Enhanced resting-state functional connectivity between core memory-task activation peaks is associated with memory impairment in MCI

The relationship between APOE genotype, CSF Tau and cognition across the Alzheimer's disease spectrum, moderation and mediation role of insula network connectivity

AIMS

To investigate whether insula network connectivity modulates the relationship between apolipoprotein E (APOE) ε4 genotype, cerebrospinal fluid (CSF) biomarkers (Aβ, Tau, and pTau) and cognition across Alzheimer's disease (AD) spectrum.

METHODS

Forty-six cognitive normal (CN), 35 subjective memory complaint (SMC), 41 mild cognitive impairment (MCI), and 32 AD subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were obtained. Multivariable linear regression analyses were conducted to investigate the main effects and interaction of the APOE genotype and disease status on the insula functional connectivity (IFC) network. Mediation and moderation analysis were performed to investigate whether IFC strengths regulate the association between APOE genotype, CSF biomarkers and cognition. Additionally, the support vector machine (SVM) model integrating APOE genotype, CSF biomarkers, and neuroimaging biomarkers (insula volumes and altered regional IFCs) was used to classify the AD spectrum.

RESULTS

The interactive effect of the APOE genotype and disease on the insula network was found in the left medial superior frontal gyrus (SFGmed.L), right anterior medial prefrontal cortex (aMPFC.R), and bilateral thalamus (THA.B). The functional connectivities (FCs) in the left insula (LIns) connecting with the left posterior middle temporal gyrus (pMTG.L), SFGmed.L, and right lingual gyrus (LING.R) were correlated with cognition. LIns-SFGmed.L and LIns-pMTG.L FCs could moderate the effects of Tau on cognition. Furthermore, LIns-SFGmed.L FC may suppress the association between APOE genotype and cognition. More importantly, the integrated biomarkers from the SVM model yielded strong powers for classifying the AD spectrum.

CONCLUSIONS

Insula functional connectivity regulated the association between APOE genotype, CSF Tau and cognition and provided stage-dependent biomarkers for early differentiation of the AD spectrum. The present study used a cross-sectional design. Follow-up studies are needed to validate the relationship.

Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals

Introduction

Maintaining high cognitive functions is desirable for "wellbeing" in old age and is particularly relevant to a super-aging society. According to their individual cognitive functions, optimal intervention for older individuals facilitates the maintenance of cognitive functions. Cognitive function is a result of whole-brain interactions. These interactions are reflected in several measures in graph theory analysis for the topological characteristics of functional connectivity. Betweenness centrality (BC), which can identify the "hub" node, i.e., the most important node affecting whole-brain network activity, may be appropriate for capturing whole-brain interactions. During the past decade, BC has been applied to capture changes in brain networks related to cognitive deficits arising from pathological conditions. In this study, we hypothesized that the hub structure of functional networks would reflect cognitive function, even in healthy elderly individuals.

Method

To test this hypothesis, based on the BC value of the functional connectivity obtained using the phase lag index from the electroencephalogram under the eyes closed resting state, we examined the relationship between the BC value and cognitive function measured using the Five Cognitive Functions test total score.

Results

We found a significant positive correlation of BC with cognitive functioning and a significant enhancement in the BC value of individuals with high cognitive functioning, particularly in the frontal theta network.

Discussion

The hub structure may reflect the sophisticated integration and transmission of information in whole-brain networks to support high-level cognitive function. Our findings may contribute to the development of biomarkers for assessing cognitive function, enabling optimal interventions for maintaining cognitive function in older individuals.

Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment

Prospective memory (PM, the memory of future intentions) is one of the first complaints of those that develop dementia-related disease. Little is known about the neurophysiology of PM in ageing and those with mild cognitive impairment (MCI). By using a novel artificial neural network to investigate the spatial and temporal features of PM related brain activity, new insights can be uncovered. Young adults (n = 30), healthy older adults (n = 39) and older adults with MCI (n = 27) completed a working memory and two PM (perceptual, conceptual) tasks. Time-locked electroencephalographic potentials (ERPs) from 128-electrodes were analysed using a brain-inspired spiking neural network (SNN) architecture. Local and global connectivity from the SNNs was then evaluated. SNNs outperformed other machine learning methods in classification of brain activity between younger, older and older adults with MCI. SNNs trained using PM related brain activity had better classification accuracy than working memory related brain activity. In general, younger adults exhibited greater local cluster connectivity compared to both older adult groups. Older adults with MCI demonstrated decreased global connectivity in response to working memory and perceptual PM tasks but increased connectivity in the conceptual PM models relative to younger and healthy older adults. SNNs can provide a useful method for differentiating between those with and without MCI. Using brain activity related to PM in combination with SNNs may provide a sensitive biomarker for detecting cognitive decline. Cognitively demanding tasks may increase the amount connectivity in older adults with MCI as a means of compensation.

Deep Spatio-Temporal Attention-based Recurrent Network from Dynamic Adaptive Functional Connectivity for MCI Identification

Most existing methods of constructing dynamic functional connectivity (dFC) network obtain the connectivity strength via the sliding window correlation (SWC) method, which estimates the connectivity strength at each time segment, rather than at each time point, and thus is difficult to produce accurate dFC network due to the influence of the window type and window width. Furthermore, the deep learning methods may not capture the discriminative spatio-temporal information that is closely related to disease, thus impacting the performance of (mild cognitive impairment) MCI identification. In this paper, a novel spatio-temporal attention-based bidirectional gated recurrent unit (STA-BiGRU) network is proposed to extract inherent spatio-temporal information from a dynamic adaptive functional connectivity (dAFC) network for MCI diagnosis. Specifically, we adopt a group lasso-based Kalman filter algorithm to obtain the dAFC network with more accurate connectivity strength at each time step. Then a spatial attention module with self-attention and a temporal attention module with multiple temporal attention vectors are incorporated into the BiGRU network to extract more discriminative disease-related spatio-temporal information. Finally, the spatio-temporal regularizations are employed to better guide the attention learning of STA-BiGRU network to enhance the robustness of the deep network. Experimental results show that the proposed framework achieves mean accuracies of 90.2%, 90.0%, and 81.5%, respectively, for three MCI classification tasks. This study provides a more effective deep spatio-temporal attention-based recurrent network and obtains good performance and interpretability of deep learning for psychiatry diagnosis research.

An Activation Likelihood Estimation Meta-Analysis of Specific Functional Alterations in Dorsal Attention Network in Mild Cognitive Impairment

Background

Mild cognitive impairment (MCI) is known as the prodromal stage of the Alzheimer’s disease (AD) spectrum. The recent studies have advised that functional alterations in the dorsal attention network (DAN) could be used as a sensitive marker to forecast the progression from MCI to AD. Therefore, our aim was to investigate specific functional alterations in the DAN in MCI.

Methods

We systematically searched PubMed, EMBASE, and Web of Science and chose relevant articles based on the three functional indicators, the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in the DAN in MCI. Based on the activation likelihood estimation, we accomplished the aggregation of specific coordinates and the analysis of functional alterations.

Results

A total of 38 studies were involved in our meta-analysis. By summing up included articles, we acquired specific brain region alterations in the DAN mainly in the superior temporal gyrus (STG), middle temporal gyrus (MTG), superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior frontal gyrus (IFG), precentral gyrus (preCG), inferior parietal lobule (IPL), superior parietal lobule (SPL). At the same time, the key area that shows anti-interaction with default mode network included the IPL in the DAN. The one showing interactions with executive control network was mainly in the MFG. Finally, the frontoparietal network showed a close connection with DAN especially in the IPL and IFG.

Conclusion

This study demonstrated abnormal functional markers in the DAN and its interactions with other networks in MCI group, respectively. It provided the foundation for future targeted interventions in preventing the progression of AD.

Systematic Review Registration

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021287958].

TMS-EEG Co-Registration in Patients with Mild Cognitive Impairment, Alzheimer's Disease and Other Dementias: A Systematic Review

An established method to assess effective brain connectivity is the combined use of transcranial magnetic stimulation with simultaneous electroencephalography (TMS–EEG) because TMS-induced cortical responses propagate to distant anatomically connected brain areas. Alzheimer’s disease (AD) and other dementias are associated with changes in brain networks and connectivity, but the underlying pathophysiology of these processes is poorly defined. We performed here a systematic review of the studies employing TMS–EEG co-registration in patients with dementias. TMS–EEG studies targeting the motor cortex have revealed a significantly reduced TMS-evoked P30 in AD patients in the temporo-parietal cortex ipsilateral to stimulation side as well as in the contralateral fronto-central area, and we have demonstrated a deep rearrangement of the sensorimotor system even in mild AD patients. TMS–EEG studies targeting other cortical areas showed alterations of effective dorsolateral prefrontal cortex connectivity as well as an inverse correlation between prefrontal-to-parietal connectivity and cognitive impairment. Moreover, TMS–EEG analysis showed a selective increase in precuneus neural activity. TMS–EEG co-registrations can also been used to investigate whether different drugs may affect cognitive functions in patients with dementias.

Brain Activity of Benzoate, a D-Amino Acid Oxidase Inhibitor, in Patients With Mild Cognitive Impairment in a Randomized, Double-Blind, Placebo Controlled Clinical Trial

BACKGROUND

Current anti-dementia drugs cannot benefit mild cognitive impairment (MCI). Sodium benzoate (a D-amino acid oxidase [DAO] inhibitor) has been found to improve the cognitive function of patients with early-phase Alzheimer's disease (mild Alzheimer's disease or MCI). However, its effect on brain function remains unknown. This study aimed to evaluate the influence of benzoate on functional magnetic resonance imaging in patients with amnestic MCI.

METHODS

This was a 24-week, randomized, double-blind, placebo-controlled trial that enrolled 21 patients with amnestic MCI and allocated them randomly to either of 2 treatment groups: (1) benzoate group (250-1500 mg/d), or (2) placebo group. We assessed the patients' working memory, verbal learning and memory, and resting-state functional magnetic resonance imaging and regional homogeneity (ReHo) maps at baseline and endpoint.

RESULTS

Resting-state ReHo decreased in right orbitofrontal cortex after benzoate treatment but did not change after placebo. Moreover, after benzoate treatment, the change in working memory was positively correlated with the change in ReHo in right precentral gyrus and right middle occipital gyrus; and the change in verbal learning and memory was positively correlated with the change in ReHo in left precuneus. In contrast, after placebo treatment, the change in working memory or in verbal learning and memory was not correlated with the change in ReHo in any brain region.

CONCLUSION

The current study is the first to our knowledge to demonstrate that a DAO inhibitor, sodium benzoate herein, can alter brain activity as well as cognitive functions in individuals with MCI. The preliminary finding lends supports for DAO inhibition as a novel approach for early dementing processes.

Altered Weibull Degree Distribution in Resting-State Functional Brain Networks Is Associated With Cognitive Decline in Mild Cognitive Impairment

The topological organization of human brain networks can be mathematically characterized by the connectivity degree distribution of network nodes. However, there is no clear consensus on whether the topological structure of brain networks follows a power law or other probability distributions, and whether it is altered in Alzheimer's disease (AD). Here we employed resting-state functional MRI and graph theory approaches to investigate the fitting of degree distributions of the whole-brain functional networks and seven subnetworks in healthy subjects and individuals with amnestic mild cognitive impairment (aMCI), i.e., the prodromal stage of AD, and whether they are altered and correlated with cognitive performance in patients. Forty-one elderly cognitively healthy controls and 30 aMCI subjects were included. We constructed functional connectivity matrices among brain voxels and examined nodal degree distributions that were fitted by maximum likelihood estimation. In the whole-brain networks and all functional subnetworks, the connectivity degree distributions were fitted better by the Weibull distribution [f(x)~x^(β−1)e^(−λxβ)] than power law or power law with exponential cutoff. Compared with the healthy control group, the aMCI group showed lower Weibull β parameters (shape factor) in both the whole-brain networks and all seven subnetworks (false-discovery rate-corrected, p < 0.05). These decreases of the Weibull β parameters in the whole-brain networks and all subnetworks except for ventral attention were associated with reduced cognitive performance in individuals with aMCI. Thus, we provided a short-tailed model to capture intrinsic connectivity structure of the human brain functional networks in health and disease.

The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer's disease

In Alzheimer's disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNF_Val66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aβ) on neurodegeneration and cognitive decline, rendering BDNF_Val66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNF_Val66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNF_Val66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNF_Val66Met carriers compared to BDNF_Val homozogytes. BDNF_Val66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNF_Val66Met could be also found in elderly subjects with sporadically occurring Aβ, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNF_Val66Met was associated with a stronger effect of more abnormal Aβ-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNF_Val66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

Nocturnal Hypoxemia Is Associated with Altered Parahippocampal Functional Brain Connectivity in Older Adults at Risk for Dementia

BACKGROUND

Obstructive sleep apnea is associated with an increased risk of developing mild cognitive impairment and dementia. Intermittent nocturnal hypoxemia in obstructive sleep apnea is associated with brain changes in key regions that underpin memory.

OBJECTIVE

To determine whether older adults with severe nocturnal hypoxemia would exhibit reduced functional connectivity within these regions, with associated deficits in memory.

METHODS

Seventy-two participants 51 years and over underwent polysomnography with continuous blood oxygen saturation recorded via oximetry. The oxygen desaturation index (ODI, 3% dips in oxygen levels per hour) was the primary outcome measure. ODI was split into tertiles, with analyses comparing the lowest and highest tertiles (N = 48). Thirty-five of the 48 participants from these two tertiles had mild cognitive impairment. Participants also underwent resting-state fMRI and comprehensive neuropsychological, medical, and psychiatric assessment.

RESULTS

The highest ODI tertile group demonstrated significantly reduced connectivity between the left and right parahippocampal cortex, relative to the lowest ODI tertile group (t(42) = -3.26, p = 0.041, beta = -1.99).The highest ODI tertile group also had poorer working memory performance. In the highest ODI tertile group only, higher left-right parahippocampal functional connectivity was associated with poorer visual memory recall (between-groups z = -2.93, p = 0.0034).

CONCLUSIONS

Older adults with severe nocturnal hypoxemia demonstrate impaired functional connectivity in medial temporal structures, key regions involved in sleep memory processing and implicated in dementia pathophysiology. Oxygen desaturation and functional connectivity in these individuals each relate to cognitive performance. Research is now required to further elucidate these findings.

Low-Frequency Repetitive Transcranial Magnetic Stimulation of the Right Dorsolateral Prefrontal Cortex Enhances Recognition Memory in Alzheimer's Disease

BACKGROUND

The lack of effective pharmacological or behavioral interventions for memory impairments associated with Alzheimer's disease (AD) emphasizes the need for the investigation of approaches based on neuromodulation.

OBJECTIVE

This study examined the effects of inhibitory repetitive transcranial magnetic stimulation (rTMS) of prefrontal cortex on recognition memory in AD patients.

METHODS

In a first experiment, 24 mild AD patients received sham and real 1Hz rTMS over the left and right dorsolateral prefrontal cortex (DLPFC), in different sessions, between encoding and retrieval phases of a non-verbal recognition memory task. In a second experiment, another group of 14 AD patients underwent sham controlled repeated sessions of 1Hz rTMS of the right DLPFC across a two week treatment. Non-verbal recognition memory task was performed at baseline, at the end of the two weeks period and at a follow up of 1 month.

RESULTS

Right real rTMS significantly improved memory performance compared to right sham rTMS (p = 0.001). Left real rTMS left the memory performance unchanged as compared with left sham rTMS (p = 0.46). The two sham conditions did not differ between each other (p = 0.24). In the second experiment, AD patients treated with real rTMS showed an improvement of memory performance at the end of the two weeks treatment (p = 0.0009), that persisted at 1-month follow-up (p = 0.002).

CONCLUSION

These findings provide evidence that inhibitory rTMS over the right DLPFC can improve recognition memory function in AD patients. They also suggest the importance of a new approach of non-invasive brain stimulation as a promising treatment in AD.

Default Mode Network Connectivity Moderates the Relationship Between the APOE Genotype and Cognition and Individualizes Identification Across the Alzheimer's Disease Spectrum

Although previous studies have investigated the effects of the apolipoprotein E (APOE) ɛ4 genotype on the default mode network (DMN) in the Alzheimer's disease (AD) spectrum, it is still unclear how the APOE genotype regulates the DMN and subsequently affects cognitive decline in the AD spectrum. One hundred sixty-nine subjects with resting-state functional magnetic resonance imaging data and neuropsychological test scores were selected from the Alzheimer's Disease Neuroimaging Initiative. The main effects and interaction of the APOE genotype and disease status on the DMN were explored. A moderation analysis was performed to investigate the relationship among the APOE genotype, DMN connectivity, and cognition. Additionally, the pair-wised DMN connectivity was used to classify AD spectrum, and the classification accuracy was validated. Compared to APOEɛ4 non-carriers, APOEɛ4 carriers showed the opposite trajectory of DMN connectivity across the AD spectrum. Specifically, the strengths in the posterior cingulate cortex (PCC) connecting with the right precuneus, insular, and fusiform area (FFA) were positively correlated with Mini-Mental State Examination (MMSE) scores in APOEɛ4 non-carriers but not in APOEɛ4 carriers. Furthermore, PCC-right FFA connectivity could moderate the effects of the APOE genotype on MMSE scores across the disease groups. More importantly, using a receiver operating characteristic analysis, these altered connectivities yielded strong classification powers in a pathological stage-dependent manner in the AD spectrum. These findings first identified the intrinsic DMN connectivity moderating the effect of the APOE genotype on cognition and provided a pathological stage-dependent neuroimaging biomarker for early differentiation of the AD spectrum.

Distinct Disruptive Patterns of Default Mode Subnetwork Connectivity Across the Spectrum of Preclinical Alzheimer's Disease

Background: The early progression continuum of Alzheimer’s disease (AD) has been considered to advance through subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI). Altered functional connectivity (FC) in the default mode network (DMN) is regarded as a hallmark of AD. Furthermore, the DMN can be divided into two subnetworks, the anterior and posterior subnetworks. However, little is known about distinct disruptive patterns in the subsystems of the DMN across the preclinical AD spectrum. This study investigated the connectivity patterns of anterior DMN (aDMN) and posterior DMN (pDMN) across the preclinical AD spectrum.

Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in the DMN subnetworks in 20 healthy controls (HC), eight SCD, 11 naMCI, and 28 aMCI patients. Moreover, a correlation analysis was used to examine associations between the altered connectivity of the DMN subnetworks and the neurocognitive performance.

Results: Compared to the HC, SCD patients showed increased FC in the bilateral superior frontal gyrus (SFG), naMCI patients showed increased FC in the left inferior parietal lobule (IPL), and aMCI patients showed increased FC in the bilateral IPL in the aDMN; while SCD patients showed decreased FC in the precuneus, naMCI patients showed increased FC in the left middle temporal gyrus (MTG), and aMCI patients also showed increased FC in the right middle frontal gyrus (MFG) in the pDMN. Notably, the FC between the ventromedial prefrontal cortex (vmPFC) and the left MFG and the IPL in the aDMN was associated with episodic memory in the SCD and aMCI groups. Interestingly, the FC between the posterior cingulated cortex (PCC) and several regions in the pDMN was associated with other cognitive functions in the SCD and naMCI groups.

Conclusions: This study demonstrates that the three preclinical stages of AD exhibit distinct FC alternations in the DMN subnetworks. Furthermore, the patient group data showed that the altered FC involves cognitive function. These findings can provide novel insights for tailored clinical intervention across the preclinical AD spectrum.

Cardiovascular risk and encoding-related hippocampal connectivity in older adults

Background

Cardiovascular conditions contribute to brain volume loss, reduced cerebrovascular health, and increased dementia risk in aging adults. Altered hippocampal connectivity has also been observed in individuals with cardiovascular conditions, yet the functional consequences of these changes remain unclear. In the present study, we collected functional magnetic resonance imaging data during memory encoding and used a psychophysiological interaction analysis to examine whether cardiovascular burden, indexed using the Framingham risk score, was associated with encoding-related hippocampal connectivity and task performance in cognitively-intact older adults between 65 and 85 years of age. Our goal was to better understand the early functional consequences of vascular and metabolic dysfunction in those at risk for cognitive decline.

Results

High Framingham risk scores were associated with lower total brain volumes. In addition, those with high Framingham risk scores showed an altered relationship between left hippocampal-medial prefrontal coupling and task performance compared to those with low Framingham risk scores. Specifically, we found a significant interaction of Framingham risk and learning on connectivity between the left hippocampus and primarily left midline prefrontal regions comprising the left ventral anterior cingulate cortex and medial prefrontal cortex. Those with lower Framingham risk scores showed a pattern of weaker connectivity between left hippocampal and medial prefrontal regions associated with better task performance. Those with higher Framingham risk scores showed the opposite pattern; stronger connectivity was associated with better performance.

Conclusions

Findings from the current study show that amongst older adults with cardiovascular conditions, higher Framingham risk is associated with lower brain volume and altered left hippocampal-medial prefrontal coupling during task performance compared to those with lower Framingham risk scores. This may reflect a compensatory mechanism in support of memory function and suggests that older adults with elevated cardiovascular risk are vulnerable to early Alzheimer disease-like dysfunction within the episodic memory system.

Predicting Alzheimer's disease severity by means of TMS-EEG coregistration

Clinical manifestations of Alzheimer's disease (AD) are associated with a breakdown in large-scale communication, such that AD may be considered as a "disconnection syndrome." An established method to test effective connectivity is the combination of transcranial magnetic stimulation with electroencephalography (TMS-EEG) because the TMS-induced cortical response propagates to distant anatomically connected regions. To investigate whether prefrontal connectivity alterations may predict disease severity, we explored the relationship of dorsolateral prefrontal cortex connectivity (derived from TMS-EEG) with cognitive decline (measured with Mini Mental State Examination and a face-name association memory task) in 26 patients with AD. The amplitude of TMS-EEG evoked component P30, which was found to be generated in the right superior parietal cortex, predicted Mini Mental State Examination and face-name memory scores: higher P30 amplitudes predicted poorer cognitive and memory performances. The present results indicate that advancing disease severity might be associated with effective connectivity increase involving long-distance frontoparietal connections, which might represent a maladaptive pathogenic mechanism reflecting a damaged excitatory-inhibitory balance between anterior and posterior regions.

Neural bases underlying the association between balanced time perspective and trait anxiety

The aims of present study were to investigate the association between balanced time perspective (BTP) and trait anxiety, and the neural substrates underlying this association using voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) methods. 140 college students (83 females) ranging in age from 17 to 25 years were assessed on deviation from the balanced time perspective (DBTP) and trait anxiety. Behavioral analyses found BTP could significantly predict trait anxiety after controlling age and gender. Whole-brain VBM analyses found that DBTP was positively correlated with gray matter volume (GMV) in the parahippocampal gyrus (PHG) and precuneus, while trait anxiety positively correlated with GMV in the PHG. Considering the overlapping region in the PHG, we further defined the overlapping region as the seed, and calculated seed-to-voxel-based functional connectivity in resting-state. RSFC results showed that DBTP was positively associated with the RSFC between the PHG and medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and precuneus, whereas negatively correlated with the RSFC between the PHG and cuneus. Trait anxiety was also positively correlated with the RSFC between the PHG and PCC while negatively correlated with the RSFC between the PHG and cuneus. Mediation analysis further found GMV in the overlapping PHG and PHG-PCC, PHG-cuneus functional connectivity played significantly mediating roles in the relation between DBTP and trait anxiety. In sum, our research suggests the structural features of the PHG and its connectivity with PCC and cuneus may be the neural bases underlying the association between BTP and trait anxiety.

Correspondence Between Resting-State and Episodic Memory-Task Related Networks in Elderly Subjects

Resting-state fMRI studies demonstrated temporally synchronous fluctuations in brain activity among ensembles of brain regions, suggesting the existence of intrinsic functional networks. A spatial match between some of the resting-state networks and regional brain activation during cognitive tasks has been noted, suggesting that resting-state networks support particular cognitive abilities. However, the spatial match and predictive value of any resting-state network and regional brain activation during episodic memory is only poorly understood. In order to address this research gap, we obtained fMRI acquired both during rest and a face-name association task in 38 healthy elderly subjects. In separate independent component analyses, networks of correlated brain activity during rest or the episodic memory task were identified. For the independent components identified for task-based fMRI, the design matrix of successful encoding or retrieval trials was regressed against the time course of each of the component to identify significantly activated networks. Spatial regression was used to assess the match of resting-state networks against those related to successful memory encoding or retrieval. We found that resting-state networks covering the medial temporal, middle temporal, and frontal areas showed increased activity during successful encoding. Resting-state networks located within posterior brain regions showed increased activity during successful recognition. However, the level of resting-state network connectivity was not predictive of the task-related activity in these networks. These results suggest that a circumscribed number of functional networks detectable during rest become engaged during successful episodic memory. However, higher intrinsic connectivity at rest may not translate into higher network expression during episodic memory.

Current understanding of magnetic resonance imaging biomarkers and memory in Alzheimer's disease

Alzheimer's disease (AD) is caused by a cascade of changes to brain integrity. Neuroimaging biomarkers are important in diagnosis and monitoring the effects of interventions. As memory impairments are among the first symptoms of AD, the relationship between imaging findings and memory deficits is important in biomarker research. The most established magnetic resonance imaging (MRI) finding is hippocampal atrophy, which is related to memory decline and currently used as a diagnostic criterion for AD. While the medial temporal lobes are impacted early by the spread of neurofibrillary tangles, other networks and regional changes can be found quite early in the progression. Atrophy in several frontal and parietal regions, cortical thinning, and white matter alterations correlate with memory deficits in early AD. Changes in activation and connectivity have been detected by functional MRI (fMRI). Task-based fMRI studies have revealed medial temporal lobe hypoactivation, parietal hyperactivation, and frontal hyperactivation in AD during memory tasks, and activation patterns of these regions are also altered in preclinical and prodromal AD. Resting state fMRI has revealed alterations in default mode network activity related to memory in early AD. These studies are limited in part due to the historic inclusion of patients who had suspected AD but likely did not have the disorder. Modern biomarkers allow for more diagnostic certainty, allowing better understanding of neuroimaging markers in true AD, even in the preclinical stage. Larger patient cohorts, comparison of candidate imaging biomarkers to more established biomarkers, and inclusion of more detailed neuropsychological batteries to assess multiple aspects of memory are needed to better understand the memory deficit in AD and help develop new biomarkers. This article reviews MRI findings related to episodic memory impairments in AD and introduces a new study with multimodal imaging and comprehensive neuropsychiatric evaluation to overcome current limitations.

Left Frontal Hub Connectivity during Memory Performance Supports Reserve in Aging and Mild Cognitive Impairment

Reserve in aging and Alzheimer's disease (AD) is defined as maintaining cognition at a relatively high level in the presence of neurodegeneration, an ability often associated with higher education among other life factors. Recent evidence suggests that higher resting-state functional connectivity within the frontoparietal control network, specifically the left frontal cortex (LFC) hub, contributes to higher reserve. Following up these previous resting-state fMRI findings, we probed memory-task related functional connectivity of the LFC hub as a neural substrate of reserve. In elderly controls (CN, n = 37) and patients with mild cognitive impairment (MCI, n = 17), we assessed global connectivity of the LFC hub during successful face-name association learning, using generalized psychophysiological interaction analyses. Reserve was quantified as residualized memory performance, accounted for gender and proxies of neurodegeneration (age, hippocampus atrophy, and APOE genotype). We found that greater education was associated with higher LFC-connectivity in both CN and MCI during successful memory. Furthermore, higher LFC-connectivity predicted higher residualized memory (i.e., reserve). These results suggest that higher LFC-connectivity contributes to reserve in both healthy and pathological aging.

Measuring compensation in neurodegeneration using MRI

PURPOSE OF REVIEW

Despite signs of cortical and subcortical loss, patients with prodromal and early-stage neurodegenerative disease are able to perform at a level comparable to the normal population. It is presumed that the onset of compensatory processes, that is changes in brain activation within a function-specific network or in the recruitment of a region outside of the task-network, underlies this maintenance of normal performance. However, in most studies to date, increased brain activity is not correlated with indices of both disease and performance and what appears to be compensation could simply be a symptom of neurodegeneration.

RECENT FINDINGS

MRI studies have explored compensation in neurodegenerative disease, claiming that compensation is evident across a number of disorders, including Alzheimer's and Parkinson's disease, but generally always in early stages; after this point, compensation is generally no longer able to operate under the severe burden of disease. However, none of these studies explicitly adopted a particular model of compensation. Thus, we also discuss our recent attempts to operationalize compensation for empirical testing.

SUMMARY

There is clear evidence of compensatory processes in the early stages of neurodegenerative disease. However, for a more complete understanding, this requires more explicit empirical modelling.

A posterior-to-anterior shift of brain functional dynamics in aging

Convergent evidence from task-based functional magnetic resonance imaging (fMRI) studies suggests a posterior-to-anterior shift as an adaptive compensatory scaffolding mechanism for aging. This study aimed to investigate whether brain functional dynamics at rest follow the same scaffolding mechanism for aging using a large Chinese sample aged from 22 to 79 years (n = 277). We defined a probability of brain regions being hubs over a period of time to characterize functional hub dynamic, and defined variability of the functional connectivity to characterize dynamic functional connectivity using resting-state fMRI. Our results revealed that both functional hub dynamics and dynamic functional connectivity posited an age-related posterior-to-anterior shift. Specifically, the posterior brain region showed attenuated dynamics, while the anterior brain regions showed augmented dynamics in aging. Interestingly, our analysis further indicated that the age-related episodic memory decline was associated with the age-related decrease in the brain functional dynamics of the posterior regions. Hence, these findings provided a new dimension to view the scaffolding mechanism for aging based on the brain functional dynamics.

Hippocampal formation alterations differently contribute to autobiographic memory deficits in mild cognitive impairment and Alzheimer's disease

Autobiographical memory (AM) is part of declarative memory and includes both semantic and episodic aspects. AM deficits are among the major complaints of patients with Alzheimer's disease (AD) even in early or preclinical stages. Previous MRI studies in AD patients have showed that deficits in semantic and episodic AM are associated with hippocampal alterations. However, the question which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits of AM in individuals with mild cognitive impairment (MCI) and AD patients has not been investigated so far. Hundred and seven participants (38 AD patients, 38 MCI individuals and 31 healthy controls [HC]) underwent MRI at 3 Tesla. AM was assessed with a semi-structured interview (E-AGI). FreeSurfer 5.3 was used for hippocampal parcellation. Semantic and episodic AM scores were related to the volume of 5 hippocampal subfields and cortical thickness in the parahippocampal and entorhinal cortex. Both semantic and episodic AM deficits were associated with bilateral hippocampal alterations. These associations referred mainly to CA1, CA2-3, presubiculum, and subiculum atrophy. Episodic, but not semantic AM loss was associated with cortical thickness reduction of the bilateral parahippocampal and enthorinal cortex. In MCI individuals, episodic, but not semantic AM deficits were associated with alterations of the CA1, presubiculum and subiculum. Our findings support the crucial role of CA1, presubiculum, and subiculum in episodic memory. The present results implicate that in MCI individuals, semantic and episodic AM deficits are subserved by distinct neuronal systems.