnerability of the posterior MTL subregions, particularly the parahippocampal cortex, to age‐associated FC decline.ConclusionTogether, the current results provide evidence for aberrant connectivity in the preclinical stage of AD that may have implications for early AD pathophysiology.

Using an ex vivo MRI atlas of the human medial temporal lobe to characterize the 3D distribution of neurofibrillary tangle burden across histologically defined subregions

AbstractBackgroundAccumulation of tau neurofibrillary tangles (NFT) in the medial temporal lobe (MTL) is an early pathological change associated with neurodegeneration in Alzheimer’s Disease (AD). Current understanding of the spread of NFTs within the MTL is based on 2‐D histological sections sampled at sparse locations. Here, using human MTL specimens from donors with diagnoses spanning the AD continuum, we examine 3‐D quantitative maps of NFT burden derived from serial histology leveraging a high‐resolution, ex vivo MRI atlas, thus enabling more granular analyses.MethodWe combined ex vivo MRI scans (0.2×0.2×0.2mm3, 9.4T) of 55 MTL specimens using a customized registration approach to construct a 3‐D atlas (Ravikumar et al., Acta Neuropathol Comm, 2021). MTL subregions in the atlas were labelled based on cytoarchitecture using serial Nissl histology (n = 17) (Fig.1). For 25 specimens with a primary diagnosis of AD or primary age‐related tauopathy (78.6±10.9 years; 16M/9F), quantitative NFT burden maps were derived from serial anti‐tau immunohistochemistry histology and registered to the atlas for group‐level analysis (Yushkevich et al., Brain, 2021). For quantitative comparisons, we computed the mean NFT burden and cortical thickness within each subregion.ResultFig.2A shows average and summary frequency maps of NFT burden, computed separately for specimens with a low Braak stage (Braak0‐II; n = 11) and high Braak stage (BraakIV‐VI), that reveal a clear anterior‐to‐posterior gradient in NFT burden. At low Braak stages, we observe high levels of NFT burden in cornu ammonis (CA)1, entorhinal cortex (EC), and Brodmann area 35 (BA35;≈transentorhinal region), particularly in the outer cortical layers. CA1 and EC also show higher NFT burden relative to BA35 (Fig.2C). At high Braak stages, overall NFT burden is visibly higher and more widespread, with significant increases found across almost all subregions (Fig.2B). Moreover, significant correlations between NFT burden and cortical thinning were found in the perforant pathway (PP; molecular layer of the subiculum), dentate gyrus, EC and Areas TE, TF and TH (Fig.3).ConclusionBuilding on earlier work, we provide a detailed characterization of the distribution of NFT burden in the MTL. Our findings of specific subregional involvement of early NFT pathology can help inform the development of improved in vivo neuroimaging biomarkers

Tau PET accumulation in Brodmann areas 35 and 36 is associated with individual differences in cognition in non‐demented older adults

AbstractBackgroundMounting evidence indicates that tau accumulation in the entorhinal cortex (EC) occurs early in the course of Alzheimer’s disease (AD). Recent advances in automated segmentation methods allow for the investigation of smaller regions of the medial temporal lobes (MTL), including subregions of the EC. This study examined tau deposition in relation to individual differences in cognition among older adults, assessing whether MTL subregions explained a greater proportion of variance in cognition, when compared to standard labeling methods.MethodAnalyses included 91 BIOCARD study participants who were cognitively unimpaired (CU; n = 82) or had mild cognitive impairment (MCI; n = 9). Stepwise linear regressions were used to examine the contributions of regional tau burden to individual differences in the CDR sum of boxes (CDR‐SB), MMSE, and composite scores of global cognition and memory. Other model variables included amyloid burden, APOE4 status, sex, and education. Amyloid burden was assessed by 11C‐PiB and regional tau was assessed by 18F‐MK‐6240 PET. SUVR values representing tau accumulation were extracted using two MRI segmentation methods: (1) the FreeSurfer‐derived EC label, and (2) Automatic Segmentation of Hippocampal Subfields (ASHS)‐derived MTL subregions, including the EC and Brodmann areas 35 and 36 (Br35, Br36) defined in 1mm‐MNI space. Partial volume correction was applied to the motion‐corrected PET data.ResultTau burden in the right Br35, right Br36, and age were significant predictors of CDR‐SB scores, with the greatest proportion of variance explained when all three were included. The FreeSurfer‐labeled EC and other variables did not significantly contribute to the model. Right Br36 and age were significant predictors of MMSE while right Br36 and APOE4 status were significant predictors of the global cognition composite score, and right Br36 was a significant predictor of the memory composite score. Follow‐up analyses showed that addition of the FreeSurfer EC region did not significantly contribute to any of the models.ConclusionQuantifying tau burden in Br35 and Br36 better accounted for individual variability in cognition, when compared to standard EC labeling approaches. This suggests tau burden in these subregions may help identify CU and MCI individuals who are on a trajectory of decline due to AD.

Longitudinal morphometry of medial temporal lobe subregions in earlyAlzheimer’s disease

AbstractBackgroundStructural MRI is frequently used to track Alzheimer’s disease (AD) progression in clinic, research, and pharmacological trials. It has been shown that established MRI‐derived measures lack diagnostic sensitivity particularly in early stages of AD. Here, we investigate if the utility of structural MRI for tracking early AD progression can be increased when focusing on subregions of the medial temporal lobe (MTL) which are known to exhibit earliest AD‐related neuropathological change.MethodWe used data from N = 143 participants enrolled in the DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE). This included cognitively unimpaired participants who were either Aß‐negative (CU Aß‐; n = 67) or Aß‐positive (CU Aß+; n = 20), Aß+ participants with subjective cognitive decline (SCD Aß+; n = 38), and Aß+ participants with MCI (MCI Aß+; n = 18). Participants underwent annual assessments up to three years after baseline, including MRI (2.19 ± 0.86 follow‐ups) and a neuropsychological testing (2.18 ± 0.83 follow‐ups). Segmentations of MTL subregions were generated using a longiudinal, template‐based implementation of the Automated Segmentation of Hippocampal Subfields (ASHS; Yushkevich et al., 2015, Hum Brain Mapp.) algorithm (Figure 1). Linear mixed models were fitted to derive volumetric slopes and to test their relationship with longitudinal changes in Preclinical Alzheimer Cognitive Composite (PACC‐5) scores.ResultWe observed significant volume losses across diagnostic groups with the MCI Aß+ group exhibiting the fastest rates. Compared with the CU Aß‐ group, there were accelerated volume losses in the subiculum and dentate gyrus in the SCD Aß+ group and, additionally, in the entorhinal cortex and Brodmann areas 35 and 36 in the MCI Aß+ group. There was also a trend towards faster volume losses in the entorhinal cortex in the CU Aß+ group. Higher rates of MTL subregional volume losses, particularly in the cornu ammonis 1 subfield, were related to a faster decline on the PACC‐5 in the MCI Aß+ group. This effect remained significant when controlling for baseline volumes.ConclusionOur findings highlight the viability of subregional MTL morphometry for tracking earliest neurodegeneration and related cognitive decline due to AD.

Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease

AbstractBackgroundThe medial temporal lobe (MTL) is a site of early tau pathology and neurodegeneration in AD. In recent work [1], we reported that rates of change in MTL subregion volumes on longitudinal structural T1‐MRI differ significantly between cognitively unimpaired individuals with and without amyloid pathology (A+CU vs A‐CU), suggesting that these measures are effective biomarkers for tracking disease progression in preclinical AD. Here, we develop a specialized pipeline that quantifies pointwise longitudinal change across the MTL, revealing more informative spatial patterns of early neurodegeneration than summary volumetric longitudinal measures.MethodOur pipeline, SkelDBM, combines skeletonization and deformation‐based morphometry to generate maps of annualized rate of atrophy on the skeleton of an MTL template (Figure 1). SkelDBM samples subjects’ atrophy maps along the skeleton of an MTL template, increasing robustness to subject‐to‐template registration errors. We evaluate SkelDBM using a subset of ADNI data studied in [1] (Table 1). Two preclinical AD groups (A+CU and tau‐positive A+CU) are compared to a control group (A‐CU) using general linear models (GLM) with age as nuisance covariate; permutation testing is used to derive statistically significant clusters.ResultThe full A+CU vs A‐CU comparison shows significant differences in rates of change in right anterior hippocampus, right entorhinal cortex, right transentorhinal cortex, and left posterior hippocampus (Figure 2). Limiting the A+CU group to tau‐positive individuals yields more widespread differences, including most of the right anterior MTL cortex and both hippocampi. These patterns align with volumetric longitudinal data reported in [1] but provide a richer characterization of spatial atrophy patterns.ConclusionSkelDBM is sensitive to longitudinal atrophy occurring over relatively short periods (∼2 years) in preclinical AD and characterizes patterns of atrophy more comprehensively than summary volumetric measures. Summary measures are also subject to biases, since larger structures are typically associated with less measurement error and hence may show exaggerated statistical effects compared to smaller structures even when the underlying neurodegeneration rates are the same. Regional maps of longitudinal change may be more robust to this bias and may help discovery of “signature regions” associated with specific pathological drivers of neurodegeneration. [1] Xie et al., Human Brain Mapping, 2020.

Longitudinal morphometry of medial temporal lobe subregions in earlyAlzheimer’s disease

AbstractBackgroundStructural MRI is frequently used to track Alzheimer’s disease (AD) progression in clinic, research, and pharmacological trials. It has been shown that established MRI‐derived measures lack diagnostic sensitivity particularly in early stages of AD. Here, we investigate if the utility of structural MRI for tracking early AD progression can be increased when focusing on subregions of the medial temporal lobe (MTL) which are known to exhibit earliest AD‐related neuropathological change.MethodWe used data from N = 143 participants enrolled in the DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE). This included cognitively unimpaired participants who were either Aβ‐negative (CU Aβ‐; n = 67) or Aβ‐positive (CU Aβ+; n = 20), Aβ+ participants with subjective cognitive decline (SCD Aβ+; n = 38), and Aβ+ participants with MCI (MCI Aβ+; n = 18).Participants underwent annual assessments up to three years after baseline, including MRI (2.19 ± 0.86 follow‐ups) and a neuropsychological testing (2.18 ± 0.83 follow‐ups). Segmentations of MTL subregions were generated using a longiudinal, template‐based implementation of the Automated Segmentation of Hippocampal Subfields (ASHS; Yushkevich et al., 2015, Hum Brain Mapp.) algorithm (Figure 1). Linear mixed models were fitted to derive volumetric slopes and to test their relationship with longitudinal changes in Preclinical Alzheimer Cognitive Composite (PACC‐5) scores.ResultWe observed significant volume losses across diagnostic groups with the MCI Aβ+ group exhibiting the fastest rates. Compared with the CU Aβ‐ group, there were accelerated volume losses in the subiculum and dentate gyrus in the SCD Aβ+ group and, additionally, in the entorhinal cortex and Brodmann areas 35 and 36 in the MCI Aβ+ group. There was also a trend towards faster volume losses in the entorhinal cortex in the CU Aβ+ group. Higher rates of MTL subregional volume losses, particularly in the cornu ammonis 1 subfield, were related to a faster decline on the PACC‐5 in the MCI Aβ+ group. This effect remained significant when controlling for baseline volumes.ConclusionOur findings highlight the viability of subregional MTL morphometry for tracking earliest neurodegeneration and related cognitive decline due to AD.

Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease

AbstractBackgroundThe medial temporal lobe (MTL) is a site of early tau pathology and neurodegeneration in AD. In recent work [1], we reported that rates of change in MTL subregion volumes on longitudinal structural T1‐MRI differ significantly between cognitively unimpaired individuals with and without amyloid pathology (A+CU vs A‐CU), suggesting that these measures are effective biomarkers for tracking disease progression in preclinical AD. Here, we develop a specialized pipeline that quantifies pointwise longitudinal change across the MTL, revealing more informative spatial patterns of early neurodegeneration than summary volumetric longitudinal measures.MethodsOur pipeline, SkelDBM, combines skeletonization and deformation‐based morphometry to generate maps of annualized rate of atrophy on the skeleton of an MTL template (Figure 1). SkelDBM samples subjects’ atrophy maps along the skeleton of an MTL template, increasing robustness to subject‐to‐template registration errors. We evaluate SkelDBM using a subset of ADNI data studied in [1] (Table 1). Two preclinical AD groups (A+CU and tau‐positive A+CU) are compared to a control group (A‐CU) using general linear models (GLM) with age as nuisance covariate; permutation testing is used to derive statistically significant clusters.ResultsThe full A+CU vs A‐CU comparison shows significant differences in rates of change in right anterior hippocampus, right entorhinal cortex, right transentorhinal cortex, and left posterior hippocampus (Figure 2). Limiting the A+CU group to tau‐positive individuals yields more widespread differences, including most of the right anterior MTL cortex and both hippocampi. These patterns align with volumetric longitudinal data reported in [1] but provide a richer characterization of spatial atrophy patterns.ConclusionSkelDBM is sensitive to longitudinal atrophy occurring over relatively short periods (∼2 years) in preclinical AD and characterizes patterns of atrophy more comprehensively than summary volumetric measures. Summary measures are also subject to biases, since larger structures are typically associated with less measurement error and hence may show exaggerated statistical effects compared to smaller structures even when the underlying neurodegeneration rates are the same. Regional maps of longitudinal change may be more robust to this bias and may help discovery of “signature regions” associated with specific pathological drivers of neurodegeneration.[1] Xie et al., Human Brain Mapping, 2020.

Microstructural integrity and structural connectivity of medial temporal lobe subregions is related to Alzheimer’s pathology

AbstractBackgroundThe earliest effects of Alzheimer’s disease pathology on medial temporal lobe (MTL) gray matter microstructure and white matter connectivity are still unknown. Here, we applied ultra‐high‐resolution diffusion MRI to characterize microstructural integrity and structural connectivity of the MTL, and tested associations with Alzheimer’s pathology and memory performance in cognitively normal older adults.Method83 participants (M = 71.7yrs, 66% female) received structural and ultra‐high‐resolution diffusion MRI (0.67×0.67×3mm). Subsamples received [18F]‐florbetapir (FBP) to measure Aß (n = 77; global summary SUVR), [18F]‐MK6240 to measure tau (n = 23; entorhinal SUVR), and performed an object mnemonic discrimination task (n = 74). Structural MRI was processed with ASHS to obtain MTL ROIs (Fig1). Diffusion MRI was processed with FSL DTIfit to calculate mean diffusivity (MD), an index of cellular integrity. Tractography was performed with DSI Studio. ROI‐to‐ROI streamlines were calculated (Fig3A) and used for structural connectivity graph analyses of the MTL network. Analyses controlled for age and sex, with scan interval and education in relevant models.ResultEntorhinal MK6240 SUVR was associated with increased MD in transentorhinal cortex (BA35; r = 0.72, p<0.001), entorhinal cortex (EC; r = 0.61, p = 0.004), and dentate gyrus (DG; r = 0.46, p = 0.04; Fig2A), while global FBP SUVR was associated with higher MD in EC (r = 0.25, p = 0.03). Worse mnemonic discrimination performance was associated with increased MD in DG (r = ‐0.29, p = 0.01), with trends in EC (r = ‐0.23, p = 0.06) and CA3 (r = ‐0.20, p = 0.09; Fig2B). The number of streamlines between EC and DG was not significantly associated with entorhinal MK6240 SUVR (r = ‐0.32, p = 0.17), FBP SUVR, or mnemonic discrimination (ps>0.37). Lower global efficiency of the MTL network was associated with increased entorhinal MK6240 SUVR (r = ‐0.50, p = 0.025) yet better mnemonic discrimination performance (r = ‐0.28, p = 0.02; Fig3B).ConclusionEntorhinal tau pathology and memory performance are closely related to microstructural integrity and structural connectivity of the MTL, suggesting tau‐related MTL neurodegeneration may drive early memory decline.

Microstructural integrity and structural connectivity of medial temporal lobe subregions is related to Alzheimer’s pathology

AbstractBackgroundThe earliest effects of Alzheimer’s disease pathology on medial temporal lobe (MTL) gray matter microstructure and white matter connectivity are still unknown. Here, we applied ultra‐high‐resolution diffusion MRI to characterize microstructural integrity and structural connectivity of the MTL, and tested associations with Alzheimer’s pathology and memory performance in cognitively normal older adults.Method83 participants (M = 71.7yrs, 66% female) received structural and ultra‐high‐resolution diffusion MRI (0.67×0.67×3mm). Subsamples received [18F]‐florbetapir (FBP) to measure Aβ (n = 77; global summary SUVR), [18F]‐MK6240 to measure tau (n = 23; entorhinal SUVR), and performed an object mnemonic discrimination task (n = 74). Structural MRI was processed with ASHS to obtain MTL ROIs (Fig1). Diffusion MRI was processed with FSL DTIfit to calculate mean diffusivity (MD), an index of cellular integrity. Tractography was performed with DSI Studio. ROI‐to‐ROI streamlines were calculated (Fig3A) and used for structural connectivity graph analyses of the MTL network. Analyses controlled for age and sex, with scan interval and education in relevant models.ResultEntorhinal MK6240 SUVR was associated with increased MD in transentorhinal cortex (BA35; r = 0.72, p<0.001), entorhinal cortex (EC; r = 0.61, p = 0.004), and dentate gyrus (DG; r = 0.46, p = 0.04; Fig2A), while global FBP SUVR was associated with higher MD in EC (r = 0.25, p = 0.03). Worse mnemonic discrimination performance was associated with increased MD in DG (r = ‐0.29, p = 0.01), with trends in EC (r = ‐0.23, p = 0.06) and CA3 (r = ‐0.20, p = 0.09; Fig2B). The number of streamlines between EC and DG was not significantly associated with entorhinal MK6240 SUVR (r = ‐0.32, p = 0.17), FBP SUVR, or mnemonic discrimination (ps>0.37). Lower global efficiency of the MTL network was associated with increased entorhinal MK6240 SUVR (r = ‐0.50, p = 0.025) yet better mnemonic discrimination performance (r = ‐0.28, p = 0.02; Fig3B).ConclusionEntorhinal tau pathology and memory performance are closely related to microstructural integrity and structural connectivity of the MTL, suggesting tau‐related MTL neurodegeneration may drive early memory decline.

42 Cognitive and Neuroanatomic Correlates of Olfactory Function in Cognitively Unimpaired and Impaired Older Adults

Objective:Olfactory function declines during normal aging; however, accelerated olfactory decline is observed in neurodegenerative diseases, such as Alzheimer’s disease (AD). Moreover, olfactory deficits in pre-clinical AD are associated with future cognitive decline. Odor identification and memory deficits have been consistently reported in early stage AD indicating its potential sensitivity to AD pathophysiology in olfactory and limbic structures, yet few studies of olfaction have incorporated structural measures in a well-characterized cohort of older adults. In the current study we examined the association between odor identification impairment, cognition, and medial temporal lobe (MTL) sub-regions in cognitively unimpaired and impaired older adults.Participants and Methods:We enrolled 140 participants (age=72.25±6.54, 56% female, years of education=16.30±2.63, 82% Caucasian, 15% Black/AA, 3% Multiracial) from the Penn Alzheimer’s Disease Research Center Clinical Cohort. Participants completed the Sniffin’ Sticks Odor Identification Test (SS-OIT), cognitive testing (NACC UDS2 or UDS3 and additional cognitive tests), and MRI scans (3T Siemens MAGNETOM Prisma MRI scanner). For the SS-OIT, participants were presented with 16 odorants using felt-tipped pen dispensers and asked to identify each odor from four multiple-choice options. Scores range from 0 to 16. Additionally, cognitive domains were created by averaging z-scores from tests within each domain: attention, memory, language, executive function, and visuospatial. This cohort was divided into participants with unimpaired cognition (n=96) and impaired cognition (MCI, dementia; n=44) using established normative data and consensus diagnosis. Linear regressions were performed to examine the association between SS-OIT score, each cognitive domain, and MTL measurements for unimpaired and impaired groups. For all analyses, we controlled for age, race, sex, education, smoking status, and hypertension and additionally for MOCA score and intracranial volume with MTL measurements.Results:In the unimpaired group, SS-OIT significantly associated with language (p<.05). In the impaired group, SS-OIT significantly associated with language and memory (p<.05). In the unimpaired group, SS-OIT significantly associated with right anterior hippocampal volume (p<.05). In the impaired group, significant associations were found between SS-OIT and right anterior hippocampal volume (p<.05) and left hippocampal mean thickness (p<.05). Additionally, SS-OIT significantly associated with left and right entorhinal cortex volume (p<.05) and mean thickness (p<.05).Conclusions:This study reveals that lower odor identification performance is related to lower performance on measures of cognition and atrophy in MTL sub-regions in unimpaired and impaired older adults. Our findings support prior results demonstrating relationships between olfactory function, cognition, and MTL sub-regions. Specifically, olfactory function and episodic memory have been shown to follow similar patterns of decline in the course of AD, potentially reflecting AD pathology in shared regions of the MTL subserving episodic memory and olfactory function. Our findings demonstrate that reductions in both cortical thickness and grey matter volume of MTL regions are linked to olfactory deficits in individuals at risk for Alzheimer’s dementia. Future steps will include the analysis of longitudinal cognitive and imaging indices and the incorporation of fluid biomarker data.

Ultra-high-field 7T MRI reveals changes in human medial temporal lobe volume in female adults during menstrual cycle

Ovarian hormones have substantial effects on the brain, and early menopause has been associated with increased risk of accelerated brain aging and dementia later in life. However, the impact of ovarian hormone fluctuations on brain structure earlier in life is less understood. Here we show that ovarian hormone fluctuations shape structural brain plasticity during the reproductive years. We use longitudinal ultra-high field neuroimaging across the menstrual cycle to map the morphology of medial temporal lobe subregions in 27 participants. Controlling for water content and blood flow, our findings reveal positive associations between estradiol and parahippocampal cortex volume, progesterone and subiculum and perirhinal area 35 volumes, and an estradiol*progesterone interaction with CA1 volume. This research offers a blueprint for future studies on the shared dynamics of the brain and ovarian function and a fundamental stepping stone towards developing sex-specific strategies to improve brain health and mental health.

Morphometric analysis of medial temporal lobe subregions in Alzheimer's disease using high-resolution MRI.

The spread pattern of progressive degeneration seen in Alzheimer's disease (AD) to small-scale medial temporal lobe subregions is critical for early diagnosis. In this context, it was aimed to examine the morphometric changes of the hippocampal subfields, amygdala nuclei, entorhinal cortex (ERC), and parahippocampal cortex (PHC) using MRI. MRI data of patients diagnosed with 20 Alzheimer's disease dementia (ADD), 30 amnestic mild cognitive impairment (aMCI), and 30 subjective cognitive impairment (SCI) without demographic differences were used. Segmentation and parcellation were performed using FreeSurfer. The segmentation process obtained volume values of 12 hippocampal subfields and 9 amygdala nuclei. Thickness values of ERC and PHC were calculated with the parcellation process. ANCOVA was performed using age, education and gender as covariates to evaluate the intergroup differences. Linear discriminant analysis was used to investigate whether atrophy predicted groups at an early stage. ERC and PHC thickness decreased significantly throughout the disease continuum, while only ERC was affected in the early stage. When the hippocampal and amygdala subfields were compared volumetrically, significant differences were found in the amygdala between the SCI and aMCI groups. In the early period, only volume reduction in the anterior amygdaloid area of the amygdala nuclei exceeded the significance threshold. Research on AD primarily focuses on original hippocampocentric structures and their main function which is episodic memory. Our results emphasized the significance of so far relatively neglected olfactocentric structures and their functions, such as smell and social cognition in the pre-dementia stages of the AD process.

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.

Tau burden is associated with cross‐sectional and longitudinal neurodegeneration in the medial temporal lobe in cognitively normal individuals

AbstractBackgroundNeurofibrillary tangle pathology is thought to drive neurodegeneration in beta‐amyloid positive (A+) cognitively normal (CN) individuals, i.e., preclinical Alzheimer’s disease (AD). However, in beta‐amyloid negative (A‐) CN, the contribution of tau pathology [primary age‐related tauopathy (PART)] to neurodegeneration remains uncertain. We investigate the correlation between tau burden measured by PET in the medial temporal lobe (MTL) and MRI‐derived cross‐sectional and longitudinal structural atrophy in these cohorts.Methods420 CN (A‐/A+: 294/101, Table 1) individuals from ADNI with AV1451 PET and T1‐weighted MRI acquired within one year were included. Bilateral anterior/posterior hippocampal volume and thickness of entorhinal cortex (ERC), Brodmann areas 35/36 (BA35/BA36) and parahipocampal cortex (PHC) were obtained from baseline MRI scans. Bilateral MTL tau burden was computed as AV1451 uptake across ERC and BA35. Beta‐amyloid status was determined with PET by standard cut‐offs (Florbetapir: 1.11; Florbetaben: 1.08). In a subset of participants with prospective longitudinal MRI scans (up to 4.5 years), annualized volume change rate of each MTL subregion was estimated. Partial Pearson’s correlation, controlling for age, sex, and MRI‐PET date difference, was performed between MTL tau burden and structural atrophy measurements. Intracranial volume and MRI follow‐up time were additional covariates for cross‐sectional and longitudinal analysis respectively. We performed the analysis separately for each hemisphere in the whole CN cohort and its A+ and A‐ subgroups.ResultsTau burden was significantly associated with cross‐sectional left BA35/36 thickness in the whole cohort and bilateral posterior hippocampus volume in both A+ CN and the whole cohort (Table 2, Figure 1), but not in in A‐ CN. Stronger correlations between MTL tau burden and longitudinal atrophy, despite smaller sample size, was observed in almost all the MTL subregions regardless of amyloid status (Table 3, Figure 1). In general, effects from the left hemisphere were stronger than those from the right hemisphere. All significant correlations were maintained when corrected for beta‐amyloid PET SUVR.ConclusionsThe results demonstrated that elevated tau predicts subsequent neurodegeneration in early Braak regions in CN subjects regardless of amyloid status. This indicates that PART may be an important driver of neurodegeneration already during normal ageing in cognitively normal individuals.