Neural Network Connectivity During Post-encoding Rest: Linking Episodic Memory Encoding and Retrieval

Commonly, a switch between networks mediating memory encoding and those mediating retrieval is observed. This may not only be due to differential involvement of neural resources due to distinct cognitive processes but could also reflect the formation of new memory traces and their dynamic change during consolidation. We used resting state fMRI to measure functional connectivity (FC) changes during post-encoding rest, hypothesizing that during this phase, new functional connections between encoding- and retrieval-related regions are created. Interfering and reminding tasks served as experimental modulators to corroborate that the observed FC differences indeed reflect changes specific to post-encoding rest. The right inferior occipital and fusiform gyri (active during encoding) showed increased FC with the left inferior frontal gyrus and the left middle temporal gyrus (MTG) during post-encoding rest. Importantly, the left MTG subsequently also mediated successful retrieval. This finding might reflect the formation of functional connections between encoding- and retrieval-related regions during undisturbed post-encoding rest. These connections were vulnerable to experimental modulation: Cognitive interference disrupted FC changes during post-encoding rest resulting in poorer memory performance. The presentation of reminders also inhibited FC increases but without affecting memory performance. Our results contribute to a better understanding of the mechanisms by which post-encoding rest bridges the gap between encoding- and retrieval-related networks

On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease

The diagnosis of Alzheimer's disease (AD), especially in the early stage, is still not very reliable and the development of new diagnosis tools is desirable. A diagnosis based on functional magnetic resonance imaging (fMRI) is a suitable candidate, since fMRI is non-invasive, readily available, and indirectly measures synaptic dysfunction, which can be observed even at the earliest stages of AD. However, the results of previous attempts to analyze graph properties of resting state fMRI data are contradictory, presumably caused by methodological differences in graph construction. This comprises two steps: clustering the voxels of the functional image to define the nodes of the graph, and calculating the graph's edge weights based on a functional connectivity measure of the average cluster activities. A variety of methods are available for each step, but the robustness of results to method choice, and the suitability of the methods to support a diagnostic tool, are largely unknown. To address this issue, we employ a range of commonly and rarely used clustering and edge definition methods and analyze their graph theoretic measures (graph weight, shortest path length, clustering coefficient, and weighted degree distribution and modularity) on a small data set of 26 healthy controls, 16 subjects with mild cognitive impairment (MCI) and 14 with Alzheimer's disease. We examine the results with respect to statistical significance of the mean difference in graph properties, the sensitivity of the results to model and parameter choices, and relative diagnostic power based on both a statistical model and support vector machines. We find that different combinations of graph construction techniques yield contradicting, but statistically significant, relations of graph properties between health conditions, explaining the discrepancy across previous studies, but casting doubt on such analyses as a method to gain insight into disease effects. The production of significant differences in mean graph properties turns out not to be a good predictor of future diagnostic capacity. Highest predictive power, expressed by largest negative surprise values, are achieved for both atlas-driven and data-driven clustering (Ward clustering), as long as graphs are small and clusters large, in combination with edge definitions based on correlations and mutual information transfer

Impact of tau and amyloid burden on glucose metabolism in Alzheimer's disease.

In a multimodal PET imaging approach, we determined the differential contribution of neurofibrillary tangles (measured with [18F]AV-1451) and beta-amyloid burden (measured with [11C]PiB) on degree of neurodegeneration (i.e., glucose metabolism measured with [18F]FDG-PET) in patients with Alzheimer's disease. Across brain regions, we observed an interactive effect of beta-amyloid burden and tau deposition on glucose metabolism which was most pronounced in the parietal lobe. Elevated beta-amyloid burden was associated with a stronger influence of tau accumulation on glucose metabolism. Our data provide the first in vivo insights into the differential contribution of Aβ and tau to neurodegeneration in Alzheimer's disease

Neural Network Connectivity During Post-encoding Rest: Linking Episodic Memory Encoding and Retrieval

Commonly, a switch between networks mediating memory encoding and those mediating retrieval is observed. This may not only be due to differential involvement of neural resources due to distinct cognitive processes but could also reflect the formation of new memory traces and their dynamic change during consolidation. We used resting state fMRI to measure functional connectivity (FC) changes during post-encoding rest, hypothesizing that during this phase, new functional connections between encoding- and retrieval-related regions are created. Interfering and reminding tasks served as experimental modulators to corroborate that the observed FC differences indeed reflect changes specific to post-encoding rest. The right inferior occipital and fusiform gyri (active during encoding) showed increased FC with the left inferior frontal gyrus and the left middle temporal gyrus (MTG) during post-encoding rest. Importantly, the left MTG subsequently also mediated successful retrieval. This finding might reflect the formation of functional connections between encoding- and retrieval-related regions during undisturbed post-encoding rest. These connections were vulnerable to experimental modulation: Cognitive interference disrupted FC changes during post-encoding rest resulting in poorer memory performance. The presentation of reminders also inhibited FC increases but without affecting memory performance. Our results contribute to a better understanding of the mechanisms by which post-encoding rest bridges the gap between encoding- and retrieval-related networks

Graph Theory Analysis Reveals Resting-State Compensatory Mechanisms in Healthy Aging and Prodromal Alzheimer's Disease

Several theories of cognitive compensation have been suggested to explain sustained cognitive abilities in healthy brain aging and early neurodegenerative processes. The growing number of studies investigating various aspects of task-based compensation in these conditions is contrasted by the shortage of data about resting-state compensatory mechanisms. Using our proposed criterion-based framework for compensation, we investigated 45 participants in three groups: (i) patients with mild cognitive impairment (MCI) and positive biomarkers indicative of Alzheimer's disease (AD); (ii) cognitively normal young adults; (iii) cognitively normal older adults. To increase reliability, three sessions of resting-state functional magnetic resonance imaging for each participant were performed on different days (135 scans in total). To elucidate the dimensions and dynamics of resting-state compensatory mechanisms, we used graph theory analysis along with volumetric analysis. Graph theory analysis was applied based on the Brainnetome atlas, which provides a connectivity-based parcellation framework. Comprehensive neuropsychological examinations including the Rey Auditory Verbal Learning Test (RAVLT) and the Trail Making Test (TMT) were performed, to relate graph measures of compensatory nodes to cognition. To avoid false-positive findings, results were corrected for multiple comparisons. First, we observed an increase of degree centrality in cognition related brain regions of the middle frontal gyrus, precentral gyrus and superior parietal lobe despite local atrophy in MCI and healthy aging, indicating a resting-state connectivity increase with positive biomarkers. When relating the degree centrality measures to cognitive performance, we observed that greater connectivity led to better RAVLT and TMT scores in MCI and, hence, might constitute a compensatory mechanism. The detection and improved understanding of the compensatory dynamics in healthy aging and prodromal AD is mandatory for implementing and tailoring preventive interventions aiming at preserved overall cognitive functioning and delayed clinical onset of dementia

Fine-grained age-matching improves atrophy-based detection of mild cognitive impairment more than amyloid-negative reference subjects

Introduction: In clinical practice, differentiating between age-related gray matter (GM) atrophy and neurodegeneration-related atrophy at early disease stages, such as mild cognitive impairment (MCI), remains challenging. We hypothesized that fined-grained adjustment for age effects and using amyloid-negative reference subjects could increase classification accuracy. Methods: T1-weighted magnetic resonance imaging (MRI) data of 131 cognitively normal (CN) individuals and 91 patients with MCI from the Alzheimer’s disease neuroimaging initiative (ADNI) characterized concerning amyloid status, as well as 19 CN individuals and 19 MCI patients from an independent validation sample were segmented, spatially normalized and analyzed in the framework of voxel-based morphometry (VBM). For each participant, statistical maps of GM atrophy were computed as the deviation from the GM of CN reference groups at the voxel level. CN reference groups composed with different degrees of age-matching, and mixed and strictly amyloid-negative CN reference groups were examined regarding their effect on the accuracy in distinguishing between CN and MCI. Furthermore, the effects of spatial smoothing and atrophy threshold were assessed. Results: Approaches with a specific reference group for each age significantly outperformed all other age-adjustment strategies with a maximum area under the curve of 1.0 in the ADNI sample and 0.985 in the validation sample. Accounting for age in a regression-based approach improved classification accuracy over that of a single CN reference group in the age range of the patient sample. Using strictly amyloid-negative reference groups improved classification accuracy only when age was not considered. Conclusion: Our results demonstrate that VBM can differentiate between age-related and MCI-associated atrophy with high accuracy. Crucially, age-specific reference groups significantly increased accuracy, more so than regression-based approaches and using amyloid-negative reference groups

Relationship of Tau Deposition and Hypometabolism in Alzheimer’s Disease: A Multimodal Imaging Approach Miami Florida, USA)

Relationship of Tau Deposition and Hypometabolism in Alzheimer’s Disease: A Multimodal Imaging ApproachGérard N. Bischof 1,2, Jochen Hammes1, Julian Dronse2,3 ,Klaus Fliessbach4,5, Frank Jessen5,6, Bernd Neumaier7, Özgür Onur3, Juraj Kukolja3, Alexander Drzezga1,5 & Thilo van Eimeren1,2,31Multimodal Neuroimaging Group, Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany 2Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Jülich, Germany 3Department of Neurology, University Hospital Cologne, Cologne, Germany 4Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany5 German Center for Neurodegenerative Diseases (DZNE)6Department of Psychiatry, University Hospital Cologne, Cologne, Germany 7Institute of Radiochemistry and Experimental Molecular Imaging, University of CologneIn Alzheimer’s Disease (AD), brain atrophy is preceded by gradual metabolic decline, as measured by [18F]FDG PET. Neuropathological hallmarks of the disease are beta-amyloid plaques (Aβ) and tau-based neurofibrillary tangles (Tau). While specific for AD, Aβ burden, as quantified by in vivo PET ligands, is largely unrelated to magnitude and topology of metabolic decline. The very recent development of [18F]AV-1451 (T807) for the in vivo quantification of Tau, allows us to test if tau pathology is more intimately linked to metabolic decline than Aβ. To this end, we adopted a multimodal imaging approach to investigate the relationship of regional glucose hypometabolism (assessed by [18F]FDG PET) with regional measures of Tau ([18F]AV-1451 PET), and Aβ ([11C]PiB PET) in six AD patients. We created z-score deviation images of [18F]AV-1451 and [18F]FDG PET using healthy controls as reference samples (significance threshold: z-score >2). Regional cortical deviation of [18F]AV-1451 uptake correlated strongly with regional glucose hypometabolism (r =.77, p <.001), whereas PiB uptake did not (r = -.01, n.s.) (see Figure, panel A). Deviation of tangle pathology and hypometabolism was most pronounced in brain regions known to be affected by hypometabolism consistently in AD, even in early stages (i.e., parietal cortex, posterior cingulate and temporal cortex). Consistent with the notion that regional tau deposition may precede regional glucose hypometabolism, we found more regions exhibiting exclusive tau deviations (Tau+), than regions with isolated hypometabolism (FDG+; see Figure, panel B). Overall, our results indicate a linear relationship of regional tau deposition and metabolic decline in AD and provide evidence for tau as a potential instigator of neurodegeneration in AD

Decreased Efficiency of Between-Network Dynamics During Early Memory Consolidation With Aging

Aging is associated with memory decline and progressive disabilities in the activities of daily living. These deficits have a significant impact on the quality of life of the aging population and lead to a tremendous burden on societies and health care systems. Understanding the mechanisms underlying aging-related memory decline is likely to inform the development of compensatory strategies promoting independence in old age. Research on aging-related memory decline has mainly focused on encoding and retrieval. However, some findings suggest that memory deficits may at least partly be due to impaired consolidation. To date, it remains elusive whether aging-related memory decline results from defective consolidation. This study examined age effects on consolidation-related neural mechanisms and their susceptibility to interference using functional magnetic resonance imaging data from 13 younger (20–30 years, 8 female) and 16 older (49–75 years, 5 female) healthy participants. fMRI was performed before and during a memory paradigm comprised of encoding, consolidation, and retrieval phases. Consolidation was variously challenged: (1) control (no manipulation), (2) interference (repeated stimulus presentation with interfering information), and (3) reminder condition (repeated presentation without interfering information). We analyzed the fractional amplitude of low-frequency fluctuations (fALFF) to compare brain activity changes from pre- to post-encoding rest. In the control condition, fALFF was decreased in the left supramarginal gyrus, right middle temporal gyrus, and left precuneus but increased in parts of the occipital and inferior temporal cortex. Connectivity analyses between fALFF-derived seeds and network ROIs revealed an aging-related decrease in the efficiency of functional connectivity (FC) within the ventral stream network and between salience, default mode, and central executive networks during consolidation. Moreover, our results indicate increased interference susceptibility in older individuals with dynamics between salience and default mode networks as a neurophysiological correlate. Conclusively, aging-related memory decline is partly caused by inefficient consolidation. Memory consolidation requires a complex interplay between large-scale brain networks, which qualitatively decreases with age

A new piece to the puzzle: Contributions of in vivo tau to neurodegeneration in Alzheimer’s disease

A new piece to the puzzle:Contributions of in vivo Tau to Neurodegeneration in Alzheimer’s DiseaseGérard N. Bischof 1,2, Julian Dronse 2,3, Klaus Fliessbach 4,5, Juraj Kukolja 2,3, Jochen Hammes1, Özgür Onur 3, Gereon Fink 2,3, Frank Jessen 5,6, Bernd Neumaier 7, Alexander Drzezga 1,5 & Thilo van Eimeren 1,2,3,51 Multimodal Neuroimaging Group, Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany2 Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Jülich, Germany3 Department of Neurology, University Hospital Cologne, Cologne, Germany4 Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany5 German Center for Neurodegenerative Diseases (DZNE), Germany6 Department of Psychiatry, University Hospital Cologne, Cologne, Germany7 Institute of Radiochemistry and Experimental Molecular Imaging, University of Cologne, GermanyIntroduction: In Alzheimer’s Disease (AD), extracellular beta-amyloid plaques (Aβ) and intracellular neurofibrillary tangles (tau) represent the primary pathological hallmarks. However, the relative contributions of these protein aggregations to neurodegeneration remain elusive. Although modern molecular imaging methods allow to address this question in vivo, previous studies have failed to show a direct relationship between Aβ-deposition (as measured with [11C]PiB PET) and regional neurodegeneration (as measured with [18F]FDG-PET) . With the advent of a novel PET tracer for tau imaging ([18F]AV-1451 aka T807) that shows high affinity to intracellular tangle pathology, it may now be possible to establish the missing link between protein aggregation pathology and neurodegeneration.A better understanding of the relative contribution of tau and Aβ pathology to neurodegeneration in AD will not only advance our knowledge of disease mechanisms, but will provide crucial information for disease-modifying interventions. To this end, we assessed the relationship of tau and Aβ pathology to regional and global measures of hypometabolism in AD patients using multimodal PET.Methods: We adopted a multimodal imaging approach to investigate the relationship of glucose hypometabolism (assessed by [18F]FDG PET) with measures of Tau ([18F]AV-1451 PET), and Aβ ([11C]PiB PET) in ten AD patients. After spatial normalization, we created standardized uptake value ratio (SUVR) images normalized by the non-specific binding potential of the cerebellum. We created mean and standard deviation images of glucose metabolism and tau deposition using modality-specific reference samples of age-matched healthy controls. We then calculated z-score deviation maps to examine disease-related patterns of hypometabolism and tau deposition. A structure-based parcellation of cortical and hippocampal brain regions using the automatic anatomic labeling atlas (AAL) was applied to the deviation images. Z-scores and SUVR values from the [11C]PiB images for each individual were extracted. We performed correlational and multivariate analyses to investigate the relationship of tau deposition and amyloid burden to hypometabolism.Results: Across brain regions, we found a strong linear relationship between measures of tau deposition and hypometabolism (r=.71, p<.001), whereas in vivo measures of Aβ were not related to hypometabolism (r=-.17, ns). Within regions, association of tau deposition and hypometabolism was most pronounced in the parietal, temporal and occipital lobe. Interestingly, in the very same regions, we also found an association of hypometabolism and Aβ measures. Multivariate analysis revealed that frontal and parietal hypometabolism was predicted only by tau deposition, whereas in temporal and occipital lobes, we found interactive effects of tau and amyloid best predicting hypometabolism.Conclusion:Measuring tau deposition using [18F]AV-1451 PET in conjunction with [18F]FDG PET and [11C]PiB PET provided novel insights into the underlying neurodegenerative characteristics in AD. Our results provide evidence for the hypothesis that tau pathology may represent a direct instigator of neuronal injury and, thus, of regional neurodegeneration in AD. In contrast, effects of Aβ deposition on neuronal function (if present) were observed only in dependence of tau pathology. This implicates a more indirect role of Aβ aggregation pathology in causing neurodegeneration. This study emphasizes that tau pathology may prove to be an instrumental target for disease-modifying strategies in AD

Entorhinal Tau Predicts Hippocampal Activation and Memory Deficits in Alzheimer's Disease

Background: To date, it remains unclear how amyloid plaques and neurofibrillary tangles are related to neural activation and, consequently, cognition in Alzheimer's disease (AD). Recent findings indicate that tau accumulation may drive hippocampal hyperactivity in cognitively normal aging, but it remains to be elucidated how tau accumulation is related to neural activation in AD. Objective: To determine whether the association between tau accumulation and hippocampal hyperactivation persists in mild cognitive impairment (MCI) and mild dementia or if the two measures dissociate with disease progression, we investigated the relationship between local tau deposits and memory-related neural activation in MCI and mild dementia due to AD. Methods: Fifteen patients with MCI or mild dementia due to AD underwent a neuropsychological assessment and performed an item memory task during functional magnetic resonance imaging. Cerebral tau accumulation was assessed using positron emission tomography and [F-18]-AV-1451. Results: Entorhinal, but not global tau accumulation, was highly correlated with hippocampal activation due to visual item memory encoding and predicted memory loss over time. Neural activation in the posterior cingulate cortex and the fusiform gyrus was not significantly correlated with tau accumulation. Conclusion: These findings extend previous observations in cognitively normal aging, demonstrating that entorhinal tau continues to be closely associated with hippocampal hyperactivity and memory performance in MCI and mild dementia due to AD. Furthermore, data suggest that this association is strongest in medial temporal lobe structures. In summary, our data provide novel insights into the relationship of tau accumulation to neural activation and memory in AD