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

Episodic memory network characteristics in patients with amnestic mild cognitive impairment accompanied by executive function impairment

OBJECTIVE

To explore the functional connectivity (FC) characteristics of the episodic memory network (EMN) in amnestic mild cognitive impairment (aMCI) patients with different levels of executive function (EF).

METHODS

This study included 76 participants from the Alzheimer's Disease Neuroimaging Initiative database, comprising 23 healthy controls (HCs) and 53 aMCI patients. Based on EF levels, aMCI patients were categorized into aMCI-highEF and aMCI-lowEF groups. Cognitive function scores, pathological markers (cerebrospinal fluid β-amyloid, total tau protein, phosphorylated tau protein, AV45-PET, and FDG-PET), and functional magnetic resonance imaging were collected and compared among the three groups. Seed-based FC analysis was used to examine differences in the EMN among the groups, and partial correlation analysis was employed to investigate the relationship between changes in FC and cognitive function scores as well as pathological markers.

RESULTS

Compared to the aMCI-highEF group, the aMCI-lowEF group exhibited more severe cognitive impairment, decreased cerebral glucose metabolism, and elevated AV45 levels. Significant FC differences in the left superior temporal gyrus (STG) of the EMN were observed among the three groups. Post hoc analysis revealed that the aMCI-lowEF group had increased FC in the left STG compared to the HCs and aMCI-highEF groups, with statistically significant differences. Correlation analysis showed a significant negative correlation between the differences in FC in the left STG of aMCI-highEF and aMCI-lowEF groups and Rey Auditory Verbal Learning Test forgetting scores. Receiver operator characteristic curve analysis indicated an area under the curve of 0.741 for distinguishing between aMCI-highEF and aMCI-lowEF groups based on FC of left STG, with a sensitivity of 0.808 and a specificity of 0.667.

CONCLUSION

aMCI-lowEF exhibits characteristic changes in FC within the EMN, providing theoretical support for the role of EF in mediating EMN alterations and, consequently, impacting episodic memory function.

Directed Functional Connectivity Changes of Triple Networks for Stable and Progressive Mild Cognitive Impairment

Mild cognitive impairment includes two distinct subtypes, namely progressive mild cognitive impairment and stable mild cognitive impairment. While alterations in extensive functional connectivity have been observed in both subtypes, limited attention has been given to directed functional connectivity. A triple network, composed of the central executive network, default mode network, and salience network, is considered to be the core cognitive network. We evaluated the alterations in directed functional connectivity within and between the triple network in progressive and stable mild cognitive impairment groups and investigated its role in predicting disease conversion. Resting-state functional magnetic resonance imaging was used to analyze directed functional connectivity within the triple networks. A correlation analysis was performed to investigate potential associations between altered directed functional connectivity within the triple networks and the neurocognitive performance of the participants. Our study revealed significant differences in directed functional connectivity within and between the triple network in the progressive and stable mild cognitive impairment groups. Altered directed functional connectivity within the triple network was involved in episodic memory and executive function. Thus, the directed functional connectivity of the triple network may be used as an imaging marker of mild cognitive impairment.

Repetitive transcranial magnetic stimulation regulates effective connectivity patterns of brain networks in the spectrum of preclinical Alzheimer's disease

Objectives

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered as the spectrum of preclinical Alzheimer's disease (AD), with abnormal brain network connectivity as the main neuroimaging feature. Repetitive transcranial magnetic stimulation (rTMS) has been proven to be an effective non-invasive technique for addressing neuropsychiatric disorders. This study aims to explore the potential of targeted rTMS to regulate effective connectivity within the default mode network (DMN) and the executive control network (CEN), thereby improving cognitive function.

Methods

This study included 86 healthy controls (HCs), 72 SCDs, and 86 aMCIs. Among them, 10 SCDs and 11 aMCIs received a 2-week rTMS course of 5-day, once-daily. Cross-sectional analysis with the spectral dynamic causal model (spDCM) was used to analyze the DMN and CEN effective connectivity patterns of the three groups. Afterwards, longitudinal analysis was conducted on the changes in effective connectivity patterns and cognitive function before and after rTMS for SCD and aMCI, and the correlation between them was analyzed.

Results

Cross-sectional analysis showed different effective connectivity patterns in the DMN and CEN among the three groups. Longitudinal analysis showed that the effective connectivity pattern of the SCD had changed, accompanied by improvements in episodic memory. Correlation analysis indicated a negative relationship between effective connectivity from the left angular gyrus (ANG) to the anterior cingulate gyrus and the ANG.R to the right middle frontal gyrus, with visuospatial and executive function, respectively. In patients with aMCI, episodic memory and executive function improved, while the effective connectivity pattern remained unchanged.

Conclusion

This study demonstrates that PCUN-targeted rTMS in SCD regulates the abnormal effective connectivity patterns in DMN and CEN, thereby improving cognition function. Conversely, in aMCI, the mechanism of improvement may differ. Our findings further suggest that rTMS is more effective in preventing or delaying disease progression in the earlier stages of the AD spectrum.

Clinical Trial Registration

http://www.chictr.org.cn, ChiCTR2000034533.

Causal functional connectivity in Alzheimer's disease computed from time series fMRI data

Functional connectivity between brain regions is known to be altered in Alzheimer's disease and promises to be a biomarker for early diagnosis. Several approaches for functional connectivity obtain an un-directed network representing stochastic associations (correlations) between brain regions. However, association does not necessarily imply causation. In contrast, Causal Functional Connectivity (CFC) is more informative, providing a directed network representing causal relationships between brain regions. In this paper, we obtained the causal functional connectome for the whole brain from resting-state functional magnetic resonance imaging (rs-fMRI) recordings of subjects from three clinical groups: cognitively normal, mild cognitive impairment, and Alzheimer's disease. We applied the recently developed Time-aware PC (TPC) algorithm to infer the causal functional connectome for the whole brain. TPC supports model-free estimation of whole brain CFC based on directed graphical modeling in a time series setting. We compared the CFC outcome of TPC with that of other related approaches in the literature. Then, we used the CFC outcomes of TPC and performed an exploratory analysis of the difference in strengths of CFC edges between Alzheimer's and cognitively normal groups, based on edge-wise p-values obtained by Welch's t-test. The brain regions thus identified are found to be in agreement with literature on brain regions impacted by Alzheimer's disease, published by researchers from clinical/medical institutions.

Altered brain regional homogeneity is associated with cognitive dysfunction in first-episode drug-naive major depressive disorder: A resting-state fMRI study

BACKGROUND

Our study aimed to explore the abnormal spontaneous brain activity by regional homogeneity (ReHo) and its association with cognitive function to understand the neuropathology of major depressive disorder (MDD).

METHODS

ReHo was used to investigate brain activities of 60 patients with first-episode drug-naive MDD and 60 healthy controls (HCs). Partial correlation analysis was conducted on altered ReHo values and the severity of symptoms and cognitive deficits. Moreover, support vector machine analysis was used to evaluate the accuracy of abnormal ReHo values in distinguishing patients with MDD from HCs.

RESULTS

Compared with HCs, patients with MDD showed significantly increased ReHo values in the right cerebellum crus2 and right thalamus and decreased ReHo values in the right angular gyrus (AG) and right precuneus (PCUN). The ReHo values in right cerebellum crus2 and right AG were positively associated with working memory and visual learning, respectively. Furthermore, the combination of ReHo values in the right cerebellum crus2 and right PCUN discriminated the patients with MDD from HCs with specificity, sensitivity, and accuracy of 0.9688, 0.6250, and 0.90, respectively.

LIMITATIONS

The design of repeated cross-sectional surveys does not allow analyses of within individual changes.

CONCLUSIONS

Our study revealed that the pathophysiology mechanism of cognitive deficits in MDD may be related to abnormal spontaneous brain activity. Moreover, the combination of ReHo values in the right cerebellum crus2 and right PCUN can be used to discriminate patients with MDD from HCs effectively.

Aberrant spontaneous static and dynamic amplitude of low-frequency fluctuations in cerebral small vessel disease with or without mild cognitive impairment

BACKGROUND

Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration.

METHODS

Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p < .05).

RESULTS

Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r = 0.713, p = .002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r = -0.560, p = .002).

CONCLUSION

There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Hypoconnectivity within the cingulo-opercular network in patients with mild cognitive impairment in Chinese communities

INTRODUCTION

At rest, the brain's higher cognitive systems engage in correlated activity patterns, forming networks. With mild cognitive impairment (MCI), it is essential to understand how functional connectivity within and between resting-state networks changes. This study used resting-state functional connectivity to identify significant differences within and between the cingulo-opercular network (CON) and default mode network (DMN).

METHODS

We assessed cognitive function in patients using the Chinese version of the Alzheimer's disease assessment scale-Cognitive subscale (ADAS-Cog). A group of MCI subjects (ages 60-83 years, n = 45) was compared to age-matched healthy controls (n = 70). Resting-state functional connectivity was used to determine functional connectivity strength within and between the CON and DMN.

RESULTS

Compared to healthy controls, the MCI group showed significantly lower functional connectivity within the CON (F = 10.76, df = 1, p = 0.001, FDR adjusted p = 0.003). Additionally, the MCI group displayed no distinct differences in functional connectivity within DMN (F = 0.162, df = 1, p = 0.688, FDR adjusted p = 0.688) and between CON and DMN (F = 2.270, df = 1, p = 0.135, FDR adjusted p = 0.262). Moreover, we found no correlation between ADAS-Cog and within- or between-connectivity metrics among subjects with MCI.

CONCLUSIONS

Our findings indicate that specific patterns of hypoconnectivity within CON circuitry may characterize MCI relative to healthy controls. This work improves our understanding of network dysfunction underlying MCI and could inform more targeted treatment.

Accumulation of network redundancy marks the early stage of Alzheimer's disease

Brain wiring redundancy counteracts aging-related cognitive decline by reserving additional communication channels as a neuroprotective mechanism. Such a mechanism plays a potentially important role in maintaining cognitive function during the early stages of neurodegenerative disorders such as Alzheimer's disease (AD). AD is characterized by severe cognitive decline and involves a long prodromal stage of mild cognitive impairment (MCI). Since MCI subjects are at high risk of converting to AD, identifying MCI individuals is essential for early intervention. To delineate the redundancy profile during AD progression and enable better MCI diagnosis, we define a metric that reflects redundant disjoint connections between brain regions and extract redundancy features in three high-order brain networks-medial frontal, frontoparietal, and default mode networks-based on dynamic functional connectivity (dFC) captured by resting-state functional magnetic resonance imaging (rs-fMRI). We show that redundancy increases significantly from normal control (NC) to MCI individuals and decreases slightly from MCI to AD individuals. We further demonstrate that statistical features of redundancy are highly discriminative and yield state-of-the-art accuracy of up to 96.8 ± 1.0% in support vector machine (SVM) classification between NC and MCI individuals. This study provides evidence supporting the notion that redundancy serves as a crucial neuroprotective mechanism in MCI.

Differential decay of gist and detail memory in older adults with amnestic mild cognitive impairment

Amnestic mild cognitive impairment (aMCI) has been identified as a risk factor for dementia due to Alzheimer's disease. The medial temporal structures, which are crucial for memory processing, are the earliest affected regions in the brains of patients with aMCI, and episodic memory performance has been identified as a reliable way to discriminate between patients with aMCI and cognitively normal older adults. However, whether the detail and gist memory of patients with aMCI and cognitively normal older adults decay differently remains unclear. In this study, we hypothesized that detail and gist memory would be retrieved differentially, with a larger group performance gap in detail memory than in gist memory. In addition, we explored whether an increasing group performance gap between detail memory and gist memory groups would be observed over a 14-day period. Furthermore, we hypothesized that unisensory (audio-only) and multisensory (audiovisual) encoding would lead to differences in retrievals, with the multisensory condition reducing between and within-group performance gaps observed under the unisensory condition. The analyses conducted were analyses of covariance controlling for age, sex, and education and correlational analyses to examine behavioral performance and the association between behavioral data and brain variables. Compared with cognitively normal older adults, the patients with aMCI performed poorly on both detail and gist memory tests, and this performance gap persisted over time. Moreover, the memory performance of the patients with aMCI was enhanced by the provision of multisensory information, and bimodal input was significantly associated with medial temporal structure variables. Overall, our findings suggest that detail and gist memory decay differently, with a longer lasting group gap in gist memory than in detail memory. Multisensory encoding effectively reduced or overcame the between- and within-group gaps between time intervals, especially for gist memory, compared with unisensory encoding.

Individual Proportion Loss of Functional Connectivity Strength: A Novel Individual Functional Connectivity Biomarker for Subjective Cognitive Decline Populations

High individual variation in the subjective cognitive decline (SCD) population makes functional connectivity (FC) biomarkers unstable. This study proposed a novel individual FC index, named individual proportion loss of functional connectivity strength (IPLFCS), and explored potential biomarkers for SCD using this new index. We proposed an IPLFCS analysis framework and compared it with traditional FC in Chinese and Western cohorts. Post hoc tests were used to determine biomarkers. Pearson's correlation analysis was used to investigate the correlation between neuropsychological scores or cortical amyloid deposits and IPLFCS biomarkers. Receiver operating characteristic curves were utilized to evaluate the ability of potential biomarkers to distinguish between groups. IPLFCS of the left middle temporal gyrus (LMTG) was identified as a potential biomarker. The IPLFC was correlated with the traditional FC (r = 0.956, p < 0.001; r = 0.946, p < 0.001) and cortical amyloid deposition (r = -0.245, p = 0.029; r = -0.185, p = 0.048) in both cohorts. Furthermore, the IPLFCS decreased across the Alzheimer's disease (AD) continuum. Its diagnostic efficiency was superior to that of existing fMRI biomarkers. These findings suggest that IPLFCS of the LMTG could be a potential biomarker of SCD.

Effects of Remote Expressive Arts Program in Older Adults with Mild Cognitive Impairment: A Randomized Controlled Trial

BACKGROUND

Mild cognitive impairment (MCI) is a stage of cognitive ability loss with intact activities of daily living and an increased risk for the development of dementia.

OBJECTIVE

This study evaluated the intervention effect of remote expressive arts program (rEAP) on cognitive function in older adults with MCI and investigated the underlying neurobiological mechanisms.

METHODS

We assigned 73 older MCI patients to receive rEAP or health education (HE), who underwent neuropsychological evaluation and resting-state functional magnetic resonance imaging before and after treatment. Neuropsychological scores were analyzed using SPSS software, and regional homogeneity (ReHo) values and seed-based functional connectivity (FC) were analyzed using Matlab software.

RESULTS

The rEAP group showed more significant improvements in cognitive function than the HE group. rEAP affected spontaneous brain activity and brain networks. The ReHo values in the right anterior cingulate/paracingulate cortex and the left dorsolateral superior frontal gyrus significantly increased and decreased, respectively, in the rEAP and HE groups. Further, ReHo value changes were significantly associated with the corresponding neuropsychological test score changes in the rEAP group. Moreover, the rEAP group showed decreased FC between the posterior cingulate cortex and the right middle temporal gyrus and increased FC between the ventromedial prefrontal cortex and left angular gyrus.

CONCLUSION

The 12-week rEAP improved cognitive function in MCI patients. Additionally, the alterations of spontaneous brain network connections and activity helped improve and maintain cognitive function in MCI patients.

Increased functional connectivity patterns in mild Alzheimer's disease: A rsfMRI study

Background

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer's disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques.

Methods

In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer's disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer's disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson's correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed.

Results

Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition.

Conclusion

The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.

Altered functional hubs and connectivity in type 2 diabetes mellitus with and without mild cognitive impairment

Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities of brain networks, especially the damage to hub nodes in networks. This study explored the abnormal hub nodes of brain functional networks in patients with T2DM under different cognitive states. Sixty-five patients with T2DM and 34 healthy controls (HCs) underwent neuropsychological assessment. Then, degree centrality (DC) analysis and seed-based functional connectivity (FC) analysis were performed to identify the abnormal hub nodes and the FC patterns of these hubs in T2DM patients with mild cognitive impairment (MCI) (DMCI group, N = 31) and without MCI (DMCN group, N = 34). Correlation analyzes examined the relationship between abnormal DC and FC and clinical/cognitive variables. Compared with HCs, both T2DM groups showed decreased DC values in the visual cortex, and the T2DM patients with MCI (DMCI) showed more extensive alterations in the right parahippocampal gyrus (PHG), bilateral posterior cingulate cortex (PCC), and left superior frontal gyrus (SFG) regions than T2DM patients with normal cognitive function. Seed-based FC analysis of PHG and PCC nodes showed that functional disconnection mainly occurred in visual and memory connectivity in patients with DMCI. Multiple abnormal DC values correlated with neuropsychological tests in patients with T2DM. In conclusion, this study found that the DMCI group displayed more extensive alterations in hub nodes and FC in vision and memory-related brain regions, suggesting that visual-related regions dysfunctions and disconnection may be involved in the neuropathology of visuospatial function impairment in patients with DMCI.

Altered anterior cingulate cortex subregional connectivity associated with cognitions for distinguishing the spectrum of pre-clinical Alzheimer's disease

Background

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered part of the early progression continuum of Alzheimer's disease (AD). The anterior cingulate cortex (ACC), a hub of information processing and regulation in the brain, plays an essential role in AD pathophysiology. In the present study, we aimed to systematically identify changes in the functional connectivity (FC) of ACC subregions in patients with SCD and aMCI and evaluate the association of these changes with cognition.

Materials and methods

Functional connectivity (FC) analysis of ACC sub-regions was performed among 66 patients with SCD, 71 patients with aMCI, and 78 healthy controls (HCs). Correlation analyses were performed to examine the relationship between FC of altered ACC subnetworks and cognition.

Results

Compared to HCs, SCD patients showed increased FC of the bilateral precuneus (PCUN) and caudal ACC, left superior frontal gyrus (SFG) and subgenual ACC, left inferior parietal lobule (IPL) and dorsal ACC, left middle occipital gyrus (MOG) and dorsal ACC, and left middle temporal gyrus (MTG) and subgenual ACC, while aMCI patients showed increased FC of the left inferior frontal gyrus (IFG) and dorsal ACC and left medial frontal gyrus (MFG) and subgenual ACC. Compared to patients with SCD, patients with aMCI showed increased FC of the right MFG and dorsal ACC and left ACC and subgenual ACC, while the left posterior cingulate cortex (PCC) showed decreased FC with the caudal ACC. Moreover, some FC values among the altered ACC subnetworks were significantly correlated with episodic memory and executive function.

Conclusion

SCD and aMCI, part of the spectrum of pre-clinical AD, share some convergent and divergent altered intrinsic connectivity of ACC subregions. These results may serve as neuroimaging biomarkers of the preclinical phase of AD and provide new insights into the design of preclinical interventions.

Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI

Background/Objective

Neuroimaging studies have reported abnormalities in the examination of functional connectivity in late-life depression (LLD) in the default mode network (DMN). The present study aims to study resting-state functional connectivity within the DMN in people diagnosed with late-life major depressive disorder (MDD) compared to healthy controls (HCs). Moreover, we would like to differentiate these same connectivity patterns between participants with high vs. low anxiety levels.

Method

The sample comprised 56 participants between the ages of 60 and 75; 27 of them were patients with a diagnosis of MDD. Patients were further divided into two samples according to anxiety level: the four people with the highest anxiety level and the five with the lowest anxiety level. Clinical aspects were measured using psychological questionnaires. Each participant underwent functional magnetic resonance imaging (fMRI) acquisition in different regions of interest (ROIs) of the DMN.

Results

There was a greater correlation between pairs of ROIs in the control group than in patients with LLD, being this effect preferentially observed in patients with higher anxiety levels.

Conclusions

There are differences in functional connectivity within the DMN depending on the level of psychopathology. This can be reflected in these correlations and in the number of clusters and how the brain lateralizes (clustering).

Shared and specific dynamics of brain activity and connectivity in amnestic and nonamnestic mild cognitive impairment

AIMS

The present study aimed to compare temporal variability in the spontaneous fluctuations of activity and connectivity between amnestic MCI (aMCI) and nonamnestic MCI (naMCI), which enhances the understanding of their different pathophysiologies and provides targets for individualized intervention.

METHODS

Sixty-five naMCI and 48 aMCI subjects and 75 healthy controls were recruited. A sliding window analysis was used to evaluate the dynamic amplitude of low-frequency fluctuations (dALFF), dynamic regional homogeneity (dReHo), and dynamic functional connectivity (dFC). The caudal/rostral hippocampus was selected as the seeds for calculating dFC.

RESULTS

Both aMCI and naMCI exhibited abnormal dALFF, dReHo, and hippocampal dFC compared with healthy controls. Compared with individuals with naMCI, those with aMCI exhibited (1) higher dALFF variability in the right putamen, left Rolandic operculum, and right middle cingulum, (2) lower dReHo variability in the right superior parietal lobule, and (3) lower dFC variability between the hippocampus and other regions (left superior occipital gyrus, middle frontal gyrus, inferior cerebellum, precuneus, and right superior frontal gyrus). Additionally, variability in dALFF, dReHo, and hippocampal dFC exhibited different associations with cognitive scores in aMCI and naMCI patients, respectively. Finally, dReHo variability in the right superior parietal lobule and dFC variability between the right caudal hippocampus and left inferior cerebellum exhibited partially mediated effects on the different memory scores between people with aMCI and naMCI.

CONCLUSION

The aMCI and naMCI patients exhibited shared and specific patterns of dynamic brain activity and connectivity. The dReHo of the superior parietal lobule and dFC of the hippocampus-cerebellum contributed to the memory heterogeneity of MCI subtypes. Analyzing the temporal variability in the spontaneous fluctuations of brain activity and connectivity provided a new perspective for exploring the different pathophysiological mechanisms in MCI subtypes.

The fractional amplitude of low-frequency fluctuations signals related to amyloid uptake in high-risk populations—A pilot fMRI study

Background

Patients with type 2 diabetes mellitus (T2DM) and subjective cognitive decline (SCD) have a higher risk to develop Alzheimer's Disease (AD). Resting-state-functional magnetic resonance imaging (rs-fMRI) was used to document neurological involvement in the two groups from the aspect of brain dysfunction. Accumulation of amyloid-β (Aβ) starts decades ago before the onset of clinical symptoms and may already have been associated with brain function in high-risk populations. However, this study aims to compare the patterns of fractional amplitude of low-frequency fluctuations (fALFF) maps between cognitively normal high-risk groups (SCD and T2DM) and healthy elderly and evaluate the association between regional amyloid deposition and local fALFF signals in certain cortical regions.

Materials and methods

A total of 18 T2DM, 11 SCD, and 18 healthy elderlies were included in this study. The differences in the fALFF maps were compared between HC and high-risk groups. Regional amyloid deposition and local fALFF signals were obtained and further correlated in two high-risk groups.

Results

Compared to HC, the altered fALFF signals of regions were shown in SCD such as the left posterior cerebellum, left putamen, and cingulate gyrus. The T2DM group illustrated altered neural activity in the superior temporal gyrus, supplementary motor area, and precentral gyrus. The correlation between fALFF signals and amyloid deposition was negative in the left anterior cingulate cortex for both groups. In the T2DM group, a positive correlation was shown in the right occipital lobe and left mesial temporal lobe.

Conclusion

The altered fALFF signals were demonstrated in high-risk groups compared to HC. Very early amyloid deposition in SCD and T2DM groups was observed to affect the neural activity mainly involved in the default mode network (DMN).

Modulation of Brain Activity and Functional Connectivity by Acupuncture Combined With Donepezil on Mild-to-Moderate Alzheimer's Disease: A Neuroimaging Pilot Study

Background

Functional brain imaging changes have been proven as potential pathophysiological targets in early-stage AD. Current longitudinal neuroimaging studies of AD treated by acupuncture, which is one of the growingly acknowledged non-pharmacological interventions, have neither adopted comprehensive acupuncture protocols, nor explored the changes after a complete treatment duration. Thus, the mechanisms of acupuncture effects remain not fully investigated.

Objective

This study aimed to investigate the changes in spontaneous brain activity and functional connectivity and provide evidence for central mechanism of a 12-week acupuncture program on mild-to-moderate AD.

Methods

A total of forty-four patients with mild-to-moderate AD and twenty-two age- and education-level-matched healthy subjects were enrolled in this study. The forty-four patients with AD received a 12-week intervention of either acupuncture combined with Donepezil (the treatment group) or Donepezil alone (the control group). The two groups received two functional magnetic resonance imaging (fMRI) scans before and after treatment. The healthy subject group underwent no intervention, and only one fMRI scan was performed after enrollment. The fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) were applied to analyze the imaging data. The correlations between the imaging indicators and the changed score of Alzheimer's Disease Assessment Scale-Cognitive Section (ADAS-cog) were also explored.

Results

After the 12-week intervention, compared to those in the control group, patients with AD in the treatment group scored significantly lower on ADAS-cog value. Moreover, compared to healthy subjects, the areas where the fALFF value decreased in patients with AD were mainly located in the right inferior temporal gyrus, middle/inferior frontal gyrus, middle occipital gyrus, left precuneus, and bilateral superior temporal gyrus. Compared with the control group, the right precuneus demonstrated the greatest changed value of fALFF after the intervention in the treatment group. The difference in ADAS-cog after interventions was positively correlated with the difference in fALFF value in the left temporal lobe. Right precuneus-based FC analysis showed that the altered FC by the treatment group compared to the control group was mainly located in the bilateral middle temporal gyrus.

Conclusion

The study revealed the key role of precuneus in the effect of the combination of acupuncture and Donepezil on mild-to-moderate AD for cognitive function, as well as its connection with middle temporal gyrus, which provided a potential treating target for AD.

Trial Registration Number:

NCT03810794 (http://www.clinicaltrials.gov).

The Effects of Normal Aging, Subjective Cognitive Decline, Mild Cognitive Impairment, or Alzheimer’s Disease on Visual Search

Background: Alzheimer’s disease (AD) has been confirmed as an influencing factor of visual impairment, but potential concomitant effects on visual and cognitive performance are not well understood. Objective: To provide a new method for early screening of Alzheimer’s disease and further explore the theoretical mechanism of the decline of whole visual and cognitive performance in AD. Methods: We studied 60 individuals without dementia as normal control (NC), 74 individuals with subjective cognitive decline (SCD), 60 individuals with amnesia mild cognitive impairment (aMCI), and 75 patients with AD on a battery of tests designed to measure multiple aspects of basic and higher-order visual perception and cognition. All subjects performed on same visual and cognitive test batteries. Results: The results showed both of four groups, with the stimulus-presentation time being longer, the visual-search performance improved, and both the eye interest-area first fixation duration and the interest-area-fixation count increased. Particularly under the noise-masking condition, the AD group performed the worst at stimulus-presentation times between 300 and 900 ms. The aMCI group, but not the SCD group, performed worse than the NC group at the stimulus-presentation time of either 300 or 500 ms. The interest-area-fixation count was higher in all the patient groups than that in the NC group, and distinguishable between participants with AD and those with SCD or aMCI. Conclusion: The visual-search performance combined with eye-movement tracking under the noise-masking condition can be used for distinguishing AD from normal aging, SCD, and aMCI.

Longitudinal functional connectivity patterns of the default mode network in healthy older adults

Cross-sectional studies have consistently identified age-associated alterations in default mode network (DMN) functional connectivity (FC). Yet, research on longitudinal trajectories of FC changes of the DMN in healthy aging is less conclusive. For the present study, we used a resting state functional MRI dataset drawn from the Longitudinal Healthy Aging Brain Database Project (LHAB) collected in 5 occasions over a course of 7 years (baseline N = 232, age range: 64-87 y, mean age = 70.85 y). FC strength changes within the DMN and its regions were investigated using a network-based statistical method suitable for the analysis of longitudinal data. The average DMN FC strength remained stable, however, various DMN components showed differential age- and time-related effects. Our results revealed a complex pattern of longitudinal change seen as decreases and increases of FC strength encompassing the majority of DMN regions, while age-related effects were negative and present in select brain areas. These findings testify to the growing importance of longitudinal studies using more sophisticated fine-grained tools needed to highlight the complexity of the functional reorganization of DMN with healthy aging.

Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

While mild cognitive impairment (MCI) has been classified into amnestic MCI (aMCI) and nonamnestic MCI (naMCI), the neuropathological bases of these two subtypes remain elusive. Here, we performed a systematic review and meta-analysis to determine the subtype specificity of neuroimaging abnormalities in MCI and to identify neural features that may differ between aMCI and naMCI. We synthesized 50 studies that used common neuroimaging modalities, including magnetic resonance imaging and positron emission tomography, to compare brain atrophy, white matter abnormalities, cortical thinning, cerebral hypometabolism, amyloid/tau deposition, or other features among aMCI, naMCI, and normal cognition. Compared with normal cognition, aMCI shows diverse neuroimaging abnormalities of large effect sizes. In contrast, naMCI exhibits restricted abnormalities of small effect sizes. Some features, including medial temporal lobe atrophy and white matter abnormalities, are shared by the two MCI subtypes. Overall, brain abnormalities are worse, if not similar, in aMCI than in naMCI. The only neuroimaging abnormality specific to aMCI is increased amyloid burden; no feature specific to naMCI was found. Taken together, our findings have elucidated the neuropathological changes that occur in aMCI and naMCI. Clarifying the neuroimaging profiles of aMCI and naMCI can improve the early identification, differentiation, and intervention of prodromal dementia.

Brain network hierarchy reorganization in Alzheimer's disease: A resting‐state functional magnetic resonance imaging study

Hierarchy is a fundamental organizational principle of the human brain network. Whether and how the network hierarchy changes in Alzheimer's disease (AD) remains unclear. To explore brain network hierarchy alterations in AD and their clinical relevance. Forty‐nine healthy controls (HCs), 49 patients with mild cognitive impairment (MCI), and 49 patients with AD were included. The brain network hierarchy of each group was depicted by connectome gradient analyses. We assessed the network hierarchy changes by comparing the gradient values in each network across the AD, MCI, and HC groups. Whole‐brain voxel‐level gradient values were compared across the AD, MCI, and HC groups to identify abnormal brain regions. Finally, we examined the relationships between altered gradient values and clinical features. In the secondary gradient, the posterior default mode network (DMN) gradient values decreased significantly in patients with AD compared with HCs. Regionally, compared with HCs, both MCI and AD groups showed that most of the brain regions with increased gradient values were located in anterior DMN, while most of the brain regions with decreased gradient values were located in posterior DMN. The decrease of gradients in the left middle occipital gyrus was associated with better logical memory performance. The increase of gradients in the right middle frontal gyrus was associated with lower rates of dementia. The network hierarchy changed characteristically in patients with AD and was closely related to memory function and disease severity. These results provide a novel view for further understanding the underlying neuro‐mechanisms of AD.

High efficiency of left superior frontal gyrus and the symptom features of major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) patients with anhedonia tend to have a poor prognosis. The underlying imaging basis for anhedonia in MDD remains largely unknown. The relationship between nodal properties and anhedonia in MDD patients need to be further investigated. Herein, this study aims to explore differences of cerebral functional node characteristics in MDD patients with severe anhedonia (MDD-SA) and MDD patients with mild anhedonia (MDD-MA) before and after the antidepressant treatment.

METHODS

Ninety participants with current MDD were recruited in this study. 24-Item Hamilton Depression Scale (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess the severity of depression and anhedonia at baseline and the end of 6-months treatment. The MDD patients who scored above the 25th percentile on the SHAPS were assigned to an MDD-SA group (n=19), while those who scored below the 25th percentile were assigned to an MDD-MA group (n=18). All patients in the 2 groups received antidepressant treatment. Functional magnetic resonance imaging (fMRI) images of all the patients were collected at baseline and the end of 6-months treatment. Graph theory was applied to analyze the patients' cerebral functional nodal characteristics, which were measured by efficiency (ei) and degree (ki).

RESULTS

Repeated measures 2-factor ANCOVA showed significant main effects on group on the ei and ki values of left superior frontal gyrus (LSFG) (P=0.003 and P=0.008, respectively), and on the ei and ki values of left medial orbital-frontal gyrus (LMOFG) (P=0.004 and P=0.008, respectively). Compared with the MDD-MA group, the significantly higher ei and ki values of the LSFG (P=0.015 and P=0.021, respectively), and the significantly higher ei and ki values of the LMOFG (P=0.015 and P=0.037, respectively) were observed in the MDD-SA group at baseline. Meanwhile, higher SHAPS scores could result in higher ei and ki values of LSFG (P=0.019 and P=0.026, respectively), and higher ei value of LMOFG (P=0.040) at baseline; higher SHAPS scores could result in higher ei values of LSFG (P=0.049) at the end of 6-months treatment. The multiple linear regression analysis revealed that sex were negatively correlated with the ei and ki values of LSFG (r= -0.014, P=0.004; r=-1.153, P=0.001, respectively). The onset age of MDD was negatively correlated with the ki value of LSFG (r=-0.420, P=0.034) at the end of 6-months treatment. We also found that SHAPS scores at baseline were positively correlated with the HAMD-24 scores (r=0.387, P=0.022) at the end of 6-months treatment.

CONCLUSIONS

There are obvious differences in nodal properties between the MDD-SA and the MDD-MA patients, such as the high ei of LSFG in the MDD-SA patients, which may be associated with the severity of anhedonia. These nodal properties could be potential biomarkers for the prognosis of MDD. The increased ei and ki values in the LSFG of MDD-SA patients may underlie a compensatory mechanism or protective mechanism. The mechanism may be an important component of the pathological mechanism of MDD-SA. The poor prognosis in the MDD-SA patients suggests that anhedonia may predict a worse prognosis in MDD patients. Sex and onset age of MDD may affect the nodal properties of LSFG at baseline and the end of 6-months treatment.

A Systematic Review of Neuroimaging Studies Comparing Individuals with Subjective Cognitive Decline to Healthy Controls

Background: Individuals with subjective cognitive decline (SCD) are hypothesized to be the earliest along the cognitive continuum between healthy aging and Alzheimer’s disease (AD), although more research is needed on this topic. Given that treatment approaches may be most effective pre-clinically, a primary objective of emerging research is to identify biological markers of SCD using neuroimaging methods. Objective: The current review aimed to comprehensively present the neuroimaging studies on SCD to date. Methods: PubMed and PsycINFO databases were searched for neuroimaging studies of individuals with SCD. Quality assessments were completed using the Appraisal tool for Cross-Sectional Studies. Results: In total, 62 neuroimaging studies investigating differences between participants with SCD and healthy controls were identified. Specifically, the number of studies were as follows: 36 MRI, 6 PET, 8 MRI/PET, 4 EEG, 7 MEG, and 1 SPECT. Across neuroimaging modalities, 48 of the 62 included studies revealed significant differences in brain structure and/or function between groups. Conclusion: Neuroimaging methods can identify differences between healthy controls and individuals with SCD. However, inconsistent results were found within and between neuroimaging modalities. Discrepancies across studies may be best accounted for by methodological differences, notably variable criteria for SCD, and differences in participant characteristics and risk factors for AD. Clinic based recruitment and cross-sectional study design were common and may bias the literature. Future neuroimaging investigations of SCD should consistently incorporate the standardized research criteria for SCD (as recommended by the SCD-Initiative), include more details of their SCD sample and their symptoms, and examine groups longitudinally.

Hyperconnectivity Associated with Anosognosia Accelerating Clinical Progression in Amnestic Mild Cognitive Impairment

The incidence and prevalence of anosognosia are highly variable in amnestic mild cognitive impairment (aMCI) patients. The study aims to explore the neuropathological mechanism of anosognosia in aMCI patients using two different but complementary technologies, including ¹⁸F-flortaucipir positron emission tomography and resting state functional magnetic resonance imaging. The study found that anosognosia was related to higher tau accumulation in the left medial orbitofrontal cortex (OFC), left posterior cingulate cortex, and right precuneus in aMCI patients. Intrinsic functional connectivity analyses found significant correlations between anosognosia index and hypoconnectivity between the left medial OFC and left middle temporal gyrus (MTG), right precuneus and left lingual gyrus. Longitudinally, the connectivity of these brain regions as well as the right precuneus and right cuneus showed hyperconnectivity in aMCI patients with anosognosia. The anosognosia index was also correlated with AD pathological markers (i.e., Aβ, t-tau, and p-tau) and brain glucose metabolism in aMCI patients. In conclusion, anosognosia in aMCI patients is associated with the dysfunction of medial OFC-MTG circuit and the precuneus-visual cortex circuit and accelerates clinical progression to AD dementia.

Hippocampal-Subregion Mechanisms of Repetitive Transcranial Magnetic Stimulation Causally Associated with Amelioration of Episodic Memory in Amnestic Mild Cognitive Impairment

Background: Altered hippocampal subregions (HIPsub) and their network connectivity relate to episodic memory decline in amnestic mild cognitive impairment (aMCI), which is significantly limited by over-dependence on correlational associations. Objective: To identify whether restoration of HIPsub and its network connectivity using repetitive transcranial magnetic stimulation (rTMS) is causally linked to amelioration of episodic memory in aMCI. Methods: In the first cohort, analysis of HIPsub grey matter (GM) and its functional connectivity was performed to identify an episodic memory-related circuit in aMCI by using a pattern classification approach. In the second cohort, this circuit was experimentally modulated with rTMS. Structural equation modeling was employed to investigate rTMS regulatory mechanism in amelioration of episodic memory. Results: First, in the first cohort, this study identified HIPsub circuit pathology of episodic memory decline in aMCI patients. Second, in the second cohort, restoration of HIPc GM and its connectivity with left middle temporal gyrus (MTG.L) are causally associated with amelioration of episodic memory in aMCI after 4 weeks of rTMS. Especially important, the effects of HIPc GM changes on the improvement of episodic memory were significantly mediated by HIPc connectivity with MTG.L changes in aMCI. Conclusion: This study provides novel experimental evidence about a biological substrate for the treatment of the disabling episodic memory in aMCI patients. Correction of breakdown in HIPc structure and its connectivity with MTG can causally ameliorate episodic memory in aMCI.

Alterations of dynamic redundancy of functional brain subnetworks in Alzheimer's disease and major depression disorders

The human brain is not only efficiently but also "redundantly" connected. The redundancy design could help the brain maintain resilience to disease attacks. This paper explores subnetwork-level redundancy dynamics and the potential of such metrics in disease studies. As such, we looked into specific functional subnetworks, including those associated with high-level functions. We investigated how the subnetwork redundancy dynamics change along with Alzheimer's disease (AD) progression and with major depressive disorder (MDD), two major disorders that could share similar subnetwork alterations. We found an increased dynamic redundancy of the subcortical-cerebellum subnetwork and its connections to other high-order subnetworks in the mild cognitive impairment (MCI) and AD compared to the normal control (NC). With gained spatial specificity, we found such a redundancy index was sensitive to disease symptoms and could act as a protective mechanism to prevent the collapse of the brain network and functions. The dynamic redundancy of the medial frontal subnetwork and its connections to the frontoparietal subnetwork was also found decreased in MDD compared to NC. The spatial specificity of the redundancy dynamics changes may provide essential knowledge for a better understanding of shared neural substrates in AD and MDD.

Predicting Delayed Neurocognitive Recovery After Non-cardiac Surgery Using Resting-State Brain Network Patterns Combined With Machine Learning

Delayed neurocognitive recovery (DNR) is a common subtype of postoperative neurocognitive disorders. An objective approach for identifying subjects at high risk of DNR is yet lacking. The present study aimed to predict DNR using the machine learning method based on multiple cognitive-related brain network features. A total of 74 elderly patients (≥ 60-years-old) undergoing non-cardiac surgery were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) before the surgery. Seed-based whole-brain functional connectivity (FC) was analyzed with 18 regions of interest (ROIs) located in the default mode network (DMN), limbic network, salience network (SN), and central executive network (CEN). Multiple machine learning models (support vector machine, decision tree, and random forest) were constructed to recognize the DNR based on FC network features. The experiment has three parts, including performance comparison, feature screening, and parameter adjustment. Then, the model with the best predictive efficacy for DNR was identified. Finally, independent testing was conducted to validate the established predictive model. Compared to the non-DNR group, the DNR group exhibited aberrant whole-brain FC in seven ROIs, including the right posterior cingulate cortex, right medial prefrontal cortex, and left lateral parietal cortex in the DMN, the right insula in the SN, the left anterior prefrontal cortex in the CEN, and the left ventral hippocampus and left amygdala in the limbic network. The machine learning experimental results identified a random forest model combined with FC features of DMN and CEN as the best prediction model. The area under the curve was 0.958 (accuracy = 0.935, precision = 0.899, recall = 0.900, F1 = 0.890) on the test set. Thus, the current study indicated that the random forest machine learning model based on rs-FC features of DMN and CEN predicts the DNR following non-cardiac surgery, which could be beneficial to the early prevention of DNR. Clinical Trial Registration: The study was registered at the Chinese Clinical Trial Registry (Identification number: ChiCTR-DCD-15006096).

Functional Integrity of Executive Control Network Contributed to Retained Executive Abilities in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is considered to be a transitional state between normal aging and Alzheimer's dementia (AD). Recent studies have indicated that executive function (EF) declines during MCI. However, only a limited number of studies have investigated the neural basis of EF deficits in MCI. Herein, we investigate the changes of regional brain spontaneous activity and functional connectivity (FC) of the executive control network (ECN) between high EF and low EF groups. Methods: According to EF composite score (ADNI-EF) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we divided MCI into two groups, including the MCI-highEF group and MCI-lowEF group. Resting-state functional MRI was utilized to investigate the fractional amplitude of low-frequency fluctuation (fALFF) and ECN functional connectivity across 23 healthy controls (HC), 11 MCI-highEF, and 14 MCI-lowEF participants. Moreover, a partial correlation analysis was carried out to examine the relationship between altered fALFF or connectivity of the ECN and the ADNI-EF. Results: Compared to HC, the MCI-highEF participants demonstrated increased fALFF in the left superior temporal gyrus (STG), as well as decreased fALFF in the right precentral gyrus, right postcentral gyrus, and left middle frontal gyrus (MFG). The MCI-lowEF participants demonstrated increased fALFF in the cerebellar vermis and decreased fALFF in the left MFG. Additionally, compared to HC, the MCI-highEF participants indicated no significant difference in connectivity of the ECN. Furthermore, the MCI-lowEF participants showed increased ECN FC in the left cuneus and left MFG, as well as decreased ECN functional connectivity in the right parahippocampal gyrus (PHG). Notably, the altered fALFF in the left MFG was positively correlated to ADNI-EF, while the altered fALFF in cerebellar vermis is negatively correlated with ADNI-EF across the two MCI groups and the HC group. Altered ECN functional connectivity in the right PHG is negatively correlated to ADNI-EF, while altered ECN functional connectivity in the left cuneus is negatively correlated to ADNI-EF across the three groups. Conclusions: Our current study demonstrates the presence of different patterns of regional brain spontaneous activity and ECN FC in the MCI-highEF group and MCI-lowEF group. Furthermore, the ECN FC of the MCI-highEF group was not disrupted, which may contribute to retained EF in MCI.

Convergent Functional Changes of Default Mode Network in Mild Cognitive Impairment Using Activation Likelihood Estimation

Background: Mild cognitive impairment (MCI) represents a transitional state between normal aging and dementia disorders, especially Alzheimer's disease (AD). The disruption of the default mode network (DMN) is often considered to be a potential biomarker for the progression from MCI to AD. The purpose of this study was to assess MRI-specific changes of DMN in MCI patients by elucidating the convergence of brain regions with abnormal DMN function.

Methods: We systematically searched PubMed, Ovid, and Web of science for relevant articles. We identified neuroimaging studies by using amplitude of low frequency fluctuation /fractional amplitude of low frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo), and functional connectivity (FC) in MCI patients. Based on the activation likelihood estimation (ALE) algorithm, we carried out connectivity modeling of coordination-based meta-analysis and functional meta-analysis.

Results: In total, this meta-analysis includes 39 articles on functional neuroimaging studies. Using computer software analysis, we discovered that DMN changes in patients with MCI mainly occur in bilateral inferior frontal lobe, right medial frontal lobe, left inferior parietal lobe, bilateral precuneus, bilateral temporal lobe, and parahippocampal gyrus (PHG).

Conclusions: Herein, we confirmed the presence of DMN-specific damage in MCI, which is helpful in revealing pathology of MCI and further explore mechanisms of conversion from MCI to AD. Therefore, we provide a new specific target and direction for delaying conversion from MCI to AD.

Impairment of Episodic-Specific Autobiographical Memory in Individuals with Subjective Cognitive Decline and in Patients with Prodromal or Mild Alzheimer's Disease

BACKGROUND

Autobiographical memory (AM) is a personal form of memory that becomes impaired in the early, clinical stages of Alzheimer's disease (AD). In the "preclinical" phase of AD, neuropathological hallmarks are present (especially in a brain network underpinning AM), but performance on standardized neuropsychological tests is normal. Even so, some patients have subjective cognitive decline (SCD).

OBJECTIVE

The aim was to 1) investigate AM performance on two tests with different approaches in SCD, and in prodromal and mild AD, and 2) examine the association between the AM tests.

METHODS

We included 17 SCD patients with heightened risk of AD, 17 amnestic mild cognitive impairment (aMCI) patients, 17 patients with mild dementia due to AD, and 30 healthy controls. Patients were diagnosed according to international criteria, and all participants had MMSE scores≥24. AM was assessed using the Columbia Autobiographical Memory Interview-Short Form (CAMI-SF) and the Three Events Test. These tests measure the production of contextual details.

RESULTS

Significant group effects were found for the Three Events Test and the CAMI-SF. All patient groups produced significantly fewer contextual details than the controls on the Three Events Test. On CAMI-SF, the aMCI and mild AD groups were able to answer fewer questions or gave significantly less detailed answers than the other groups. The SCD patients performed below the controls on CAMI-SF, but the difference was not significant.

CONCLUSION

AM may be impaired in very early AD, even in the phases where standardized episodic memory tests show no decline.

Differences in Functional Brain Networks Between Subjective Cognitive Decline with and without Worry Groups: A Graph Theory Study from SILCODE

BACKGROUND

Evidence suggests that subjective cognitive decline (SCD) individuals with worry have a higher risk of cognitive decline. However, how SCD-related worry influences the functional brain network is still unknown.

OBJECTIVE

In this study, we aimed to explore the differences in functional brain networks between SCD subjects with and without worry.

METHODS

A total of 228 participants were enrolled from the Sino Longitudinal Study on Cognitive Decline (SILCODE), including 39 normal control (NC) subjects, 117 SCD subjects with worry, and 72 SCD subjects without worry. All subjects completed neuropsychological assessments, APOE genotyping, and resting-state functional magnetic resonance imaging (rs-fMRI). Graph theory was applied for functional brain network analysis based on both the whole brain and default mode network (DMN). Parameters including the clustering coefficient, shortest path length, local efficiency, and global efficiency were calculated. Two-sample T-tests and chi-square tests were used to analyze differences between two groups. In addition, a false discovery rate-corrected post hoc test was applied.

RESULTS

Our analysis showed that compared to the SCD without worry group, SCD with worry group had significantly increased functional connectivity and shortest path length (p = 0.002) and a decreased clustering coefficient (p = 0.013), global efficiency (p = 0.001), and local efficiency (p < 0.001). The above results appeared in both the whole brain and DMN.

CONCLUSION

There were significant differences in functional brain networks between SCD individuals with and without worry. We speculated that worry might result in alterations of the functional brain network for SCD individuals and then result in a higher risk of cognitive decline.

Disrupted Dynamic Functional Connectivity in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment Based on the Triple-Network Model

Background: Subjective cognitive decline and amnestic mild cognitive impairment (aMCI) were widely thought to be preclinical AD spectrum disorders, characterized by aberrant functional connectivity (FC) within the triple networks of the default mode network (DMN), the salience network (SN), and the executive control network (ECN). Dynamic FC (DFC) analysis can capture temporal fluctuations in brain FC during the scan, which static FC analysis cannot. The purpose of the current study was to explore the changes in dynamic FC within the triple networks of the preclinical AD spectrum and further reveal their potential diagnostic value in diagnosing preclinical AD spectrum disorders.

Methods: We collected resting-state functional magnetic resonance imaging data from 44 patients with subjective cognitive decline (SCD), 49 with aMCI, and 58 healthy controls (HCs). DFC analysis based on the sliding time-window correlation method was used to analyze DFC variability within the triple networks in the three groups. Then, correlation analysis was conducted to reveal the relationship between altered DFC variability within the triple networks and a decline in cognitive function. Furthermore, logistic regression analysis was used to assess the diagnostic accuracy of altered DFC variability within the triple networks in patients with SCD and aMCI.

Results: Compared with the HC group, the groups with SCD and aMCI both showed altered DFC variability within the triple networks. DFC variability in the right middle temporal gyrus and left inferior frontal gyrus (IFG) within the ECN were significantly different between patients with SCD and aMCI. Moreover, the altered DFC variability in the left IFG within the ECN was obviously associated with a decline in episodic memory and executive function. The logistic regression analysis showed that multivariable analysis had high sensitivity and specificity for diagnosing SCD and aMCI.

Conclusions: Subjective cognitive decline and aMCI showed varying degrees of change in DFC variability within the triple networks and altered DFC variability within the ECN involved episodic memory and executive function. More importantly, altered DFC variability and the triple-network model proved to be important biomarkers for diagnosing and identifying patients with preclinical AD spectrum disorders.

Functional Inhibitory Connections Modulate the Electrophysiological Activity Patterns of Cortical-Hippocampal Ensembles

The brain is a complex organ composed of billions of neurons connected through excitatory and inhibitory synapses. Its structure reveals a modular topological organization, where neurons are arranged in interconnected assemblies. The generated patterns of electrophysiological activity are shaped by two main factors: network heterogeneity and the topological properties of the underlying connectivity that strongly push the dynamics toward different brain-states. In this work, we exploited an innovative polymeric structure coupled to Micro-Electrode Arrays (MEAs) to recreate in vitro heterogeneous interconnected (modular) neuronal networks made up of cortical and hippocampal neurons. We investigated the propagation of spike sequences between the two interconnected subpopulations during the networks' development, correlating functional and structural connectivity to dynamics. The simultaneous presence of two neuronal types shaped the features of the functional connections (excitation vs. inhibition), orchestrating the emerging patterns of electrophysiological activity. In particular, we found that hippocampal neurons mostly project inhibitory connections toward the cortical counterpart modulating the temporal scale of the population events (network bursts). In contrast, cortical neurons establish a larger amount of intrapopulation connections. Moreover, we proved topological properties such as small-worldness, degree distribution, and modularity of neuronal assemblies were favored by the physical environment where networks developed and matured.

Divergent Connectivity Changes in Gray Matter Structural Covariance Networks in Subjective Cognitive Decline, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease

Alzheimer’s disease (AD) has a long preclinical stage that can last for decades prior to progressing toward amnestic mild cognitive impairment (aMCI) and/or dementia. Subjective cognitive decline (SCD) is characterized by self-experienced memory decline without any evidence of objective cognitive decline and is regarded as the later stage of preclinical AD. It has been reported that the changes in structural covariance patterns are affected by AD pathology in the patients with AD and aMCI within the specific large-scale brain networks. However, the changes in structural covariance patterns including normal control (NC), SCD, aMCI, and AD are still poorly understood. In this study, we recruited 42 NCs, 35 individuals with SCD, 43 patients with aMCI, and 41 patients with AD. Gray matter (GM) volumes were extracted from 10 readily identifiable regions of interest involved in high-order cognitive function and AD-related dysfunctional structures. The volume values were used to predict the regional densities in the whole brain by using voxel-based statistical and multiple linear regression models. Decreased structural covariance and weakened connectivity strength were observed in individuals with SCD compared with NCs. Structural covariance networks (SCNs) seeding from the default mode network (DMN), salience network, subfields of the hippocampus, and cholinergic basal forebrain showed increased structural covariance at the early stage of AD (referring to aMCI) and decreased structural covariance at the dementia stage (referring to AD). Moreover, the SCN seeding from the executive control network (ECN) showed a linearly increased extent of the structural covariance during the early and dementia stages. The results suggest that changes in structural covariance patterns as the order of NC-SCD-aMCI-AD are divergent and dynamic, and support the structural disconnection hypothesis in individuals with SCD.

Altered theta rhythm and hippocampal-cortical interactions underlie working memory deficits in a hyperglycemia risk factor model of Alzheimer's disease

Diabetes mellitus is a metabolic disease associated with dysregulated glucose and insulin levels and an increased risk of developing Alzheimer’s disease (AD) later in life. It is thought that chronic hyperglycemia leads to neuroinflammation and tau hyperphosphorylation in the hippocampus leading to cognitive decline, but effects on hippocampal network activity are unknown. A sustained hyperglycemic state was induced in otherwise healthy animals and subjects were then tested on a spatial delayed alternation task while recording from the hippocampus and anterior cingulate cortex (ACC). Hyperglycemic animals performed worse on long delay trials and had multiple electrophysiological differences throughout the task. We found increased delta power and decreased theta power in the hippocampus, which led to altered theta/delta ratios at the end of the delay period. Cross frequency coupling was significantly higher in multiple bands and delay period hippocampus-ACC theta coherence was elevated, revealing hypersynchrony. The highest coherence values appeared long delays on error trials for STZ animals, the opposite of what was observed in controls, where lower delay period coherence was associated with errors. Consistent with previous investigations, we found increases in phosphorylated tau in STZ animals’ hippocampus and cortex, which might account for the observed oscillatory and cognitive changes.

To investigate the effects of chronic hyperglycemia on hippocampal network activity Wirt et al induced sustained hyperglycemia in rats and tested them in a spatial delayed alternation task while recording from the hippocampus and anterior cingulate cortex. They demonstrated that hyperglycemia impaired task performance and altered theta rhythm as well as increasing tau phosphorylation, which suggest there is potentially a direct link between chronic hyperglycemia and Alzheimer’s disease.

Altered Spontaneous Neural Activity and Functional Connectivity in Parkinson's Disease With Subthalamic Microlesion

Background

Transient improvement in motor symptoms are immediately observed in patients with Parkinson's disease (PD) after an electrode has been implanted into the subthalamic nucleus (STN) for deep brain stimulation (DBS). This phenomenon is known as the microlesion effect (MLE). However, the underlying mechanisms of MLE is poorly understood.

Purpose

We utilized resting state functional MRI (rs-fMRI) to evaluate changes in spontaneous brain activity and networks in PD patients during the microlesion period after DBS.

Method

Overall, 37 PD patients and 13 gender- and age-matched healthy controls (HCs) were recruited for this study. Rs-MRI information was collected from PD patients three days before DBS and one day after DBS, whereas the HCs group was scanned once. We utilized the amplitude of low-frequency fluctuation (ALFF) method in order to analyze differences in spontaneous whole-brain activity among all subjects. Furthermore, functional connectivity (FC) was applied to investigate connections between other brain regions and brain areas with significantly different ALFF before and after surgery in PD patients.

Result

Relative to the PD-Pre-DBS group, the PD-Post-DBS group had higher ALFF in the right putamen, right inferior frontal gyrus, right precentral gyrus and lower ALFF in right angular gyrus, right precuneus, right posterior cingulate gyrus (PCC), left insula, left middle temporal gyrus (MTG), bilateral middle frontal gyrus and bilateral superior frontal gyrus (dorsolateral). Functional connectivity analysis revealed that these brain regions with significantly different ALFF scores demonstrated abnormal FC, largely in the temporal, prefrontal cortices and default mode network (DMN).

Conclusion

The subthalamic microlesion caused by DBS in PD was found to not only improve the activity of the basal ganglia-thalamocortical circuit, but also reduce the activity of the DMN and executive control network (ECN) related brain regions. Results from this study provide new insights into the mechanism of MLE.

Impaired Memory Awareness and Loss Integration in Self-Referential Network Across the Progression of Alzheimer's Disease Spectrum

BACKGROUND

Anosognosia, or unawareness of memory deficits, is a common manifestation of Alzheimer's disease (AD), but greatly variable in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) subjects. Self-referential network (SRN) is responsible for self-referential processing and considered to be related to AD progression.

OBJECTIVE

Our aim is to explore connectivity changes of SRN and its interaction with memory-related network and primary sensorimotor network (SMN) in the AD spectrum.

METHODS

About 444 Alzheimer's Disease Neuroimaging Initiative subjects (86 cognitively normal [CN]; 156 SCD; 146 aMCI; 56 AD) were enrolled in our study. The independent component analysis (ICA) method was used to extract the SRN, SMN, and memory-related network from all subjects. The alteration of functional connectivity (FC) within SRN and its connectivity with memory-related network/SMN were compared among four groups and further correlation analysis between altered FC and memory awareness index as well as episodic memory score were performed.

RESULTS

Compared with CN group, individuals with SCD exhibited hyperconnectivity within SRN, while aMCI and AD patients showed hypoconnectivity. Furthermore, aMCI patients and AD patients both showed the interruption of the FC between the SRN and memory-related network compared to CN group. Pearson correlation analysis showed that disruptive FC within SRN and its interaction with memory-related network were related to memory awareness index and episodic memory scores.

CONCLUSION

In conclusion, impaired memory awareness and episodic memory in the AD spectrum are correlated to the disconnection within SRN and its interaction with memory-related network.

Differences Changes in Cerebellar Functional Connectivity Between Mild Cognitive Impairment and Alzheimer's Disease: A Seed-Based Approach

Background: Recent studies have discovered that functional connections are impaired among patients with Alzheimer's disease (AD), even at the preclinical stage. The cerebellum has been implicated as playing a role in cognitive processes. However, functional connectivity (FC) among cognitive sub-regions of the cerebellum in patients with AD and mild cognitive impairment (MCI) remains to be further elucidated. Objective: Our study aims to investigate the FC changes of the cerebellum among patients with AD and MCI, compared to healthy controls (HC). Additionally, we explored the role of cerebellum FC changes in the cognitive performance of all subjects. Materials: Resting-state functional magnetic resonance imaging (rs-fMRI) data from three different groups (28 AD patients, 26 MCI patients, and 30 HC) was collected. We defined cerebellar crus II and lobule IX as seed regions to assess the intragroup differences of cortico-cerebellar connectivity. Bias correlational analysis was performed to investigate the relationship between changes in FC and neuropsychological performance. Results: Compared to HC, AD patients had decreased FC within the caudate, limbic lobe, medial frontal gyrus (MFG), middle temporal gyrus, superior frontal gyrus, parietal lobe/precuneus, inferior temporal gyrus, and posterior cingulate gyrus. Interestingly, MCI patients demonstrated increased FC within inferior parietal lobe, and MFG, while they had decreased FC in the thalamus, inferior frontal gyrus, and superior frontal gyrus. Further analysis indicated that FC changes between the left crus II and the right thalamus, as well as between left lobule IX and the right parietal lobe, were both associated with cognitive decline in AD. Disrupted FC between left crus II and right thalamus, as well as between left lobule IX and right parietal lobe, was associated with attention deficit among subjects with MCI. Conclusion: These findings indicate that cortico-cerebellar FC in MCI and AD patients was significantly disrupted with different distributions, particularly in the default mode networks (DMN) and fronto-parietal networks (FPN) region. Increased activity within the fronto-parietal areas of MCI patients indicated a possible compensatory role for the cerebellum in cognitive impairment. Therefore, alterations in the cortico-cerebellar FC represent a novel approach for early diagnosis and a potential therapeutic target for early intervention.

Distinctive Alterations of Functional Connectivity Strength between Vascular and Amnestic Mild Cognitive Impairment

Widespread structural and functional alterations have been reported in the two highly prevalent mild cognitive impairment (MCI) subtypes, amnestic MCI (aMCI) and vascular MCI (VaMCI). However, the changing pattern in functional connectivity strength (FCS) remains largely unclear. The aim of the present study is to detect the differences of FCS and to further explore the detailed resting-state functional connectivity (FC) alterations among VaMCI subjects, aMCI subjects, and healthy controls (HC). Twenty-six aMCI subjects, 31 VaMCI participants, and 36 HC participants underwent cognitive assessments and resting-state functional MRI scans. At first, one-way ANCOVA and post hoc analysis indicated significant decreased FCS in the left middle temporal gyrus (MTG) in aMCI and VaMCI groups compared to HC, especially in the VaMCI group. Then, we selected the left MTG as a seed to further explore the detailed resting-state FC alterations among the three groups, and the results indicated that FC between the left MTG and some frontal brain regions were significantly decreased mainly in VaMCI. Finally, partial correlation analysis revealed that the FC values between the left MTG and left inferior frontal gyrus were positively correlated with the cognitive performance episodic memory and negatively related to the living status. The present study demonstrated that different FCS alterations existed in aMCI and VaMCI. These findings may provide a novel insight into the understanding of pathophysiological mechanisms underlying different MCI subtypes.

Structural and Functional Disruption of Salience Network in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

Salience network (SN), playing a vital role in advanced cognitive function, is regarded to be impaired in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The purpose of the study was to explore the importance of structural and functional features of SN in the diagnosis of SCD and aMCI. Structural and resting-state functional magnetic resonance imaging were collected from SCD, aMCI, and healthy control (HC). Cortex thickness, gray matter (GM) volume, spontaneous brain activity, functional connectivity (FC) within SN, and its relationship with cognitive function were analyzed. Moreover, the receiver operating characteristic analysis was performed to assess diagnostic efficacy of altered indictors for SCD and aMCI. Compared to HC, both SCD and aMCI showed decreased GM volume, decreased spontaneous brain activity, and increased FC within SN, while aMCI showed additional decreased cortex thickness. Furthermore, the altered FC in SCD and aMCI was significantly correlated with cognitive function. Particularly, the best-fitting classification models of SCD and aMCI were based on the combined multiple indicators. In conclusion, structure and function of SN were disrupted in SCD and aMCI, which involved in cognitive decline. The combined multiple indicators of SN provided powerful biomarkers for the diagnosis of SCD and aMCI.

Differential functional connectivity of insular subdivisions in de novo Parkinson's disease with mild cognitive impairment

The insula, consisting of functionally diverse subdivisions, plays a significant role in Parkinson's disease (PD)-related cognitive disorders. However, the functional connectivity (FC) patterns of insular subdivisions in PD remain unclear. Our aim is to investigate the changes in FC patterns of insular subdivisions and their relationships with cognitive domains. Three groups of participants were recruited in this study, including PD patients with mild cognitive impairment (PD-MCI, n = 25), PD patients with normal cognition (PD-NC, n = 13), and healthy controls (HCs, n = 17). Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in insular subdivisions of the three groups. Moreover, all participants underwent a neuropsychological battery to assess cognition so that the relationship between altered FC and cognitive performance could be elucidated. Compared with the PD-NC group, the PD-MCI group exhibited increased FC between the left dorsal anterior insular (dAI) and the right superior parietal gyrus (SPG), and altered FC was negatively correlated with memory and executive function. Compared with the HC group, the PD-MCI group showed significantly increased FC between the right dAI and the right median cingulate and paracingulate gyri (DCG), and altered FC was positively related to attention/working memory, visuospatial function, and language. Our findings highlighted the different abnormal FC patterns of insular subdivisions in PD patients with different cognitive abilities. Furthermore, dysfunction of the dAI may partly contribute to the decline in executive function and memory in early drug-naïve PD patients.

Altered Regional Cerebral Blood Flow and Brain Function Across the Alzheimer's Disease Spectrum: A Potential Biomarker

Objective: To investigate variation in the characteristics of regional cerebral blood flow (rCBF), brain activity, and intrinsic functional connectivity (FC) across the Alzheimer's disease spectrum (ADS).

Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC). All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests. Additionally, the normalized CBF, regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) of individual subjects were compared in the ADS. Moreover, the changes in intrinsic FC were investigated across the ADS using the abnormal rCBF regions as seeds and behavioral correlations. Finally, a support-vector classifier model of machine learning was used to distinguish individuals with ADS from HC.

Results: Compared to the HC subjects, patients with AD showed the poorest level of rCBF in the left precuneus (LPCUN) and right middle frontal gyrus (RMFG) among all participants. In addition, there was a significant decrease in the ALFF in the bilateral posterior cingulate cortex (PCC) and ReHo in the right PCC. Moreover, RMFG- and LPCUN-based FC analysis revealed that the altered FCs were primarily located in the posterior brain regions. Finally, a combination of altered rCBF, ALFF, and ReHo in posterior cingulate cortex/precuneus (PCC/PCUN) showed a better ability to differentiate ADS from HC, AD from SCD and MCI, but not MCI from SCD.

Conclusions: The study demonstrated the significance of an altered rCBF and brain activity in the early stages of ADS. These findings, therefore, present a potential diagnostic neuroimaging-based biomarker in ADS. Additionally, the study provides a better understanding of the pathophysiology of AD.

Altered Frequency-Dependent Brain Activation and White Matter Integrity Associated With Cognition in Characterizing Preclinical Alzheimer's Disease Stages

Background

Subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI) are regarded to be at high risk of converting to Alzheimer's disease (AD). Amplitude of low-frequency fluctuations (ALFF) can reflect functional deterioration while diffusion tensor imaging (DTI) is capable of detecting white matter integrity. Our study aimed to investigate the structural and functional alterations to further reveal convergence and divergence among SCD, naMCI, and aMCI and how these contribute to cognitive deterioration.

Methods

We analyzed ALFF under slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands and white matter fiber integrity among normal controls (CN), SCD, naMCI, and aMCI groups. Correlation analyses were further utilized among paired DTI alteration, ALFF deterioration, and cognitive decline.

Results

For ALFF calculation, ascended ALFF values were detected in the lingual gyrus (LING) and superior frontal gyrus (SFG) within SCD and naMCI patients, respectively. Descended ALFF values were presented mainly in the LING, SFG, middle frontal gyrus, and precuneus in aMCI patients compared to CN, SCD, and naMCI groups. For DTI analyses, white matter alterations were detected within the uncinate fasciculus (UF) in aMCI patients and within the superior longitudinal fasciculus (SLF) in naMCI patients. SCD patients presented alterations in both fasciculi. Correlation analyses revealed that the majority of these structural and functional alterations were associated with complicated cognitive decline. Besides, UF alterations were correlated with ALFF deterioration in the SFG within aMCI patients.

Conclusions

SCD shares structurally and functionally deteriorative characteristics with aMCI and naMCI, and tends to convert to either of them. Furthermore, abnormalities in white matter fibers may be the structural basis of abnormal brain activation in preclinical AD stages. Combined together, it suggests that structural and functional integration may characterize the preclinical AD progression.

Altered Insular Subregional Connectivity Associated With Cognitions for Distinguishing the Spectrum of Pre-clinical Alzheimer's Disease

Background: Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are regarded as part of the pre-clinical Alzheimer's disease (AD) spectrum. The insular subregional networks are thought to have diverse intrinsic connectivity patterns that are involved in cognitive and emotional processing. We set out to investigate convergent and divergent altered connectivity patterns of the insular subregions across the spectrum of pre-clinical AD and evaluated how well these patterns can differentiate the pre-clinical AD spectrum.

Method: Functional connectivity (FC) analyses in insular subnetworks were carried out among 38 patients with SCD, 56 patients with aMCI, and 55 normal controls (CNs). Logistic regression analyses were used to construct models for aMCI and CN, as well as SCD and CN classification. Finally, we conducted correlation analyses to measure the relationship between FCs of altered insular subnetworks and cognition.

Results: Patients with SCD presented with reduced FC in the bilateral cerebellum posterior lobe and increased FC in the medial frontal gyrus and the middle temporal gyrus. On the other hand, patients with aMCI largely presented with decreased FC in the bilateral inferior parietal lobule, the cerebellum posterior lobe, and the anterior cingulate cortex, as well as increased FC in the medial and inferior frontal gyrus, and the middle and superior temporal gyrus. Logistic regression analyses indicated that a model composed of FCs among altered insular subnetworks in patients with SCD was able to appropriately classify 83.9% of patients with SCD and CN, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.876, 81.6% sensitivity, and 81.8% specificity. A model consisting of altered insular subnetwork FCs in patients with aMCI was able to appropriately classify 86.5% of the patients with aMCI and CNs, with an AUC of 0.887, 80.4% sensitivity, and 83.6% specificity. Furthermore, some of the FCs among altered insular subnetworks were significantly correlated with episodic memory and executive function.

Conclusions: Patients with SCD and aMCI are likely to share similar convergent and divergent altered intrinsic FC patterns of insular subnetworks as the pre-clinical AD spectrum, and presented with abnormalities among subnetworks. Based on these abnormalities, individuals can be correctly differentiated in the pre-clinical AD spectrum. These results suggest that alterations in insular subnetworks can be utilized as a potential biomarker to aid in conducting a clinical diagnosis of the spectrum of pre-clinical AD.

Dynamic Connectivity Alteration Facilitates Cognitive Decline in Alzheimer's Disease Spectrum

Introduction: It is unknown the alterations in the dynamic networks of the brain and the underlying molecular pathological mechanism of Alzheimer's disease (AD) spectrum. Here, we aim to explore the association between alterations in the dynamic brain networks' trajectory and cognitive decline in the AD spectrum. Methods: One hundred sixty subjects were recruited from the ADNI database, including 49 early mild cognitive impairment, 28 late mild cognitive impairment, 24 AD patients, and 59 cognitively normal. All participants completed the resting-state functional magnetic resonance imaging scan and neuropsychological tests. We integrated a new method combining large-scale network analysis and canonical correlation analysis to explore the dynamic spatiotemporal patterns within- and between resting-state networks (RSNs) and their significance in the AD spectrum. Results: All RSNs represented an increase in connectivity within networks by enhancing inner cohesive ability, while 7 out of 10 RSNs were characterized by a decrease in connectivity between networks, which indicated a weakened connector among networks from the early stage to dementia. This dichotomous mode presenting large-scale dynamic network abnormality was significantly correlated with the levels of molecular biomarkers of AD, and cognitive performance, as well as with the accumulating effects of 10 identified AD-related genetic risk factors. Discussion: These findings deepen our understanding of the associated mechanism underlying large-scale network disruption, linking known molecular biomarkers and phenotypic variations in the AD spectrum.

Disrupted Patterns of Rich-Club and Diverse-Club Organizations in Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

Background

Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) were considered to be a continuum of Alzheimer’s disease (AD) spectrum. The abnormal topological architecture and rich-club organization in the brain functional network can reveal the pathology of the AD spectrum. However, few studies have explored the disrupted patterns of diverse club organizations and the combination of rich- and diverse-club organizations in SCD and aMCI.

Methods

We collected resting-state functional magnetic resonance imaging data of 19 SCDs, 29 aMCIs, and 28 healthy controls (HCs) from the Alzheimer’s Disease Neuroimaging Initiative. Graph theory analysis was used to analyze the network metrics and rich- and diverse-club organizations simultaneously.

Results

Compared with HC, the aMCI group showed altered small-world and network efficiency, whereas the SCD group remained relatively stable. The aMCI group showed reduced rich-club connectivity compared with the HC. In addition, the aMCI group showed significantly increased feeder connectivity and decreased local connectivity of the diverse club compared with the SCD group. The overlapping nodes of the rich club and diverse club showed a significant difference in nodal efficiency and shortest path length (L_p) between groups. Notably, the L_p values of overlapping nodes in the SCD and aMCI groups were significantly associated with episodic memory.

Conclusion

The present study demonstrates that the network properties of SCD and aMCI have varying degrees of damage. The combination of the rich club and the diverse club can provide a novel insight into the pathological mechanism of the AD spectrum. The altered patterns in overlapping nodes might be potential biomarkers in the diagnosis of the AD spectrum.

Voxelwise Meta-Analysis of Gray Matter Abnormalities in Mild Cognitive Impairment and Subjective Cognitive Decline Using Activation Likelihood Estimation

Background: Voxel-based morphometry studies have not yielded consistent results among patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Objective: Therefore, we aimed to conduct a meta-analysis of gray matter (GM) abnormalities acquired from these studies to determine their respective neuroanatomical changes. Methods: We systematically searched for voxel-based whole-brain morphometry studies that compared MCI or SCD subjects with healthy controls in PubMed, Web of Science, and EMBASE databases. We used the coordinate-based method of activation likelihood estimation to determine GM changes in SCD, MCI, and MCI sub-groups (amnestic MCI and non-amnestic MCI). Results: A total of 45 studies were included in our meta-analysis. In the MCI group, we found structural atrophy of the bilateral hippocampus, parahippocampal gyrus (PHG), amygdala, right lateral globus pallidus, right insula, and left middle temporal gyrus. The aMCI group exhibited GM atrophy in the bilateral hippocampus, PHG, and amygdala. The naMCI group presented with structural atrophy in the right putamen, right insula, right precentral gyrus, left medial/superior frontal gyrus, and left anterior cingulate. The right lingual gyrus, right cuneus, and left medial frontal gyrus were atrophic GM regions in the SCD group. Conclusion: Our meta-analysis identified unique patterns of neuroanatomical alternations in both the MCI and SCD group. Structural changes in SCD patients provide new evidence for the notion that subtle impairment of visual function, perception, and cognition may be related to early signs of cognitive impairment. In addition, our findings provide a foundation for future targeted interventions at different stages of preclinical Alzheimer’s disease.

Altered Patterns of Functional Connectivity and Causal Connectivity in Salience Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

The subjective cognitive decline (SCD) may last for decades prior to the onset of dementia and has been proposed as a risk population for development to amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Disruptions of functional connectivity and causal connectivity (CC) in the salience network (SN) are generally perceived as prominent hallmarks of the preclinical AD. Nevertheless, the alterations in anterior SN (aSN), and posterior SN (pSN) remain unclear. Here, we hypothesized that both the functional connectivity (FC) and CC of the SN subnetworks, comprising aSN and pSN, were distinct disruptive in the SCD and aMCI. We utilized resting-state functional magnetic resonance imaging to investigate the altered FC and CC of the SN subnetworks in 28 healthy controls, 23 SCD subjects, and 29 aMCI subjects. In terms of altered patterns of FC in SN subnetworks, aSN connected to the whole brain was significantly increased in the left orbital superior frontal gyrus, left insula lobule, right caudate lobule, and left rolandic operculum gyrus (ROG), whereas decreased FC was found in the left cerebellum superior lobule and left middle temporal gyrus when compared with the HC group. Notably, no prominent statistical differences were obtained in pSN. For altered patterns of CC in SN subnetworks, compared to the HC group, the aberrant connections in aMCI group were separately involved in the right cerebellum inferior lobule (CIL), right supplementary motor area (SMA), and left ROG, whereas the SCD group exhibited more regions of aberrant connection, comprising the right superior parietal lobule, right CIL, left inferior parietal lobule, left post-central gyrus (PG), and right angular gyrus. Especially, SCD group showed increased CC in the right CIL and left PG, whereas the aMCI group showed decreased CC in the left pre-cuneus, corpus callosum, and right SMA when compared to the SCD group. Collectively, our results suggest that analyzing the altered FC and CC observed in SN subnetworks, served as impressible neuroimaging biomarkers, may supply novel insights for designing preclinical interventions in the preclinical stages of AD.

Altered Patterns of Phase Position Connectivity in Default Mode Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

Alzheimer’s disease (AD), which most commonly occurs in the elder, is a chronic neurodegenerative disease with no agreed drugs or treatment protocols at present. Amnestic mild cognitive impairment (aMCI), earlier than AD onset and later than subjective cognitive decline (SCD) onset, has a serious probability of converting into AD. The SCD, which can last for decades, subjectively complains of decline impairment in memory. Distinct altered patterns of default mode network (DMN) subnetworks connected to the whole brain are perceived as prominent hallmarks of the early stages of AD. Nevertheless, the aberrant phase position connectivity (PPC) connected to the whole brain in DMN subnetworks remains unknown. Here, we hypothesized that there exist distinct variations of PPC in DMN subnetworks connected to the whole brain for patients with SCD and aMCI, which might be acted as discriminatory neuroimaging biomarkers. We recruited 27 healthy controls (HC), 20 SCD and 28 aMCI subjects, respectively, to explore aberrant patterns of PPC in DMN subnetworks connected to the whole brain. In anterior DMN (aDMN), SCD group exhibited aberrant PPC in the regions of right superior cerebellum lobule (SCL), right superior frontal gyrus of medial part (SFGMP), and left fusiform gyrus (FG) in comparison of HC group, by contrast, no prominent difference was found in aMCI group. It is important to note that aMCI group showed increased PPC in the right SFGMP in comparison with SCD group. For posterior DMN (pDMN), SCD group showed decreased PPC in the left superior parietal lobule (SPL) and right superior frontal gyrus (SFG) compared to HC group. It is noteworthy that aMCI group showed decreased PPC in the left middle frontal gyrus of orbital part (MFGOP) and right SFG compared to HC group, yet increased PPC was found in the left superior temporal gyrus of temporal pole (STGTP). Additionally, aMCI group exhibited decreased PPC in the left MFGOP compared to SCD group. Collectively, our results have shown that the aberrant regions of PPC observed in DMN are related to cognitive function, and it might also be served as impressible neuroimaging biomarkers for timely intervention before AD occurs.